source stringlengths 3 92 | c stringlengths 26 2.25M |
|---|---|
alloc_benchmark.c | /*
* Copyright (C) 2016 Intel Corporation.
* All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions are met:
* 1. Redistributions of source code must retain the above copyright notice(s),
* this list of conditions and the following disclaimer.
* 2. Redistributions in binary form must reproduce the above copyright notice(s),
* this list of conditions and the following disclaimer in the documentation
* and/or other materials provided with the distribution.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDER(S) ``AS IS'' AND ANY EXPRESS
* OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
* MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO
* EVENT SHALL THE COPYRIGHT HOLDER(S) BE LIABLE FOR ANY DIRECT, INDIRECT,
* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
* LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
* LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE
* OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF
* ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
#include <stdio.h>
#include <stdlib.h>
#include <time.h>
#include <sys/time.h>
#include <unistd.h>
#include <stdint.h>
#include <limits.h>
#ifdef _OPENMP
#include <omp.h>
#endif
#if defined(HBWMALLOC)
#include <hbwmalloc.h>
#define MALLOC_FN hbw_malloc
#define FREE_FN hbw_free
#elif defined (TBBMALLOC)
#include "tbbmalloc.h"
#define MALLOC_FN scalable_malloc
#define FREE_FN scalable_free
#else
#define MALLOC_FN malloc
#define FREE_FN free
#endif
double ctimer(void);
void usage(char * name);
int main(int argc, char * argv[])
{
#ifdef _OPENMP
int nthr = omp_get_max_threads();
#else
int nthr = 1;
#endif
long N, SIZE;
size_t alloc_size;
unsigned long i;
double dt, t_start, t_end, t_malloc, t_free, t_first_malloc, t_first_free,
malloc_time = 0.0, free_time = 0.0, first_malloc_time, first_free_time;
void* ptr;
#ifdef TBBMALLOC
int ret;
ret = load_tbbmalloc_symbols();
if (ret) {
printf("Error: TBB symbols not loaded (ret: %d)\n", ret);
return EXIT_FAILURE;
}
#endif
/* Handle command line arguments */
if (argc == 3) {
N = atol(argv[1]);
SIZE = atol(argv[2]);
}
if (argc != 3 || N < 0 || SIZE < 0 || SIZE > (LONG_MAX >> 10)) {
usage(argv[0]);
return EXIT_FAILURE;
}
alloc_size = (size_t) SIZE * 1024;
/* Get pagesize and compute page_mask */
const size_t page_size = sysconf(_SC_PAGESIZE);
const size_t page_mask = ~(page_size-1);
/* Warm up */
t_first_malloc = ctimer();
ptr = MALLOC_FN(alloc_size);
first_malloc_time = ctimer() - t_first_malloc;
if (ptr == NULL) {
printf("Error: first allocation failed\n");
return EXIT_FAILURE;
}
t_first_free = ctimer();
FREE_FN(ptr);
first_free_time = ctimer() - t_first_free;
ptr = NULL;
t_start = ctimer();
#pragma omp parallel private(i,t_malloc,t_free,ptr) reduction(max:malloc_time,free_time)
{
malloc_time = 0.0;
free_time = 0.0;
for (i=0; i<N; i++) {
t_malloc = ctimer();
ptr = (void*) MALLOC_FN(alloc_size);
malloc_time += ctimer() - t_malloc;
#pragma omp critical
{
if (ptr == NULL) {
printf("Error: allocation failed\n");
exit(EXIT_FAILURE);
}
}
/* Make sure to touch every page */
char* end = ptr + alloc_size;
char* aligned_beg = (char*)((uintptr_t)ptr & page_mask);
while(aligned_beg < end) {
char* temp_ptr = (char*) aligned_beg;
char value = temp_ptr[0];
temp_ptr[0] = value;
aligned_beg += page_size;
}
t_free = ctimer();
FREE_FN(ptr);
free_time += ctimer() - t_free;
ptr = NULL;
}
}
t_end = ctimer();
dt = t_end - t_start;
printf("%d %lu %8.6f %8.6f %8.6f %8.6f %8.6f\n",
nthr, SIZE, dt/N, malloc_time/N, free_time/N, first_malloc_time, first_free_time);
return EXIT_SUCCESS;
}
void usage(char * name)
{
printf("Usage: %s <N> <SIZE>, where \n"
"N is an number of repetitions \n"
"SIZE is an allocation size in kbytes\n", name);
}
inline double ctimer()
{
struct timeval tmr;
gettimeofday(&tmr, NULL);
/* Return time in ms */
return (tmr.tv_sec + tmr.tv_usec/1000000.0)*1000;
}
|
o3logon_fmt_plug.c | /*
* This software was written by JimF jfoug AT cox dot net
* in 2016. No copyright is claimed, and the software is hereby
* placed in the public domain. In case this attempt to disclaim
* copyright and place the software in the public domain is deemed
* null and void, then the software is Copyright (c) 2016 JimF
* and it is hereby released to the general public under the following
* terms:
*
* This software may be modified, redistributed, and used for any
* purpose, in source and binary forms, with or without modification.
*
*/
#if FMT_EXTERNS_H
extern struct fmt_main fmt_o3logon;
#elif FMT_REGISTERS_H
john_register_one(&fmt_o3logon);
#else
#include <string.h>
#include <openssl/des.h>
#include "arch.h"
#include "misc.h"
#include "common.h"
#include "formats.h"
#include "sha.h"
#include "unicode.h"
#include "base64_convert.h"
#ifdef _OPENMP
static int omp_t = 1;
#include <omp.h>
#ifndef OMP_SCALE
#define OMP_SCALE 512 // tuned on core i7
//#define OMP_SCALE 8192 // tuned on K8-Dual HT
#endif
#endif
#include "memdbg.h"
#define FORMAT_LABEL "o3logon"
#define FORMAT_NAME "Oracle O3LOGON protocol"
#define FORMAT_TAG "$o3logon$"
#define FORMAT_TAG_LEN (sizeof(FORMAT_TAG)-1)
#define ALGORITHM_NAME "SHA1 DES 32/" ARCH_BITS_STR
#define BENCHMARK_COMMENT ""
#define BENCHMARK_LENGTH -1
#define PLAINTEXT_LENGTH 32
#define BINARY_SIZE 0
#define BINARY_ALIGN 1
#define MAX_USERNAME_LEN 30
#define SALT_SIZE (sizeof(ora9_salt))
#define SALT_ALIGN (sizeof(unsigned int))
#define CIPHERTEXT_LENGTH 16
#define MIN_KEYS_PER_CRYPT 1
#define MAX_KEYS_PER_CRYPT 1
#define MAX_HASH_LEN (FORMAT_TAG_LEN+MAX_USERNAME_LEN+1+32+1+80)
//#define DEBUG_ORACLE
//
// The keys are $ora9i$ user $ auth_sess_key $ auth_pass_key These can be found in sniffed network traffic.
static struct fmt_tests tests[] = {
{"$o3logon$PASSWORD9$8CF28B36E4F3D2095729CF59510003BF$3078D7DE44385654CC952A9C56E2659B", "password9"},
{"$o3logon$scott$819D062FE5D93F79FF19BDAFE2F9872A$C6D1ED7E6F4D3A6D94F1E49460122D39A3832CC792AD7137", "scottscottscott1"},
{"$o3logon$SCOTT$8E9E3E07864D99BB602C443F45E4AFC1$3591851B327BB85A114BD73D51B80AF58E942002B9612F82", "scottscottscott1234"},
{"$o3logon$scott$4488AFD7905E9966912CA680A3C0A23E$628FBAC5CF0E5548743E16123BF027B9314D7EE8B4E30DB213F683F8D7E786EA", "scottscottscott12345"},
{NULL}
};
typedef struct ora9_salt_t {
int userlen, auth_pass_len;
UTF16 user[MAX_USERNAME_LEN+1];
unsigned char auth_sesskey[16];
unsigned char auth_pass[40];
} ora9_salt;
static ora9_salt *cur_salt;
static UTF16 (*cur_key)[PLAINTEXT_LENGTH + 1];
static char (*plain_key)[PLAINTEXT_LENGTH + 1];
static int *cur_key_len;
static int *cracked, any_cracked;
static DES_key_schedule desschedule1; // key 0x0123456789abcdef
static void init(struct fmt_main *self)
{
DES_set_key((DES_cblock *)"\x01\x23\x45\x67\x89\xab\xcd\xef", &desschedule1);
#ifdef _OPENMP
omp_t = omp_get_max_threads();
self->params.min_keys_per_crypt *= omp_t;
omp_t *= OMP_SCALE;
self->params.max_keys_per_crypt *= omp_t;
#endif
cur_key = mem_calloc(self->params.max_keys_per_crypt,
sizeof(*cur_key));
plain_key = mem_calloc(self->params.max_keys_per_crypt,
sizeof(*plain_key));
cur_key_len = mem_calloc(self->params.max_keys_per_crypt,
sizeof(*cur_key_len));
cracked = mem_calloc(self->params.max_keys_per_crypt,
sizeof(*cracked));
}
static void done(void)
{
MEM_FREE(cracked);
MEM_FREE(cur_key_len);
MEM_FREE(plain_key);
MEM_FREE(cur_key);
}
static int valid(char *ciphertext, struct fmt_main *self)
{
char *cp;
char tmp[32*5+1];
UTF16 cur_key_mixedcase[MAX_USERNAME_LEN+2];
int len, extra;
if (strncmp(ciphertext, FORMAT_TAG, FORMAT_TAG_LEN))
return 0;
ciphertext += FORMAT_TAG_LEN;
cp = strchr(ciphertext, '$');
if (!cp)
return 0;
// make sure username fits in MAX_USERNAME_LEN UTF16
if (cp-ciphertext > sizeof(tmp)-1)
return 0;
memcpy(tmp, ciphertext, cp-ciphertext);
tmp[cp-ciphertext] = 0;
len = enc_to_utf16((UTF16 *)cur_key_mixedcase, MAX_USERNAME_LEN+1, (unsigned char*)tmp, strlen(tmp));
if (len < 0 || (len == 0 && cp-ciphertext)) {
static int error_shown = 0;
#ifdef HAVE_FUZZ
if (options.flags & (FLG_FUZZ_CHK | FLG_FUZZ_DUMP_CHK))
return 0;
#endif
if (!error_shown)
fprintf(stderr, "%s: Input file is not UTF-8. Please use --input-enc to specify a codepage.\n", self->params.label);
error_shown = 1;
return 0;
}
if (len > MAX_USERNAME_LEN)
return 0;
ciphertext = cp+1;
cp = strchr(ciphertext, '$');
if (!cp || cp-ciphertext != 32 || hexlenu(ciphertext, 0) != 32)
return 0;
ciphertext = cp+1;
cp = strchr(ciphertext, '$');
len = strlen(ciphertext);
if (!len || cp || len%16 || hexlenu(ciphertext, &extra) != len || extra)
return 0;
return 1;
}
static char *split(char *ciphertext, int index, struct fmt_main *self)
{
static char out[MAX_HASH_LEN*5+1];
strnzcpy(out, ciphertext, MAX_HASH_LEN+1);
enc_strupper(&out[FORMAT_TAG_LEN]);
return out;
}
static void set_salt(void *salt) {
cur_salt = (ora9_salt *)salt;
}
static void oracle_set_key(char *key, int index) {
UTF16 cur_key_mixedcase[PLAINTEXT_LENGTH+1];
UTF16 *c;
int key_length;
strcpy(plain_key[index], key);
// Can't use enc_to_utf16_be() because we need to do utf16_uc later
key_length = enc_to_utf16(cur_key_mixedcase, PLAINTEXT_LENGTH, (unsigned char*)key, strlen(key));
if (key_length < 0)
key_length = strlen16(cur_key_mixedcase);
// We convert and uppercase in one shot
key_length = utf16_uc(cur_key[index], PLAINTEXT_LENGTH, cur_key_mixedcase, key_length);
// we have no way to 'undo' here, since the expansion is due to single-2-multi expansion in the upcase,
// and we can not 'fix' our password. We simply have to 'not' properly decrypt this one, but protect ourselves.
if (key_length < 0)
key_length *= -1;
cur_key_len[index] = key_length * sizeof(UTF16);
// Now byte-swap to UTF16-BE
c = cur_key[index];
while((*c = *c << 8 | *c >> 8))
c++;
#ifdef DEBUG_ORACLE
dump_stuff_msg("cur_key ", (unsigned char*)cur_key[index], cur_key_len[index]);
#endif
}
static char *get_key(int index) {
return plain_key[index];
}
static int ORACLE_TNS_Create_Key_SHA1 (unsigned char *input, int input_len, const unsigned char *Entropy, int EntropyLen, int desired_keylen, unsigned char *out_key)
{
SHA_CTX ctx;
SHA1_Init (&ctx);
SHA1_Update (&ctx, input, input_len);
SHA1_Update (&ctx, Entropy, EntropyLen);
SHA1_Final (out_key, &ctx);
SHA1_Init (&ctx);
SHA1_Update (&ctx, input, input_len);
SHA1_Update (&ctx, "\x2", 1);
SHA1_Update (&ctx, &out_key[1], 19);
SHA1_Update (&ctx, Entropy, EntropyLen);
SHA1_Final (out_key+20, &ctx);
return 0;
}
static int ORACLE_TNS_Decrypt_3DES_CBC (unsigned char* input, int input_len, const unsigned char key[24], unsigned char *decrypted)
{
DES_key_schedule ks1,ks2,ks3;
unsigned char iv[] = {0x80,0x20,0x40,0x04,0x08,0x02,0x10,0x01};
DES_set_key((DES_cblock*) &key[0], &ks1);
DES_set_key((DES_cblock*) &key[8], &ks2);
DES_set_key((DES_cblock*) &key[16], &ks3);
DES_ede3_cbc_encrypt(input,decrypted,input_len,&ks1,&ks2,&ks3,(DES_cblock*) iv,DES_DECRYPT);
return 0;
}
static unsigned char fixed31 [] = {0xA2,0xFB,0xE6,0xAD,0x4C,0x7D,0x1E,0x3D,
0x6E,0xB0,0xB7,0x6C,0x97,0xEF,0xFF,0x84,
0x44,0x71,0x02,0x84,0xAC,0xF1,0x3B,0x29,
0x5C,0x0F,0x0C,0xB1,0x87,0x75,0xEF};
static unsigned char fixed23 [] = {0xF2,0xFF,0x97,0x87,0x15,0x37,0x07,0x76,
0x07,0x27,0xE2,0x7F,0xA3,0xB1,0xD6,0x73,
0x3F,0x2F,0xD1,0x52,0xAB,0xAC,0xC0};
static int ORACLE_TNS_Decrypt_Password_9i (unsigned char OracleHash[8], unsigned char *auth_sesskey, int auto_sesskeylen, unsigned char *auth_password, int auth_passwordlen, unsigned char *decrypted)
{
unsigned char triple_des_key[64];
unsigned char sesskey[16];
unsigned char obfuscated[256];
int PassLen = auth_passwordlen;
ORACLE_TNS_Create_Key_SHA1 (OracleHash, 8, fixed31, sizeof(fixed31), 24, triple_des_key);
ORACLE_TNS_Decrypt_3DES_CBC (auth_sesskey, 16, triple_des_key, sesskey);
ORACLE_TNS_Create_Key_SHA1 (sesskey, 16, fixed23, sizeof(fixed23), 24, triple_des_key);
ORACLE_TNS_Decrypt_3DES_CBC (auth_password, PassLen, triple_des_key, obfuscated);
//ORACLE_TNS_DeObfuscate (triple_des_key, obfuscated, &PassLen);
memcpy(decrypted, &obfuscated[PassLen-4], 4);
memcpy(&decrypted[4], &obfuscated[4], PassLen-4);
return PassLen;
}
static int crypt_all(int *pcount, struct db_salt *salt)
{
const int count = *pcount;
int idx = 0;
if (any_cracked) {
memset(cracked, 0, sizeof(*cracked) * count);
any_cracked = 0;
}
#ifdef DEBUG_ORACLE
dump_stuff_msg("cur_salt ", buf, cur_salt->userlen+key_length);
#endif
#ifdef _OPENMP
#pragma omp parallel for
for (idx = 0; idx < count; idx++)
#endif
{
unsigned char buf[256], buf1[256];
unsigned int l;
uint32_t iv[2];
DES_key_schedule desschedule2;
l = cur_salt->userlen + cur_key_len[idx];
memcpy(buf, cur_salt->user, cur_salt->userlen);
memcpy(buf + cur_salt->userlen, cur_key[idx], cur_key_len[idx]);
iv[0] = iv[1] = 0;
DES_ncbc_encrypt((unsigned char *)buf, buf1, l, &desschedule1, (DES_cblock *) iv, DES_ENCRYPT);
DES_set_key((DES_cblock *)iv, &desschedule2);
iv[0] = iv[1] = 0;
DES_ncbc_encrypt((unsigned char *)buf, buf1, l, &desschedule2, (DES_cblock *) iv, DES_ENCRYPT);
#ifdef DEBUG_ORACLE
dump_stuff_msg(" iv (the hash key) ", (unsigned char*)&iv[0], 8);
#endif
ORACLE_TNS_Decrypt_Password_9i ((unsigned char*)iv, cur_salt->auth_sesskey, 16, cur_salt->auth_pass, cur_salt->auth_pass_len, buf);
if (!strncmp((char*)buf, plain_key[idx], strlen(plain_key[idx])))
{
cracked[idx] = 1;
#ifdef _OPENMP
#pragma omp atomic
#endif
any_cracked |= 1;
}
}
return count;
}
static void *get_salt(char *ciphertext)
{
static ora9_salt salt;
UTF8 tmp[MAX_USERNAME_LEN*5+1];
char *cp;
memset(&salt, 0, sizeof(salt));
ciphertext += FORMAT_TAG_LEN;
cp = strchr(ciphertext, '$');
strncpy((char*)tmp, ciphertext, cp-ciphertext);
tmp[cp-ciphertext] = 0;
salt.userlen = enc_to_utf16_be(salt.user, MAX_USERNAME_LEN, tmp, cp-ciphertext);
if (salt.userlen < 0)
salt.userlen = strlen16(salt.user);
salt.userlen *= 2;
base64_convert(cp+1,e_b64_hex,32,salt.auth_sesskey,e_b64_raw,16,0,0);
cp = strchr(cp+1, '$') + 1;
salt.auth_pass_len = strlen(cp)/2;
base64_convert(cp,e_b64_hex,salt.auth_pass_len*2,salt.auth_pass,e_b64_raw,salt.auth_pass_len,0,0);
return &salt;
}
// Public domain hash function by DJ Bernstein (salt is a username)
static int salt_hash(void *salt)
{
UTF16 *s = ((UTF16*)salt) + 1;
unsigned int hash = 5381;
while (*s)
hash = ((hash << 5) + hash) ^ *s++;
return hash & (SALT_HASH_SIZE - 1);
}
static int cmp_all(void *binary, int count)
{
return any_cracked;
}
static int cmp_one(void *binary, int count)
{
return cracked[count];
}
static int cmp_exact(char *source, int index)
{
return 1;
}
struct fmt_main fmt_o3logon = {
{
FORMAT_LABEL,
FORMAT_NAME,
ALGORITHM_NAME,
BENCHMARK_COMMENT,
BENCHMARK_LENGTH,
0,
PLAINTEXT_LENGTH,
BINARY_SIZE,
BINARY_ALIGN,
SALT_SIZE,
SALT_ALIGN,
MIN_KEYS_PER_CRYPT,
MAX_KEYS_PER_CRYPT,
FMT_8_BIT | FMT_UNICODE | FMT_UTF8 | FMT_SPLIT_UNIFIES_CASE | FMT_CASE | FMT_OMP,
{ NULL },
{ FORMAT_TAG },
tests
}, {
init,
done,
fmt_default_reset,
fmt_default_prepare,
valid,
split,
fmt_default_binary,
get_salt,
{ NULL },
fmt_default_source,
{
fmt_default_binary_hash
},
salt_hash,
NULL,
set_salt,
oracle_set_key,
get_key,
fmt_default_clear_keys,
crypt_all,
{
fmt_default_get_hash
},
cmp_all,
cmp_one,
cmp_exact
}
};
#endif /* plugin stanza */
|
GB_Matrix_diag.c | //------------------------------------------------------------------------------
// GB_Matrix_diag: construct a diagonal matrix from a vector
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2022, All Rights Reserved.
// SPDX-License-Identifier: Apache-2.0
//------------------------------------------------------------------------------
#define GB_FREE_WORKSPACE \
{ \
GB_Matrix_free (&T) ; \
}
#define GB_FREE_ALL \
{ \
GB_FREE_WORKSPACE ; \
GB_phbix_free (C) ; \
}
#include "GB_diag.h"
GrB_Info GB_Matrix_diag // build a diagonal matrix from a vector
(
GrB_Matrix C, // output matrix
const GrB_Matrix V_in, // input vector (as an n-by-1 matrix)
int64_t k,
GB_Context Context
)
{
//--------------------------------------------------------------------------
// check inputs
//--------------------------------------------------------------------------
GrB_Info info ;
ASSERT_MATRIX_OK (C, "C input for GB_Matrix_diag", GB0) ;
ASSERT_MATRIX_OK (V_in, "V input for GB_Matrix_diag", GB0) ;
ASSERT (GB_VECTOR_OK (V_in)) ; // V_in is a vector on input
ASSERT (!GB_aliased (C, V_in)) ; // C and V_in cannot be aliased
ASSERT (!GB_IS_HYPERSPARSE (V_in)) ; // vectors cannot be hypersparse
struct GB_Matrix_opaque T_header ;
GrB_Matrix T = NULL ;
GrB_Type ctype = C->type ;
GrB_Type vtype = V_in->type ;
int64_t n = V_in->vlen + GB_IABS (k) ; // C must be n-by-n
ASSERT (GB_NROWS (C) == GB_NCOLS (C))
ASSERT (GB_NROWS (C) == n)
ASSERT (GB_Type_compatible (ctype, vtype)) ;
//--------------------------------------------------------------------------
// finish any pending work in V_in and clear the output matrix C
//--------------------------------------------------------------------------
GB_MATRIX_WAIT (V_in) ;
GB_phbix_free (C) ;
//--------------------------------------------------------------------------
// ensure V is not bitmap
//--------------------------------------------------------------------------
GrB_Matrix V ;
if (GB_IS_BITMAP (V_in))
{
// make a deep copy of V_in and convert to CSC
// set T->iso = V_in->iso OK
GB_CLEAR_STATIC_HEADER (T, &T_header) ;
GB_OK (GB_dup_worker (&T, V_in->iso, V_in, true, NULL, Context)) ;
GB_OK (GB_convert_bitmap_to_sparse (T, Context)) ;
V = T ;
}
else
{
// use V_in as-is
V = V_in ;
}
//--------------------------------------------------------------------------
// allocate C as sparse or hypersparse with vnz entries and vnz vectors
//--------------------------------------------------------------------------
// C is sparse if V is dense and k == 0, and hypersparse otherwise
const int64_t vnz = GB_nnz (V) ;
const bool V_is_full = GB_is_dense (V) ;
const int C_sparsity = (V_is_full && k == 0) ? GxB_SPARSE : GxB_HYPERSPARSE;
const bool C_iso = V->iso ;
if (C_iso)
{
GBURBLE ("(iso diag) ") ;
}
const bool csc = C->is_csc ;
const float bitmap_switch = C->bitmap_switch ;
const int sparsity_control = C->sparsity_control ;
// set C->iso = C_iso OK
GB_OK (GB_new_bix (&C, // existing header
ctype, n, n, GB_Ap_malloc, csc, C_sparsity, false,
C->hyper_switch, vnz, vnz, true, C_iso, Context)) ;
C->sparsity_control = sparsity_control ;
C->bitmap_switch = bitmap_switch ;
//--------------------------------------------------------------------------
// handle the CSR/CSC format of C and determine position of diagonal
//--------------------------------------------------------------------------
if (!csc)
{
// The kth diagonal of a CSC matrix is the same as the (-k)th diagonal
// of the CSR format, so if C is CSR, negate the value of k. Then
// treat C as if it were CSC in the rest of this method.
k = -k ;
}
int64_t kpositive, knegative ;
if (k >= 0)
{
kpositive = k ;
knegative = 0 ;
}
else
{
kpositive = 0 ;
knegative = -k ;
}
//--------------------------------------------------------------------------
// get the contents of C and determine # of threads to use
//--------------------------------------------------------------------------
GB_GET_NTHREADS_MAX (nthreads_max, chunk, Context) ;
int nthreads = GB_nthreads (vnz, chunk, nthreads_max) ;
int64_t *restrict Cp = C->p ;
int64_t *restrict Ch = C->h ;
int64_t *restrict Ci = C->i ;
GB_Type_code vcode = vtype->code ;
GB_Type_code ccode = ctype->code ;
size_t vsize = vtype->size ;
//--------------------------------------------------------------------------
// copy the contents of V into the kth diagonal of C
//--------------------------------------------------------------------------
if (C_sparsity == GxB_SPARSE)
{
//----------------------------------------------------------------------
// V is full, or can be treated as full, and k == 0
//----------------------------------------------------------------------
// C->x = (ctype) V->x
GB_cast_matrix (C, V, Context) ;
// construct Cp and Ci
int64_t p ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < vnz ; p++)
{
Cp [p] = p ;
Ci [p] = p ;
}
}
else if (V_is_full)
{
//----------------------------------------------------------------------
// V is full, or can be treated as full, and k != 0
//----------------------------------------------------------------------
// C->x = (ctype) V->x
GB_cast_matrix (C, V, Context) ;
// construct Cp, Ch, and Ci
int64_t p ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < vnz ; p++)
{
Cp [p] = p ;
Ch [p] = p + kpositive ;
Ci [p] = p + knegative ;
}
}
else
{
//----------------------------------------------------------------------
// V is sparse
//----------------------------------------------------------------------
// C->x = (ctype) V->x
GB_cast_matrix (C, V, Context) ;
int64_t *restrict Vi = V->i ;
// construct Cp, Ch, and Ci
int64_t p ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < vnz ; p++)
{
Cp [p] = p ;
Ch [p] = Vi [p] + kpositive ;
Ci [p] = Vi [p] + knegative ;
}
}
//--------------------------------------------------------------------------
// finalize the matrix C
//--------------------------------------------------------------------------
Cp [vnz] = vnz ;
C->nvec = vnz ;
C->nvec_nonempty = vnz ;
C->magic = GB_MAGIC ;
//--------------------------------------------------------------------------
// free workspace, conform C to its desired format, and return result
//--------------------------------------------------------------------------
GB_FREE_WORKSPACE ;
ASSERT_MATRIX_OK (C, "C before conform for GB_Matrix_diag", GB0) ;
GB_OK (GB_conform (C, Context)) ;
ASSERT_MATRIX_OK (C, "C output for GB_Matrix_diag", GB0) ;
return (GrB_SUCCESS) ;
}
|
solution4b.c | # include <stdio.h>
# include <stdlib.h>
# include <omp.h>
/*
* Parallelisation of this loop
*
* for (i = 1; i < n; i++)
* a[i] = a[i] + a[i - 1]
*
* with OpenMP (see the parallel region).
*
* Overhead: In the parallel version the total number of additions almost
* doubles.
*/
void get_omp_range(const int n, int *i1, int *i2, int *i_thread);
int main(int argc, char *argv[])
{
const int n = 40;
int a[n];
int i, i1, i2, i_thread, n_thread;
int *psum;
for (i = 0; i < n; i++)
a[i] = i;
n_thread = omp_get_max_threads();
psum = (int *) malloc(n_thread * sizeof(int));
#pragma omp parallel private(i, i1, i2, i_thread)
{
get_omp_range(n, &i1, &i2, &i_thread);
for (i = i1 + 1; i <= i2; i++)
a[i] = a[i] + a[i - 1];
psum[i_thread] = a[i2];
#pragma omp barrier
if (i_thread == 0)
for (i = 1; i < n_thread; i++)
psum[i] = psum[i] + psum[i - 1];
#pragma omp barrier
if (i_thread > 0)
for (i = i1; i <= i2; i++)
a[i] = a[i] + psum[i_thread - 1];
}
for (i = 0; i < n; i++)
printf("%d\n", a[i]);
return 0;
}
void get_omp_range(const int n, int *i1, int *i2, int *i_thread)
{
int chunk, rest;
int n_thread = omp_get_num_threads();
*i_thread = omp_get_thread_num();
chunk = n / n_thread;
rest = n % n_thread;
if (*i_thread < rest) {
chunk++;
*i1 = chunk * *i_thread;
} else {
*i1 = chunk * *i_thread + rest;
}
*i2 = *i1 + chunk - 1;
}
|
GB_unop__ceil_fp64_fp64.c | //------------------------------------------------------------------------------
// GB_unop: hard-coded functions for each built-in unary operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2020, All Rights Reserved.
// http://suitesparse.com See GraphBLAS/Doc/License.txt for license.
//------------------------------------------------------------------------------
// If this file is in the Generated/ folder, do not edit it (auto-generated).
#include "GB.h"
#ifndef GBCOMPACT
#include "GB_control.h"
#include "GB_unop__include.h"
// C=unop(A) is defined by the following types and operators:
// op(A) function: GB_unop_apply__ceil_fp64_fp64
// op(A') function: GB_unop_tran__ceil_fp64_fp64
// C type: double
// A type: double
// cast: double cij = aij
// unaryop: cij = ceil (aij)
#define GB_ATYPE \
double
#define GB_CTYPE \
double
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA) \
double aij = Ax [pA]
#define GB_CX(p) Cx [p]
// unary operator
#define GB_OP(z, x) \
z = ceil (x) ;
// casting
#define GB_CAST(z, aij) \
double z = aij ;
// cij = op (aij)
#define GB_CAST_OP(pC,pA) \
{ \
/* aij = Ax [pA] */ \
double aij = Ax [pA] ; \
/* Cx [pC] = op (cast (aij)) */ \
double z = aij ; \
Cx [pC] = ceil (z) ; \
}
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_CEIL || GxB_NO_FP64)
//------------------------------------------------------------------------------
// Cx = op (cast (Ax)): apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_unop_apply__ceil_fp64_fp64
(
double *Cx, // Cx and Ax may be aliased
const double *Ax,
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t p ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
double aij = Ax [p] ;
double z = aij ;
Cx [p] = ceil (z) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (cast (A')): transpose, typecast, and apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_unop_tran__ceil_fp64_fp64
(
GrB_Matrix C,
const GrB_Matrix A,
int64_t *GB_RESTRICT *Rowcounts,
GBI_single_iterator Iter,
const int64_t *GB_RESTRICT A_slice,
int naslice
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#define GB_PHASE_2_OF_2
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
IndexLinear.c | #ifndef TH_GENERIC_FILE
#define TH_GENERIC_FILE "generic/IndexLinear.c"
#else
#ifdef _OPENMP
#include <omp.h>
#endif
/* Threshold used to trigger multithreading */
#ifndef THNN_SPARSE_OMP_THRESHOLD
#define THNN_SPARSE_OMP_THRESHOLD 100000
#endif
/* Threshold used to trigger BLAS axpy call */
#ifndef THNN_SPARSE_OUTDIM_THRESHOLD
#define THNN_SPARSE_OUTDIM_THRESHOLD 49
#endif
/* sign MACRO */
#ifndef THNN_INDEXLINEAR_SIGN
#define THNN_INDEXLINEAR_SIGN(a) ( ( (a) < 0 ) ? -1 : ( (a) > 0 ) )
#endif
static bool THNN_(checkKeysValues)(THLongTensor* keys, THTensor* values)
{
return THLongTensor_size(keys, 0) == THTensor_(nElement)(values)
&& THTensor_(nDimension)(values) == 1
&& THLongTensor_nDimension(keys) == 1;
}
void THNN_(IndexLinear_updateOutput)(
THNNState *state,
THLongTensor *keys,
long keysOffset,
THTensor *values,
THLongTensor *sizes,
THLongTensor *cumSumSizes,
THTensor *output,
THTensor *weight,
THTensor *bias,
THTensor *normalizedValues,
int train)
{
/* Retrieve all the dimensions of the problem */
long batchSize = THLongTensor_size(sizes, 0);
long keysSize = THLongTensor_size(keys, 0);
long outDim = THTensor_(size)(bias, 0);
long woutDim = THTensor_(size)(weight, 1);
int maxNormalize = woutDim - outDim;
long* sizesData = THLongTensor_data(sizes);
long* cumSumSizesData = THLongTensor_data(cumSumSizes);
/* Define/resize the normalized values tensor if maxNormalize is > 0 */
real* normalizedValuesData = NULL;
if (maxNormalize)
{
THTensor_(resize1d)(normalizedValues, keysSize);
normalizedValuesData = THTensor_(data)(normalizedValues);
}
/* Resize the output */
THTensor_(resize2d)(output, batchSize, outDim);
/* Access the storage data/strides */
real* outputData = THTensor_(data)(output);
real* valuesData = THTensor_(data)(values);
real* weightData = THTensor_(data)(weight);
long weightStride0 = weight->stride[0];
real* biasData = THTensor_(data)(bias);
long* keysData = THLongTensor_data(keys);
/* Make sure these inputs are contiguous to accelerate computations */
THArgCheck(THLongTensor_isContiguous(keys), 1, "keys vector must be contiguous");
THArgCheck(THTensor_(isContiguous)(values), 3, "values vector must be contiguous");
THArgCheck(THTensor_(isContiguous)(output), 6, "output vector must be contiguous");
THArgCheck(THTensor_(isContiguous)(weight), 7, "weight matrix must be contiguous");
THArgCheck(THTensor_(isContiguous)(bias), 8, "bias vector must be contiguous");
THArgCheck(THNN_(checkKeysValues)(keys, values), 1, "Keys and values should have the same number of elements");
THArgCheck(THTensor_(isContiguous)(normalizedValues), 9, "normalizedValues vector must be contiguous");
long i,j,k;
/* Separate cases: output dimension is == 1, or > 1
* This allows for some optimizations. */
if (outDim == 1)
{
THVector_(fill)(outputData, *biasData, batchSize);
if (maxNormalize)
{
/* Parallelize on the batch itself */
#pragma omp parallel \
for private(i,j) \
firstprivate(outDim, keysOffset, \
weightData, keysData, \
valuesData, outputData, \
cumSumSizesData, sizesData) \
schedule(static) \
if(keysSize*outDim > THNN_SPARSE_OMP_THRESHOLD && batchSize > 1)
for (j = 0; j < batchSize; j++)
{
real* loutputData = outputData + j;
real val = 0;
real absVal = 0;
long offset = j == 0 ? 0 : cumSumSizesData[j - 1];
for (i = 0; i < sizesData[j]; i++)
{
long woffset = weightStride0*(keysData[offset] + keysOffset);
absVal = fabs(valuesData[offset]);
if (train)
{
if (absVal > weightData[woffset])
{
weightData[woffset] = absVal;
weightData[woffset+1] = 1/absVal;
}
/*
* The following can be used to scale the size of the updates
* depending on some rule, e.g. the frequency of a feature, ...
* This is used at update time.
* TODO: implement a smarter update scale.
*/
weightData[woffset+2] = 1;
}
normalizedValuesData[offset] = (absVal > weightData[woffset] ? THNN_INDEXLINEAR_SIGN(valuesData[offset]):valuesData[offset]*weightData[woffset+1]) + weightData[woffset+3];
val += normalizedValuesData[offset] * weightData[woffset+maxNormalize];
offset++;
}
*loutputData += val;
}
}
else
{
/* Parallelize on the batch itself */
#pragma omp parallel \
for private(i,j) \
firstprivate(outDim, weightData, \
keysData, valuesData, \
outputData, cumSumSizesData, \
sizesData) \
schedule(static) \
if(keysSize*outDim > THNN_SPARSE_OMP_THRESHOLD && batchSize > 1)
for (j = 0; j < batchSize; j++)
{
long offset = j == 0 ? 0 : cumSumSizesData[j - 1];
real* loutputData = outputData + j;
real val = 0;
for (i = 0; i < sizesData[j]; i++)
{
val += weightData[weightStride0*(keysData[offset] + keysOffset)] * valuesData[offset];
offset++;
}
*loutputData += val;
}
}
}
else {
#pragma omp parallel \
for private(i,j,k) \
firstprivate(outDim, weightData, \
keysData, valuesData, \
biasData, outputData, \
cumSumSizesData, sizesData) \
schedule(static) \
if(keysSize*outDim > THNN_SPARSE_OMP_THRESHOLD && batchSize > 1)
for (j = 0; j < batchSize; j++)
{
long offset = j == 0 ? 0 : cumSumSizesData[j - 1];
real val = 0;
real* loutputData = outputData + j*outDim;
real* lweightData = weightData;
memcpy(loutputData, biasData, outDim*sizeof(real));
for (i = 0; i < sizesData[j]; i++)
{
real val;
long woffset = weightStride0*(keysData[offset] + keysOffset);
if (maxNormalize)
{
val = valuesData[offset];
real absVal = fabs(val);
if (train)
{
if (absVal > weightData[woffset])
{
weightData[woffset] = absVal;
weightData[woffset+1] = 1/absVal;
}
/*
* The following can be used to scale the size of the updates
* depending on some rule, e.g. the frequency of a feature, ...
* The commented section thereafter is just an example of what can be done:
*
*```
* weightData[woffset+2] = weightData[woffset+2]==0?1:(weightData[woffset+2] / (weightData[woffset+2] + 1));
* real alpha = 1;
* real beta = 0.01;
* real gamma = 1 - 0.000001;
* real l = weightData[woffset+2]==0?1/gamma:(weightData[woffset+2] - beta) / (alpha - beta);
* l = gamma*l;
* weightData[woffset+2] = (alpha-beta)*l + beta;
* ```
*
* TODO: implement a smarter update scale.
*/
weightData[woffset+2] = 1;
}
/* Normalize + Clamp */
val = (absVal > weightData[woffset] ? THNN_INDEXLINEAR_SIGN(val):val*weightData[woffset+1]) + weightData[woffset+3];
normalizedValuesData[offset] = val;
lweightData = weightData + woffset + maxNormalize;
}
else
{
val = valuesData[offset];
lweightData = weightData + woffset;
}
if (outDim > THNN_SPARSE_OUTDIM_THRESHOLD)
{
THBlas_(axpy)(outDim, val, lweightData, 1, loutputData, 1);
}
else
{
for (k=0; k < outDim; k++)
{
loutputData[k] += lweightData[k] * val;
}
}
offset++;
}
}
}
return;
}
void THNN_(IndexLinear_updateParameters)(
THNNState *state,
THTensor *gradWeight,
THTensor *gradBias,
THTensor *weight,
THTensor *bias,
THLongTensor *runningKeys,
THLongTensor *cumSumSizes,
long keysOffset,
accreal weightDecay_,
accreal learningRate_)
{
real weightDecay = TH_CONVERT_ACCREAL_TO_REAL(weightDecay_);
real learningRate = TH_CONVERT_ACCREAL_TO_REAL(learningRate_);
/* Retrieve all the dimensions of the problem */
long outDim = THTensor_(size)(bias, 0);
long woutDim = THTensor_(size)(weight, 1);
int maxNormalize = woutDim - outDim;
long keysSize = THLongTensor_size(runningKeys, 0);
/* Access the storage data/strides */
real* gradWeightData = THTensor_(data)(gradWeight);
real* weightData = THTensor_(data)(weight);
long weightStride0 = weight->stride[0];
real* gradBiasData = THTensor_(data)(gradBias);
real* biasData = THTensor_(data)(bias);
long* keysData = THLongTensor_data(runningKeys);
/* Make sure these inputs are contiguous to accelerate computations */
THArgCheck(THTensor_(isContiguous)(gradWeight), 1, "gradWeight must be contiguous");
THArgCheck(THTensor_(isContiguous)(gradBias), 2, "gradBias vector must be contiguous");
THArgCheck(THTensor_(isContiguous)(weight), 3, "gradBias vector must be contiguous");
THArgCheck(THTensor_(isContiguous)(bias), 4, "gradBias vector must be contiguous");
THArgCheck(THLongTensor_isContiguous(runningKeys), 5, "keys vector must be contiguous");
int j,k;
long offset = 0;
/* Update the bias first */
THVector_(cadd)(biasData, biasData, gradBiasData, -learningRate, outDim);
/* Separate cases: output dimension is == 1, or > 1
* This allows for some optimizations.
* No multithreading here as this could
* corrupt the results (hogwild style) */
if (outDim == 1)
{
if (maxNormalize)
{
if (weightDecay)
{
for (j = 0; j < keysSize; j++)
{
long woffset = weightStride0*(keysData[j] + keysOffset) + maxNormalize;
real lr = learningRate*weightData[woffset-2];
weightData[woffset-1] -= weightData[woffset]*gradWeightData[2*j]*lr;
weightData[woffset] -= gradWeightData[2*j+1]*lr - weightDecay * weightData[woffset-2] * weightData[woffset];
}
}
else
{
for (j = 0; j < keysSize; j++)
{
long woffset = weightStride0*(keysData[j] + keysOffset) + maxNormalize;
real lr = learningRate*weightData[woffset-2];
weightData[woffset-1] -= weightData[woffset]*gradWeightData[2*j]*lr;
weightData[woffset] -= gradWeightData[2*j+1]*lr;
}
}
}
else
{
if (weightDecay)
{
for (j = 0; j < keysSize; j++)
{
long woffset = weightStride0*(keysData[j] + keysOffset);
weightData[woffset] -= gradWeightData[j]*learningRate + weightDecay * weightData[woffset];
}
}
else
{
for (j = 0; j < keysSize; j++)
{
weightData[weightStride0*(keysData[j] + keysOffset)] -= gradWeightData[j]*learningRate;
}
}
}
}
else
{
for (j = 0; j < keysSize; j++)
{
real lr = learningRate;
real wd = weightDecay;
real* lweightData;
long woffset = weightStride0*(keysData[j] + keysOffset);
real* lgradWeightData = gradWeightData + j*outDim;
if (maxNormalize)
{
lgradWeightData += j*outDim;
/* weightData[woffset + 2] */
lweightData = weightData + woffset + maxNormalize - 2;
lr = lr*lweightData[0];
wd = weightDecay*lweightData[0];
/* weightData[woffset + 3] */
lweightData++;
for (k=0; k < outDim; k++)
{
lweightData[0] -= lgradWeightData[k]*lweightData[k+1]*lr;
}
lweightData++;
lgradWeightData += outDim;
}
else
{
lweightData = weightData + woffset;
}
/* We do sparse weight decay.
* We think it makes more sense. */
if (weightDecay)
{
for (k=0; k < outDim; k++)
{
lweightData[k] -= lweightData[k]*wd;
}
}
if (outDim > THNN_SPARSE_OUTDIM_THRESHOLD)
{
THBlas_(axpy)(outDim, -lr, lgradWeightData, 1, lweightData, 1);
}
else
{
for (k=0; k < outDim; k++)
{
lweightData[k] -= lgradWeightData[k]*lr;
}
}
}
}
}
void THNN_(IndexLinear_accUpdateGradParameters)(
THNNState *state,
THLongTensor *keys,
long keysOffset,
THTensor *values,
THLongTensor *sizes,
THLongTensor *cumSumSizes,
THTensor *gradOutput,
THTensor *weight,
THTensor *bias,
accreal weightDecay_,
accreal scale_)
{
real weightDecay = TH_CONVERT_ACCREAL_TO_REAL(weightDecay_);
real scale = TH_CONVERT_ACCREAL_TO_REAL(scale_);
/* Retrieve all the dimensions of the problem */
long batchSize = THLongTensor_size(sizes, 0);
long keysSize = THLongTensor_size(keys, 0);
long outDim = THTensor_(size)(bias, 0);
long woutDim = THTensor_(size)(weight, 1);
int maxNormalize = woutDim - outDim;
THArgCheck(THNN_(checkKeysValues)(keys, values), 1, "Keys and values should have the same number of elements");
/* Access the storage data/strides */
real* gradOutputData = THTensor_(data)(gradOutput);
real* valuesData =THTensor_(data)(values);
real* weightData = THTensor_(data)(weight);
real* biasData = THTensor_(data)(bias);
long weightStride0 = weight->stride[0];
long biasStride = bias->stride[0];
long* keysData = THLongTensor_data(keys);
long* sizesData = THLongTensor_data(sizes);
/* Make sure these inputs are contiguous to accelerate computations */
THArgCheck(THLongTensor_isContiguous(keys), 1, "keys vector must be contiguous");
THArgCheck(THTensor_(isContiguous)(values), 3, "values vector must be contiguous");
THArgCheck(THTensor_(isContiguous)(gradOutput), 6, "gradOutput vector must be contiguous");
THArgCheck(THTensor_(isContiguous)(weight), 7, "weight matrix must be contiguous");
THArgCheck(THTensor_(isContiguous)(bias), 8, "bias matrix must be contiguous");
int i,j,k;
/* Separate cases: output dimension is == 1, or > 1
* This allows for some optimizations.
* No multithreading here as this could
* corrupt the results (hogwild style) */
if (outDim == 1)
{
if (maxNormalize)
{
long offset = 0;
for (j = 0; j < batchSize; j++)
{
real* lgradOutputData = gradOutputData + j;
*biasData -= *lgradOutputData * scale;
real val = *lgradOutputData * scale;
real* lweightData = weightData;
for (i = 0; i < sizesData[j]; i++)
{
long idx = weightStride0*(keysData[offset] + keysOffset) + maxNormalize;
weightData[idx-1] -= weightData[idx]*val*weightData[idx-2];
weightData[idx] -= (val*valuesData[offset] - weightDecay * weightData[idx])*weightData[idx-2];
offset++;
}
}
offset = 0;
for (j = 0; j < batchSize; j++)
{
real* lweightData = weightData;
for (i = 0; i < sizesData[j]; i++)
{
long idx = weightStride0*(keysData[offset] + keysOffset) + maxNormalize;
weightData[idx-2] = 0;
offset++;
}
}
}
else
{
if (weightDecay)
{
long offset = 0;
for (j = 0; j < batchSize; j++)
{
real* lgradOutputData = gradOutputData + j;
*biasData -= *lgradOutputData * scale;
real val = *lgradOutputData * scale;
real* lweightData = weightData;
for (i = 0; i < sizesData[j]; i++)
{
long idx = weightStride0*(keysData[offset] + keysOffset);
weightData[idx] -= val * valuesData[offset] + weightData[idx] * weightDecay;
offset++;
}
}
}
else
{
long offset = 0;
for (j = 0; j < batchSize; j++)
{
real val = gradOutputData[j] * scale;
for (i = 0; i < sizesData[j]; i++)
{
weightData[(keysData[offset] + keysOffset)*weightStride0] -= val * valuesData[offset];
offset++;
}
*biasData -= val;
}
}
}
}
else {
long offset = 0;
for (j = 0; j < batchSize; j++)
{
real val = 0;
real* lgradOutputData = gradOutputData + j*outDim;
real* lweightData = weightData;
THVector_(cadd)(biasData, biasData, lgradOutputData, -scale, outDim);
for (i = 0; i < sizesData[j]; i++)
{
real val = valuesData[offset] * scale;
real wd = weightDecay;
// Max normalize case
if (maxNormalize)
{
lweightData = weightData + weightStride0*(keysData[offset] + keysOffset) + (maxNormalize-2);
val *= lweightData[0];
wd *= lweightData[0];
for (k=0; k < outDim; k++)
{
lweightData[1] -= lweightData[k+2]*scale*lgradOutputData[k]*lweightData[0];
}
lweightData += 2;
}
else
{
lweightData = weightData + weightStride0*(keysData[offset] + keysOffset);
}
/* We do sparse weight decay.
* We think it makes more sense. */
if (weightDecay)
{
if (outDim > THNN_SPARSE_OUTDIM_THRESHOLD)
{
THBlas_(axpy)(outDim, -wd, lweightData, 1, lweightData, 1);
}
else
{
for (k=0; k < outDim; k++)
{
lweightData[k] -= wd * lweightData[k];
}
}
}
if (outDim > THNN_SPARSE_OUTDIM_THRESHOLD)
{
THBlas_(axpy)(outDim, -val, lgradOutputData, 1, lweightData, 1);
}
else
{
for (k=0; k < outDim; k++)
{
lweightData[k] -= val * lgradOutputData[k];
}
}
offset++;
}
}
/* Max Normalize case:
* Reset the smart update scaling if
* one does it batch-wise.
* TODO: Decide what to do with that piece of code.
* NB: If the code belowe is uncommented, so should the commented
* code in IndexLinear:zeroGradParameters() */
/*
if (maxNormalize)
{
offset = 0;
for (j = 0; j < batchSize; j++)
{
real* lweightData = weightData;
for (i = 0; i < sizesData[j]; i++)
{
real val = valuesData[offset] * scale;
real wd = weightDecay;
lweightData = weightData + weightStride0*(keysData[offset] + keysOffset) + (maxNormalize-2);
lweightData[0] = 0;
offset++;
}
}
}
*/
}
return;
}
void THNN_(IndexLinear_accGradParameters)(
THNNState *state,
THLongTensor *keys,
long keysOffset,
THTensor *values,
THLongTensor *sizes,
THLongTensor *cumSumSizes,
THTensor *gradOutput,
THTensor *gradWeight,
THTensor *gradBias,
THTensor *weight,
THTensor *bias,
THTensor *valuesBuffer,
accreal weightDecay_,
accreal scale_)
{
real weightDecay = TH_CONVERT_ACCREAL_TO_REAL(weightDecay_);
real scale = TH_CONVERT_ACCREAL_TO_REAL(scale_);
/* Retrieve all the dimensions of the problem */
long batchSize = THLongTensor_size(sizes, 0);
long keysSize = THLongTensor_size(keys, 0);
long outDim = THTensor_(size)(bias, 0);
long woutDim = THTensor_(size)(weight, 1);
long maxNormalize = (woutDim - outDim) > 0 ?1:0;
THArgCheck(THNN_(checkKeysValues)(keys, values), 1, "Keys and values should have the same number of elements");
long* sizesData = THLongTensor_data(sizes);
/* COmpute the cumulative sizes */
THLongTensor* cumSizes = THLongTensor_new();
THLongTensor_cumsum(cumSizes, sizes, 0);
long* cumSizesData = THLongTensor_data(cumSizes);
/* Resize the gradWeight buffer to keep it dense.
* That speeds up updates A LOT assuming random mem access. */
THTensor_(resize2d)(gradWeight, keysSize, outDim * (maxNormalize>0?2:1));
/* Access the storage data/strides */
real* gradOutputData = THTensor_(data)(gradOutput);
real* valuesData =THTensor_(data)(values);
real* gradWeightData = THTensor_(data)(gradWeight);
real* weightData = THTensor_(data)(weight);
real* gradBiasData = THTensor_(data)(gradBias);
long gradWeightStride0 = gradWeight->stride[0];
long weightStride0 = weight->stride[0];
long* keysData = THLongTensor_data(keys);
/* Make sure these inputs are contiguous to accelerate computations */
THArgCheck(THLongTensor_isContiguous(keys), 1, "keys vector must be contiguous");
THArgCheck(THTensor_(isContiguous)(values), 3, "values vector must be contiguous");
THArgCheck(THTensor_(isContiguous)(gradOutput), 6, "gradOutput vector must be contiguous");
THArgCheck(THTensor_(isContiguous)(gradWeight), 7, "gradWeight must be contiguous");
THArgCheck(THTensor_(isContiguous)(gradBias), 8, "gradBias vector must be contiguous");
THArgCheck(THTensor_(isContiguous)(weight), 9, "weight must be contiguous");
THArgCheck(THTensor_(isContiguous)(bias), 10, "bias vector must be contiguous");
THArgCheck(THTensor_(isContiguous)(valuesBuffer), 11, "valuesBuffer must be contiguous");
int i,j,k;
/* Separate cases: output dimension is == 1, or > 1
* This allows for some optimizations.
* No multithreading here as this could
* corrupt the results (hogwild style) */
if (outDim == 1)
{
for (j = 0; j < batchSize; j++)
{
long offset = j==0?0:cumSizesData[j-1];
real val = gradOutputData[j] * scale;
real* lgradWeightData = gradWeightData + offset;
real* lvaluesData = valuesData + offset;
long end = sizesData[j];
if (maxNormalize)
{
lgradWeightData += offset;
i = 0;
for(;i < end; i++)
{
lgradWeightData[2*i] = val;
lgradWeightData[2*i+1] = val * lvaluesData[i];
}
}
else
{
i = 0;
for(;i < end-4; i += 4)
{
lgradWeightData[i] = val * lvaluesData[i];
lgradWeightData[i+1] = val * lvaluesData[i+1];
lgradWeightData[i+2] = val * lvaluesData[i+2];
lgradWeightData[i+3] = val * lvaluesData[i+3];
}
for(; i < end; i++)
{
lgradWeightData[i] = val * lvaluesData[i];
}
}
*gradBiasData += val;
offset += end;
}
}
else {
for (j = 0; j < batchSize; j++)
{
long offset = j==0?0:cumSizesData[j-1];
real val = 0;
real* lgradOutputData = gradOutputData + j*outDim;
real* lgradWeightData = gradWeightData;
real* lweightData = weightData;
THVector_(cadd)(gradBiasData, gradBiasData, lgradOutputData, scale, outDim);
for (i = 0; i < sizesData[j]; i++)
{
real val = valuesData[offset] * scale;
lgradWeightData = gradWeightData + offset*outDim;
if (maxNormalize)
{
lgradWeightData += offset*outDim;
k = 0;
for(;k < outDim-4; k += 4)
{
lgradWeightData[k] = lgradOutputData[k]*scale;
lgradWeightData[k+1] = lgradOutputData[k+1]*scale;
lgradWeightData[k+2] = lgradOutputData[k+2]*scale;
lgradWeightData[k+3] = lgradOutputData[k+3]*scale;
}
for(; k < outDim; k++)
{
lgradWeightData[k] = lgradOutputData[k]*scale;
}
lgradWeightData += outDim;
}
k = 0;
for(;k < outDim-4; k += 4)
{
lgradWeightData[k] = val * lgradOutputData[k];
lgradWeightData[k+1] = val * lgradOutputData[k+1];
lgradWeightData[k+2] = val * lgradOutputData[k+2];
lgradWeightData[k+3] = val * lgradOutputData[k+3];
}
for(; k < outDim; k++)
{
lgradWeightData[k] = val * lgradOutputData[k];
}
offset++;
}
}
}
THLongTensor_free(cumSizes);
return;
}
#endif
|
Fig_7.11_fibonacciTasks.c | #include <omp.h>
int fib(int n) {
int x, y;
if (n < 2)
return n;
#pragma omp task shared(x)
x = fib(n - 1);
#pragma omp task shared(y)
y = fib(n - 2);
#pragma omp taskwait
return (x + y);
}
int main() {
int NW = 30;
#pragma omp parallel
{
#pragma omp single
fib(NW);
}
}
|
GB_assign_zombie4.c | //------------------------------------------------------------------------------
// GB_assign_zombie4: delete entries in C(i,:) for C_replace_phase
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2021, All Rights Reserved.
// SPDX-License-Identifier: Apache-2.0
//------------------------------------------------------------------------------
// For GrB_Row_assign or GrB_Col_assign, C(i,J)<M,repl>=..., if C_replace is
// true, and mask M is present, then any entry C(i,j) outside the list J must
// be deleted, if M(0,j)=0.
// GB_assign_zombie3 and GB_assign_zombie4 are transposes of each other.
// C must be sparse or hypersparse.
// M can have any sparsity structure: hypersparse, sparse, bitmap, or full
#include "GB_assign.h"
#include "GB_assign_zombie.h"
void GB_assign_zombie4
(
GrB_Matrix C, // the matrix C, or a copy
const GrB_Matrix M,
const bool Mask_comp,
const bool Mask_struct,
const int64_t i, // index of entries to delete
const GrB_Index *J,
const int64_t nJ,
const int Jkind,
const int64_t Jcolon [3],
GB_Context Context
)
{
//--------------------------------------------------------------------------
// check inputs
//--------------------------------------------------------------------------
ASSERT (!GB_IS_FULL (C)) ;
ASSERT (!GB_IS_BITMAP (C)) ;
ASSERT (GB_ZOMBIES_OK (C)) ;
ASSERT (!GB_JUMBLED (C)) ; // binary search on C
ASSERT (!GB_PENDING (C)) ;
ASSERT (!GB_ZOMBIES (M)) ;
ASSERT (!GB_JUMBLED (M)) ;
ASSERT (!GB_PENDING (M)) ;
ASSERT (!GB_aliased (C, M)) ; // NO ALIAS of C==M
//--------------------------------------------------------------------------
// get C
//--------------------------------------------------------------------------
const int64_t *restrict Ch = C->h ;
const int64_t *restrict Cp = C->p ;
const int64_t Cnvec = C->nvec ;
int64_t *restrict Ci = C->i ;
int64_t nzombies = C->nzombies ;
const int64_t zorig = nzombies ;
//--------------------------------------------------------------------------
// get M
//--------------------------------------------------------------------------
const int64_t *restrict Mp = M->p ;
const int64_t *restrict Mh = M->h ;
const int8_t *restrict Mb = M->b ;
const GB_void *restrict Mx = (GB_void *) (Mask_struct ? NULL : (M->x)) ;
const size_t msize = M->type->size ;
const int64_t Mnvec = M->nvec ;
const int64_t Mvlen = M->vlen ;
ASSERT (Mvlen == 1) ;
const bool M_is_hyper = GB_IS_HYPERSPARSE (M) ;
const bool M_is_bitmap = GB_IS_BITMAP (M) ;
const bool M_is_full = GB_IS_FULL (M) ;
//--------------------------------------------------------------------------
// determine the number of threads to use
//--------------------------------------------------------------------------
GB_GET_NTHREADS_MAX (nthreads_max, chunk, Context) ;
int nthreads = GB_nthreads (Cnvec, chunk, nthreads_max) ;
int ntasks = (nthreads == 1) ? 1 : (64 * nthreads) ;
//--------------------------------------------------------------------------
// delete entries in C(i,:)
//--------------------------------------------------------------------------
// The entry C(i,j) is deleted if j is not in the J, and if M(0,j)=0 (if
// the mask is not complemented) or M(0,j)=1 (if the mask is complemented.
int taskid ;
#pragma omp parallel for num_threads(nthreads) schedule(dynamic,1) \
reduction(+:nzombies)
for (taskid = 0 ; taskid < ntasks ; taskid++)
{
int64_t kfirst, klast ;
GB_PARTITION (kfirst, klast, Cnvec, taskid, ntasks) ;
for (int64_t k = kfirst ; k < klast ; k++)
{
//------------------------------------------------------------------
// get C(:,j) and determine if j is outside the list J
//------------------------------------------------------------------
int64_t j = GBH (Ch, k) ;
bool j_outside = !GB_ij_is_in_list (J, nJ, j, Jkind, Jcolon) ;
if (j_outside)
{
//--------------------------------------------------------------
// j is not in J; find C(i,j)
//--------------------------------------------------------------
int64_t pC = Cp [k] ;
int64_t pC_end = Cp [k+1] ;
int64_t pright = pC_end - 1 ;
bool found, is_zombie ;
GB_BINARY_SEARCH_ZOMBIE (i, Ci, pC, pright, found, zorig,
is_zombie) ;
//--------------------------------------------------------------
// delete C(i,j) if found, not a zombie, and M(0,j) allows it
//--------------------------------------------------------------
if (found && !is_zombie)
{
//----------------------------------------------------------
// C(i,j) is a live entry not in the C(I,J) submatrix
//----------------------------------------------------------
// Check the mask M to see if it should be deleted.
bool mij = false ;
if (M_is_bitmap || M_is_full)
{
// M is bitmap/full, no need for GB_lookup
int64_t pM = j ;
mij = GBB (Mb, pM) && GB_mcast (Mx, pM, msize) ;
}
else
{
// M is sparse or hypersparse
int64_t pM, pM_end ;
int64_t pleft = 0 ;
int64_t pright = Mnvec - 1 ;
GB_lookup (M_is_hyper, Mh, Mp, Mvlen, &pleft, pright,
j, &pM, &pM_end) ;
if (pM < pM_end)
{
// found it
mij = GB_mcast (Mx, pM, msize) ;
}
}
if (Mask_comp)
{
// negate the mask if Mask_comp is true
mij = !mij ;
}
if (!mij)
{
// delete C(i,j) by marking it as a zombie
nzombies++ ;
Ci [pC] = GB_FLIP (i) ;
}
}
}
}
}
//--------------------------------------------------------------------------
// return result
//--------------------------------------------------------------------------
C->nzombies = nzombies ;
}
|
GB_binop__isne_fc32.c | //------------------------------------------------------------------------------
// GB_binop: hard-coded functions for each built-in binary operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2021, All Rights Reserved.
// SPDX-License-Identifier: Apache-2.0
//------------------------------------------------------------------------------
// If this file is in the Generated2/ folder, do not edit it
// (it is auto-generated from Generator/*).
#include "GB.h"
#ifndef GBCOMPACT
#include "GB_emult.h"
#include "GB_control.h"
#include "GB_ek_slice.h"
#include "GB_dense.h"
#include "GB_atomics.h"
#include "GB_bitmap_assign_methods.h"
#include "GB_binop__include.h"
// C=binop(A,B) is defined by the following types and operators:
// A+B function (eWiseAdd): GB (_AaddB__isne_fc32)
// A.*B function (eWiseMult): GB (_AemultB_01__isne_fc32)
// A.*B function (eWiseMult): GB (_AemultB_02__isne_fc32)
// A.*B function (eWiseMult): GB (_AemultB_03__isne_fc32)
// A.*B function (eWiseMult): GB (_AemultB_bitmap__isne_fc32)
// A*D function (colscale): GB ((none))
// D*A function (rowscale): GB ((none))
// C+=B function (dense accum): GB (_Cdense_accumB__isne_fc32)
// C+=b function (dense accum): GB (_Cdense_accumb__isne_fc32)
// C+=A+B function (dense ewise3): GB ((none))
// C=A+B function (dense ewise3): GB (_Cdense_ewise3_noaccum__isne_fc32)
// C=scalar+B GB (_bind1st__isne_fc32)
// C=scalar+B' GB (_bind1st_tran__isne_fc32)
// C=A+scalar GB (_bind2nd__isne_fc32)
// C=A'+scalar GB (_bind2nd_tran__isne_fc32)
// C type: GxB_FC32_t
// A type: GxB_FC32_t
// B,b type: GxB_FC32_t
// BinaryOp: cij = GB_FC32_isne (aij, bij)
#define GB_ATYPE \
GxB_FC32_t
#define GB_BTYPE \
GxB_FC32_t
#define GB_CTYPE \
GxB_FC32_t
// true if the types of A and B are identical
#define GB_ATYPE_IS_BTYPE \
1
// true if the types of C and A are identical
#define GB_CTYPE_IS_ATYPE \
1
// true if the types of C and B are identical
#define GB_CTYPE_IS_BTYPE \
1
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA,A_iso) \
GxB_FC32_t aij = GBX (Ax, pA, A_iso)
// bij = Bx [pB]
#define GB_GETB(bij,Bx,pB,B_iso) \
GxB_FC32_t bij = GBX (Bx, pB, B_iso)
// declare scalar of the same type as C
#define GB_CTYPE_SCALAR(t) \
GxB_FC32_t t
// cij = Ax [pA]
#define GB_COPY_A_TO_C(cij,Ax,pA,A_iso) \
cij = GBX (Ax, pA, A_iso)
// cij = Bx [pB]
#define GB_COPY_B_TO_C(cij,Bx,pB,B_iso) \
cij = GBX (Bx, pB, B_iso)
#define GB_CX(p) Cx [p]
// binary operator
#define GB_BINOP(z,x,y,i,j) \
z = GB_FC32_isne (x, y) ;
// true if the binop must be flipped
#define GB_BINOP_FLIP \
0
// op is second
#define GB_OP_IS_SECOND \
0
// do the numerical phases of GB_add and GB_emult
#define GB_PHASE_2_OF_2
// hard-coded loops can be vectorized
#define GB_PRAGMA_SIMD_VECTORIZE GB_PRAGMA_SIMD
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_ISNE || GxB_NO_FC32 || GxB_NO_ISNE_FC32)
//------------------------------------------------------------------------------
// C += A+B, all 3 matrices dense
//------------------------------------------------------------------------------
#if 0
// The op must be MIN, MAX, PLUS, MINUS, RMINUS, TIMES, DIV, or RDIV.
void GB ((none))
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix B,
const int nthreads
)
{
#include "GB_dense_ewise3_accum_template.c"
}
#endif
//------------------------------------------------------------------------------
// C = A+B, all 3 matrices dense
//------------------------------------------------------------------------------
GrB_Info GB (_Cdense_ewise3_noaccum__isne_fc32)
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix B,
const int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_dense_ewise3_noaccum_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C += B, accumulate a sparse matrix into a dense matrix
//------------------------------------------------------------------------------
GrB_Info GB (_Cdense_accumB__isne_fc32)
(
GrB_Matrix C,
const GrB_Matrix B,
const int64_t *B_ek_slicing, const int B_ntasks, const int B_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
{
#include "GB_dense_subassign_23_template.c"
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C += b, accumulate a scalar into a dense matrix
//------------------------------------------------------------------------------
GrB_Info GB (_Cdense_accumb__isne_fc32)
(
GrB_Matrix C,
const GB_void *p_bwork,
const int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
{
// get the scalar b for C += b, of type GxB_FC32_t
GxB_FC32_t bwork = (*((GxB_FC32_t *) p_bwork)) ;
#include "GB_dense_subassign_22_template.c"
return (GrB_SUCCESS) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = A*D, column scale with diagonal D matrix
//------------------------------------------------------------------------------
#if 0
GrB_Info GB ((none))
(
GrB_Matrix C,
const GrB_Matrix A, bool A_is_pattern,
const GrB_Matrix D, bool D_is_pattern,
const int64_t *A_ek_slicing, const int A_ntasks, const int A_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
GxB_FC32_t *restrict Cx = (GxB_FC32_t *) C->x ;
#include "GB_AxB_colscale_template.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
//------------------------------------------------------------------------------
// C = D*B, row scale with diagonal D matrix
//------------------------------------------------------------------------------
#if 0
GrB_Info GB ((none))
(
GrB_Matrix C,
const GrB_Matrix D, bool D_is_pattern,
const GrB_Matrix B, bool B_is_pattern,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
GxB_FC32_t *restrict Cx = (GxB_FC32_t *) C->x ;
#include "GB_AxB_rowscale_template.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
//------------------------------------------------------------------------------
// eWiseAdd: C = A+B or C<M> = A+B
//------------------------------------------------------------------------------
GrB_Info GB (_AaddB__isne_fc32)
(
GrB_Matrix C,
const int C_sparsity,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const bool Ch_is_Mh,
const int64_t *restrict C_to_M,
const int64_t *restrict C_to_A,
const int64_t *restrict C_to_B,
const GB_task_struct *restrict TaskList,
const int C_ntasks,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
GB_WERK_DECLARE (M_ek_slicing, int64_t) ;
GB_WERK_DECLARE (A_ek_slicing, int64_t) ;
GB_WERK_DECLARE (B_ek_slicing, int64_t) ;
#include "GB_add_template.c"
GB_FREE_WORK ;
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C = A.*B or C<M> = A.*B
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_01__isne_fc32)
(
GrB_Matrix C,
const int C_sparsity,
const int ewise_method,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *restrict C_to_M,
const int64_t *restrict C_to_A,
const int64_t *restrict C_to_B,
const GB_task_struct *restrict TaskList,
const int C_ntasks,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_emult_01_meta.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C<#> = A.*B when A is sparse/hyper and B is bitmap/full
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_02__isne_fc32)
(
GrB_Matrix C,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const bool flipxy,
const int64_t *restrict Cp_kfirst,
const int64_t *A_ek_slicing, const int A_ntasks, const int A_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#if GB_BINOP_FLIP
// The operator is not commutative, and does not have a flipped
// variant. For example z=atan2(y,x).
if (flipxy)
{
// use fmult(y,x)
#undef GB_FLIPPED
#define GB_FLIPPED 1
#include "GB_emult_02_template.c"
}
else
{
// use fmult(x,y)
#undef GB_FLIPPED
#define GB_FLIPPED 0
#include "GB_emult_02_template.c"
}
#else
// No need to handle the flip: the operator is either commutative, or
// has been handled by changing z=div(y,x) to z=rdiv(x,y) for example.
#undef GB_FLIPPED
#define GB_FLIPPED 0
#include "GB_emult_02_template.c"
#endif
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C<M> = A.*B, M sparse/hyper, A and B bitmap/full
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_03__isne_fc32)
(
GrB_Matrix C,
const GrB_Matrix M,
const bool Mask_struct,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *restrict Cp_kfirst,
const int64_t *M_ek_slicing, const int M_ntasks, const int M_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_emult_03_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C=A.*B, C<M>=A.*B, C<!M>=A.*B where C is bitmap
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_bitmap__isne_fc32)
(
GrB_Matrix C,
const int ewise_method,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *M_ek_slicing, const int M_ntasks, const int M_nthreads,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_bitmap_emult_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (x,Bx): apply a binary operator to a matrix with scalar bind1st
//------------------------------------------------------------------------------
GrB_Info GB (_bind1st__isne_fc32)
(
GB_void *Cx_output, // Cx and Bx may be aliased
const GB_void *x_input,
const GB_void *Bx_input,
const int8_t *restrict Bb,
int64_t bnz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
GxB_FC32_t *Cx = (GxB_FC32_t *) Cx_output ;
GxB_FC32_t x = (*((GxB_FC32_t *) x_input)) ;
GxB_FC32_t *Bx = (GxB_FC32_t *) Bx_input ;
int64_t p ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < bnz ; p++)
{
if (!GBB (Bb, p)) continue ;
GxB_FC32_t bij = GBX (Bx, p, false) ;
Cx [p] = GB_FC32_isne (x, bij) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (Ax,y): apply a binary operator to a matrix with scalar bind2nd
//------------------------------------------------------------------------------
GrB_Info GB (_bind2nd__isne_fc32)
(
GB_void *Cx_output, // Cx and Ax may be aliased
const GB_void *Ax_input,
const GB_void *y_input,
const int8_t *restrict Ab,
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t p ;
GxB_FC32_t *Cx = (GxB_FC32_t *) Cx_output ;
GxB_FC32_t *Ax = (GxB_FC32_t *) Ax_input ;
GxB_FC32_t y = (*((GxB_FC32_t *) y_input)) ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
if (!GBB (Ab, p)) continue ;
GxB_FC32_t aij = GBX (Ax, p, false) ;
Cx [p] = GB_FC32_isne (aij, y) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (x, A'): transpose and apply a binary operator
//------------------------------------------------------------------------------
// cij = op (x, aij), no typecasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
GxB_FC32_t aij = GBX (Ax, pA, false) ; \
Cx [pC] = GB_FC32_isne (x, aij) ; \
}
GrB_Info GB (_bind1st_tran__isne_fc32)
(
GrB_Matrix C,
const GB_void *x_input,
const GrB_Matrix A,
int64_t *restrict *Workspaces,
const int64_t *restrict A_slice,
int nworkspaces,
int nthreads
)
{
// GB_unop_transpose.c uses GB_ATYPE, but A is
// the 2nd input to binary operator z=f(x,y).
#undef GB_ATYPE
#define GB_ATYPE \
GxB_FC32_t
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
GxB_FC32_t x = (*((const GxB_FC32_t *) x_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
#undef GB_ATYPE
#define GB_ATYPE \
GxB_FC32_t
}
//------------------------------------------------------------------------------
// C = op (A', y): transpose and apply a binary operator
//------------------------------------------------------------------------------
// cij = op (aij, y), no typecasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
GxB_FC32_t aij = GBX (Ax, pA, false) ; \
Cx [pC] = GB_FC32_isne (aij, y) ; \
}
GrB_Info GB (_bind2nd_tran__isne_fc32)
(
GrB_Matrix C,
const GrB_Matrix A,
const GB_void *y_input,
int64_t *restrict *Workspaces,
const int64_t *restrict A_slice,
int nworkspaces,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
GxB_FC32_t y = (*((const GxB_FC32_t *) y_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
hpgmg-fv.c | //------------------------------------------------------------------------------------------------------------------------------
// Copyright Notice
//------------------------------------------------------------------------------------------------------------------------------
// HPGMG, Copyright (c) 2014, The Regents of the University of
// California, through Lawrence Berkeley National Laboratory (subject to
// receipt of any required approvals from the U.S. Dept. of Energy). All
// rights reserved.
//
// If you have questions about your rights to use or distribute this
// software, please contact Berkeley Lab's Technology Transfer Department
// at TTD@lbl.gov.
//
// NOTICE. This software is owned by the U.S. Department of Energy. As
// such, the U.S. Government has been granted for itself and others
// acting on its behalf a paid-up, nonexclusive, irrevocable, worldwide
// license in the Software to reproduce, prepare derivative works, and
// perform publicly and display publicly. Beginning five (5) years after
// the date permission to assert copyright is obtained from the U.S.
// Department of Energy, and subject to any subsequent five (5) year
// renewals, the U.S. Government is granted for itself and others acting
// on its behalf a paid-up, nonexclusive, irrevocable, worldwide license
// in the Software to reproduce, prepare derivative works, distribute
// copies to the public, perform publicly and display publicly, and to
// permit others to do so.
//------------------------------------------------------------------------------------------------------------------------------
// Samuel Williams
// SWWilliams@lbl.gov
// Lawrence Berkeley National Lab
//------------------------------------------------------------------------------------------------------------------------------
#include <stdio.h>
#include <stdlib.h>
#include <stdint.h>
#include <string.h>
#include <math.h>
//------------------------------------------------------------------------------------------------------------------------------
#ifdef USE_MPI
#include <mpi.h>
#endif
#ifdef _OPENMP
#include <omp.h>
#endif
//------------------------------------------------------------------------------------------------------------------------------
#include "timers.h"
#include "defines.h"
#include "level.h"
#include "mg.h"
#include "operators.h"
#include "solvers.h"
//------------------------------------------------------------------------------------------------------------------------------
void bench_hpgmg(mg_type *all_grids, int onLevel, double a, double b, double rtol){
int doTiming;
int minSolves = 10; // do at least minSolves MGSolves
double timePerSolve = 0;
for(doTiming=0;doTiming<=1;doTiming++){ // first pass warms up, second pass times
#ifdef USE_HPM // IBM performance counters for BGQ...
if( (doTiming==1) && (onLevel==0) )HPM_Start("FMGSolve()");
#endif
#ifdef USE_MPI
double minTime = 60.0; // minimum time in seconds that the benchmark should run
double startTime = MPI_Wtime();
if(doTiming==1){
if((minTime/timePerSolve)>minSolves)minSolves=(minTime/timePerSolve); // if one needs to do more than minSolves to run for minTime, change minSolves
}
#endif
if(all_grids->levels[onLevel]->my_rank==0){
if(doTiming==0){fprintf(stdout,"\n\n===== Warming up by running %d solves ==========================================\n",minSolves);}
else{fprintf(stdout,"\n\n===== Running %d solves ========================================================\n",minSolves);}
fflush(stdout);
}
int numSolves = 0; // solves completed
MGResetTimers(all_grids);
while( (numSolves<minSolves) ){
zero_vector(all_grids->levels[onLevel],VECTOR_U);
#ifdef USE_FCYCLES
FMGSolve(all_grids,onLevel,VECTOR_U,VECTOR_F,a,b,rtol);
#else
MGSolve(all_grids,onLevel,VECTOR_U,VECTOR_F,a,b,rtol);
#endif
numSolves++;
}
#ifdef USE_MPI
if(doTiming==0){
double endTime = MPI_Wtime();
timePerSolve = (endTime-startTime)/numSolves;
MPI_Bcast(&timePerSolve,1,MPI_DOUBLE,0,MPI_COMM_WORLD); // after warmup, process 0 broadcasts the average time per solve (consensus)
}
#endif
#ifdef USE_HPM // IBM performance counters for BGQ...
if( (doTiming==1) && (onLevel==0) )HPM_Stop("FMGSolve()");
#endif
}
}
//------------------------------------------------------------------------------------------------------------------------------
int main(int argc, char **argv){
int my_rank=0;
int num_tasks=1;
int OMP_Threads = 1;
//- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
#ifdef _OPENMP
#pragma omp parallel
{
#pragma omp master
{
OMP_Threads = omp_get_num_threads();
}
}
#endif
//- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
// initialize MPI and HPM
#ifdef USE_MPI
int actual_threading_model = -1;
int requested_threading_model = -1;
requested_threading_model = MPI_THREAD_SINGLE;
//requested_threading_model = MPI_THREAD_FUNNELED;
//requested_threading_model = MPI_THREAD_SERIALIZED;
//requested_threading_model = MPI_THREAD_MULTIPLE;
#ifdef _OPENMP
requested_threading_model = MPI_THREAD_FUNNELED;
//requested_threading_model = MPI_THREAD_SERIALIZED;
//requested_threading_model = MPI_THREAD_MULTIPLE;
#endif
MPI_Init_thread(&argc, &argv, requested_threading_model, &actual_threading_model);
MPI_Comm_size(MPI_COMM_WORLD, &num_tasks);
MPI_Comm_rank(MPI_COMM_WORLD, &my_rank);
#ifdef USE_HPM // IBM HPM counters for BGQ...
HPM_Init();
#endif
#endif // USE_MPI
//- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
// parse the arguments...
int log2_box_dim = 6; // 64^3
int target_boxes_per_rank = 1;
//int64_t target_memory_per_rank = -1; // not specified
int64_t box_dim = -1;
int64_t boxes_in_i = -1;
int64_t target_boxes = -1;
if(argc==3){
log2_box_dim=atoi(argv[1]);
target_boxes_per_rank=atoi(argv[2]);
if(log2_box_dim>9){
// NOTE, in order to use 32b int's for array indexing, box volumes must be less than 2^31 doubles
if(my_rank==0){fprintf(stderr,"log2_box_dim must be less than 10\n");}
#ifdef USE_MPI
MPI_Finalize();
#endif
exit(0);
}
if(log2_box_dim<4){
if(my_rank==0){fprintf(stderr,"log2_box_dim must be at least 4\n");}
#ifdef USE_MPI
MPI_Finalize();
#endif
exit(0);
}
if(target_boxes_per_rank<1){
if(my_rank==0){fprintf(stderr,"target_boxes_per_rank must be at least 1\n");}
#ifdef USE_MPI
MPI_Finalize();
#endif
exit(0);
}
#ifndef MAX_COARSE_DIM
#define MAX_COARSE_DIM 11
#endif
box_dim=1<<log2_box_dim;
target_boxes = (int64_t)target_boxes_per_rank*(int64_t)num_tasks;
boxes_in_i = -1;
int64_t bi;
for(bi=1;bi<1000;bi++){ // search all possible problem sizes to find acceptable boxes_in_i
int64_t total_boxes = bi*bi*bi;
if(total_boxes<=target_boxes){
int64_t coarse_grid_dim = box_dim*bi;
while( (coarse_grid_dim%2) == 0){coarse_grid_dim=coarse_grid_dim/2;}
if(coarse_grid_dim<=MAX_COARSE_DIM){
boxes_in_i = bi;
}
}
}
if(boxes_in_i<1){
if(my_rank==0){fprintf(stderr,"failed to find an acceptable problem size\n");}
#ifdef USE_MPI
MPI_Finalize();
#endif
exit(0);
}
} // argc==3
#if 0
else if(argc==2){ // interpret argv[1] as target_memory_per_rank
char *ptr = argv[1];
char *tmp;
target_memory_per_rank = strtol(ptr,&ptr,10);
if(target_memory_per_rank<1){
if(my_rank==0){fprintf(stderr,"unrecognized target_memory_per_rank... '%s'\n",argv[1]);}
#ifdef USE_MPI
MPI_Finalize();
#endif
exit(0);
}
tmp=strstr(ptr,"TB");if(tmp){ptr=tmp+2;target_memory_per_rank *= (uint64_t)(1<<30)*(1<<10);}
tmp=strstr(ptr,"GB");if(tmp){ptr=tmp+2;target_memory_per_rank *= (uint64_t)(1<<30);}
tmp=strstr(ptr,"MB");if(tmp){ptr=tmp+2;target_memory_per_rank *= (uint64_t)(1<<20);}
tmp=strstr(ptr,"tb");if(tmp){ptr=tmp+2;target_memory_per_rank *= (uint64_t)(1<<30)*(1<<10);}
tmp=strstr(ptr,"gb");if(tmp){ptr=tmp+2;target_memory_per_rank *= (uint64_t)(1<<30);}
tmp=strstr(ptr,"mb");if(tmp){ptr=tmp+2;target_memory_per_rank *= (uint64_t)(1<<20);}
if( (ptr) && (*ptr != '\0') ){
if(my_rank==0){fprintf(stderr,"unrecognized units... '%s'\n",ptr);}
#ifdef USE_MPI
MPI_Finalize();
#endif
exit(0);
}
// FIX, now search for an 'acceptable' box_dim and boxes_in_i constrained by target_memory_per_rank, num_tasks, and MAX_COARSE_DIM
} // argc==2
#endif
else{
if(my_rank==0){fprintf(stderr,"usage: ./hpgmg-fv [log2_box_dim] [target_boxes_per_rank]\n");}
//fprintf(stderr," ./hpgmg-fv [target_memory_per_rank[MB,GB,TB]]\n");}
#ifdef USE_MPI
MPI_Finalize();
#endif
exit(0);
}
//- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
if(my_rank==0){
fprintf(stdout,"\n\n");
fprintf(stdout,"********************************************************************************\n");
fprintf(stdout,"*** HPGMG-FV Benchmark ***\n");
fprintf(stdout,"********************************************************************************\n");
#ifdef USE_MPI
if(requested_threading_model == MPI_THREAD_MULTIPLE )fprintf(stdout,"Requested MPI_THREAD_MULTIPLE, ");
else if(requested_threading_model == MPI_THREAD_SINGLE )fprintf(stdout,"Requested MPI_THREAD_SINGLE, ");
else if(requested_threading_model == MPI_THREAD_FUNNELED )fprintf(stdout,"Requested MPI_THREAD_FUNNELED, ");
else if(requested_threading_model == MPI_THREAD_SERIALIZED)fprintf(stdout,"Requested MPI_THREAD_SERIALIZED, ");
else if(requested_threading_model == MPI_THREAD_MULTIPLE )fprintf(stdout,"Requested MPI_THREAD_MULTIPLE, ");
else fprintf(stdout,"Requested Unknown MPI Threading Model (%d), ",requested_threading_model);
if(actual_threading_model == MPI_THREAD_MULTIPLE )fprintf(stdout,"got MPI_THREAD_MULTIPLE\n");
else if(actual_threading_model == MPI_THREAD_SINGLE )fprintf(stdout,"got MPI_THREAD_SINGLE\n");
else if(actual_threading_model == MPI_THREAD_FUNNELED )fprintf(stdout,"got MPI_THREAD_FUNNELED\n");
else if(actual_threading_model == MPI_THREAD_SERIALIZED)fprintf(stdout,"got MPI_THREAD_SERIALIZED\n");
else if(actual_threading_model == MPI_THREAD_MULTIPLE )fprintf(stdout,"got MPI_THREAD_MULTIPLE\n");
else fprintf(stdout,"got Unknown MPI Threading Model (%d)\n",actual_threading_model);
#endif
fprintf(stdout,"%d MPI Tasks of %d threads\n",num_tasks,OMP_Threads);
fprintf(stdout,"\n\n===== Benchmark setup ==========================================================\n");
}
//- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
// create the fine level...
#ifdef USE_PERIODIC_BC
int bc = BC_PERIODIC;
int minCoarseDim = 2; // avoid problems with black box calculation of D^{-1} for poisson with periodic BC's on a 1^3 grid
#else
int bc = BC_DIRICHLET;
int minCoarseDim = 1; // assumes you can drop order on the boundaries
#endif
level_type level_h;
int ghosts=stencil_get_radius();
create_level(&level_h,boxes_in_i,box_dim,ghosts,VECTORS_RESERVED,bc,my_rank,num_tasks);
#ifdef USE_HELMHOLTZ
double a=1.0;double b=1.0; // Helmholtz
if(my_rank==0)fprintf(stdout," Creating Helmholtz (a=%f, b=%f) test problem\n",a,b);
#else
double a=0.0;double b=1.0; // Poisson
if(my_rank==0)fprintf(stdout," Creating Poisson (a=%f, b=%f) test problem\n",a,b);
#endif
double h=1.0/( (double)boxes_in_i*(double)box_dim ); // [0,1]^3 problem
initialize_problem(&level_h,h,a,b); // initialize VECTOR_ALPHA, VECTOR_BETA*, and VECTOR_F
rebuild_operator(&level_h,NULL,a,b); // calculate Dinv and lambda_max
if(level_h.boundary_condition.type == BC_PERIODIC){ // remove any constants from the RHS for periodic problems
double average_value_of_f = mean(&level_h,VECTOR_F);
if(average_value_of_f!=0.0){
if(my_rank==0){fprintf(stderr," WARNING... Periodic boundary conditions, but f does not sum to zero... mean(f)=%e\n",average_value_of_f);}
shift_vector(&level_h,VECTOR_F,VECTOR_F,-average_value_of_f);
}
}
//- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
// create the MG hierarchy...
mg_type MG_h;
MGBuild(&MG_h,&level_h,a,b,minCoarseDim); // build the Multigrid Hierarchy
//- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
// HPGMG-500 benchmark proper
// evaluate performance on problem sizes of h, 2h, and 4h
// (i.e. examine dynamic range for problem sizes N, N/8, and N/64)
double rtol=1e-10; // converged if ||b-Ax|| / ||b|| < rtol
int l;
#ifndef TEST_ERROR
// run at least 3 problem sizes with the caveat that the smallest is at least 16^3.
#define DYNAMIC_RANGE 3
double AverageSolveTime[DYNAMIC_RANGE];
for(l=0;l<DYNAMIC_RANGE;l++){
// if(problem size too small)break;
if(l>0)restriction(MG_h.levels[l],VECTOR_F,MG_h.levels[l-1],VECTOR_F,RESTRICT_CELL);
bench_hpgmg(&MG_h,l,a,b,rtol);
AverageSolveTime[l] = (double)MG_h.timers.MGSolve / (double)MG_h.MGSolves_performed;
if(my_rank==0){fprintf(stdout,"\n\n===== Timing Breakdown =========================================================\n");}
MGPrintTiming(&MG_h,l);
}
if(my_rank==0){
#ifdef CALIBRATE_TIMER
double _timeStart=getTime();sleep(1);double _timeEnd=getTime();
double SecondsPerCycle = (double)1.0/(double)(_timeEnd-_timeStart);
#else
double SecondsPerCycle = 1.0;
#endif
fprintf(stdout,"\n\n===== Performance Summary ======================================================\n");
for(l=0;l<DYNAMIC_RANGE;l++){
// if(problem size too small)break;
double DOF = (double)MG_h.levels[l]->dim.i*(double)MG_h.levels[l]->dim.j*(double)MG_h.levels[l]->dim.k;
double seconds = SecondsPerCycle*(double)AverageSolveTime[l];
double DOFs = DOF / seconds;
fprintf(stdout," h=%0.15e DOF=%0.15e time=%0.6f DOF/s=%0.3e MPI=%d OMP=%d\n",MG_h.levels[l]->h,DOF,seconds,DOFs,num_tasks,OMP_Threads);
}
}
#endif // TEST_ERROR not defined
//- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
if(my_rank==0){fprintf(stdout,"\n\n===== Richardson error analysis ================================================\n");}
// solve A^h u^h = f^h
// solve A^2h u^2h = f^2h
// solve A^4h u^4h = f^4h
// error analysis...
MGResetTimers(&MG_h);
for(l=0;l<3;l++){
if(l>0)restriction(MG_h.levels[l],VECTOR_F,MG_h.levels[l-1],VECTOR_F,RESTRICT_CELL);
zero_vector(MG_h.levels[l],VECTOR_U);
#ifdef USE_FCYCLES
FMGSolve(&MG_h,l,VECTOR_U,VECTOR_F,a,b,rtol);
#else
MGSolve(&MG_h,l,VECTOR_U,VECTOR_F,a,b,rtol);
#endif
}
richardson_error(&MG_h,0,VECTOR_U);
//- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
if(my_rank==0){fprintf(stdout,"\n\n===== Deallocating memory ======================================================\n");}
MGDestroy(&MG_h);
destroy_level(&level_h);
//- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
if(my_rank==0){fprintf(stdout,"\n\n===== Done =====================================================================\n");}
#ifdef USE_MPI
#ifdef USE_HPM // IBM performance counters for BGQ...
HPM_Print();
#endif
MPI_Finalize();
#endif
return(0);
//- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
}
|
test.c | #include <stdlib.h>
#include <stdio.h>
#pragma omp requires unified_shared_memory
#include "../utilities/check.h"
#include "../utilities/utilities.h"
#define N 100
#define TEST_BROKEN 0 /* disable tests reardless of value below */
#define TEST1 1
#define TEST1 1
#define TEST2 1
#define TEST3 1
#define TEST4 1
#define TEST5 1
#define TEST6 1
#define TEST7 1
#define TEST8 1
#define TEST9 1
#define TEST10 1
#define TEST11 1
#define TEST11 1
#define TEST12 1
#define TEST13 1
#define TEST14 1
#define TEST15 1
#define TEST16 1
#define TEST17 1
#define TEST18 1
#define TEST19 1
#define TEST20 1
#define TEST21 1
#define TEST21 1
#define TEST22 1
#define TEST23 1
#define TEST24 1
#define TEST25 1
#define TEST26 1
#define TEST27 1
#define TEST28 1
#define TEST39 1
#define TEST31 1
#define TEST31 1
#define TEST32 1
#define TEST33 1
#define TEST34 1
#define TEST35 1
#define TEST36 1
#define TEST37 1
int main ()
{
int a[N], b[N], c[N];
#if TEST1
check_offloading();
#endif
long cpuExec = 0;
int fail, ch;
#pragma omp target map(tofrom: cpuExec)
{
cpuExec = omp_is_initial_device();
}
#if TEST2
// Test: no clauses
fail = 0;
for (int i = 0 ; i < N ; i++) {
a[i] = -1;
b[i] = i;
c[i] = 2*i;
}
if (!cpuExec) {
#pragma omp target map(tofrom: a) map(to: b,c)
#pragma omp parallel
#pragma omp for simd
for (int i = 0 ; i < N ; i++)
a[i] += b[i] + c[i];
for (int i = 0 ; i < N ; i++)
if (a[i] != (-1 + i + 2*i)) {
printf("Error at %d: device = %d, host = %d\n", i, a[i], (-1 + i + 2*i));
fail = 1;
}
}
if (fail)
printf ("Failed 2\n");
else
printf("Succeeded 2\n");
#endif
#if TEST3
// Test: private, firstprivate, lastprivate, linear
fail = 0;
for (int i = 0 ; i < N ; i++) {
a[i] = -1;
b[i] = i;
c[i] = 2*i;
}
int q = -5;
int p = -3;
int r = 0;
int l = 10;
if (!cpuExec) {
#pragma omp target teams num_teams(1) thread_limit(1024) map(tofrom: a, r) map(to: b,c)
#pragma omp parallel
#pragma omp for simd private(q) firstprivate(p) lastprivate(r) linear(l:2)
for (int i = 0 ; i < N ; i++) {
q = i + 5;
p += i + 2;
a[i] += p*b[i] + c[i]*q +l;
r = i;
}
for (int i = 0 ; i < N ; i++) {
int expected = (-1 + (-3 + i + 2)*i + (2*i)*(i + 5) + 10+(2*i));
if (a[i] != expected) {
printf("Error at %d: device = %d, host = %d\n", i, a[i], expected);
fail = 1;
}
}
if (r != N-1) {
printf("Error for lastprivate: device = %d, host = %d\n", r, N-1);
fail = 1;
}
}
if (fail)
printf ("Failed 3\n");
else
printf("Succeeded 3\n");
#endif
#if TEST4
// Test: schedule static no chunk
fail = 0;
for (int i = 0 ; i < N ; i++) {
a[i] = -1;
b[i] = i;
c[i] = 2*i;
}
if (!cpuExec) {
#pragma omp target map(tofrom: a) map(to: b,c)
#pragma omp parallel
#pragma omp for simd schedule(static)
for (int i = 0 ; i < N ; i++)
a[i] += b[i] + c[i];
for (int i = 0 ; i < N ; i++)
if (a[i] != (-1 + i + 2*i)) {
printf("Error at %d: device = %d, host = %d\n", i, a[i], (-1 + i + 2*i));
fail = 1;
}
}
if (fail)
printf ("Failed 4\n");
else
printf("Succeeded 4\n");
#endif
#if TEST5
// Test: schedule static no chunk, monotonic
fail = 0;
for (int i = 0 ; i < N ; i++) {
a[i] = -1;
b[i] = i;
c[i] = 2*i;
}
if (!cpuExec) {
#pragma omp target teams num_teams(1) thread_limit(1024) map(tofrom: a) map(to: b,c)
#pragma omp parallel
#pragma omp for simd schedule(monotonic: static)
for (int i = 0 ; i < N ; i++)
a[i] += b[i] + c[i];
for (int i = 0 ; i < N ; i++)
if (a[i] != (-1 + i + 2*i)) {
printf("Error at %d: device = %d, host = %d\n", i, a[i], (-1 + i + 2*i));
fail = 1;
}
}
if (fail)
printf ("Failed 5\n");
else
printf("Succeeded 5\n");
#endif
#if TEST6
// Test: schedule static no chunk, simd
fail = 0;
for (int i = 0 ; i < N ; i++) {
a[i] = -1;
b[i] = i;
c[i] = 2*i;
}
if (!cpuExec) {
#pragma omp target map(tofrom: a) map(to: b,c)
#pragma omp parallel
#pragma omp for simd schedule(simd: static)
for (int i = 0 ; i < N ; i++)
a[i] += b[i] + c[i];
for (int i = 0 ; i < N ; i++)
if (a[i] != (-1 + i + 2*i)) {
printf("Error at %d: device = %d, host = %d\n", i, a[i], (-1 + i + 2*i));
fail = 1;
}
}
if (fail)
printf ("Failed 6\n");
else
printf("Succeeded 6\n");
#endif
#if TEST7
// Test: schedule static chunk
fail = 0;
for (int i = 0 ; i < N ; i++) {
a[i] = -1;
b[i] = i;
c[i] = 2*i;
}
ch = 10;
if (!cpuExec) {
#pragma omp target map(tofrom: a) map(to: b,c)
#pragma omp parallel
#pragma omp for simd schedule(static, ch)
for (int i = 0 ; i < N ; i++)
a[i] += b[i] + c[i];
for (int i = 0 ; i < N ; i++)
if (a[i] != (-1 + i + 2*i)) {
printf("Error at %d: device = %d, host = %d\n", i, a[i], (-1 + i + 2*i));
fail = 1;
}
}
if (fail)
printf ("Failed 7\n");
else
printf("Succeeded 7\n");
#endif
#if TEST8
// Test: schedule static chunk, monotonic
fail = 0;
for (int i = 0 ; i < N ; i++) {
a[i] = -1;
b[i] = i;
c[i] = 2*i;
}
ch = 10;
if (!cpuExec) {
#pragma omp target map(tofrom: a) map(to: b,c)
#pragma omp parallel
#pragma omp for simd schedule(monotonic: static, ch)
for (int i = 0 ; i < N ; i++)
a[i] += b[i] + c[i];
for (int i = 0 ; i < N ; i++)
if (a[i] != (-1 + i + 2*i)) {
printf("Error at %d: device = %d, host = %d\n", i, a[i], (-1 + i + 2*i));
fail = 1;
}
}
if (fail)
printf ("Failed 8\n");
else
printf("Succeeded 8\n");
#endif
#if TEST9
// Test: schedule static chunk, simd
fail = 0;
for (int i = 0 ; i < N ; i++) {
a[i] = -1;
b[i] = i;
c[i] = 2*i;
}
ch = 10;
if (!cpuExec) {
#pragma omp target map(tofrom: a) map(to: b,c)
#pragma omp parallel
#pragma omp for simd schedule(simd: static, ch)
for (int i = 0 ; i < N ; i++)
a[i] += b[i] + c[i];
for (int i = 0 ; i < N ; i++)
if (a[i] != (-1 + i + 2*i)) {
printf("Error at %d: device = %d, host = %d\n", i, a[i], (-1 + i + 2*i));
fail = 1;
}
}
if (fail)
printf ("Failed 9\n");
else
printf("Succeeded 9\n");
#endif
#if TEST10
// Test: schedule dyanmic no chunk
fail = 0;
for (int i = 0 ; i < N ; i++) {
a[i] = -1;
b[i] = i;
c[i] = 2*i;
}
if (!cpuExec) {
#pragma omp target map(tofrom: a) map(to: b,c)
#pragma omp parallel
#pragma omp for simd schedule(dynamic)
for (int i = 0 ; i < N ; i++)
a[i] += b[i] + c[i];
for (int i = 0 ; i < N ; i++)
if (a[i] != (-1 + i + 2*i)) {
printf("Error at %d: device = %d, host = %d\n", i, a[i], (-1 + i + 2*i));
fail = 1;
}
}
if (fail)
printf ("Failed 10\n");
else
printf("Succeeded 10\n");
#endif
#if TEST11 && TEST_BROKEN // hangs
// Test: schedule dyanmic no chunk, monotonic
fail = 0;
for (int i = 0 ; i < N ; i++) {
a[i] = -1;
b[i] = i;
c[i] = 2*i;
}
if (!cpuExec) {
#pragma omp target map(tofrom: a) map(to: b,c)
#pragma omp parallel
#pragma omp for simd schedule(monotonic: dynamic)
for (int i = 0 ; i < N ; i++)
a[i] += b[i] + c[i];
for (int i = 0 ; i < N ; i++)
if (a[i] != (-1 + i + 2*i)) {
printf("Error at %d: device = %d, host = %d\n", i, a[i], (-1 + i + 2*i));
fail = 1;
}
}
if (fail)
printf ("Failed 11\n");
else
printf("Succeeded 11\n");
#endif
#if TEST12 && TEST_BROKEN // hangs
// Test: schedule dyanmic no chunk, nonmonotonic
fail = 0;
for (int i = 0 ; i < N ; i++) {
a[i] = -1;
b[i] = i;
c[i] = 2*i;
}
if (!cpuExec) {
#pragma omp target map(tofrom: a) map(to: b,c)
#pragma omp parallel
#pragma omp for simd schedule(nonmonotonic: dynamic)
for (int i = 0 ; i < N ; i++)
a[i] += b[i] + c[i];
for (int i = 0 ; i < N ; i++)
if (a[i] != (-1 + i + 2*i)) {
printf("Error at %d: device = %d, host = %d\n", i, a[i], (-1 + i + 2*i));
fail = 1;
}
}
if (fail)
printf ("Failed 12\n");
else
printf("Succeeded 12\n");
#endif
#if TEST13
// Test: schedule dyanmic no chunk, simd
fail = 0;
for (int i = 0 ; i < N ; i++) {
a[i] = -1;
b[i] = i;
c[i] = 2*i;
}
if (!cpuExec) {
#pragma omp target map(tofrom: a) map(to: b,c)
#pragma omp parallel
#pragma omp for simd schedule(simd: dynamic)
for (int i = 0 ; i < N ; i++)
a[i] += b[i] + c[i];
for (int i = 0 ; i < N ; i++)
if (a[i] != (-1 + i + 2*i)) {
printf("Error at %d: device = %d, host = %d\n", i, a[i], (-1 + i + 2*i));
fail = 1;
}
}
if (fail)
printf ("Failed 13\n");
else
printf("Succeeded 13\n");
#endif
#if TEST14
// Test: schedule dynamic chunk
fail = 0;
for (int i = 0 ; i < N ; i++) {
a[i] = -1;
b[i] = i;
c[i] = 2*i;
}
ch = 10;
if (!cpuExec) {
#pragma omp target map(tofrom: a) map(to: b,c)
#pragma omp parallel
#pragma omp for simd schedule(dynamic, ch)
for (int i = 0 ; i < N ; i++)
a[i] += b[i] + c[i];
for (int i = 0 ; i < N ; i++)
if (a[i] != (-1 + i + 2*i)) {
printf("Error at %d: device = %d, host = %d\n", i, a[i], (-1 + i + 2*i));
fail = 1;
}
}
if (fail)
printf ("Failed 14\n");
else
printf("Succeeded 14\n");
#endif
#if TEST15 && TEST_BROKEN
// Test: schedule dynamic chunk, monotonic
fail = 0;
for (int i = 0 ; i < N ; i++) {
a[i] = -1;
b[i] = i;
c[i] = 2*i;
}
ch = 10;
if (!cpuExec) {
#pragma omp target map(tofrom: a) map(to: b,c)
#pragma omp parallel
#pragma omp for simd schedule(monotonic: dynamic, ch)
for (int i = 0 ; i < N ; i++)
a[i] += b[i] + c[i];
for (int i = 0 ; i < N ; i++)
if (a[i] != (-1 + i + 2*i)) {
printf("Error at %d: device = %d, host = %d\n", i, a[i], (-1 + i + 2*i));
fail = 1;
}
}
if (fail)
printf ("Failed 15\n");
else
printf("Succeeded 15\n");
#endif
#if TEST16 && TEST_BROKEN
// Test: schedule dynamic chunk, nonmonotonic
fail = 0;
for (int i = 0 ; i < N ; i++) {
a[i] = -1;
b[i] = i;
c[i] = 2*i;
}
ch = 10;
if (!cpuExec) {
#pragma omp target map(tofrom: a) map(to: b,c)
#pragma omp parallel
#pragma omp for simd schedule(nonmonotonic: dynamic, ch)
for (int i = 0 ; i < N ; i++)
a[i] += b[i] + c[i];
for (int i = 0 ; i < N ; i++)
if (a[i] != (-1 + i + 2*i)) {
printf("Error at %d: device = %d, host = %d\n", i, a[i], (-1 + i + 2*i));
fail = 1;
}
}
if (fail)
printf ("Failed 16\n");
else
printf("Succeeded 16\n");
#endif
#if TEST17
// Test: schedule dynamic chunk, simd
fail = 0;
for (int i = 0 ; i < N ; i++) {
a[i] = -1;
b[i] = i;
c[i] = 2*i;
}
ch = 10;
if (!cpuExec) {
#pragma omp target map(tofrom: a) map(to: b,c)
#pragma omp parallel
#pragma omp for simd schedule(simd: dynamic, ch)
for (int i = 0 ; i < N ; i++)
a[i] += b[i] + c[i];
for (int i = 0 ; i < N ; i++)
if (a[i] != (-1 + i + 2*i)) {
printf("Error at %d: device = %d, host = %d\n", i, a[i], (-1 + i + 2*i));
fail = 1;
}
}
if (fail)
printf ("Failed 17\n");
else
printf("Succeeded 17\n");
#endif
#if TEST18
// Test: schedule guided no chunk
fail = 0;
for (int i = 0 ; i < N ; i++) {
a[i] = -1;
b[i] = i;
c[i] = 2*i;
}
if (!cpuExec) {
#pragma omp target map(tofrom: a) map(to: b,c)
#pragma omp parallel
#pragma omp for simd schedule(guided)
for (int i = 0 ; i < N ; i++)
a[i] += b[i] + c[i];
for (int i = 0 ; i < N ; i++)
if (a[i] != (-1 + i + 2*i)) {
printf("Error at %d: device = %d, host = %d\n", i, a[i], (-1 + i + 2*i));
fail = 1;
}
}
if (fail)
printf ("Failed 18\n");
else
printf("Succeeded 18\n");
#endif
#if TEST19 && TEST_BROKEN
// Test: schedule guided no chunk, monotonic
fail = 0;
for (int i = 0 ; i < N ; i++) {
a[i] = -1;
b[i] = i;
c[i] = 2*i;
}
if (!cpuExec) {
#pragma omp target map(tofrom: a) map(to: b,c)
#pragma omp parallel
#pragma omp for simd schedule(monotonic: guided)
for (int i = 0 ; i < N ; i++)
a[i] += b[i] + c[i];
for (int i = 0 ; i < N ; i++)
if (a[i] != (-1 + i + 2*i)) {
printf("Error at %d: device = %d, host = %d\n", i, a[i], (-1 + i + 2*i));
fail = 1;
}
}
if (fail)
printf ("Failed 19\n");
else
printf("Succeeded 19\n");
#endif
#if TEST20 && TEST_BROKEN
// Test: schedule guided no chunk, nonmonotonic
fail = 0;
for (int i = 0 ; i < N ; i++) {
a[i] = -1;
b[i] = i;
c[i] = 2*i;
}
if (!cpuExec) {
#pragma omp target map(tofrom: a) map(to: b,c)
#pragma omp parallel
#pragma omp for simd schedule(nonmonotonic: guided)
for (int i = 0 ; i < N ; i++)
a[i] += b[i] + c[i];
for (int i = 0 ; i < N ; i++)
if (a[i] != (-1 + i + 2*i)) {
printf("Error at %d: device = %d, host = %d\n", i, a[i], (-1 + i + 2*i));
fail = 1;
}
}
if (fail)
printf ("Failed 20\n");
else
printf("Succeeded 20\n");
#endif
#if TEST21
// Test: schedule guided no chunk, simd
fail = 0;
for (int i = 0 ; i < N ; i++) {
a[i] = -1;
b[i] = i;
c[i] = 2*i;
}
if (!cpuExec) {
#pragma omp target map(tofrom: a) map(to: b,c)
#pragma omp parallel
#pragma omp for simd schedule(simd: guided)
for (int i = 0 ; i < N ; i++)
a[i] += b[i] + c[i];
for (int i = 0 ; i < N ; i++)
if (a[i] != (-1 + i + 2*i)) {
printf("Error at %d: device = %d, host = %d\n", i, a[i], (-1 + i + 2*i));
fail = 1;
}
}
if (fail)
printf ("Failed 21\n");
else
printf("Succeeded 21\n");
#endif
#if TEST22
// Test: schedule guided chunk
fail = 0;
for (int i = 0 ; i < N ; i++) {
a[i] = -1;
b[i] = i;
c[i] = 2*i;
}
ch = 10;
if (!cpuExec) {
#pragma omp target map(tofrom: a) map(to: b,c)
#pragma omp parallel
#pragma omp for simd schedule(guided, ch)
for (int i = 0 ; i < N ; i++)
a[i] += b[i] + c[i];
for (int i = 0 ; i < N ; i++)
if (a[i] != (-1 + i + 2*i)) {
printf("Error at %d: device = %d, host = %d\n", i, a[i], (-1 + i + 2*i));
fail = 1;
}
}
if (fail)
printf ("Failed 22\n");
else
printf("Succeeded 22\n");
#endif
#if TEST23 && TEST_BROKEN
// Test: schedule guided chunk, monotonic
fail = 0;
for (int i = 0 ; i < N ; i++) {
a[i] = -1;
b[i] = i;
c[i] = 2*i;
}
ch = 10;
if (!cpuExec) {
#pragma omp target map(tofrom: a) map(to: b,c)
#pragma omp parallel
#pragma omp for simd schedule(monotonic: guided, ch)
for (int i = 0 ; i < N ; i++)
a[i] += b[i] + c[i];
for (int i = 0 ; i < N ; i++)
if (a[i] != (-1 + i + 2*i)) {
printf("Error at %d: device = %d, host = %d\n", i, a[i], (-1 + i + 2*i));
fail = 1;
}
}
if (fail)
printf ("Failed 23\n");
else
printf("Succeeded 23\n");
#endif
#if TEST24 && TEST_BROKEN
// Test: schedule guided chunk, nonmonotonic
fail = 0;
for (int i = 0 ; i < N ; i++) {
a[i] = -1;
b[i] = i;
c[i] = 2*i;
}
ch = 10;
if (!cpuExec) {
#pragma omp target map(tofrom: a) map(to: b,c)
#pragma omp parallel
#pragma omp for simd schedule(nonmonotonic: guided, ch)
for (int i = 0 ; i < N ; i++)
a[i] += b[i] + c[i];
for (int i = 0 ; i < N ; i++)
if (a[i] != (-1 + i + 2*i)) {
printf("Error at %d: device = %d, host = %d\n", i, a[i], (-1 + i + 2*i));
fail = 1;
}
}
if (fail)
printf ("Failed 24\n");
else
printf("Succeeded 24\n");
#endif
#if TEST25
// Test: schedule guided chunk, simd
fail = 0;
for (int i = 0 ; i < N ; i++) {
a[i] = -1;
b[i] = i;
c[i] = 2*i;
}
ch = 10;
if (!cpuExec) {
#pragma omp target map(tofrom: a) map(to: b,c)
#pragma omp parallel
#pragma omp for simd schedule(simd: guided, ch)
for (int i = 0 ; i < N ; i++)
a[i] += b[i] + c[i];
for (int i = 0 ; i < N ; i++)
if (a[i] != (-1 + i + 2*i)) {
printf("Error at %d: device = %d, host = %d\n", i, a[i], (-1 + i + 2*i));
fail = 1;
}
}
if (fail)
printf ("Failed 25\n");
else
printf("Succeeded 25\n");
#endif
#if TEST26
// Test: schedule auto
fail = 0;
for (int i = 0 ; i < N ; i++) {
a[i] = -1;
b[i] = i;
c[i] = 2*i;
}
if (!cpuExec) {
#pragma omp target map(tofrom: a) map(to: b,c)
#pragma omp parallel
#pragma omp for simd schedule(auto)
for (int i = 0 ; i < N ; i++)
a[i] += b[i] + c[i];
for (int i = 0 ; i < N ; i++)
if (a[i] != (-1 + i + 2*i)) {
printf("Error at %d: device = %d, host = %d\n", i, a[i], (-1 + i + 2*i));
fail = 1;
}
}
if (fail)
printf ("Failed 26\n");
else
printf("Succeeded 26\n");
#endif
#if TEST27
// Test: schedule auto, monotonic
fail = 0;
for (int i = 0 ; i < N ; i++) {
a[i] = -1;
b[i] = i;
c[i] = 2*i;
}
if (!cpuExec) {
#pragma omp target map(tofrom: a) map(to: b,c)
#pragma omp parallel
#pragma omp for simd schedule(monotonic: auto)
for (int i = 0 ; i < N ; i++)
a[i] += b[i] + c[i];
for (int i = 0 ; i < N ; i++)
if (a[i] != (-1 + i + 2*i)) {
printf("Error at %d: device = %d, host = %d\n", i, a[i], (-1 + i + 2*i));
fail = 1;
}
}
if (fail)
printf ("Failed 27\n");
else
printf("Succeeded 27\n");
#endif
#if TEST28
// Test: schedule auto, simd
fail = 0;
for (int i = 0 ; i < N ; i++) {
a[i] = -1;
b[i] = i;
c[i] = 2*i;
}
if (!cpuExec) {
#pragma omp target map(tofrom: a) map(to: b,c)
#pragma omp parallel
#pragma omp for simd schedule(simd: auto)
for (int i = 0 ; i < N ; i++)
a[i] += b[i] + c[i];
for (int i = 0 ; i < N ; i++)
if (a[i] != (-1 + i + 2*i)) {
printf("Error at %d: device = %d, host = %d\n", i, a[i], (-1 + i + 2*i));
fail = 1;
}
}
if (fail)
printf ("Failed 28\n");
else
printf("Succeeded 28\n");
#endif
#if TEST29
// Test: schedule runtime
fail = 0;
for (int i = 0 ; i < N ; i++) {
a[i] = -1;
b[i] = i;
c[i] = 2*i;
}
if (!cpuExec) {
#pragma omp target map(tofrom: a) map(to: b,c)
#pragma omp parallel
#pragma omp for simd schedule(runtime)
for (int i = 0 ; i < N ; i++)
a[i] += b[i] + c[i];
for (int i = 0 ; i < N ; i++)
if (a[i] != (-1 + i + 2*i)) {
printf("Error at %d: device = %d, host = %d\n", i, a[i], (-1 + i + 2*i));
fail = 1;
}
}
if (fail)
printf ("Failed 29\n");
else
printf("Succeeded 29\n");
#endif
#if TEST30 && TEST_BROKEN
// Test: schedule runtime, monotonic
fail = 0;
for (int i = 0 ; i < N ; i++) {
a[i] = -1;
b[i] = i;
c[i] = 2*i;
}
if (!cpuExec) {
#pragma omp target map(tofrom: a) map(to: b,c)
#pragma omp parallel
#pragma omp for simd schedule(monotonic: runtime)
for (int i = 0 ; i < N ; i++)
a[i] += b[i] + c[i];
for (int i = 0 ; i < N ; i++)
if (a[i] != (-1 + i + 2*i)) {
printf("Error at %d: device = %d, host = %d\n", i, a[i], (-1 + i + 2*i));
fail = 1;
}
}
if (fail)
printf ("Failed 30\n");
else
printf("Succeeded 30\n");
#endif
#if TEST31
// Test: schedule runtime, simd
fail = 0;
for (int i = 0 ; i < N ; i++) {
a[i] = -1;
b[i] = i;
c[i] = 2*i;
}
if (!cpuExec) {
#pragma omp target map(tofrom: a) map(to: b,c)
#pragma omp parallel
#pragma omp for simd schedule(simd: runtime)
for (int i = 0 ; i < N ; i++)
a[i] += b[i] + c[i];
for (int i = 0 ; i < N ; i++)
if (a[i] != (-1 + i + 2*i)) {
printf("Error at %d: device = %d, host = %d\n", i, a[i], (-1 + i + 2*i));
fail = 1;
}
}
if (fail)
printf ("Failed 31\n");
else
printf("Succeeded 31\n");
#endif
#if TEST32
// Test: collapse
fail = 0;
int ma[N][N], mb[N][N], mc[N][N];
for (int i = 0 ; i < N ; i++)
for (int j = 0 ; j < N ; j++) {
ma[i][j] = -1;
mb[i][j] = i;
mc[i][j] = 2*i;
}
if (!cpuExec) {
#pragma omp target map(tofrom: ma) map(to: mb,mc)
#pragma omp parallel
#pragma omp for simd collapse(2)
for (int i = 0 ; i < N ; i++)
for (int j = 0 ; j < N ; j++)
ma[i][j] += mb[i][j] + mc[i][j];
for (int i = 0 ; i < N ; i++)
for (int j = 0 ; j < N ; j++)
if (ma[i][j] != (-1 + i + 2*i)) {
printf("Error at %d: device = %d, host = %d\n", i, ma[i][j], (-1 + i + 2*i));
fail = 1;
}
}
if (fail)
printf ("Failed 32\n");
else
printf("Succeeded 32\n");
#endif
#if TEST33
// Test: ordered
fail = 0;
for (int i = 0 ; i < N ; i++) {
a[i] = -1;
b[i] = i;
c[i] = 2*i;
}
if (!cpuExec) {
#pragma omp target map(tofrom: a) map(to: b,c)
#pragma omp parallel
#pragma omp for simd ordered
for (int i = 0 ; i < N ; i++)
a[i] += b[i] + c[i];
for (int i = 0 ; i < N ; i++)
if (a[i] != (-1 + i + 2*i)) {
printf("Error at %d: device = %d, host = %d\n", i, a[i], (-1 + i + 2*i));
fail = 1;
}
}
if (fail)
printf ("Failed 33\n");
else
printf("Succeeded 33\n");
#endif
#if TEST34
// Test: nowait
fail = 0;
for (int i = 0 ; i < N ; i++) {
a[i] = -1;
b[i] = i;
c[i] = 2*i;
}
if (!cpuExec) {
#pragma omp target map(tofrom: a) map(to: b,c)
#pragma omp parallel
#pragma omp for simd nowait
for (int i = 0 ; i < N ; i++)
a[i] += b[i] + c[i];
for (int i = 0 ; i < N ; i++)
if (a[i] != (-1 + i + 2*i)) {
printf("Error at %d: device = %d, host = %d\n", i, a[i], (-1 + i + 2*i));
fail = 1;
}
}
if (fail)
printf ("Failed 34\n");
else
printf("Succeeded 34\n");
#endif
#if TEST35
// Test: safelen
fail = 0;
for (int i = 0 ; i < N ; i++) {
a[i] = -1;
b[i] = i;
c[i] = 2*i;
}
if (!cpuExec) {
#pragma omp target map(tofrom: a) map(to: b,c)
#pragma omp parallel
#pragma omp for simd safelen(16)
for (int i = 0 ; i < N ; i++)
a[i] += b[i] + c[i];
for (int i = 0 ; i < N ; i++)
if (a[i] != (-1 + i + 2*i)) {
printf("Error at %d: device = %d, host = %d\n", i, a[i], (-1 + i + 2*i));
fail = 1;
}
}
if (fail)
printf ("Failed 35\n");
else
printf("Succeeded 35\n");
#endif
#if TEST36
// Test: simdlen
fail = 0;
for (int i = 0 ; i < N ; i++) {
a[i] = -1;
b[i] = i;
c[i] = 2*i;
}
if (!cpuExec) {
#pragma omp target map(tofrom: a) map(to: b,c)
#pragma omp parallel
#pragma omp for simd simdlen(16)
for (int i = 0 ; i < N ; i++)
a[i] += b[i] + c[i];
for (int i = 0 ; i < N ; i++)
if (a[i] != (-1 + i + 2*i)) {
printf("Error at %d: device = %d, host = %d\n", i, a[i], (-1 + i + 2*i));
fail = 1;
}
}
if (fail)
printf ("Failed 36\n");
else
printf("Succeeded 36\n");
#endif
#if TEST37
// Test: aligned
fail = 0;
for (int i = 0 ; i < N ; i++) {
a[i] = -1;
b[i] = i;
c[i] = 2*i;
}
if (!cpuExec) {
#pragma omp target map(tofrom: a) map(to: b,c)
#pragma omp parallel
#pragma omp for simd aligned(a,b,c:8)
for (int i = 0 ; i < N ; i++)
a[i] += b[i] + c[i];
for (int i = 0 ; i < N ; i++)
if (a[i] != (-1 + i + 2*i)) {
printf("Error at %d: device = %d, host = %d\n", i, a[i], (-1 + i + 2*i));
fail = 1;
}
}
if (fail)
printf ("Failed 37\n");
else
printf("Succeeded 37\n");
#endif
return 0;
}
|
GB_unop__isnan_bool_fc64.c | //------------------------------------------------------------------------------
// GB_unop: hard-coded functions for each built-in unary operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2022, All Rights Reserved.
// SPDX-License-Identifier: Apache-2.0
//------------------------------------------------------------------------------
// If this file is in the Generated2/ folder, do not edit it
// (it is auto-generated from Generator/*).
#include "GB.h"
#ifndef GBCUDA_DEV
#include "GB_control.h"
#include "GB_atomics.h"
#include "GB_unop__include.h"
// C=unop(A) is defined by the following types and operators:
// op(A) function: GB (_unop_apply__isnan_bool_fc64)
// op(A') function: GB (_unop_tran__isnan_bool_fc64)
// C type: bool
// A type: GxB_FC64_t
// cast: GxB_FC64_t cij = (aij)
// unaryop: cij = GB_cisnan (aij)
#define GB_ATYPE \
GxB_FC64_t
#define GB_CTYPE \
bool
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA) \
GxB_FC64_t aij = Ax [pA]
#define GB_CX(p) Cx [p]
// unary operator
#define GB_OP(z, x) \
z = GB_cisnan (x) ;
// casting
#define GB_CAST(z, aij) \
GxB_FC64_t z = (aij) ;
// cij = op (aij)
#define GB_CAST_OP(pC,pA) \
{ \
/* aij = Ax [pA] */ \
GxB_FC64_t aij = Ax [pA] ; \
/* Cx [pC] = op (cast (aij)) */ \
GxB_FC64_t z = (aij) ; \
Cx [pC] = GB_cisnan (z) ; \
}
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_ISNAN || GxB_NO_BOOL || GxB_NO_FC64)
//------------------------------------------------------------------------------
// Cx = op (cast (Ax)): apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB (_unop_apply__isnan_bool_fc64)
(
bool *Cx, // Cx and Ax may be aliased
const GxB_FC64_t *Ax,
const int8_t *restrict Ab, // A->b if A is bitmap
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t p ;
if (Ab == NULL)
{
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
GxB_FC64_t aij = Ax [p] ;
GxB_FC64_t z = (aij) ;
Cx [p] = GB_cisnan (z) ;
}
}
else
{
// bitmap case, no transpose; A->b already memcpy'd into C->b
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
if (!Ab [p]) continue ;
GxB_FC64_t aij = Ax [p] ;
GxB_FC64_t z = (aij) ;
Cx [p] = GB_cisnan (z) ;
}
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (cast (A')): transpose, typecast, and apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB (_unop_tran__isnan_bool_fc64)
(
GrB_Matrix C,
const GrB_Matrix A,
int64_t *restrict *Workspaces,
const int64_t *restrict A_slice,
int nworkspaces,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
convolution_3x3_fp16.c | /*
* Copyright (C) 2016-2022 T-Head Semiconductor Co., Ltd. All rights reserved.
*
* SPDX-License-Identifier: Apache-2.0
*
* Licensed under the Apache License, Version 2.0 (the License); you may
* not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an AS IS BASIS, WITHOUT
* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
/* CSI-NN2 version 1.12.x */
#include "csi_thead_rvv.h"
/*************************************************************
note: VLEN = 128/256 ...
*************************************************************/
static void winograd_pad_input_pack1ton_fp16(const __fp16 *input, __fp16 *input_padded, int inc,
int inh, int inw, int padded_h, int padded_w,
int pad_top, int pad_left)
{
const int packn = csrr_vlenb() / sizeof(__fp16);
const int vl = vsetvl_e16m1(packn);
int padded_hw = padded_h * padded_w;
const int in_size = inh * inw; // per-channel size
__fp16 *pad_ptr = input_padded;
__fp16 *inp_ptr = (__fp16 *)input;
int pad_down = padded_h - pad_top - inh; // remain to pad on h (pad_down)
int pad_right = padded_w - pad_left - inw; // remain to pad on w (pad_right)
vfloat16m1_t _zero = vfmv_v_f_f16m1(0.0f, vl);
int c = 0;
for (; c + packn - 1 < inc; c += packn) {
inp_ptr = (__fp16 *)input + c * in_size;
// pad h_top
for (int i = 0; i < pad_top * padded_w; i++) {
vse16_v_f16m1(pad_ptr, _zero, vl);
pad_ptr += packn;
}
// pad h_mid
for (int i = 0; i < inh; i++) {
// pad w_left
for (int j = 0; j < pad_left; j++) {
vse16_v_f16m1(pad_ptr, _zero, vl);
pad_ptr += packn;
}
// pad w_mid
for (int j = 0; j < inw; j++) {
vfloat16m1_t _tmp = vlse16_v_f16m1(inp_ptr, in_size * sizeof(__fp16), vl);
inp_ptr++;
vse16_v_f16m1(pad_ptr, _tmp, vl);
pad_ptr += packn;
}
// pad w_end
for (int j = 0; j < pad_right; j++) {
vse16_v_f16m1(pad_ptr, _zero, vl);
pad_ptr += packn;
}
}
// pad h_bottom
for (int i = 0; i < pad_down * padded_w; i++) {
vse16_v_f16m1(pad_ptr, _zero, vl);
pad_ptr += packn;
}
}
}
static void winograd_crop_output_packnto1_fp16(const __fp16 *output_trans, __fp16 *output,
int out_c, int out_h, int out_w, int wino_h,
int wino_w)
{
const int packn = csrr_vlenb() / sizeof(__fp16);
const int vl = vsetvl_e16m1(packn);
const int out_size = out_h * out_w; // per-channel size
const int crop_size = wino_h * wino_w;
__fp16 *out_tm_ptr = (__fp16 *)output_trans;
__fp16 *out_ptr = output;
int c = 0;
for (; c + packn - 1 < out_c; c += packn) {
out_tm_ptr = (__fp16 *)output_trans + c * crop_size;
out_ptr = output + c * out_size;
for (int h = 0; h < out_h; h++) {
__fp16 *crop_ptr = out_tm_ptr + h * wino_w * packn;
for (int w = 0; w < out_w; w++) {
vfloat16m1_t _tmp = vle16_v_f16m1(crop_ptr, vl);
crop_ptr += packn;
vsse16_v_f16m1(out_ptr, out_size * sizeof(__fp16), _tmp, vl);
out_ptr++;
}
}
}
}
/*
pack n = VLEN / 16 (128/16=8 or 256/16=16)
constrain: output channel % n = 0
input channel % n = 0
kernel before: [O I 3*3]
kernel after : [O/n 8*8 I n]
*/
void csi_nn_rvv_conv3x3s1_winograd64_transform_kernel_packn_fp16(struct csi_tensor *o_kernel,
struct csi_tensor *t_kernel)
{
int32_t outch = o_kernel->dim[0];
int32_t inch = o_kernel->dim[1];
__fp16 *kernel_data = (__fp16 *)o_kernel->data;
// for kernel transform buf, 3x3 --> 8x8
__fp16 *kernel_tm = (__fp16 *)csi_mem_alloc(outch * inch * 8 * 8 * sizeof(__fp16));
// kernel transform matrix: G
const __fp16 ktm[8][3] = {{1.0f, 0.0f, 0.0f},
{-2.0f / 9, -2.0f / 9, -2.0f / 9},
{-2.0f / 9, 2.0f / 9, -2.0f / 9},
{1.0f / 90, 1.0f / 45, 2.0f / 45},
{1.0f / 90, -1.0f / 45, 2.0f / 45},
{1.0f / 45, 1.0f / 90, 1.0f / 180},
{1.0f / 45, -1.0f / 90, 1.0f / 180},
{0.0f, 0.0f, 1.0f}};
// const __fp16 ktm[8][3] = {
// {1.0f, 0.0f, 0.0f},
// {-2.0f / 9, -2.0f / 9, -2.0f / 9},
// {-2.0f / 9, 2.0f / 9, -2.0f / 9},
// {1.0f / 90, 1.0f / 45, 2.0f / 45},
// {1.0f / 90, -1.0f / 45, 2.0f / 45},
// {32.0f / 45, 16.0f / 45, 8.0f / 45},
// {32.0f / 45, -16.0f / 45, 8.0f / 45},
// {0.0f, 0.0f, 1.0f}
// };
csi_tensor_copy(t_kernel, o_kernel);
for (int p = 0; p < outch; p++) {
for (int q = 0; q < inch; q++) {
const __fp16 *kernel0 = kernel_data + p * inch * 9 + q * 9;
__fp16 *kernel_tmp = kernel_tm + p * inch * 64 + q * 64;
// transform kernel
const __fp16 *k0 = kernel0;
const __fp16 *k1 = kernel0 + 3;
const __fp16 *k2 = kernel0 + 6;
// h : first compute the transport matrix tmp = (g * GT)T
__fp16 tmp[8][3];
for (int i = 0; i < 8; i++) {
tmp[i][0] = k0[0] * ktm[i][0] + k0[1] * ktm[i][1] + k0[2] * ktm[i][2];
tmp[i][1] = k1[0] * ktm[i][0] + k1[1] * ktm[i][1] + k1[2] * ktm[i][2];
tmp[i][2] = k2[0] * ktm[i][0] + k2[1] * ktm[i][1] + k2[2] * ktm[i][2];
}
// U
for (int j = 0; j < 8; j++) {
__fp16 *tmpp = &tmp[j][0];
for (int i = 0; i < 8; i++) {
kernel_tmp[j * 8 + i] =
tmpp[0] * ktm[i][0] + tmpp[1] * ktm[i][1] + tmpp[2] * ktm[i][2];
}
}
}
}
// optimized layout for winograd64
const int packn = csrr_vlenb() / sizeof(__fp16);
__fp16 *kernel_tm_packn = (__fp16 *)csi_mem_alloc(outch * inch * 8 * 8 * sizeof(__fp16));
t_kernel->data = kernel_tm_packn;
for (int oc = 0; oc < outch / packn; oc++) {
__fp16 *g0 = kernel_tm_packn + oc * 64 * inch * packn;
for (int k = 0; k < 64; k++) {
__fp16 *g00 = g0 + k * inch * packn;
for (int ic = 0; ic < inch / packn; ic++) {
for (int i = 0; i < packn; i++) {
for (int j = 0; j < packn; j++) {
const __fp16 *k00 =
kernel_tm + (oc * packn + j) * 64 * inch + (ic * packn + i) * 64;
*g00++ = k00[k];
}
}
}
}
}
csi_mem_free(kernel_tm);
}
/*
n = VLEN / 16
constrain: output channel % n = 0
input channel % n = 0
*/
int csi_nn_rvv_conv3x3s1_winograd64_packn_fp16(struct csi_tensor *input, struct csi_tensor *output,
struct csi_tensor *kernel, struct csi_tensor *bias,
struct conv2d_params *params)
{
__fp16 *input_data = (__fp16 *)input->data;
__fp16 *output_data = (__fp16 *)output->data;
__fp16 *kernel_data = (__fp16 *)params->conv_extra.kernel_tm->data;
__fp16 *bias_data = (__fp16 *)bias->data;
// param
int kernel_h = kernel->dim[2];
int kernel_w = kernel->dim[3];
int stride_h = params->stride_height;
int stride_w = params->stride_width;
int dilation_h = params->dilation_height;
int dilation_w = params->dilation_width;
int pad_left = params->pad_left;
int pad_top = params->pad_top;
int batch = input->dim[0];
int in_c = input->dim[1];
int in_h = input->dim[2];
int in_w = input->dim[3];
int input_size = in_c * in_h * in_w;
int kernel_size = in_c * kernel_h * kernel_w;
int out_c = kernel->dim[0];
int out_h = output->dim[2];
int out_w = output->dim[3];
int output_size = out_c * out_h * out_w;
// winograd param
int block_h = (out_h + 5) / 6;
int block_w = (out_w + 5) / 6;
int padded_in_h =
block_h * 6 +
2; // block * 4 for alignment with 4，kernel = 3 * 3 ，stride = 1，thus input_size + 2
int padded_in_w = block_w * 6 + 2;
int padded_in_hw = padded_in_h * padded_in_w; // element size after padding per channel
/****************************** bias *****************************/
bool flag_bias = 1; // default: conv2d layer include bias
if (bias_data == NULL) {
flag_bias = 0;
bias_data = (__fp16 *)csi_mem_alloc(out_c * sizeof(__fp16));
}
const int packn = csrr_vlenb() / sizeof(__fp16);
const int vl = vsetvl_e16m1(packn);
for (int n = 0; n < batch; n++) {
// pad buffer: [in_c/8 h w 8]
__fp16 *input_padd_buf = (__fp16 *)csi_mem_alloc(in_c * padded_in_hw * sizeof(__fp16));
// pad input
winograd_pad_input_pack1ton_fp16(input_data, input_padd_buf, in_c, in_h, in_w, padded_in_h,
padded_in_w, pad_top, pad_left);
input_data += input_size;
// input transform buffer1: [in_ch/8, 64, blocks, 8]
__fp16 *input_tm1_buf =
(__fp16 *)csi_mem_alloc(in_c * block_h * block_w * 8 * 8 * sizeof(__fp16));
/****************************** transform input *****************************/
/*
BT = {
{ 1 0 -5.25 0 5.25 0 -1 0 };
{ 0 1 1 -4.25 -4.25 1 1 0 };
{ 0 -1 1 4.25 -4.25 -1 1 0 };
{ 0 0.5 0.25 -2.5 -1.25 2 1 0 };
{ 0 -0.5 0.25 2.5 -1.25 -2 1 0 };
{ 0 2 4 -2.5 -5 0.5 1 0 };
{ 0 -2 4 2.5 -5 -0.5 1 0 };
{ 0 -1 0 5.25 0 -5.25 0 1 }
};
*/
int tiles = block_h * block_w;
#pragma omp parallel for num_threads(1)
for (int q = 0; q < in_c / packn; q++) {
__fp16 *img0 = input_padd_buf + q * padded_in_h * padded_in_w *
packn; // feature map after padding - q channel
__fp16 *img0_tm =
input_tm1_buf + q * 64 * tiles * packn; // transform and interleave - q channel
__fp16 tmp[8][8][packn];
for (int i = 0; i < block_h; i++) {
for (int j = 0; j < block_w; j++) {
__fp16 *r0 = img0 + (i * padded_in_w * 6 + j * 6) *
packn; // feature map after padding 8*8 start addr
__fp16 *r0_tm =
img0_tm + (i * block_w + j) * packn; // input_tm1 8*8 block start addr
for (int m = 0; m < 8; m++) {
vfloat16m1_t _r00 = vle16_v_f16m1(r0, vl);
vfloat16m1_t _r01 = vle16_v_f16m1(r0 + packn * 1, vl);
vfloat16m1_t _r02 = vle16_v_f16m1(r0 + packn * 2, vl);
vfloat16m1_t _r03 = vle16_v_f16m1(r0 + packn * 3, vl);
vfloat16m1_t _r04 = vle16_v_f16m1(r0 + packn * 4, vl);
vfloat16m1_t _r05 = vle16_v_f16m1(r0 + packn * 5, vl);
vfloat16m1_t _r06 = vle16_v_f16m1(r0 + packn * 6, vl);
vfloat16m1_t _r07 = vle16_v_f16m1(r0 + packn * 7, vl);
vfloat16m1_t _tmp0m = vfmacc_vf_f16m1(vfsub_vv_f16m1(_r00, _r06, vl), 5.25f,
vfsub_vv_f16m1(_r04, _r02, vl), vl);
vfloat16m1_t _tmp7m = vfmacc_vf_f16m1(vfsub_vv_f16m1(_r07, _r01, vl), 5.25f,
vfsub_vv_f16m1(_r03, _r05, vl), vl);
vfloat16m1_t _tmp12a =
vfmacc_vf_f16m1(vfadd_vv_f16m1(_r02, _r06, vl), -4.25f, _r04, vl);
vfloat16m1_t _tmp12b =
vfmacc_vf_f16m1(vfadd_vv_f16m1(_r01, _r05, vl), -4.25f, _r03, vl);
vfloat16m1_t _tmp1m = vfadd_vv_f16m1(_tmp12a, _tmp12b, vl);
vfloat16m1_t _tmp2m = vfsub_vv_f16m1(_tmp12a, _tmp12b, vl);
vfloat16m1_t _tmp34a = vfmacc_vf_f16m1(
vfmacc_vf_f16m1(_r06, 0.25f, _r02, vl), -1.25f, _r04, vl);
vfloat16m1_t _tmp34b = vfmacc_vf_f16m1(
vfmacc_vf_f16m1(vfmul_vf_f16m1(_r01, 0.5f, vl), -2.5f, _r03, vl), 2.f,
_r05, vl);
vfloat16m1_t _tmp3m = vfadd_vv_f16m1(_tmp34a, _tmp34b, vl);
vfloat16m1_t _tmp4m = vfsub_vv_f16m1(_tmp34a, _tmp34b, vl);
vfloat16m1_t _tmp56a =
vfmacc_vf_f16m1(_r06, 4.f, vfmacc_vf_f16m1(_r02, -1.25f, _r04, vl), vl);
vfloat16m1_t _tmp56b = vfmacc_vf_f16m1(
vfmacc_vf_f16m1(vfmul_vf_f16m1(_r01, 2.f, vl), -2.5f, _r03, vl), 0.5f,
_r05, vl);
vfloat16m1_t _tmp5m = vfadd_vv_f16m1(_tmp56a, _tmp56b, vl);
vfloat16m1_t _tmp6m = vfsub_vv_f16m1(_tmp56a, _tmp56b, vl);
vse16_v_f16m1(tmp[0][m], _tmp0m, vl);
vse16_v_f16m1(tmp[7][m], _tmp7m, vl);
vse16_v_f16m1(tmp[1][m], _tmp1m, vl);
vse16_v_f16m1(tmp[2][m], _tmp2m, vl);
vse16_v_f16m1(tmp[3][m], _tmp3m, vl);
vse16_v_f16m1(tmp[4][m], _tmp4m, vl);
vse16_v_f16m1(tmp[5][m], _tmp5m, vl);
vse16_v_f16m1(tmp[6][m], _tmp6m, vl);
r0 += padded_in_w * packn;
}
for (int m = 0; m < 8; m++) {
__fp16 *r0_tm0 = r0_tm;
__fp16 *r0_tm1 = r0_tm0 + tiles * packn;
__fp16 *r0_tm2 = r0_tm1 + tiles * packn;
__fp16 *r0_tm3 = r0_tm2 + tiles * packn;
__fp16 *r0_tm4 = r0_tm3 + tiles * packn;
__fp16 *r0_tm5 = r0_tm4 + tiles * packn;
__fp16 *r0_tm6 = r0_tm5 + tiles * packn;
__fp16 *r0_tm7 = r0_tm6 + tiles * packn;
vfloat16m1_t _tmp00 = vle16_v_f16m1(tmp[m][0], vl);
vfloat16m1_t _tmp01 = vle16_v_f16m1(tmp[m][1], vl);
vfloat16m1_t _tmp02 = vle16_v_f16m1(tmp[m][2], vl);
vfloat16m1_t _tmp03 = vle16_v_f16m1(tmp[m][3], vl);
vfloat16m1_t _tmp04 = vle16_v_f16m1(tmp[m][4], vl);
vfloat16m1_t _tmp05 = vle16_v_f16m1(tmp[m][5], vl);
vfloat16m1_t _tmp06 = vle16_v_f16m1(tmp[m][6], vl);
vfloat16m1_t _tmp07 = vle16_v_f16m1(tmp[m][7], vl);
vfloat16m1_t _r0tm0 =
vfmacc_vf_f16m1(vfsub_vv_f16m1(_tmp00, _tmp06, vl), 5.25f,
vfsub_vv_f16m1(_tmp04, _tmp02, vl), vl);
vfloat16m1_t _r0tm7 =
vfmacc_vf_f16m1(vfsub_vv_f16m1(_tmp07, _tmp01, vl), 5.25f,
vfsub_vv_f16m1(_tmp03, _tmp05, vl), vl);
vfloat16m1_t _tmp12a =
vfmacc_vf_f16m1(vfadd_vv_f16m1(_tmp02, _tmp06, vl), -4.25f, _tmp04, vl);
vfloat16m1_t _tmp12b =
vfmacc_vf_f16m1(vfadd_vv_f16m1(_tmp01, _tmp05, vl), -4.25f, _tmp03, vl);
vfloat16m1_t _r0tm1 = vfadd_vv_f16m1(_tmp12a, _tmp12b, vl);
vfloat16m1_t _r0tm2 = vfsub_vv_f16m1(_tmp12a, _tmp12b, vl);
vfloat16m1_t _tmp34a = vfmacc_vf_f16m1(
vfmacc_vf_f16m1(_tmp06, 0.25f, _tmp02, vl), -1.25f, _tmp04, vl);
vfloat16m1_t _tmp34b = vfmacc_vf_f16m1(
vfmacc_vf_f16m1(vfmul_vf_f16m1(_tmp01, 0.5f, vl), -2.5f, _tmp03, vl),
2.f, _tmp05, vl);
vfloat16m1_t _r0tm3 = vfadd_vv_f16m1(_tmp34a, _tmp34b, vl);
vfloat16m1_t _r0tm4 = vfsub_vv_f16m1(_tmp34a, _tmp34b, vl);
vfloat16m1_t _tmp56a = vfmacc_vf_f16m1(
_tmp06, 4.f, vfmacc_vf_f16m1(_tmp02, -1.25f, _tmp04, vl), vl);
vfloat16m1_t _tmp56b = vfmacc_vf_f16m1(
vfmacc_vf_f16m1(vfmul_vf_f16m1(_tmp01, 2.f, vl), -2.5f, _tmp03, vl),
0.5f, _tmp05, vl);
vfloat16m1_t _r0tm5 = vfadd_vv_f16m1(_tmp56a, _tmp56b, vl);
vfloat16m1_t _r0tm6 = vfsub_vv_f16m1(_tmp56a, _tmp56b, vl);
vse16_v_f16m1(r0_tm0, _r0tm0, vl);
vse16_v_f16m1(r0_tm7, _r0tm7, vl);
vse16_v_f16m1(r0_tm1, _r0tm1, vl);
vse16_v_f16m1(r0_tm2, _r0tm2, vl);
vse16_v_f16m1(r0_tm3, _r0tm3, vl);
vse16_v_f16m1(r0_tm4, _r0tm4, vl);
vse16_v_f16m1(r0_tm5, _r0tm5, vl);
vse16_v_f16m1(r0_tm6, _r0tm6, vl);
r0_tm += tiles * packn * 8;
}
}
}
}
csi_mem_free(input_padd_buf);
/*********************************** dot ***************************************/
// reorder input_tm1_buf
int size_input_tm2 = 0;
if (tiles >= 8) {
size_input_tm2 =
64 * (tiles / 8 + (tiles % 8) / 4 + (tiles % 4) / 2 + tiles % 2) * in_c * 8;
} else if (tiles >= 4) {
size_input_tm2 = 64 * (tiles / 4 + (tiles % 4) / 2 + tiles % 2) * in_c * 4;
} else if (tiles >= 2) {
size_input_tm2 = 64 * (tiles / 2 + tiles % 2) * in_c * 2;
} else {
size_input_tm2 = 64 * tiles * in_c;
}
__fp16 *input_tm2_buf = (__fp16 *)csi_mem_alloc(size_input_tm2 * sizeof(__fp16));
#pragma omp parallel for num_threads(1)
for (int r = 0; r < 64; r++) {
__fp16 *img_tm2 = input_tm2_buf + r * size_input_tm2 / 64; // input_tm2 r channel data
int t = 0;
for (; t + 7 < tiles; t += 8) {
__fp16 *tm2 = img_tm2 + t * in_c; // img_tm2 row data
__fp16 *tm1 = input_tm1_buf;
tm1 += (r * tiles + t) * packn;
for (int q = 0; q < in_c / packn; q++) {
vfloat16m1_t _tmp0 = vle16_v_f16m1(tm1, vl);
vfloat16m1_t _tmp1 = vle16_v_f16m1(tm1 + packn * 1, vl);
vfloat16m1_t _tmp2 = vle16_v_f16m1(tm1 + packn * 2, vl);
vfloat16m1_t _tmp3 = vle16_v_f16m1(tm1 + packn * 3, vl);
vfloat16m1_t _tmp4 = vle16_v_f16m1(tm1 + packn * 4, vl);
vfloat16m1_t _tmp5 = vle16_v_f16m1(tm1 + packn * 5, vl);
vfloat16m1_t _tmp6 = vle16_v_f16m1(tm1 + packn * 6, vl);
vfloat16m1_t _tmp7 = vle16_v_f16m1(tm1 + packn * 7, vl);
vsseg8e16_v_f16m1(tm2, _tmp0, _tmp1, _tmp2, _tmp3, _tmp4, _tmp5, _tmp6, _tmp7,
vl);
tm1 += 64 * tiles * packn;
tm2 += 8 * packn;
}
}
for (; t + 3 < tiles; t += 4) {
__fp16 *tm2 = img_tm2 + (t / 8 + (t % 8) / 4) * in_c * 8; // img_tm2 row data
__fp16 *tm1 = input_tm1_buf;
tm1 += (r * tiles + t) * packn;
for (int q = 0; q < in_c / packn; q++) {
vfloat16m1_t _tmp0 = vle16_v_f16m1(tm1, vl);
vfloat16m1_t _tmp1 = vle16_v_f16m1(tm1 + packn * 1, vl);
vfloat16m1_t _tmp2 = vle16_v_f16m1(tm1 + packn * 2, vl);
vfloat16m1_t _tmp3 = vle16_v_f16m1(tm1 + packn * 3, vl);
vsseg4e16_v_f16m1(tm2, _tmp0, _tmp1, _tmp2, _tmp3, vl);
tm1 += 64 * tiles * packn;
tm2 += 4 * packn;
}
}
for (; t + 1 < tiles; t += 2) {
__fp16 *tm2 =
img_tm2 + (t / 8 + (t % 8) / 4 + (t % 4) / 2) * in_c * 8; // img_tm2 row data
__fp16 *tm1 = input_tm1_buf;
tm1 += (r * tiles + t) * packn;
for (int q = 0; q < in_c / packn; q++) {
vfloat16m1_t _tmp0 = vle16_v_f16m1(tm1, vl);
vfloat16m1_t _tmp1 = vle16_v_f16m1(tm1 + packn * 1, vl);
vsseg2e16_v_f16m1(tm2, _tmp0, _tmp1, vl);
tm1 += 64 * tiles * packn;
tm2 += 2 * packn;
}
}
for (; t < tiles; t++) {
__fp16 *tm2 = img_tm2 + (t / 8 + (t % 8) / 4 + (t % 4) / 2 + t % 2) * in_c *
8; // img_tm2 row data
__fp16 *tm1 = input_tm1_buf;
tm1 += (r * tiles + t) * packn;
for (int q = 0; q < in_c / packn; q++) {
vfloat16m1_t _tmp0 = vle16_v_f16m1(tm1, vl);
vse16_v_f16m1(tm2, _tmp0, vl);
tm1 += 64 * tiles * packn;
tm2 += 1 * packn;
}
}
}
csi_mem_free(input_tm1_buf);
// output_dot_buf： [out_c/8, 64, blocks, 8]
__fp16 *output_dot_buf =
(__fp16 *)csi_mem_alloc(out_c * block_h * block_w * 8 * 8 * sizeof(__fp16));
#pragma omp parallel for num_threads(1)
for (int p = 0; p < out_c / packn; p++) {
__fp16 *output0_tm = output_dot_buf + p * 64 * tiles * packn;
__fp16 *kernel0_tm = kernel_data + p * 64 * in_c * packn;
for (int r = 0; r < 64; r++) {
__fp16 *img_tm2 = input_tm2_buf + r * size_input_tm2 / 64; // img_tm2 第r个channel
int t = 0;
for (; t + 7 < tiles; t += 8) {
__fp16 *r0 = img_tm2 + t * in_c;
__fp16 *k0 = kernel0_tm + r * in_c * packn;
vfloat16m1_t _acc0 = vfmv_v_f_f16m1(0.0f, vl);
vfloat16m1_t _acc1 = vfmv_v_f_f16m1(0.0f, vl);
vfloat16m1_t _acc2 = vfmv_v_f_f16m1(0.0f, vl);
vfloat16m1_t _acc3 = vfmv_v_f_f16m1(0.0f, vl);
vfloat16m1_t _acc4 = vfmv_v_f_f16m1(0.0f, vl);
vfloat16m1_t _acc5 = vfmv_v_f_f16m1(0.0f, vl);
vfloat16m1_t _acc6 = vfmv_v_f_f16m1(0.0f, vl);
vfloat16m1_t _acc7 = vfmv_v_f_f16m1(0.0f, vl);
for (int c = 0; c < in_c; c++) {
vfloat16m1_t _kernel = vle16_v_f16m1(k0, vl);
k0 += packn;
_acc0 = vfmacc_vf_f16m1(_acc0, r0[0], _kernel, vl);
_acc1 = vfmacc_vf_f16m1(_acc1, r0[1], _kernel, vl);
_acc2 = vfmacc_vf_f16m1(_acc2, r0[2], _kernel, vl);
_acc3 = vfmacc_vf_f16m1(_acc3, r0[3], _kernel, vl);
_acc4 = vfmacc_vf_f16m1(_acc4, r0[4], _kernel, vl);
_acc5 = vfmacc_vf_f16m1(_acc5, r0[5], _kernel, vl);
_acc6 = vfmacc_vf_f16m1(_acc6, r0[6], _kernel, vl);
_acc7 = vfmacc_vf_f16m1(_acc7, r0[7], _kernel, vl);
r0 += 8;
}
vse16_v_f16m1(output0_tm, _acc0, vl);
vse16_v_f16m1(output0_tm + packn * 1, _acc1, vl);
vse16_v_f16m1(output0_tm + packn * 2, _acc2, vl);
vse16_v_f16m1(output0_tm + packn * 3, _acc3, vl);
vse16_v_f16m1(output0_tm + packn * 4, _acc4, vl);
vse16_v_f16m1(output0_tm + packn * 5, _acc5, vl);
vse16_v_f16m1(output0_tm + packn * 6, _acc6, vl);
vse16_v_f16m1(output0_tm + packn * 7, _acc7, vl);
output0_tm += packn * 8;
}
for (; t + 3 < tiles; t += 4) {
__fp16 *r0 = img_tm2 + (t / 8 + (t % 8) / 4) * in_c * 8;
__fp16 *k0 = kernel0_tm + r * in_c * packn;
vfloat16m1_t _acc0 = vfmv_v_f_f16m1(0.0f, vl);
vfloat16m1_t _acc1 = vfmv_v_f_f16m1(0.0f, vl);
vfloat16m1_t _acc2 = vfmv_v_f_f16m1(0.0f, vl);
vfloat16m1_t _acc3 = vfmv_v_f_f16m1(0.0f, vl);
for (int c = 0; c < in_c; c++) {
vfloat16m1_t _kernel = vle16_v_f16m1(k0, vl);
k0 += packn;
_acc0 = vfmacc_vf_f16m1(_acc0, r0[0], _kernel, vl);
_acc1 = vfmacc_vf_f16m1(_acc1, r0[1], _kernel, vl);
_acc2 = vfmacc_vf_f16m1(_acc2, r0[2], _kernel, vl);
_acc3 = vfmacc_vf_f16m1(_acc3, r0[3], _kernel, vl);
r0 += 4;
}
vse16_v_f16m1(output0_tm, _acc0, vl);
vse16_v_f16m1(output0_tm + packn * 1, _acc1, vl);
vse16_v_f16m1(output0_tm + packn * 2, _acc2, vl);
vse16_v_f16m1(output0_tm + packn * 3, _acc3, vl);
output0_tm += packn * 4;
}
for (; t + 1 < tiles; t += 2) {
__fp16 *r0 = img_tm2 + (t / 8 + (t % 8) / 4 + (t % 4) / 2) * in_c * 8;
__fp16 *k0 = kernel0_tm + r * in_c * packn;
vfloat16m1_t _acc0 = vfmv_v_f_f16m1(0.0f, vl);
vfloat16m1_t _acc1 = vfmv_v_f_f16m1(0.0f, vl);
for (int c = 0; c < in_c; c++) {
vfloat16m1_t _kernel = vle16_v_f16m1(k0, vl);
k0 += packn;
_acc0 = vfmacc_vf_f16m1(_acc0, r0[0], _kernel, vl);
_acc1 = vfmacc_vf_f16m1(_acc1, r0[1], _kernel, vl);
r0 += 2;
}
vse16_v_f16m1(output0_tm, _acc0, vl);
vse16_v_f16m1(output0_tm + packn * 1, _acc1, vl);
output0_tm += packn * 2;
}
for (; t < tiles; t++) {
__fp16 *r0 = img_tm2 + (t / 8 + (t % 8) / 4 + (t % 4) / 2 + t % 2) * in_c * 8;
__fp16 *k0 = kernel0_tm + r * in_c * packn;
vfloat16m1_t _acc0 = vfmv_v_f_f16m1(0.0f, vl);
for (int c = 0; c < in_c; c++) {
vfloat16m1_t _kernel = vle16_v_f16m1(k0, vl);
k0 += packn;
_acc0 = vfmacc_vf_f16m1(_acc0, r0[0], _kernel, vl);
r0 += 1;
}
vse16_v_f16m1(output0_tm, _acc0, vl);
output0_tm += packn * 1;
}
}
}
csi_mem_free(input_tm2_buf);
/*************************** transform output ****************************/
// output_tm1_buf: [out_c/8, out_h6, out_w6, 8]
__fp16 *output_tm1_buf =
(__fp16 *)csi_mem_alloc(out_c * block_h * block_w * 6 * 6 * sizeof(__fp16));
/*
AT = {
{ 1 1 1 1 1 1 1 0 };
{ 0 1 -1 2 -2 1/2 -1/2 0 };
{ 0 1 1 4 4 1/4 1/4 0 };
{ 0 1 -1 8 -8 1/8 -1/8 0 };
{ 0 1 1 16 16 1/16 1/16 0 };
{ 0 1 -1 32 -32 1/32 -1/32 1 }
};
AT = {
{ 1 1 1 1 1 32 32 0 };
{ 0 1 -1 2 -2 16 -16 0 };
{ 0 1 1 4 4 8 8 0 };
{ 0 1 -1 8 -8 4 -4 0 };
{ 0 1 1 16 16 2 2 0 };
{ 0 1 -1 32 -32 1 -1 1 }
};
*/
#pragma omp parallel for num_threads(1)
for (int p = 0; p < out_c / packn; p++) {
__fp16 *bias_tmp = bias_data + p * packn;
__fp16 *out0_tm = output_dot_buf +
p * 64 * block_h * block_w * packn; // 输出转换前/dot后 第p个channel
__fp16 *out0 =
output_tm1_buf + p * 6 * block_h * 6 * block_w * packn; // 转换后输出 第p个channel
__fp16 tmp[6][8][packn];
for (int i = 0; i < block_h; i++) {
for (int j = 0; j < block_w; j++) {
__fp16 *output0_tm_0 = out0_tm + (i * block_w + j) * packn; // 8*8 起始地址
__fp16 *output0_tm_1 = output0_tm_0 + tiles * packn * 1;
__fp16 *output0_tm_2 = output0_tm_0 + tiles * packn * 2;
__fp16 *output0_tm_3 = output0_tm_0 + tiles * packn * 3;
__fp16 *output0_tm_4 = output0_tm_0 + tiles * packn * 4;
__fp16 *output0_tm_5 = output0_tm_0 + tiles * packn * 5;
__fp16 *output0_tm_6 = output0_tm_0 + tiles * packn * 6;
__fp16 *output0_tm_7 = output0_tm_0 + tiles * packn * 7;
__fp16 *output0 =
out0 + (i * block_w * 6 * 6 + j * 6) * packn; // 输出 6*6 的起始地址
for (int m = 0; m < 8; m++) {
vfloat16m1_t _r00 = vle16_v_f16m1(output0_tm_0, vl);
vfloat16m1_t _r01 = vle16_v_f16m1(output0_tm_1, vl);
vfloat16m1_t _r02 = vle16_v_f16m1(output0_tm_2, vl);
vfloat16m1_t _r03 = vle16_v_f16m1(output0_tm_3, vl);
vfloat16m1_t _r04 = vle16_v_f16m1(output0_tm_4, vl);
vfloat16m1_t _r05 = vle16_v_f16m1(output0_tm_5, vl);
vfloat16m1_t _r06 = vle16_v_f16m1(output0_tm_6, vl);
vfloat16m1_t _r07 = vle16_v_f16m1(output0_tm_7, vl);
vfloat16m1_t _tmp024a = vfadd_vv_f16m1(_r01, _r02, vl);
vfloat16m1_t _tmp135a = vfsub_vv_f16m1(_r01, _r02, vl);
vfloat16m1_t _tmp024b = vfadd_vv_f16m1(_r03, _r04, vl);
vfloat16m1_t _tmp135b = vfsub_vv_f16m1(_r03, _r04, vl);
vfloat16m1_t _tmp024c = vfadd_vv_f16m1(_r05, _r06, vl);
vfloat16m1_t _tmp135c = vfsub_vv_f16m1(_r05, _r06, vl);
vfloat16m1_t _tmp0m =
vfadd_vv_f16m1(vfadd_vv_f16m1(_r00, _tmp024a, vl),
vfmacc_vf_f16m1(_tmp024b, 32.f, _tmp024c, vl), vl);
vfloat16m1_t _tmp2m = vfmacc_vf_f16m1(
vfmacc_vf_f16m1(_tmp024a, 4.f, _tmp024b, vl), 8.f, _tmp024c, vl);
vfloat16m1_t _tmp4m = vfmacc_vf_f16m1(
vfmacc_vf_f16m1(_tmp024a, 16.f, _tmp024b, vl), 2.f, _tmp024c, vl);
vfloat16m1_t _tmp1m = vfmacc_vf_f16m1(
vfmacc_vf_f16m1(_tmp135a, 2.f, _tmp135b, vl), 16.f, _tmp135c, vl);
vfloat16m1_t _tmp3m = vfmacc_vf_f16m1(
vfmacc_vf_f16m1(_tmp135a, 8.f, _tmp135b, vl), 4.f, _tmp135c, vl);
vfloat16m1_t _tmp5m =
vfadd_vv_f16m1(vfadd_vv_f16m1(_r07, _tmp135a, vl),
vfmacc_vf_f16m1(_tmp135c, 32.f, _tmp135b, vl), vl);
vse16_v_f16m1(tmp[0][m], _tmp0m, vl);
vse16_v_f16m1(tmp[2][m], _tmp2m, vl);
vse16_v_f16m1(tmp[4][m], _tmp4m, vl);
vse16_v_f16m1(tmp[1][m], _tmp1m, vl);
vse16_v_f16m1(tmp[3][m], _tmp3m, vl);
vse16_v_f16m1(tmp[5][m], _tmp5m, vl);
output0_tm_0 += tiles * packn * 8;
output0_tm_1 += tiles * packn * 8;
output0_tm_2 += tiles * packn * 8;
output0_tm_3 += tiles * packn * 8;
output0_tm_4 += tiles * packn * 8;
output0_tm_5 += tiles * packn * 8;
output0_tm_6 += tiles * packn * 8;
output0_tm_7 += tiles * packn * 8;
}
vfloat16m1_t _bias = vle16_v_f16m1(bias_tmp, vl);
for (int m = 0; m < 6; m++) {
vfloat16m1_t _tmp00 = vle16_v_f16m1(tmp[m][0], vl);
vfloat16m1_t _tmp01 = vle16_v_f16m1(tmp[m][1], vl);
vfloat16m1_t _tmp02 = vle16_v_f16m1(tmp[m][2], vl);
vfloat16m1_t _tmp03 = vle16_v_f16m1(tmp[m][3], vl);
vfloat16m1_t _tmp04 = vle16_v_f16m1(tmp[m][4], vl);
vfloat16m1_t _tmp05 = vle16_v_f16m1(tmp[m][5], vl);
vfloat16m1_t _tmp06 = vle16_v_f16m1(tmp[m][6], vl);
vfloat16m1_t _tmp07 = vle16_v_f16m1(tmp[m][7], vl);
vfloat16m1_t _tmp024a = vfadd_vv_f16m1(_tmp01, _tmp02, vl);
vfloat16m1_t _tmp135a = vfsub_vv_f16m1(_tmp01, _tmp02, vl);
vfloat16m1_t _tmp024b = vfadd_vv_f16m1(_tmp03, _tmp04, vl);
vfloat16m1_t _tmp135b = vfsub_vv_f16m1(_tmp03, _tmp04, vl);
vfloat16m1_t _tmp024c = vfadd_vv_f16m1(_tmp05, _tmp06, vl);
vfloat16m1_t _tmp135c = vfsub_vv_f16m1(_tmp05, _tmp06, vl);
vfloat16m1_t _output00 = vfadd_vv_f16m1(
_bias,
vfadd_vv_f16m1(vfadd_vv_f16m1(_tmp00, _tmp024a, vl),
vfmacc_vf_f16m1(_tmp024b, 32.f, _tmp024c, vl), vl),
vl);
vfloat16m1_t _output02 = vfadd_vv_f16m1(
_bias,
vfmacc_vf_f16m1(vfmacc_vf_f16m1(_tmp024a, 4.f, _tmp024b, vl), 8.f,
_tmp024c, vl),
vl);
vfloat16m1_t _output04 = vfadd_vv_f16m1(
_bias,
vfmacc_vf_f16m1(vfmacc_vf_f16m1(_tmp024a, 16.f, _tmp024b, vl), 2.f,
_tmp024c, vl),
vl);
vfloat16m1_t _output01 = vfadd_vv_f16m1(
_bias,
vfmacc_vf_f16m1(vfmacc_vf_f16m1(_tmp135a, 2.f, _tmp135b, vl), 16.f,
_tmp135c, vl),
vl);
vfloat16m1_t _output03 = vfadd_vv_f16m1(
_bias,
vfmacc_vf_f16m1(vfmacc_vf_f16m1(_tmp135a, 8.f, _tmp135b, vl), 4.f,
_tmp135c, vl),
vl);
vfloat16m1_t _output05 = vfadd_vv_f16m1(
_bias,
vfadd_vv_f16m1(vfadd_vv_f16m1(_tmp07, _tmp135a, vl),
vfmacc_vf_f16m1(_tmp135c, 32.f, _tmp135b, vl), vl),
vl);
vse16_v_f16m1(output0, _output00, vl);
vse16_v_f16m1(output0 + packn * 2, _output02, vl);
vse16_v_f16m1(output0 + packn * 4, _output04, vl);
vse16_v_f16m1(output0 + packn * 1, _output01, vl);
vse16_v_f16m1(output0 + packn * 3, _output03, vl);
vse16_v_f16m1(output0 + packn * 5, _output05, vl);
output0 += block_w * 6 * packn;
}
}
}
}
csi_mem_free(output_dot_buf);
// crop the output after transform: cut extra part (right , bottom)
winograd_crop_output_packnto1_fp16(output_tm1_buf, output_data, out_c, out_h, out_w,
block_h * 6, block_w * 6);
output_data += output_size;
csi_mem_free(output_tm1_buf);
}
if (!flag_bias) {
csi_mem_free(bias_data);
bias_data = NULL;
}
return CSINN_TRUE;
}
|
Example_nthrs_nesting.1.c | /*
* @@name: nthrs_nesting.1c
* @@type: C
* @@compilable: yes
* @@linkable: yes
* @@expect: success
*/
#include <stdio.h>
#include <omp.h>
int main (void)
{
omp_set_nested(1);
omp_set_dynamic(0);
#pragma omp parallel
{
#pragma omp parallel
{
#pragma omp single
{
/*
* If OMP_NUM_THREADS=2,3 was set, the following should print:
* Inner: num_thds=3
* Inner: num_thds=3
*
* If nesting is not supported, the following should print:
* Inner: num_thds=1
* Inner: num_thds=1
*/
printf ("Inner: num_thds=%d\n", omp_get_num_threads());
}
}
#pragma omp barrier
omp_set_nested(0);
#pragma omp parallel
{
#pragma omp single
{
/*
* Even if OMP_NUM_THREADS=2,3 was set, the following should
* print, because nesting is disabled:
* Inner: num_thds=1
* Inner: num_thds=1
*/
printf ("Inner: num_thds=%d\n", omp_get_num_threads());
}
}
#pragma omp barrier
#pragma omp single
{
/*
* If OMP_NUM_THREADS=2,3 was set, the following should print:
* Outer: num_thds=2
*/
printf ("Outer: num_thds=%d\n", omp_get_num_threads());
}
}
return 0;
}
|
app_baseline.c | /**
* @file app.c
* @brief Template for a Host Application Source File.
*
*/
#include "../../support/timer.h"
#include <assert.h>
#include <getopt.h>
#include <omp.h>
#include <stdbool.h>
#include <stdint.h>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <unistd.h>
static uint64_t *A;
static uint64_t *B;
static uint64_t *C;
static uint64_t *C2;
static int pos;
bool pred(const uint64_t x) {
return (x % 2) == 0;
}
void *create_test_file(unsigned int nr_elements) {
// srand(0);
A = (uint64_t *)malloc(nr_elements * sizeof(uint64_t));
B = (uint64_t *)malloc(nr_elements * sizeof(uint64_t));
C = (uint64_t *)malloc(nr_elements * sizeof(uint64_t));
printf("nr_elements\t%u\t", nr_elements);
for (int i = 0; i < nr_elements; i++) {
// A[i] = (unsigned int) (rand());
A[i] = i + 1;
B[i] = 0;
}
}
/**
* @brief compute output in the host
*/
static int select_host(int size, int t) {
pos = 0;
C[pos] = A[pos];
omp_set_num_threads(t);
#pragma omp parallel for
for (int my = 1; my < size; my++) {
if (!pred(A[my])) {
int p;
#pragma omp atomic update
pos++;
p = pos;
C[p] = A[my];
}
}
return pos;
}
// Params ---------------------------------------------------------------------
typedef struct Params {
char *dpu_type;
int input_size;
int n_warmup;
int n_reps;
int n_threads;
} Params;
void usage() {
fprintf(stderr,
"\nUsage: ./program [options]"
"\n"
"\nGeneral options:"
"\n -h help"
"\n -d <D> DPU type (default=fsim)"
"\n -t <T> # of threads (default=8)"
"\n -w <W> # of untimed warmup iterations (default=2)"
"\n -e <E> # of timed repetition iterations (default=5)"
"\n"
"\nBenchmark-specific options:"
"\n -i <I> input size (default=8M elements)"
"\n");
}
struct Params input_params(int argc, char **argv) {
struct Params p;
p.input_size = 16 << 20;
p.n_warmup = 1;
p.n_reps = 3;
p.n_threads = 5;
int opt;
while ((opt = getopt(argc, argv, "hi:w:e:t:")) >= 0) {
switch (opt) {
case 'h':
usage();
exit(0);
break;
case 'i':
p.input_size = atoi(optarg);
break;
case 'w':
p.n_warmup = atoi(optarg);
break;
case 'e':
p.n_reps = atoi(optarg);
break;
case 't':
p.n_threads = atoi(optarg);
break;
default:
fprintf(stderr, "\nUnrecognized option!\n");
usage();
exit(0);
}
}
assert(p.n_threads > 0 && "Invalid # of ranks!");
return p;
}
/**
* @brief Main of the Host Application.
*/
int main(int argc, char **argv) {
struct Params p = input_params(argc, argv);
const unsigned int file_size = p.input_size;
uint32_t accum = 0;
int total_count;
// Create an input file with arbitrary data.
create_test_file(file_size);
Timer timer;
start(&timer, 0, 0);
total_count = select_host(file_size, p.n_threads);
stop(&timer, 0);
printf("Total count = %d\t", total_count);
printf("Kernel ");
print(&timer, 0, 1);
printf("\n");
free(A);
free(B);
free(C);
return 0;
}
|
conv3x3s2_pack1to4_neon.h | // Tencent is pleased to support the open source community by making ncnn available.
//
// Copyright (C) 2019 THL A29 Limited, a Tencent company. All rights reserved.
//
// Licensed under the BSD 3-Clause License (the "License"); you may not use this file except
// in compliance with the License. You may obtain a copy of the License at
//
// https://opensource.org/licenses/BSD-3-Clause
//
// Unless required by applicable law or agreed to in writing, software distributed
// under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
// CONDITIONS OF ANY KIND, either express or implied. See the License for the
// specific language governing permissions and limitations under the License.
#include "option.h"
#include "mat.h"
namespace ncnn {
static void conv3x3s2_pack1to4_neon(const Mat& bottom_blob, Mat& top_blob, const Mat& kernel, const Mat& _bias, const Option& opt)
{
int w = bottom_blob.w;
int inch = bottom_blob.c;
int outw = top_blob.w;
int outh = top_blob.h;
int outch = top_blob.c;
const int tailstep = w - 2*outw + w;
const float* bias = _bias;
int nn_outch = 0;
int remain_outch_start = 0;
#if __ARM_NEON && __aarch64__
nn_outch = outch >> 1;
remain_outch_start = nn_outch << 1;
#pragma omp parallel for num_threads(opt.num_threads)
for (int pp=0; pp<nn_outch; pp++)
{
int p = pp * 2;
Mat out0 = top_blob.channel(p);
Mat out1 = top_blob.channel(p+1);
float32x4_t _bias0 = bias ? vld1q_f32((const float*)bias + p * 4) : vdupq_n_f32(0.f);
float32x4_t _bias1 = bias ? vld1q_f32((const float*)bias + (p+1) * 4) : vdupq_n_f32(0.f);
out0.fill(_bias0);
out1.fill(_bias1);
const float* k0 = kernel.channel(p);
const float* k1 = kernel.channel(p+1);
for (int q=0; q<inch; q++)
{
float* outptr0 = out0;
float* outptr1 = out1;
const Mat img0 = bottom_blob.channel(q);
const float* r0 = img0.row(0);
const float* r1 = img0.row(1);
const float* r2 = img0.row(2);
float32x4_t _k00_0 = vld1q_f32(k0);
float32x4_t _k01_0 = vld1q_f32(k0+4);
float32x4_t _k02_0 = vld1q_f32(k0+8);
float32x4_t _k10_0 = vld1q_f32(k0+12);
float32x4_t _k11_0 = vld1q_f32(k0+16);
float32x4_t _k12_0 = vld1q_f32(k0+20);
float32x4_t _k20_0 = vld1q_f32(k0+24);
float32x4_t _k21_0 = vld1q_f32(k0+28);
float32x4_t _k22_0 = vld1q_f32(k0+32);
float32x4_t _k00_1 = vld1q_f32(k1);
float32x4_t _k01_1 = vld1q_f32(k1+4);
float32x4_t _k02_1 = vld1q_f32(k1+8);
float32x4_t _k10_1 = vld1q_f32(k1+12);
float32x4_t _k11_1 = vld1q_f32(k1+16);
float32x4_t _k12_1 = vld1q_f32(k1+20);
float32x4_t _k20_1 = vld1q_f32(k1+24);
float32x4_t _k21_1 = vld1q_f32(k1+28);
float32x4_t _k22_1 = vld1q_f32(k1+32);
int i = 0;
for (; i < outh; i++)
{
int nn = outw >> 2;
int remain = outw & 3;
if (nn > 0)
{
asm volatile(
"0: \n"
"prfm pldl1keep, [%1, #512] \n"
"ld1 {v6.4s, v7.4s, v8.4s, v9.4s}, [%1] \n"// sum0
// r0
"prfm pldl1keep, [%3, #256] \n"
"ld1 {v0.4s, v1.4s}, [%3], #32 \n"
"ld1r {v4.4s}, [%3] \n"
"fmla v6.4s, %12.4s, v0.s[0] \n"
"fmla v7.4s, %12.4s, v0.s[2] \n"
"prfm pldl1keep, [%2, #512] \n"
"ld1 {v10.4s, v11.4s, v12.4s, v13.4s}, [%2] \n"// sum1
"fmla v8.4s, %12.4s, v1.s[0] \n"
"fmla v9.4s, %12.4s, v1.s[2] \n"
"fmla v10.4s, %21.4s, v0.s[0] \n"
"fmla v11.4s, %21.4s, v0.s[2] \n"
"fmla v12.4s, %21.4s, v1.s[0] \n"
"fmla v13.4s, %21.4s, v1.s[2] \n"
"fmla v6.4s, %13.4s, v0.s[1] \n"
"fmla v7.4s, %13.4s, v0.s[3] \n"
"fmla v8.4s, %13.4s, v1.s[1] \n"
"fmla v9.4s, %13.4s, v1.s[3] \n"
"fmla v10.4s, %22.4s, v0.s[1] \n"
"fmla v11.4s, %22.4s, v0.s[3] \n"
"fmla v12.4s, %22.4s, v1.s[1] \n"
"fmla v13.4s, %22.4s, v1.s[3] \n"
// r1
"prfm pldl1keep, [%4, #256] \n"
"ld1 {v2.4s, v3.4s}, [%4], #32 \n"
"ld1r {v5.4s}, [%4] \n"
"fmla v6.4s, %14.4s, v0.s[2] \n"
"fmla v7.4s, %14.4s, v1.s[0] \n"
"fmla v8.4s, %14.4s, v1.s[2] \n"
"fmla v9.4s, %14.4s, v4.s[0] \n"
"fmla v10.4s, %23.4s, v0.s[2] \n"
"fmla v11.4s, %23.4s, v1.s[0] \n"
"fmla v12.4s, %23.4s, v1.s[2] \n"
"fmla v13.4s, %23.4s, v4.s[0] \n"
"fmla v6.4s, %15.4s, v2.s[0] \n"
"fmla v7.4s, %15.4s, v2.s[2] \n"
"fmla v8.4s, %15.4s, v3.s[0] \n"
"fmla v9.4s, %15.4s, v3.s[2] \n"
"fmla v10.4s, %24.4s, v2.s[0] \n"
"fmla v11.4s, %24.4s, v2.s[2] \n"
"fmla v12.4s, %24.4s, v3.s[0] \n"
"fmla v13.4s, %24.4s, v3.s[2] \n"
"fmla v6.4s, %16.4s, v2.s[1] \n"
"fmla v7.4s, %16.4s, v2.s[3] \n"
"fmla v8.4s, %16.4s, v3.s[1] \n"
"fmla v9.4s, %16.4s, v3.s[3] \n"
"fmla v10.4s, %25.4s, v2.s[1] \n"
"fmla v11.4s, %25.4s, v2.s[3] \n"
"fmla v12.4s, %25.4s, v3.s[1] \n"
"fmla v13.4s, %25.4s, v3.s[3] \n"
// r2
"prfm pldl1keep, [%5, #256] \n"
"ld1 {v0.4s, v1.4s}, [%5], #32 \n"
"ld1r {v4.4s}, [%5] \n"
"fmla v6.4s, %17.4s, v2.s[2] \n"
"fmla v7.4s, %17.4s, v3.s[0] \n"
"fmla v8.4s, %17.4s, v3.s[2] \n"
"fmla v9.4s, %17.4s, v5.s[0] \n"
"fmla v10.4s, %26.4s, v2.s[2] \n"
"fmla v11.4s, %26.4s, v3.s[0] \n"
"fmla v12.4s, %26.4s, v3.s[2] \n"
"fmla v13.4s, %26.4s, v5.s[0] \n"
"fmla v6.4s, %18.4s, v0.s[0] \n"
"fmla v7.4s, %18.4s, v0.s[2] \n"
"fmla v8.4s, %18.4s, v1.s[0] \n"
"fmla v9.4s, %18.4s, v1.s[2] \n"
"fmla v10.4s, %27.4s, v0.s[0] \n"
"fmla v11.4s, %27.4s, v0.s[2] \n"
"fmla v12.4s, %27.4s, v1.s[0] \n"
"fmla v13.4s, %27.4s, v1.s[2] \n"
"fmla v6.4s, %19.4s, v0.s[1] \n"
"fmla v7.4s, %19.4s, v0.s[3] \n"
"fmla v8.4s, %19.4s, v1.s[1] \n"
"fmla v9.4s, %19.4s, v1.s[3] \n"
"fmla v10.4s, %28.4s, v0.s[1] \n"
"fmla v11.4s, %28.4s, v0.s[3] \n"
"fmla v12.4s, %28.4s, v1.s[1] \n"
"fmla v13.4s, %28.4s, v1.s[3] \n"
"fmla v6.4s, %20.4s, v0.s[2] \n"
"fmla v7.4s, %20.4s, v1.s[0] \n"
"fmla v8.4s, %20.4s, v1.s[2] \n"
"fmla v9.4s, %20.4s, v4.s[0] \n"
"fmla v10.4s, %29.4s, v0.s[2] \n"
"fmla v11.4s, %29.4s, v1.s[0] \n"
"fmla v12.4s, %29.4s, v1.s[2] \n"
"fmla v13.4s, %29.4s, v4.s[0] \n"
"subs %w0, %w0, #1 \n"
"st1 {v6.4s, v7.4s, v8.4s, v9.4s}, [%1], #64 \n"
"st1 {v10.4s, v11.4s, v12.4s, v13.4s}, [%2], #64 \n"
"bne 0b \n"
: "=r"(nn), // %0
"=r"(outptr0), // %1
"=r"(outptr1), // %2
"=r"(r0), // %3
"=r"(r1), // %4
"=r"(r2) // %5
: "0"(nn),
"1"(outptr0),
"2"(outptr1),
"3"(r0),
"4"(r1),
"5"(r2),
"w"(_k00_0), // %12
"w"(_k01_0), // %13
"w"(_k02_0), // %14
"w"(_k10_0), // %15
"w"(_k11_0), // %16
"w"(_k12_0), // %17
"w"(_k20_0), // %18
"w"(_k21_0), // %19
"w"(_k22_0), // %20
"w"(_k00_1), // %21
"w"(_k01_1), // %22
"w"(_k02_1), // %23
"w"(_k10_1), // %24
"w"(_k11_1), // %25
"w"(_k12_1), // %26
"w"(_k20_1), // %27
"w"(_k21_1), // %28
"w"(_k22_1) // %29
: "cc", "memory", "v0", "v1", "v2", "v3", "v4", "v5", "v6", "v7", "v8", "v9", "v10", "v11", "v12", "v13"
);
}
for (; remain>0; remain--)
{
float32x4_t _sum0 = vld1q_f32(outptr0);
float32x4_t _sum1 = vld1q_f32(outptr1);
float32x4_t _r0 = vld1q_f32(r0);
float32x4_t _r1 = vld1q_f32(r1);
float32x4_t _r2 = vld1q_f32(r2);
_sum0 = vfmaq_laneq_f32(_sum0, _k00_0, _r0, 0);
_sum0 = vfmaq_laneq_f32(_sum0, _k01_0, _r0, 1);
_sum0 = vfmaq_laneq_f32(_sum0, _k02_0, _r0, 2);
_sum0 = vfmaq_laneq_f32(_sum0, _k10_0, _r1, 0);
_sum0 = vfmaq_laneq_f32(_sum0, _k11_0, _r1, 1);
_sum0 = vfmaq_laneq_f32(_sum0, _k12_0, _r1, 2);
_sum0 = vfmaq_laneq_f32(_sum0, _k20_0, _r2, 0);
_sum0 = vfmaq_laneq_f32(_sum0, _k21_0, _r2, 1);
_sum0 = vfmaq_laneq_f32(_sum0, _k22_0, _r2, 2);
_sum1 = vfmaq_laneq_f32(_sum1, _k00_1, _r0, 0);
_sum1 = vfmaq_laneq_f32(_sum1, _k01_1, _r0, 1);
_sum1 = vfmaq_laneq_f32(_sum1, _k02_1, _r0, 2);
_sum1 = vfmaq_laneq_f32(_sum1, _k10_1, _r1, 0);
_sum1 = vfmaq_laneq_f32(_sum1, _k11_1, _r1, 1);
_sum1 = vfmaq_laneq_f32(_sum1, _k12_1, _r1, 2);
_sum1 = vfmaq_laneq_f32(_sum1, _k20_1, _r2, 0);
_sum1 = vfmaq_laneq_f32(_sum1, _k21_1, _r2, 1);
_sum1 = vfmaq_laneq_f32(_sum1, _k22_1, _r2, 2);
vst1q_f32(outptr0, _sum0);
vst1q_f32(outptr1, _sum1);
r0 += 2;
r1 += 2;
r2 += 2;
outptr0 += 4;
outptr1 += 4;
}
r0 += tailstep;
r1 += tailstep;
r2 += tailstep;
}
k0 += 9*4;
k1 += 9*4;
}
}
#endif // __ARM_NEON && __aarch64__
#pragma omp parallel for num_threads(opt.num_threads)
for (int p=remain_outch_start; p<outch; p++)
{
Mat out0 = top_blob.channel(p);
float32x4_t _bias0 = bias ? vld1q_f32((const float*)bias + p * 4) : vdupq_n_f32(0.f);
out0.fill(_bias0);
const float* k0 = kernel.channel(p);
for (int q=0; q<inch; q++)
{
float* outptr0 = out0;
const Mat img0 = bottom_blob.channel(q);
const float* r0 = img0.row(0);
const float* r1 = img0.row(1);
const float* r2 = img0.row(2);
float32x4_t _k00 = vld1q_f32(k0);
float32x4_t _k01 = vld1q_f32(k0+4);
float32x4_t _k02 = vld1q_f32(k0+8);
float32x4_t _k10 = vld1q_f32(k0+12);
float32x4_t _k11 = vld1q_f32(k0+16);
float32x4_t _k12 = vld1q_f32(k0+20);
float32x4_t _k20 = vld1q_f32(k0+24);
float32x4_t _k21 = vld1q_f32(k0+28);
float32x4_t _k22 = vld1q_f32(k0+32);
int i = 0;
for (; i < outh; i++)
{
int nn = outw >> 2;
int remain = outw & 3;
#if __aarch64__
if (nn > 0)
{
asm volatile(
"0: \n"
"prfm pldl1keep, [%1, #512] \n"
"ld1 {v6.4s, v7.4s, v8.4s, v9.4s}, [%1] \n"// sum0
// r0
"prfm pldl1keep, [%2, #256] \n"
"ld1 {v0.4s, v1.4s}, [%2], #32 \n"
"ld1r {v4.4s}, [%2] \n"
"fmla v6.4s, %10.4s, v0.s[0] \n"
"fmla v7.4s, %10.4s, v0.s[2] \n"
"fmla v8.4s, %10.4s, v1.s[0] \n"
"fmla v9.4s, %10.4s, v1.s[2] \n"
"fmla v6.4s, %11.4s, v0.s[1] \n"
"fmla v7.4s, %11.4s, v0.s[3] \n"
"fmla v8.4s, %11.4s, v1.s[1] \n"
"fmla v9.4s, %11.4s, v1.s[3] \n"
// r1
"prfm pldl1keep, [%3, #256] \n"
"ld1 {v2.4s, v3.4s}, [%3], #32 \n"
"ld1r {v5.4s}, [%3] \n"
"fmla v6.4s, %12.4s, v0.s[2] \n"
"fmla v7.4s, %12.4s, v1.s[0] \n"
"fmla v8.4s, %12.4s, v1.s[2] \n"
"fmla v9.4s, %12.4s, v4.s[0] \n"
"fmla v6.4s, %13.4s, v2.s[0] \n"
"fmla v7.4s, %13.4s, v2.s[2] \n"
"fmla v8.4s, %13.4s, v3.s[0] \n"
"fmla v9.4s, %13.4s, v3.s[2] \n"
"fmla v6.4s, %14.4s, v2.s[1] \n"
"fmla v7.4s, %14.4s, v2.s[3] \n"
"fmla v8.4s, %14.4s, v3.s[1] \n"
"fmla v9.4s, %14.4s, v3.s[3] \n"
// r2
"prfm pldl1keep, [%4, #256] \n"
"ld1 {v0.4s, v1.4s}, [%4], #32 \n"
"ld1r {v4.4s}, [%4] \n"
"fmla v6.4s, %15.4s, v2.s[2] \n"
"fmla v7.4s, %15.4s, v3.s[0] \n"
"fmla v8.4s, %15.4s, v3.s[2] \n"
"fmla v9.4s, %15.4s, v5.s[0] \n"
"fmla v6.4s, %16.4s, v0.s[0] \n"
"fmla v7.4s, %16.4s, v0.s[2] \n"
"fmla v8.4s, %16.4s, v1.s[0] \n"
"fmla v9.4s, %16.4s, v1.s[2] \n"
"fmla v6.4s, %17.4s, v0.s[1] \n"
"fmla v7.4s, %17.4s, v0.s[3] \n"
"fmla v8.4s, %17.4s, v1.s[1] \n"
"fmla v9.4s, %17.4s, v1.s[3] \n"
"fmla v6.4s, %18.4s, v0.s[2] \n"
"fmla v7.4s, %18.4s, v1.s[0] \n"
"fmla v8.4s, %18.4s, v1.s[2] \n"
"fmla v9.4s, %18.4s, v4.s[0] \n"
"subs %w0, %w0, #1 \n"
"st1 {v6.4s, v7.4s, v8.4s, v9.4s}, [%1], #64 \n"
"bne 0b \n"
: "=r"(nn), // %0
"=r"(outptr0), // %1
"=r"(r0), // %2
"=r"(r1), // %3
"=r"(r2) // %4
: "0"(nn),
"1"(outptr0),
"2"(r0),
"3"(r1),
"4"(r2),
"w"(_k00), // %10
"w"(_k01), // %11
"w"(_k02), // %12
"w"(_k10), // %13
"w"(_k11), // %14
"w"(_k12), // %15
"w"(_k20), // %16
"w"(_k21), // %17
"w"(_k22) // %18
: "cc", "memory", "v0", "v1", "v2", "v3", "v4", "v5", "v6", "v7", "v8", "v9"
);
}
#else // __aarch64__
if (nn > 0)
{
asm volatile(
"0: \n"
"pld [%1, #512] \n"
"vldm %1, {d0-d7} \n"// sum0
// r0
"pld [%2, #256] \n"
"vld1.f32 {d8-d11}, [%2]! \n"
"vld1.f32 {d12[]}, [%2] \n"
"vmla.f32 q0, %q10, d8[0] \n"
"vmla.f32 q1, %q10, d9[0] \n"
"vmla.f32 q2, %q10, d10[0] \n"
"vmla.f32 q3, %q10, d11[0] \n"
"vmla.f32 q0, %q11, d8[1] \n"
"vmla.f32 q1, %q11, d9[1] \n"
"vmla.f32 q2, %q11, d10[1] \n"
"vmla.f32 q3, %q11, d11[1] \n"
"vmla.f32 q0, %q12, d9[0] \n"
"vmla.f32 q1, %q12, d10[0] \n"
"vmla.f32 q2, %q12, d11[0] \n"
// r1
"pld [%3, #256] \n"
"vld1.f32 {d8-d11}, [%3]! \n"
"vld1.f32 {d13[]}, [%3] \n"
"vmla.f32 q3, %q12, d12[0] \n"
"vmla.f32 q0, %q13, d8[0] \n"
"vmla.f32 q1, %q13, d9[0] \n"
"vmla.f32 q2, %q13, d10[0] \n"
"vmla.f32 q3, %q13, d11[0] \n"
"vmla.f32 q0, %q14, d8[1] \n"
"vmla.f32 q1, %q14, d9[1] \n"
"vmla.f32 q2, %q14, d10[1] \n"
"vmla.f32 q3, %q14, d11[1] \n"
"vmla.f32 q0, %q15, d9[0] \n"
"vmla.f32 q1, %q15, d10[0] \n"
"vmla.f32 q2, %q15, d11[0] \n"
// r2
"pld [%4, #256] \n"
"vld1.f32 {d8-d11}, [%4]! \n"
"vld1.f32 {d12[]}, [%4] \n"
"vmla.f32 q3, %q15, d13[0] \n"
"vmla.f32 q0, %q16, d8[0] \n"
"vmla.f32 q1, %q16, d9[0] \n"
"vmla.f32 q2, %q16, d10[0] \n"
"vmla.f32 q3, %q16, d11[0] \n"
"vmla.f32 q0, %q17, d8[1] \n"
"vmla.f32 q1, %q17, d9[1] \n"
"vmla.f32 q2, %q17, d10[1] \n"
"vmla.f32 q3, %q17, d11[1] \n"
"vmla.f32 q0, %q18, d9[0] \n"
"vmla.f32 q1, %q18, d10[0] \n"
"vmla.f32 q2, %q18, d11[0] \n"
"vmla.f32 q3, %q18, d12[0] \n"
"subs %0, %0, #1 \n"
"vstm %1!, {d0-d7} \n"
"bne 0b \n"
: "=r"(nn), // %0
"=r"(outptr0), // %1
"=r"(r0), // %2
"=r"(r1), // %3
"=r"(r2) // %4
: "0"(nn),
"1"(outptr0),
"2"(r0),
"3"(r1),
"4"(r2),
"w"(_k00), // %10
"w"(_k01), // %11
"w"(_k02), // %12
"w"(_k10), // %13
"w"(_k11), // %14
"w"(_k12), // %15
"w"(_k20), // %16
"w"(_k21), // %17
"w"(_k22) // %18
: "cc", "memory", "q0", "q1", "q2", "q3", "q4", "q5", "q6"
);
}
#endif // __aarch64__
for (; remain>0; remain--)
{
float32x4_t _sum0 = vld1q_f32(outptr0);
float32x4_t _r0 = vld1q_f32(r0);
float32x4_t _r1 = vld1q_f32(r1);
float32x4_t _r2 = vld1q_f32(r2);
#if __aarch64__
_sum0 = vfmaq_laneq_f32(_sum0, _k00, _r0, 0);
_sum0 = vfmaq_laneq_f32(_sum0, _k01, _r0, 1);
_sum0 = vfmaq_laneq_f32(_sum0, _k02, _r0, 2);
_sum0 = vfmaq_laneq_f32(_sum0, _k10, _r1, 0);
_sum0 = vfmaq_laneq_f32(_sum0, _k11, _r1, 1);
_sum0 = vfmaq_laneq_f32(_sum0, _k12, _r1, 2);
_sum0 = vfmaq_laneq_f32(_sum0, _k20, _r2, 0);
_sum0 = vfmaq_laneq_f32(_sum0, _k21, _r2, 1);
_sum0 = vfmaq_laneq_f32(_sum0, _k22, _r2, 2);
#else
_sum0 = vmlaq_lane_f32(_sum0, _k00, vget_low_f32(_r0), 0);
_sum0 = vmlaq_lane_f32(_sum0, _k01, vget_low_f32(_r0), 1);
_sum0 = vmlaq_lane_f32(_sum0, _k02, vget_high_f32(_r0), 0);
_sum0 = vmlaq_lane_f32(_sum0, _k10, vget_low_f32(_r1), 0);
_sum0 = vmlaq_lane_f32(_sum0, _k11, vget_low_f32(_r1), 1);
_sum0 = vmlaq_lane_f32(_sum0, _k12, vget_high_f32(_r1), 0);
_sum0 = vmlaq_lane_f32(_sum0, _k20, vget_low_f32(_r2), 0);
_sum0 = vmlaq_lane_f32(_sum0, _k21, vget_low_f32(_r2), 1);
_sum0 = vmlaq_lane_f32(_sum0, _k22, vget_high_f32(_r2), 0);
#endif
vst1q_f32(outptr0, _sum0);
r0 += 2;
r1 += 2;
r2 += 2;
outptr0 += 4;
}
r0 += tailstep;
r1 += tailstep;
r2 += tailstep;
}
k0 += 9*4;
}
}
}
}
|
bug51781.c | // Use the generic state machine. On some architectures, other threads in the
// main thread's warp must avoid barrier instructions.
//
// RUN: %libomptarget-compile-run-and-check-generic
// SPMDize. There is no main thread, so there's no issue.
//
// RUN: %libomptarget-compile-generic -O1 -Rpass=openmp-opt > %t.spmd 2>&1
// RUN: %fcheck-nvptx64-nvidia-cuda -check-prefix=SPMD -input-file=%t.spmd
// RUN: %fcheck-amdgcn-amd-amdhsa -check-prefix=SPMD -input-file=%t.spmd
// RUN: %libomptarget-run-generic 2>&1 | %fcheck-generic
//
// SPMD: Transformed generic-mode kernel to SPMD-mode.
// Use the custom state machine, which must avoid the same barrier problem as
// the generic state machine.
//
// RUN: %libomptarget-compile-generic -O1 -Rpass=openmp-opt \
// RUN: -mllvm -openmp-opt-disable-spmdization > %t.custom 2>&1
// RUN: %fcheck-nvptx64-nvidia-cuda -check-prefix=CUSTOM -input-file=%t.custom
// RUN: %fcheck-amdgcn-amd-amdhsa -check-prefix=CUSTOM -input-file=%t.custom
// RUN: %libomptarget-run-generic 2>&1 | %fcheck-generic
//
// Repeat with reduction clause, which has managed to break the custom state
// machine in the past.
//
// RUN: %libomptarget-compile-generic -O1 -Rpass=openmp-opt -DADD_REDUCTION \
// RUN: -mllvm -openmp-opt-disable-spmdization > %t.custom 2>&1
// RUN: %fcheck-nvptx64-nvidia-cuda -check-prefix=CUSTOM -input-file=%t.custom
// RUN: %fcheck-amdgcn-amd-amdhsa -check-prefix=CUSTOM -input-file=%t.custom
// RUN: %libomptarget-run-generic 2>&1 | %fcheck-generic
//
// CUSTOM: Rewriting generic-mode kernel with a customized state machine.
// Hangs
// UNSUPPORTED: amdgcn-amd-amdhsa
// UNSUPPORTED: amdgcn-amd-amdhsa-newDriver
#if ADD_REDUCTION
# define REDUCTION(...) reduction(__VA_ARGS__)
#else
# define REDUCTION(...)
#endif
#include <stdio.h>
int main() {
int x = 0, y = 1;
#pragma omp target teams num_teams(1) map(tofrom:x, y) REDUCTION(+:x)
{
x += 5;
#pragma omp parallel
y = 6;
}
// CHECK: 5, 6
printf("%d, %d\n", x, y);
return 0;
}
|
classes.c | struct myclass {
int awesome;
float tubular;
};
struct otherclass {
double radical;
double gnarly;
};
struct otherclass globVar;
int myfunc(struct myclass var)
{
int i;
#pragma omp parallel for
for(i = 0; i < 10; i++)
{
globVar.radical = (double)var.tubular;
globVar.gnarly = globVar.gnarly + (double)var.awesome;
}
return var.awesome;
}
int main(int argc, char** argv)
{
struct myclass var = {42, 3.14};
myfunc(var);
}
|
GB_binop__times_uint16.c | //------------------------------------------------------------------------------
// GB_binop: hard-coded functions for each built-in binary operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2021, All Rights Reserved.
// SPDX-License-Identifier: Apache-2.0
//------------------------------------------------------------------------------
// If this file is in the Generated/ folder, do not edit it (auto-generated).
#include "GB.h"
#ifndef GBCOMPACT
#include "GB_control.h"
#include "GB_ek_slice.h"
#include "GB_dense.h"
#include "GB_atomics.h"
#include "GB_bitmap_assign_methods.h"
#include "GB_binop__include.h"
// C=binop(A,B) is defined by the following types and operators:
// A+B function (eWiseAdd): GB_AaddB__times_uint16
// A.*B function (eWiseMult): GB_AemultB__times_uint16
// A*D function (colscale): GB_AxD__times_uint16
// D*A function (rowscale): GB_DxB__times_uint16
// C+=B function (dense accum): GB_Cdense_accumB__times_uint16
// C+=b function (dense accum): GB_Cdense_accumb__times_uint16
// C+=A+B function (dense ewise3): GB_Cdense_ewise3_accum__times_uint16
// C=A+B function (dense ewise3): GB_Cdense_ewise3_noaccum__times_uint16
// C=scalar+B GB_bind1st__times_uint16
// C=scalar+B' GB_bind1st_tran__times_uint16
// C=A+scalar GB_bind2nd__times_uint16
// C=A'+scalar GB_bind2nd_tran__times_uint16
// C type: uint16_t
// A type: uint16_t
// B,b type: uint16_t
// BinaryOp: cij = (aij * bij)
#define GB_ATYPE \
uint16_t
#define GB_BTYPE \
uint16_t
#define GB_CTYPE \
uint16_t
// true if the types of A and B are identical
#define GB_ATYPE_IS_BTYPE \
1
// true if the types of C and A are identical
#define GB_CTYPE_IS_ATYPE \
1
// true if the types of C and B are identical
#define GB_CTYPE_IS_BTYPE \
1
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA) \
uint16_t aij = Ax [pA]
// bij = Bx [pB]
#define GB_GETB(bij,Bx,pB) \
uint16_t bij = Bx [pB]
// declare scalar of the same type as C
#define GB_CTYPE_SCALAR(t) \
uint16_t t
// cij = Ax [pA]
#define GB_COPY_A_TO_C(cij,Ax,pA) \
cij = Ax [pA]
// cij = Bx [pB]
#define GB_COPY_B_TO_C(cij,Bx,pB) \
cij = Bx [pB]
#define GB_CX(p) Cx [p]
// binary operator
#define GB_BINOP(z, x, y, i, j) \
z = (x * y) ;
// op is second
#define GB_OP_IS_SECOND \
0
// op is plus_fp32 or plus_fp64
#define GB_OP_IS_PLUS_REAL \
0
// op is minus_fp32 or minus_fp64
#define GB_OP_IS_MINUS_REAL \
0
// GB_cblas_*axpy gateway routine, if it exists for this operator and type:
#define GB_CBLAS_AXPY \
(none)
// do the numerical phases of GB_add and GB_emult
#define GB_PHASE_2_OF_2
// hard-coded loops can be vectorized
#define GB_PRAGMA_SIMD_VECTORIZE GB_PRAGMA_SIMD
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_TIMES || GxB_NO_UINT16 || GxB_NO_TIMES_UINT16)
//------------------------------------------------------------------------------
// C += A+B, all 3 matrices dense
//------------------------------------------------------------------------------
// The op must be MIN, MAX, PLUS, MINUS, RMINUS, TIMES, DIV, or RDIV.
void GB_Cdense_ewise3_accum__times_uint16
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix B,
const int nthreads
)
{
#include "GB_dense_ewise3_accum_template.c"
}
//------------------------------------------------------------------------------
// C = A+B, all 3 matrices dense
//------------------------------------------------------------------------------
GrB_Info GB_Cdense_ewise3_noaccum__times_uint16
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix B,
const int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_dense_ewise3_noaccum_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C += B, accumulate a sparse matrix into a dense matrix
//------------------------------------------------------------------------------
GrB_Info GB_Cdense_accumB__times_uint16
(
GrB_Matrix C,
const GrB_Matrix B,
const int64_t *GB_RESTRICT kfirst_slice,
const int64_t *GB_RESTRICT klast_slice,
const int64_t *GB_RESTRICT pstart_slice,
const int ntasks,
const int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
{
#include "GB_dense_subassign_23_template.c"
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C += b, accumulate a scalar into a dense matrix
//------------------------------------------------------------------------------
GrB_Info GB_Cdense_accumb__times_uint16
(
GrB_Matrix C,
const GB_void *p_bwork,
const int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
{
// get the scalar b for C += b, of type uint16_t
uint16_t bwork = (*((uint16_t *) p_bwork)) ;
#include "GB_dense_subassign_22_template.c"
return (GrB_SUCCESS) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = A*D, column scale with diagonal D matrix
//------------------------------------------------------------------------------
GrB_Info GB_AxD__times_uint16
(
GrB_Matrix C,
const GrB_Matrix A, bool A_is_pattern,
const GrB_Matrix D, bool D_is_pattern,
const int64_t *GB_RESTRICT kfirst_slice,
const int64_t *GB_RESTRICT klast_slice,
const int64_t *GB_RESTRICT pstart_slice,
const int ntasks,
const int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
uint16_t *GB_RESTRICT Cx = (uint16_t *) C->x ;
#include "GB_AxB_colscale_meta.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = D*B, row scale with diagonal D matrix
//------------------------------------------------------------------------------
GrB_Info GB_DxB__times_uint16
(
GrB_Matrix C,
const GrB_Matrix D, bool D_is_pattern,
const GrB_Matrix B, bool B_is_pattern,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
uint16_t *GB_RESTRICT Cx = (uint16_t *) C->x ;
#include "GB_AxB_rowscale_meta.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseAdd: C = A+B or C<M> = A+B
//------------------------------------------------------------------------------
#undef GB_FREE_ALL
#define GB_FREE_ALL \
{ \
GB_ek_slice_free (&pstart_Mslice, &kfirst_Mslice, &klast_Mslice) ; \
GB_ek_slice_free (&pstart_Aslice, &kfirst_Aslice, &klast_Aslice) ; \
GB_ek_slice_free (&pstart_Bslice, &kfirst_Bslice, &klast_Bslice) ; \
}
GrB_Info GB_AaddB__times_uint16
(
GrB_Matrix C,
const int C_sparsity,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const bool Ch_is_Mh,
const int64_t *GB_RESTRICT C_to_M,
const int64_t *GB_RESTRICT C_to_A,
const int64_t *GB_RESTRICT C_to_B,
const GB_task_struct *GB_RESTRICT TaskList,
const int C_ntasks,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t *pstart_Mslice = NULL, *kfirst_Mslice = NULL, *klast_Mslice = NULL ;
int64_t *pstart_Aslice = NULL, *kfirst_Aslice = NULL, *klast_Aslice = NULL ;
int64_t *pstart_Bslice = NULL, *kfirst_Bslice = NULL, *klast_Bslice = NULL ;
#include "GB_add_template.c"
GB_FREE_ALL ;
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C = A.*B or C<M> = A.*B
//------------------------------------------------------------------------------
GrB_Info GB_AemultB__times_uint16
(
GrB_Matrix C,
const int C_sparsity,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *GB_RESTRICT C_to_M,
const int64_t *GB_RESTRICT C_to_A,
const int64_t *GB_RESTRICT C_to_B,
const GB_task_struct *GB_RESTRICT TaskList,
const int C_ntasks,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t *pstart_Mslice = NULL, *kfirst_Mslice = NULL, *klast_Mslice = NULL ;
int64_t *pstart_Aslice = NULL, *kfirst_Aslice = NULL, *klast_Aslice = NULL ;
int64_t *pstart_Bslice = NULL, *kfirst_Bslice = NULL, *klast_Bslice = NULL ;
#include "GB_emult_template.c"
GB_FREE_ALL ;
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (x,Bx): apply a binary operator to a matrix with scalar bind1st
//------------------------------------------------------------------------------
GrB_Info GB_bind1st__times_uint16
(
GB_void *Cx_output, // Cx and Bx may be aliased
const GB_void *x_input,
const GB_void *Bx_input,
const int8_t *GB_RESTRICT Bb,
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
uint16_t *Cx = (uint16_t *) Cx_output ;
uint16_t x = (*((uint16_t *) x_input)) ;
uint16_t *Bx = (uint16_t *) Bx_input ;
int64_t p ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
if (!GBB (Bb, p)) continue ;
uint16_t bij = Bx [p] ;
Cx [p] = (x * bij) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (Ax,y): apply a binary operator to a matrix with scalar bind2nd
//------------------------------------------------------------------------------
GrB_Info GB_bind2nd__times_uint16
(
GB_void *Cx_output, // Cx and Ax may be aliased
const GB_void *Ax_input,
const GB_void *y_input,
const int8_t *GB_RESTRICT Ab,
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t p ;
uint16_t *Cx = (uint16_t *) Cx_output ;
uint16_t *Ax = (uint16_t *) Ax_input ;
uint16_t y = (*((uint16_t *) y_input)) ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
if (!GBB (Ab, p)) continue ;
uint16_t aij = Ax [p] ;
Cx [p] = (aij * y) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (x, A'): transpose and apply a binary operator
//------------------------------------------------------------------------------
// cij = op (x, aij), no typecasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
uint16_t aij = Ax [pA] ; \
Cx [pC] = (x * aij) ; \
}
GrB_Info GB_bind1st_tran__times_uint16
(
GrB_Matrix C,
const GB_void *x_input,
const GrB_Matrix A,
int64_t *GB_RESTRICT *Workspaces,
const int64_t *GB_RESTRICT A_slice,
int nworkspaces,
int nthreads
)
{
// GB_unop_transpose.c uses GB_ATYPE, but A is
// the 2nd input to binary operator z=f(x,y).
#undef GB_ATYPE
#define GB_ATYPE \
uint16_t
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
uint16_t x = (*((const uint16_t *) x_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
#undef GB_ATYPE
#define GB_ATYPE \
uint16_t
}
//------------------------------------------------------------------------------
// C = op (A', y): transpose and apply a binary operator
//------------------------------------------------------------------------------
// cij = op (aij, y), no typecasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
uint16_t aij = Ax [pA] ; \
Cx [pC] = (aij * y) ; \
}
GrB_Info GB_bind2nd_tran__times_uint16
(
GrB_Matrix C,
const GrB_Matrix A,
const GB_void *y_input,
int64_t *GB_RESTRICT *Workspaces,
const int64_t *GB_RESTRICT A_slice,
int nworkspaces,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
uint16_t y = (*((const uint16_t *) y_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
tree-vect-loop.c | /* Loop Vectorization
Copyright (C) 2003-2015 Free Software Foundation, Inc.
Contributed by Dorit Naishlos <dorit@il.ibm.com> and
Ira Rosen <irar@il.ibm.com>
This file is part of GCC.
GCC is free software; you can redistribute it and/or modify it under
the terms of the GNU General Public License as published by the Free
Software Foundation; either version 3, or (at your option) any later
version.
GCC is distributed in the hope that it will be useful, but WITHOUT ANY
WARRANTY; without even the implied warranty of MERCHANTABILITY or
FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
for more details.
You should have received a copy of the GNU General Public License
along with GCC; see the file COPYING3. If not see
<http://www.gnu.org/licenses/>. */
#include "config.h"
#include "system.h"
#include "coretypes.h"
#include "dumpfile.h"
#include "tm.h"
#include "hash-set.h"
#include "machmode.h"
#include "vec.h"
#include "double-int.h"
#include "input.h"
#include "alias.h"
#include "symtab.h"
#include "wide-int.h"
#include "inchash.h"
#include "tree.h"
#include "fold-const.h"
#include "stor-layout.h"
#include "predict.h"
#include "hard-reg-set.h"
#include "function.h"
#include "dominance.h"
#include "cfg.h"
#include "cfganal.h"
#include "basic-block.h"
#include "gimple-pretty-print.h"
#include "tree-ssa-alias.h"
#include "internal-fn.h"
#include "gimple-expr.h"
#include "is-a.h"
#include "gimple.h"
#include "gimplify.h"
#include "gimple-iterator.h"
#include "gimplify-me.h"
#include "gimple-ssa.h"
#include "tree-phinodes.h"
#include "ssa-iterators.h"
#include "stringpool.h"
#include "tree-ssanames.h"
#include "tree-ssa-loop-ivopts.h"
#include "tree-ssa-loop-manip.h"
#include "tree-ssa-loop-niter.h"
#include "tree-pass.h"
#include "cfgloop.h"
#include "hashtab.h"
#include "rtl.h"
#include "flags.h"
#include "statistics.h"
#include "real.h"
#include "fixed-value.h"
#include "insn-config.h"
#include "expmed.h"
#include "dojump.h"
#include "explow.h"
#include "calls.h"
#include "emit-rtl.h"
#include "varasm.h"
#include "stmt.h"
#include "expr.h"
#include "recog.h"
#include "insn-codes.h"
#include "optabs.h"
#include "params.h"
#include "diagnostic-core.h"
#include "tree-chrec.h"
#include "tree-scalar-evolution.h"
#include "tree-vectorizer.h"
#include "target.h"
/* Loop Vectorization Pass.
This pass tries to vectorize loops.
For example, the vectorizer transforms the following simple loop:
short a[N]; short b[N]; short c[N]; int i;
for (i=0; i<N; i++){
a[i] = b[i] + c[i];
}
as if it was manually vectorized by rewriting the source code into:
typedef int __attribute__((mode(V8HI))) v8hi;
short a[N]; short b[N]; short c[N]; int i;
v8hi *pa = (v8hi*)a, *pb = (v8hi*)b, *pc = (v8hi*)c;
v8hi va, vb, vc;
for (i=0; i<N/8; i++){
vb = pb[i];
vc = pc[i];
va = vb + vc;
pa[i] = va;
}
The main entry to this pass is vectorize_loops(), in which
the vectorizer applies a set of analyses on a given set of loops,
followed by the actual vectorization transformation for the loops that
had successfully passed the analysis phase.
Throughout this pass we make a distinction between two types of
data: scalars (which are represented by SSA_NAMES), and memory references
("data-refs"). These two types of data require different handling both
during analysis and transformation. The types of data-refs that the
vectorizer currently supports are ARRAY_REFS which base is an array DECL
(not a pointer), and INDIRECT_REFS through pointers; both array and pointer
accesses are required to have a simple (consecutive) access pattern.
Analysis phase:
===============
The driver for the analysis phase is vect_analyze_loop().
It applies a set of analyses, some of which rely on the scalar evolution
analyzer (scev) developed by Sebastian Pop.
During the analysis phase the vectorizer records some information
per stmt in a "stmt_vec_info" struct which is attached to each stmt in the
loop, as well as general information about the loop as a whole, which is
recorded in a "loop_vec_info" struct attached to each loop.
Transformation phase:
=====================
The loop transformation phase scans all the stmts in the loop, and
creates a vector stmt (or a sequence of stmts) for each scalar stmt S in
the loop that needs to be vectorized. It inserts the vector code sequence
just before the scalar stmt S, and records a pointer to the vector code
in STMT_VINFO_VEC_STMT (stmt_info) (stmt_info is the stmt_vec_info struct
attached to S). This pointer will be used for the vectorization of following
stmts which use the def of stmt S. Stmt S is removed if it writes to memory;
otherwise, we rely on dead code elimination for removing it.
For example, say stmt S1 was vectorized into stmt VS1:
VS1: vb = px[i];
S1: b = x[i]; STMT_VINFO_VEC_STMT (stmt_info (S1)) = VS1
S2: a = b;
To vectorize stmt S2, the vectorizer first finds the stmt that defines
the operand 'b' (S1), and gets the relevant vector def 'vb' from the
vector stmt VS1 pointed to by STMT_VINFO_VEC_STMT (stmt_info (S1)). The
resulting sequence would be:
VS1: vb = px[i];
S1: b = x[i]; STMT_VINFO_VEC_STMT (stmt_info (S1)) = VS1
VS2: va = vb;
S2: a = b; STMT_VINFO_VEC_STMT (stmt_info (S2)) = VS2
Operands that are not SSA_NAMEs, are data-refs that appear in
load/store operations (like 'x[i]' in S1), and are handled differently.
Target modeling:
=================
Currently the only target specific information that is used is the
size of the vector (in bytes) - "TARGET_VECTORIZE_UNITS_PER_SIMD_WORD".
Targets that can support different sizes of vectors, for now will need
to specify one value for "TARGET_VECTORIZE_UNITS_PER_SIMD_WORD". More
flexibility will be added in the future.
Since we only vectorize operations which vector form can be
expressed using existing tree codes, to verify that an operation is
supported, the vectorizer checks the relevant optab at the relevant
machine_mode (e.g, optab_handler (add_optab, V8HImode)). If
the value found is CODE_FOR_nothing, then there's no target support, and
we can't vectorize the stmt.
For additional information on this project see:
http://gcc.gnu.org/projects/tree-ssa/vectorization.html
*/
static void vect_estimate_min_profitable_iters (loop_vec_info, int *, int *);
/* Function vect_determine_vectorization_factor
Determine the vectorization factor (VF). VF is the number of data elements
that are operated upon in parallel in a single iteration of the vectorized
loop. For example, when vectorizing a loop that operates on 4byte elements,
on a target with vector size (VS) 16byte, the VF is set to 4, since 4
elements can fit in a single vector register.
We currently support vectorization of loops in which all types operated upon
are of the same size. Therefore this function currently sets VF according to
the size of the types operated upon, and fails if there are multiple sizes
in the loop.
VF is also the factor by which the loop iterations are strip-mined, e.g.:
original loop:
for (i=0; i<N; i++){
a[i] = b[i] + c[i];
}
vectorized loop:
for (i=0; i<N; i+=VF){
a[i:VF] = b[i:VF] + c[i:VF];
}
*/
static bool
vect_determine_vectorization_factor (loop_vec_info loop_vinfo)
{
struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
basic_block *bbs = LOOP_VINFO_BBS (loop_vinfo);
int nbbs = loop->num_nodes;
unsigned int vectorization_factor = 0;
tree scalar_type;
gphi *phi;
tree vectype;
unsigned int nunits;
stmt_vec_info stmt_info;
int i;
HOST_WIDE_INT dummy;
gimple stmt, pattern_stmt = NULL;
gimple_seq pattern_def_seq = NULL;
gimple_stmt_iterator pattern_def_si = gsi_none ();
bool analyze_pattern_stmt = false;
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"=== vect_determine_vectorization_factor ===\n");
for (i = 0; i < nbbs; i++)
{
basic_block bb = bbs[i];
for (gphi_iterator si = gsi_start_phis (bb); !gsi_end_p (si);
gsi_next (&si))
{
phi = si.phi ();
stmt_info = vinfo_for_stmt (phi);
if (dump_enabled_p ())
{
dump_printf_loc (MSG_NOTE, vect_location, "==> examining phi: ");
dump_gimple_stmt (MSG_NOTE, TDF_SLIM, phi, 0);
dump_printf (MSG_NOTE, "\n");
}
gcc_assert (stmt_info);
if (STMT_VINFO_RELEVANT_P (stmt_info))
{
gcc_assert (!STMT_VINFO_VECTYPE (stmt_info));
scalar_type = TREE_TYPE (PHI_RESULT (phi));
if (dump_enabled_p ())
{
dump_printf_loc (MSG_NOTE, vect_location,
"get vectype for scalar type: ");
dump_generic_expr (MSG_NOTE, TDF_SLIM, scalar_type);
dump_printf (MSG_NOTE, "\n");
}
vectype = get_vectype_for_scalar_type (scalar_type);
if (!vectype)
{
if (dump_enabled_p ())
{
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"not vectorized: unsupported "
"data-type ");
dump_generic_expr (MSG_MISSED_OPTIMIZATION, TDF_SLIM,
scalar_type);
dump_printf (MSG_MISSED_OPTIMIZATION, "\n");
}
return false;
}
STMT_VINFO_VECTYPE (stmt_info) = vectype;
if (dump_enabled_p ())
{
dump_printf_loc (MSG_NOTE, vect_location, "vectype: ");
dump_generic_expr (MSG_NOTE, TDF_SLIM, vectype);
dump_printf (MSG_NOTE, "\n");
}
nunits = TYPE_VECTOR_SUBPARTS (vectype);
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location, "nunits = %d\n",
nunits);
if (!vectorization_factor
|| (nunits > vectorization_factor))
vectorization_factor = nunits;
}
}
for (gimple_stmt_iterator si = gsi_start_bb (bb);
!gsi_end_p (si) || analyze_pattern_stmt;)
{
tree vf_vectype;
if (analyze_pattern_stmt)
stmt = pattern_stmt;
else
stmt = gsi_stmt (si);
stmt_info = vinfo_for_stmt (stmt);
if (dump_enabled_p ())
{
dump_printf_loc (MSG_NOTE, vect_location,
"==> examining statement: ");
dump_gimple_stmt (MSG_NOTE, TDF_SLIM, stmt, 0);
dump_printf (MSG_NOTE, "\n");
}
gcc_assert (stmt_info);
/* Skip stmts which do not need to be vectorized. */
if ((!STMT_VINFO_RELEVANT_P (stmt_info)
&& !STMT_VINFO_LIVE_P (stmt_info))
|| gimple_clobber_p (stmt))
{
if (STMT_VINFO_IN_PATTERN_P (stmt_info)
&& (pattern_stmt = STMT_VINFO_RELATED_STMT (stmt_info))
&& (STMT_VINFO_RELEVANT_P (vinfo_for_stmt (pattern_stmt))
|| STMT_VINFO_LIVE_P (vinfo_for_stmt (pattern_stmt))))
{
stmt = pattern_stmt;
stmt_info = vinfo_for_stmt (pattern_stmt);
if (dump_enabled_p ())
{
dump_printf_loc (MSG_NOTE, vect_location,
"==> examining pattern statement: ");
dump_gimple_stmt (MSG_NOTE, TDF_SLIM, stmt, 0);
dump_printf (MSG_NOTE, "\n");
}
}
else
{
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location, "skip.\n");
gsi_next (&si);
continue;
}
}
else if (STMT_VINFO_IN_PATTERN_P (stmt_info)
&& (pattern_stmt = STMT_VINFO_RELATED_STMT (stmt_info))
&& (STMT_VINFO_RELEVANT_P (vinfo_for_stmt (pattern_stmt))
|| STMT_VINFO_LIVE_P (vinfo_for_stmt (pattern_stmt))))
analyze_pattern_stmt = true;
/* If a pattern statement has def stmts, analyze them too. */
if (is_pattern_stmt_p (stmt_info))
{
if (pattern_def_seq == NULL)
{
pattern_def_seq = STMT_VINFO_PATTERN_DEF_SEQ (stmt_info);
pattern_def_si = gsi_start (pattern_def_seq);
}
else if (!gsi_end_p (pattern_def_si))
gsi_next (&pattern_def_si);
if (pattern_def_seq != NULL)
{
gimple pattern_def_stmt = NULL;
stmt_vec_info pattern_def_stmt_info = NULL;
while (!gsi_end_p (pattern_def_si))
{
pattern_def_stmt = gsi_stmt (pattern_def_si);
pattern_def_stmt_info
= vinfo_for_stmt (pattern_def_stmt);
if (STMT_VINFO_RELEVANT_P (pattern_def_stmt_info)
|| STMT_VINFO_LIVE_P (pattern_def_stmt_info))
break;
gsi_next (&pattern_def_si);
}
if (!gsi_end_p (pattern_def_si))
{
if (dump_enabled_p ())
{
dump_printf_loc (MSG_NOTE, vect_location,
"==> examining pattern def stmt: ");
dump_gimple_stmt (MSG_NOTE, TDF_SLIM,
pattern_def_stmt, 0);
dump_printf (MSG_NOTE, "\n");
}
stmt = pattern_def_stmt;
stmt_info = pattern_def_stmt_info;
}
else
{
pattern_def_si = gsi_none ();
analyze_pattern_stmt = false;
}
}
else
analyze_pattern_stmt = false;
}
if (gimple_get_lhs (stmt) == NULL_TREE
/* MASK_STORE has no lhs, but is ok. */
&& (!is_gimple_call (stmt)
|| !gimple_call_internal_p (stmt)
|| gimple_call_internal_fn (stmt) != IFN_MASK_STORE))
{
if (is_gimple_call (stmt))
{
/* Ignore calls with no lhs. These must be calls to
#pragma omp simd functions, and what vectorization factor
it really needs can't be determined until
vectorizable_simd_clone_call. */
if (!analyze_pattern_stmt && gsi_end_p (pattern_def_si))
{
pattern_def_seq = NULL;
gsi_next (&si);
}
continue;
}
if (dump_enabled_p ())
{
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"not vectorized: irregular stmt.");
dump_gimple_stmt (MSG_MISSED_OPTIMIZATION, TDF_SLIM, stmt,
0);
dump_printf (MSG_MISSED_OPTIMIZATION, "\n");
}
return false;
}
if (VECTOR_MODE_P (TYPE_MODE (gimple_expr_type (stmt))))
{
if (dump_enabled_p ())
{
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"not vectorized: vector stmt in loop:");
dump_gimple_stmt (MSG_MISSED_OPTIMIZATION, TDF_SLIM, stmt, 0);
dump_printf (MSG_MISSED_OPTIMIZATION, "\n");
}
return false;
}
if (STMT_VINFO_VECTYPE (stmt_info))
{
/* The only case when a vectype had been already set is for stmts
that contain a dataref, or for "pattern-stmts" (stmts
generated by the vectorizer to represent/replace a certain
idiom). */
gcc_assert (STMT_VINFO_DATA_REF (stmt_info)
|| is_pattern_stmt_p (stmt_info)
|| !gsi_end_p (pattern_def_si));
vectype = STMT_VINFO_VECTYPE (stmt_info);
}
else
{
gcc_assert (!STMT_VINFO_DATA_REF (stmt_info));
if (is_gimple_call (stmt)
&& gimple_call_internal_p (stmt)
&& gimple_call_internal_fn (stmt) == IFN_MASK_STORE)
scalar_type = TREE_TYPE (gimple_call_arg (stmt, 3));
else
scalar_type = TREE_TYPE (gimple_get_lhs (stmt));
if (dump_enabled_p ())
{
dump_printf_loc (MSG_NOTE, vect_location,
"get vectype for scalar type: ");
dump_generic_expr (MSG_NOTE, TDF_SLIM, scalar_type);
dump_printf (MSG_NOTE, "\n");
}
vectype = get_vectype_for_scalar_type (scalar_type);
if (!vectype)
{
if (dump_enabled_p ())
{
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"not vectorized: unsupported "
"data-type ");
dump_generic_expr (MSG_MISSED_OPTIMIZATION, TDF_SLIM,
scalar_type);
dump_printf (MSG_MISSED_OPTIMIZATION, "\n");
}
return false;
}
STMT_VINFO_VECTYPE (stmt_info) = vectype;
if (dump_enabled_p ())
{
dump_printf_loc (MSG_NOTE, vect_location, "vectype: ");
dump_generic_expr (MSG_NOTE, TDF_SLIM, vectype);
dump_printf (MSG_NOTE, "\n");
}
}
/* The vectorization factor is according to the smallest
scalar type (or the largest vector size, but we only
support one vector size per loop). */
scalar_type = vect_get_smallest_scalar_type (stmt, &dummy,
&dummy);
if (dump_enabled_p ())
{
dump_printf_loc (MSG_NOTE, vect_location,
"get vectype for scalar type: ");
dump_generic_expr (MSG_NOTE, TDF_SLIM, scalar_type);
dump_printf (MSG_NOTE, "\n");
}
vf_vectype = get_vectype_for_scalar_type (scalar_type);
if (!vf_vectype)
{
if (dump_enabled_p ())
{
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"not vectorized: unsupported data-type ");
dump_generic_expr (MSG_MISSED_OPTIMIZATION, TDF_SLIM,
scalar_type);
dump_printf (MSG_MISSED_OPTIMIZATION, "\n");
}
return false;
}
if ((GET_MODE_SIZE (TYPE_MODE (vectype))
!= GET_MODE_SIZE (TYPE_MODE (vf_vectype))))
{
if (dump_enabled_p ())
{
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"not vectorized: different sized vector "
"types in statement, ");
dump_generic_expr (MSG_MISSED_OPTIMIZATION, TDF_SLIM,
vectype);
dump_printf (MSG_MISSED_OPTIMIZATION, " and ");
dump_generic_expr (MSG_MISSED_OPTIMIZATION, TDF_SLIM,
vf_vectype);
dump_printf (MSG_MISSED_OPTIMIZATION, "\n");
}
return false;
}
if (dump_enabled_p ())
{
dump_printf_loc (MSG_NOTE, vect_location, "vectype: ");
dump_generic_expr (MSG_NOTE, TDF_SLIM, vf_vectype);
dump_printf (MSG_NOTE, "\n");
}
nunits = TYPE_VECTOR_SUBPARTS (vf_vectype);
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location, "nunits = %d\n", nunits);
if (!vectorization_factor
|| (nunits > vectorization_factor))
vectorization_factor = nunits;
if (!analyze_pattern_stmt && gsi_end_p (pattern_def_si))
{
pattern_def_seq = NULL;
gsi_next (&si);
}
}
}
/* TODO: Analyze cost. Decide if worth while to vectorize. */
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location, "vectorization factor = %d\n",
vectorization_factor);
if (vectorization_factor <= 1)
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"not vectorized: unsupported data-type\n");
return false;
}
LOOP_VINFO_VECT_FACTOR (loop_vinfo) = vectorization_factor;
return true;
}
/* Function vect_is_simple_iv_evolution.
FORNOW: A simple evolution of an induction variables in the loop is
considered a polynomial evolution. */
static bool
vect_is_simple_iv_evolution (unsigned loop_nb, tree access_fn, tree * init,
tree * step)
{
tree init_expr;
tree step_expr;
tree evolution_part = evolution_part_in_loop_num (access_fn, loop_nb);
basic_block bb;
/* When there is no evolution in this loop, the evolution function
is not "simple". */
if (evolution_part == NULL_TREE)
return false;
/* When the evolution is a polynomial of degree >= 2
the evolution function is not "simple". */
if (tree_is_chrec (evolution_part))
return false;
step_expr = evolution_part;
init_expr = unshare_expr (initial_condition_in_loop_num (access_fn, loop_nb));
if (dump_enabled_p ())
{
dump_printf_loc (MSG_NOTE, vect_location, "step: ");
dump_generic_expr (MSG_NOTE, TDF_SLIM, step_expr);
dump_printf (MSG_NOTE, ", init: ");
dump_generic_expr (MSG_NOTE, TDF_SLIM, init_expr);
dump_printf (MSG_NOTE, "\n");
}
*init = init_expr;
*step = step_expr;
if (TREE_CODE (step_expr) != INTEGER_CST
&& (TREE_CODE (step_expr) != SSA_NAME
|| ((bb = gimple_bb (SSA_NAME_DEF_STMT (step_expr)))
&& flow_bb_inside_loop_p (get_loop (cfun, loop_nb), bb))
|| (!INTEGRAL_TYPE_P (TREE_TYPE (step_expr))
&& (!SCALAR_FLOAT_TYPE_P (TREE_TYPE (step_expr))
|| !flag_associative_math)))
&& (TREE_CODE (step_expr) != REAL_CST
|| !flag_associative_math))
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"step unknown.\n");
return false;
}
return true;
}
/* Function vect_analyze_scalar_cycles_1.
Examine the cross iteration def-use cycles of scalar variables
in LOOP. LOOP_VINFO represents the loop that is now being
considered for vectorization (can be LOOP, or an outer-loop
enclosing LOOP). */
static void
vect_analyze_scalar_cycles_1 (loop_vec_info loop_vinfo, struct loop *loop)
{
basic_block bb = loop->header;
tree init, step;
auto_vec<gimple, 64> worklist;
gphi_iterator gsi;
bool double_reduc;
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"=== vect_analyze_scalar_cycles ===\n");
/* First - identify all inductions. Reduction detection assumes that all the
inductions have been identified, therefore, this order must not be
changed. */
for (gsi = gsi_start_phis (bb); !gsi_end_p (gsi); gsi_next (&gsi))
{
gphi *phi = gsi.phi ();
tree access_fn = NULL;
tree def = PHI_RESULT (phi);
stmt_vec_info stmt_vinfo = vinfo_for_stmt (phi);
if (dump_enabled_p ())
{
dump_printf_loc (MSG_NOTE, vect_location, "Analyze phi: ");
dump_gimple_stmt (MSG_NOTE, TDF_SLIM, phi, 0);
dump_printf (MSG_NOTE, "\n");
}
/* Skip virtual phi's. The data dependences that are associated with
virtual defs/uses (i.e., memory accesses) are analyzed elsewhere. */
if (virtual_operand_p (def))
continue;
STMT_VINFO_DEF_TYPE (stmt_vinfo) = vect_unknown_def_type;
/* Analyze the evolution function. */
access_fn = analyze_scalar_evolution (loop, def);
if (access_fn)
{
STRIP_NOPS (access_fn);
if (dump_enabled_p ())
{
dump_printf_loc (MSG_NOTE, vect_location,
"Access function of PHI: ");
dump_generic_expr (MSG_NOTE, TDF_SLIM, access_fn);
dump_printf (MSG_NOTE, "\n");
}
STMT_VINFO_LOOP_PHI_EVOLUTION_PART (stmt_vinfo)
= evolution_part_in_loop_num (access_fn, loop->num);
}
if (!access_fn
|| !vect_is_simple_iv_evolution (loop->num, access_fn, &init, &step)
|| (LOOP_VINFO_LOOP (loop_vinfo) != loop
&& TREE_CODE (step) != INTEGER_CST))
{
worklist.safe_push (phi);
continue;
}
gcc_assert (STMT_VINFO_LOOP_PHI_EVOLUTION_PART (stmt_vinfo) != NULL_TREE);
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location, "Detected induction.\n");
STMT_VINFO_DEF_TYPE (stmt_vinfo) = vect_induction_def;
}
/* Second - identify all reductions and nested cycles. */
while (worklist.length () > 0)
{
gimple phi = worklist.pop ();
tree def = PHI_RESULT (phi);
stmt_vec_info stmt_vinfo = vinfo_for_stmt (phi);
gimple reduc_stmt;
bool nested_cycle;
if (dump_enabled_p ())
{
dump_printf_loc (MSG_NOTE, vect_location, "Analyze phi: ");
dump_gimple_stmt (MSG_NOTE, TDF_SLIM, phi, 0);
dump_printf (MSG_NOTE, "\n");
}
gcc_assert (!virtual_operand_p (def)
&& STMT_VINFO_DEF_TYPE (stmt_vinfo) == vect_unknown_def_type);
nested_cycle = (loop != LOOP_VINFO_LOOP (loop_vinfo));
reduc_stmt = vect_force_simple_reduction (loop_vinfo, phi, !nested_cycle,
&double_reduc);
if (reduc_stmt)
{
if (double_reduc)
{
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"Detected double reduction.\n");
STMT_VINFO_DEF_TYPE (stmt_vinfo) = vect_double_reduction_def;
STMT_VINFO_DEF_TYPE (vinfo_for_stmt (reduc_stmt)) =
vect_double_reduction_def;
}
else
{
if (nested_cycle)
{
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"Detected vectorizable nested cycle.\n");
STMT_VINFO_DEF_TYPE (stmt_vinfo) = vect_nested_cycle;
STMT_VINFO_DEF_TYPE (vinfo_for_stmt (reduc_stmt)) =
vect_nested_cycle;
}
else
{
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"Detected reduction.\n");
STMT_VINFO_DEF_TYPE (stmt_vinfo) = vect_reduction_def;
STMT_VINFO_DEF_TYPE (vinfo_for_stmt (reduc_stmt)) =
vect_reduction_def;
/* Store the reduction cycles for possible vectorization in
loop-aware SLP. */
LOOP_VINFO_REDUCTIONS (loop_vinfo).safe_push (reduc_stmt);
}
}
}
else
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"Unknown def-use cycle pattern.\n");
}
}
/* Function vect_analyze_scalar_cycles.
Examine the cross iteration def-use cycles of scalar variables, by
analyzing the loop-header PHIs of scalar variables. Classify each
cycle as one of the following: invariant, induction, reduction, unknown.
We do that for the loop represented by LOOP_VINFO, and also to its
inner-loop, if exists.
Examples for scalar cycles:
Example1: reduction:
loop1:
for (i=0; i<N; i++)
sum += a[i];
Example2: induction:
loop2:
for (i=0; i<N; i++)
a[i] = i; */
static void
vect_analyze_scalar_cycles (loop_vec_info loop_vinfo)
{
struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
vect_analyze_scalar_cycles_1 (loop_vinfo, loop);
/* When vectorizing an outer-loop, the inner-loop is executed sequentially.
Reductions in such inner-loop therefore have different properties than
the reductions in the nest that gets vectorized:
1. When vectorized, they are executed in the same order as in the original
scalar loop, so we can't change the order of computation when
vectorizing them.
2. FIXME: Inner-loop reductions can be used in the inner-loop, so the
current checks are too strict. */
if (loop->inner)
vect_analyze_scalar_cycles_1 (loop_vinfo, loop->inner);
}
/* Function vect_get_loop_niters.
Determine how many iterations the loop is executed and place it
in NUMBER_OF_ITERATIONS. Place the number of latch iterations
in NUMBER_OF_ITERATIONSM1.
Return the loop exit condition. */
static gcond *
vect_get_loop_niters (struct loop *loop, tree *number_of_iterations,
tree *number_of_iterationsm1)
{
tree niters;
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"=== get_loop_niters ===\n");
niters = number_of_latch_executions (loop);
*number_of_iterationsm1 = niters;
/* We want the number of loop header executions which is the number
of latch executions plus one.
??? For UINT_MAX latch executions this number overflows to zero
for loops like do { n++; } while (n != 0); */
if (niters && !chrec_contains_undetermined (niters))
niters = fold_build2 (PLUS_EXPR, TREE_TYPE (niters), unshare_expr (niters),
build_int_cst (TREE_TYPE (niters), 1));
*number_of_iterations = niters;
return get_loop_exit_condition (loop);
}
/* Function bb_in_loop_p
Used as predicate for dfs order traversal of the loop bbs. */
static bool
bb_in_loop_p (const_basic_block bb, const void *data)
{
const struct loop *const loop = (const struct loop *)data;
if (flow_bb_inside_loop_p (loop, bb))
return true;
return false;
}
/* Function new_loop_vec_info.
Create and initialize a new loop_vec_info struct for LOOP, as well as
stmt_vec_info structs for all the stmts in LOOP. */
static loop_vec_info
new_loop_vec_info (struct loop *loop)
{
loop_vec_info res;
basic_block *bbs;
gimple_stmt_iterator si;
unsigned int i, nbbs;
res = (loop_vec_info) xcalloc (1, sizeof (struct _loop_vec_info));
LOOP_VINFO_LOOP (res) = loop;
bbs = get_loop_body (loop);
/* Create/Update stmt_info for all stmts in the loop. */
for (i = 0; i < loop->num_nodes; i++)
{
basic_block bb = bbs[i];
/* BBs in a nested inner-loop will have been already processed (because
we will have called vect_analyze_loop_form for any nested inner-loop).
Therefore, for stmts in an inner-loop we just want to update the
STMT_VINFO_LOOP_VINFO field of their stmt_info to point to the new
loop_info of the outer-loop we are currently considering to vectorize
(instead of the loop_info of the inner-loop).
For stmts in other BBs we need to create a stmt_info from scratch. */
if (bb->loop_father != loop)
{
/* Inner-loop bb. */
gcc_assert (loop->inner && bb->loop_father == loop->inner);
for (si = gsi_start_phis (bb); !gsi_end_p (si); gsi_next (&si))
{
gimple phi = gsi_stmt (si);
stmt_vec_info stmt_info = vinfo_for_stmt (phi);
loop_vec_info inner_loop_vinfo =
STMT_VINFO_LOOP_VINFO (stmt_info);
gcc_assert (loop->inner == LOOP_VINFO_LOOP (inner_loop_vinfo));
STMT_VINFO_LOOP_VINFO (stmt_info) = res;
}
for (si = gsi_start_bb (bb); !gsi_end_p (si); gsi_next (&si))
{
gimple stmt = gsi_stmt (si);
stmt_vec_info stmt_info = vinfo_for_stmt (stmt);
loop_vec_info inner_loop_vinfo =
STMT_VINFO_LOOP_VINFO (stmt_info);
gcc_assert (loop->inner == LOOP_VINFO_LOOP (inner_loop_vinfo));
STMT_VINFO_LOOP_VINFO (stmt_info) = res;
}
}
else
{
/* bb in current nest. */
for (si = gsi_start_phis (bb); !gsi_end_p (si); gsi_next (&si))
{
gimple phi = gsi_stmt (si);
gimple_set_uid (phi, 0);
set_vinfo_for_stmt (phi, new_stmt_vec_info (phi, res, NULL));
}
for (si = gsi_start_bb (bb); !gsi_end_p (si); gsi_next (&si))
{
gimple stmt = gsi_stmt (si);
gimple_set_uid (stmt, 0);
set_vinfo_for_stmt (stmt, new_stmt_vec_info (stmt, res, NULL));
}
}
}
/* CHECKME: We want to visit all BBs before their successors (except for
latch blocks, for which this assertion wouldn't hold). In the simple
case of the loop forms we allow, a dfs order of the BBs would the same
as reversed postorder traversal, so we are safe. */
free (bbs);
bbs = XCNEWVEC (basic_block, loop->num_nodes);
nbbs = dfs_enumerate_from (loop->header, 0, bb_in_loop_p,
bbs, loop->num_nodes, loop);
gcc_assert (nbbs == loop->num_nodes);
LOOP_VINFO_BBS (res) = bbs;
LOOP_VINFO_NITERSM1 (res) = NULL;
LOOP_VINFO_NITERS (res) = NULL;
LOOP_VINFO_NITERS_UNCHANGED (res) = NULL;
LOOP_VINFO_COST_MODEL_MIN_ITERS (res) = 0;
LOOP_VINFO_COST_MODEL_THRESHOLD (res) = 0;
LOOP_VINFO_VECTORIZABLE_P (res) = 0;
LOOP_VINFO_PEELING_FOR_ALIGNMENT (res) = 0;
LOOP_VINFO_VECT_FACTOR (res) = 0;
LOOP_VINFO_LOOP_NEST (res).create (3);
LOOP_VINFO_DATAREFS (res).create (10);
LOOP_VINFO_DDRS (res).create (10 * 10);
LOOP_VINFO_UNALIGNED_DR (res) = NULL;
LOOP_VINFO_MAY_MISALIGN_STMTS (res).create (
PARAM_VALUE (PARAM_VECT_MAX_VERSION_FOR_ALIGNMENT_CHECKS));
LOOP_VINFO_MAY_ALIAS_DDRS (res).create (
PARAM_VALUE (PARAM_VECT_MAX_VERSION_FOR_ALIAS_CHECKS));
LOOP_VINFO_GROUPED_STORES (res).create (10);
LOOP_VINFO_REDUCTIONS (res).create (10);
LOOP_VINFO_REDUCTION_CHAINS (res).create (10);
LOOP_VINFO_SLP_INSTANCES (res).create (10);
LOOP_VINFO_SLP_UNROLLING_FACTOR (res) = 1;
LOOP_VINFO_TARGET_COST_DATA (res) = init_cost (loop);
LOOP_VINFO_PEELING_FOR_GAPS (res) = false;
LOOP_VINFO_PEELING_FOR_NITER (res) = false;
LOOP_VINFO_OPERANDS_SWAPPED (res) = false;
return res;
}
/* Function destroy_loop_vec_info.
Free LOOP_VINFO struct, as well as all the stmt_vec_info structs of all the
stmts in the loop. */
void
destroy_loop_vec_info (loop_vec_info loop_vinfo, bool clean_stmts)
{
struct loop *loop;
basic_block *bbs;
int nbbs;
gimple_stmt_iterator si;
int j;
vec<slp_instance> slp_instances;
slp_instance instance;
bool swapped;
if (!loop_vinfo)
return;
loop = LOOP_VINFO_LOOP (loop_vinfo);
bbs = LOOP_VINFO_BBS (loop_vinfo);
nbbs = clean_stmts ? loop->num_nodes : 0;
swapped = LOOP_VINFO_OPERANDS_SWAPPED (loop_vinfo);
for (j = 0; j < nbbs; j++)
{
basic_block bb = bbs[j];
for (si = gsi_start_phis (bb); !gsi_end_p (si); gsi_next (&si))
free_stmt_vec_info (gsi_stmt (si));
for (si = gsi_start_bb (bb); !gsi_end_p (si); )
{
gimple stmt = gsi_stmt (si);
/* We may have broken canonical form by moving a constant
into RHS1 of a commutative op. Fix such occurrences. */
if (swapped && is_gimple_assign (stmt))
{
enum tree_code code = gimple_assign_rhs_code (stmt);
if ((code == PLUS_EXPR
|| code == POINTER_PLUS_EXPR
|| code == MULT_EXPR)
&& CONSTANT_CLASS_P (gimple_assign_rhs1 (stmt)))
swap_ssa_operands (stmt,
gimple_assign_rhs1_ptr (stmt),
gimple_assign_rhs2_ptr (stmt));
}
/* Free stmt_vec_info. */
free_stmt_vec_info (stmt);
gsi_next (&si);
}
}
free (LOOP_VINFO_BBS (loop_vinfo));
vect_destroy_datarefs (loop_vinfo, NULL);
free_dependence_relations (LOOP_VINFO_DDRS (loop_vinfo));
LOOP_VINFO_LOOP_NEST (loop_vinfo).release ();
LOOP_VINFO_MAY_MISALIGN_STMTS (loop_vinfo).release ();
LOOP_VINFO_MAY_ALIAS_DDRS (loop_vinfo).release ();
slp_instances = LOOP_VINFO_SLP_INSTANCES (loop_vinfo);
FOR_EACH_VEC_ELT (slp_instances, j, instance)
vect_free_slp_instance (instance);
LOOP_VINFO_SLP_INSTANCES (loop_vinfo).release ();
LOOP_VINFO_GROUPED_STORES (loop_vinfo).release ();
LOOP_VINFO_REDUCTIONS (loop_vinfo).release ();
LOOP_VINFO_REDUCTION_CHAINS (loop_vinfo).release ();
delete LOOP_VINFO_PEELING_HTAB (loop_vinfo);
LOOP_VINFO_PEELING_HTAB (loop_vinfo) = NULL;
destroy_cost_data (LOOP_VINFO_TARGET_COST_DATA (loop_vinfo));
free (loop_vinfo);
loop->aux = NULL;
}
/* Function vect_analyze_loop_1.
Apply a set of analyses on LOOP, and create a loop_vec_info struct
for it. The different analyses will record information in the
loop_vec_info struct. This is a subset of the analyses applied in
vect_analyze_loop, to be applied on an inner-loop nested in the loop
that is now considered for (outer-loop) vectorization. */
static loop_vec_info
vect_analyze_loop_1 (struct loop *loop)
{
loop_vec_info loop_vinfo;
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"===== analyze_loop_nest_1 =====\n");
/* Check the CFG characteristics of the loop (nesting, entry/exit, etc. */
loop_vinfo = vect_analyze_loop_form (loop);
if (!loop_vinfo)
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"bad inner-loop form.\n");
return NULL;
}
return loop_vinfo;
}
/* Function vect_analyze_loop_form.
Verify that certain CFG restrictions hold, including:
- the loop has a pre-header
- the loop has a single entry and exit
- the loop exit condition is simple enough, and the number of iterations
can be analyzed (a countable loop). */
loop_vec_info
vect_analyze_loop_form (struct loop *loop)
{
loop_vec_info loop_vinfo;
gcond *loop_cond;
tree number_of_iterations = NULL, number_of_iterationsm1 = NULL;
loop_vec_info inner_loop_vinfo = NULL;
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"=== vect_analyze_loop_form ===\n");
/* Different restrictions apply when we are considering an inner-most loop,
vs. an outer (nested) loop.
(FORNOW. May want to relax some of these restrictions in the future). */
if (!loop->inner)
{
/* Inner-most loop. We currently require that the number of BBs is
exactly 2 (the header and latch). Vectorizable inner-most loops
look like this:
(pre-header)
|
header <--------+
| | |
| +--> latch --+
|
(exit-bb) */
if (loop->num_nodes != 2)
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"not vectorized: control flow in loop.\n");
return NULL;
}
if (empty_block_p (loop->header))
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"not vectorized: empty loop.\n");
return NULL;
}
}
else
{
struct loop *innerloop = loop->inner;
edge entryedge;
/* Nested loop. We currently require that the loop is doubly-nested,
contains a single inner loop, and the number of BBs is exactly 5.
Vectorizable outer-loops look like this:
(pre-header)
|
header <---+
| |
inner-loop |
| |
tail ------+
|
(exit-bb)
The inner-loop has the properties expected of inner-most loops
as described above. */
if ((loop->inner)->inner || (loop->inner)->next)
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"not vectorized: multiple nested loops.\n");
return NULL;
}
/* Analyze the inner-loop. */
inner_loop_vinfo = vect_analyze_loop_1 (loop->inner);
if (!inner_loop_vinfo)
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"not vectorized: Bad inner loop.\n");
return NULL;
}
if (!expr_invariant_in_loop_p (loop,
LOOP_VINFO_NITERS (inner_loop_vinfo)))
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"not vectorized: inner-loop count not"
" invariant.\n");
destroy_loop_vec_info (inner_loop_vinfo, true);
return NULL;
}
if (loop->num_nodes != 5)
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"not vectorized: control flow in loop.\n");
destroy_loop_vec_info (inner_loop_vinfo, true);
return NULL;
}
gcc_assert (EDGE_COUNT (innerloop->header->preds) == 2);
entryedge = EDGE_PRED (innerloop->header, 0);
if (EDGE_PRED (innerloop->header, 0)->src == innerloop->latch)
entryedge = EDGE_PRED (innerloop->header, 1);
if (entryedge->src != loop->header
|| !single_exit (innerloop)
|| single_exit (innerloop)->dest != EDGE_PRED (loop->latch, 0)->src)
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"not vectorized: unsupported outerloop form.\n");
destroy_loop_vec_info (inner_loop_vinfo, true);
return NULL;
}
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"Considering outer-loop vectorization.\n");
}
if (!single_exit (loop)
|| EDGE_COUNT (loop->header->preds) != 2)
{
if (dump_enabled_p ())
{
if (!single_exit (loop))
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"not vectorized: multiple exits.\n");
else if (EDGE_COUNT (loop->header->preds) != 2)
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"not vectorized: too many incoming edges.\n");
}
if (inner_loop_vinfo)
destroy_loop_vec_info (inner_loop_vinfo, true);
return NULL;
}
/* We assume that the loop exit condition is at the end of the loop. i.e,
that the loop is represented as a do-while (with a proper if-guard
before the loop if needed), where the loop header contains all the
executable statements, and the latch is empty. */
if (!empty_block_p (loop->latch)
|| !gimple_seq_empty_p (phi_nodes (loop->latch)))
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"not vectorized: latch block not empty.\n");
if (inner_loop_vinfo)
destroy_loop_vec_info (inner_loop_vinfo, true);
return NULL;
}
/* Make sure there exists a single-predecessor exit bb: */
if (!single_pred_p (single_exit (loop)->dest))
{
edge e = single_exit (loop);
if (!(e->flags & EDGE_ABNORMAL))
{
split_loop_exit_edge (e);
if (dump_enabled_p ())
dump_printf (MSG_NOTE, "split exit edge.\n");
}
else
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"not vectorized: abnormal loop exit edge.\n");
if (inner_loop_vinfo)
destroy_loop_vec_info (inner_loop_vinfo, true);
return NULL;
}
}
loop_cond = vect_get_loop_niters (loop, &number_of_iterations,
&number_of_iterationsm1);
if (!loop_cond)
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"not vectorized: complicated exit condition.\n");
if (inner_loop_vinfo)
destroy_loop_vec_info (inner_loop_vinfo, true);
return NULL;
}
if (!number_of_iterations
|| chrec_contains_undetermined (number_of_iterations))
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"not vectorized: number of iterations cannot be "
"computed.\n");
if (inner_loop_vinfo)
destroy_loop_vec_info (inner_loop_vinfo, true);
return NULL;
}
if (integer_zerop (number_of_iterations))
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"not vectorized: number of iterations = 0.\n");
if (inner_loop_vinfo)
destroy_loop_vec_info (inner_loop_vinfo, true);
return NULL;
}
loop_vinfo = new_loop_vec_info (loop);
LOOP_VINFO_NITERSM1 (loop_vinfo) = number_of_iterationsm1;
LOOP_VINFO_NITERS (loop_vinfo) = number_of_iterations;
LOOP_VINFO_NITERS_UNCHANGED (loop_vinfo) = number_of_iterations;
if (!LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo))
{
if (dump_enabled_p ())
{
dump_printf_loc (MSG_NOTE, vect_location,
"Symbolic number of iterations is ");
dump_generic_expr (MSG_NOTE, TDF_DETAILS, number_of_iterations);
dump_printf (MSG_NOTE, "\n");
}
}
STMT_VINFO_TYPE (vinfo_for_stmt (loop_cond)) = loop_exit_ctrl_vec_info_type;
/* CHECKME: May want to keep it around it in the future. */
if (inner_loop_vinfo)
destroy_loop_vec_info (inner_loop_vinfo, false);
gcc_assert (!loop->aux);
loop->aux = loop_vinfo;
return loop_vinfo;
}
/* Function vect_analyze_loop_operations.
Scan the loop stmts and make sure they are all vectorizable. */
static bool
vect_analyze_loop_operations (loop_vec_info loop_vinfo, bool slp)
{
struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
basic_block *bbs = LOOP_VINFO_BBS (loop_vinfo);
int nbbs = loop->num_nodes;
unsigned int vectorization_factor = 0;
int i;
stmt_vec_info stmt_info;
bool need_to_vectorize = false;
int min_profitable_iters;
int min_scalar_loop_bound;
unsigned int th;
bool only_slp_in_loop = true, ok;
HOST_WIDE_INT max_niter;
HOST_WIDE_INT estimated_niter;
int min_profitable_estimate;
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"=== vect_analyze_loop_operations ===\n");
gcc_assert (LOOP_VINFO_VECT_FACTOR (loop_vinfo));
vectorization_factor = LOOP_VINFO_VECT_FACTOR (loop_vinfo);
if (slp)
{
/* If all the stmts in the loop can be SLPed, we perform only SLP, and
vectorization factor of the loop is the unrolling factor required by
the SLP instances. If that unrolling factor is 1, we say, that we
perform pure SLP on loop - cross iteration parallelism is not
exploited. */
for (i = 0; i < nbbs; i++)
{
basic_block bb = bbs[i];
for (gimple_stmt_iterator si = gsi_start_bb (bb); !gsi_end_p (si);
gsi_next (&si))
{
gimple stmt = gsi_stmt (si);
stmt_vec_info stmt_info = vinfo_for_stmt (stmt);
gcc_assert (stmt_info);
if ((STMT_VINFO_RELEVANT_P (stmt_info)
|| VECTORIZABLE_CYCLE_DEF (STMT_VINFO_DEF_TYPE (stmt_info)))
&& !PURE_SLP_STMT (stmt_info))
/* STMT needs both SLP and loop-based vectorization. */
only_slp_in_loop = false;
}
}
if (only_slp_in_loop)
vectorization_factor = LOOP_VINFO_SLP_UNROLLING_FACTOR (loop_vinfo);
else
vectorization_factor = least_common_multiple (vectorization_factor,
LOOP_VINFO_SLP_UNROLLING_FACTOR (loop_vinfo));
LOOP_VINFO_VECT_FACTOR (loop_vinfo) = vectorization_factor;
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"Updating vectorization factor to %d\n",
vectorization_factor);
}
for (i = 0; i < nbbs; i++)
{
basic_block bb = bbs[i];
for (gphi_iterator si = gsi_start_phis (bb); !gsi_end_p (si);
gsi_next (&si))
{
gphi *phi = si.phi ();
ok = true;
stmt_info = vinfo_for_stmt (phi);
if (dump_enabled_p ())
{
dump_printf_loc (MSG_NOTE, vect_location, "examining phi: ");
dump_gimple_stmt (MSG_NOTE, TDF_SLIM, phi, 0);
dump_printf (MSG_NOTE, "\n");
}
/* Inner-loop loop-closed exit phi in outer-loop vectorization
(i.e., a phi in the tail of the outer-loop). */
if (! is_loop_header_bb_p (bb))
{
/* FORNOW: we currently don't support the case that these phis
are not used in the outerloop (unless it is double reduction,
i.e., this phi is vect_reduction_def), cause this case
requires to actually do something here. */
if ((!STMT_VINFO_RELEVANT_P (stmt_info)
|| STMT_VINFO_LIVE_P (stmt_info))
&& STMT_VINFO_DEF_TYPE (stmt_info)
!= vect_double_reduction_def)
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"Unsupported loop-closed phi in "
"outer-loop.\n");
return false;
}
/* If PHI is used in the outer loop, we check that its operand
is defined in the inner loop. */
if (STMT_VINFO_RELEVANT_P (stmt_info))
{
tree phi_op;
gimple op_def_stmt;
if (gimple_phi_num_args (phi) != 1)
return false;
phi_op = PHI_ARG_DEF (phi, 0);
if (TREE_CODE (phi_op) != SSA_NAME)
return false;
op_def_stmt = SSA_NAME_DEF_STMT (phi_op);
if (gimple_nop_p (op_def_stmt)
|| !flow_bb_inside_loop_p (loop, gimple_bb (op_def_stmt))
|| !vinfo_for_stmt (op_def_stmt))
return false;
if (STMT_VINFO_RELEVANT (vinfo_for_stmt (op_def_stmt))
!= vect_used_in_outer
&& STMT_VINFO_RELEVANT (vinfo_for_stmt (op_def_stmt))
!= vect_used_in_outer_by_reduction)
return false;
}
continue;
}
gcc_assert (stmt_info);
if (STMT_VINFO_LIVE_P (stmt_info))
{
/* FORNOW: not yet supported. */
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"not vectorized: value used after loop.\n");
return false;
}
if (STMT_VINFO_RELEVANT (stmt_info) == vect_used_in_scope
&& STMT_VINFO_DEF_TYPE (stmt_info) != vect_induction_def)
{
/* A scalar-dependence cycle that we don't support. */
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"not vectorized: scalar dependence cycle.\n");
return false;
}
if (STMT_VINFO_RELEVANT_P (stmt_info))
{
need_to_vectorize = true;
if (STMT_VINFO_DEF_TYPE (stmt_info) == vect_induction_def)
ok = vectorizable_induction (phi, NULL, NULL);
}
if (!ok)
{
if (dump_enabled_p ())
{
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"not vectorized: relevant phi not "
"supported: ");
dump_gimple_stmt (MSG_MISSED_OPTIMIZATION, TDF_SLIM, phi, 0);
dump_printf (MSG_MISSED_OPTIMIZATION, "\n");
}
return false;
}
}
for (gimple_stmt_iterator si = gsi_start_bb (bb); !gsi_end_p (si);
gsi_next (&si))
{
gimple stmt = gsi_stmt (si);
if (!gimple_clobber_p (stmt)
&& !vect_analyze_stmt (stmt, &need_to_vectorize, NULL))
return false;
}
} /* bbs */
/* All operations in the loop are either irrelevant (deal with loop
control, or dead), or only used outside the loop and can be moved
out of the loop (e.g. invariants, inductions). The loop can be
optimized away by scalar optimizations. We're better off not
touching this loop. */
if (!need_to_vectorize)
{
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"All the computation can be taken out of the loop.\n");
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"not vectorized: redundant loop. no profit to "
"vectorize.\n");
return false;
}
if (LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo) && dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"vectorization_factor = %d, niters = "
HOST_WIDE_INT_PRINT_DEC "\n", vectorization_factor,
LOOP_VINFO_INT_NITERS (loop_vinfo));
if ((LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo)
&& (LOOP_VINFO_INT_NITERS (loop_vinfo) < vectorization_factor))
|| ((max_niter = max_stmt_executions_int (loop)) != -1
&& (unsigned HOST_WIDE_INT) max_niter < vectorization_factor))
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"not vectorized: iteration count too small.\n");
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"not vectorized: iteration count smaller than "
"vectorization factor.\n");
return false;
}
/* Analyze cost. Decide if worth while to vectorize. */
/* Once VF is set, SLP costs should be updated since the number of created
vector stmts depends on VF. */
vect_update_slp_costs_according_to_vf (loop_vinfo);
vect_estimate_min_profitable_iters (loop_vinfo, &min_profitable_iters,
&min_profitable_estimate);
LOOP_VINFO_COST_MODEL_MIN_ITERS (loop_vinfo) = min_profitable_iters;
if (min_profitable_iters < 0)
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"not vectorized: vectorization not profitable.\n");
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"not vectorized: vector version will never be "
"profitable.\n");
return false;
}
min_scalar_loop_bound = ((PARAM_VALUE (PARAM_MIN_VECT_LOOP_BOUND)
* vectorization_factor) - 1);
/* Use the cost model only if it is more conservative than user specified
threshold. */
th = (unsigned) min_scalar_loop_bound;
if (min_profitable_iters
&& (!min_scalar_loop_bound
|| min_profitable_iters > min_scalar_loop_bound))
th = (unsigned) min_profitable_iters;
LOOP_VINFO_COST_MODEL_THRESHOLD (loop_vinfo) = th;
if (LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo)
&& LOOP_VINFO_INT_NITERS (loop_vinfo) <= th)
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"not vectorized: vectorization not profitable.\n");
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"not vectorized: iteration count smaller than user "
"specified loop bound parameter or minimum profitable "
"iterations (whichever is more conservative).\n");
return false;
}
if ((estimated_niter = estimated_stmt_executions_int (loop)) != -1
&& ((unsigned HOST_WIDE_INT) estimated_niter
<= MAX (th, (unsigned)min_profitable_estimate)))
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"not vectorized: estimated iteration count too "
"small.\n");
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"not vectorized: estimated iteration count smaller "
"than specified loop bound parameter or minimum "
"profitable iterations (whichever is more "
"conservative).\n");
return false;
}
return true;
}
/* Function vect_analyze_loop_2.
Apply a set of analyses on LOOP, and create a loop_vec_info struct
for it. The different analyses will record information in the
loop_vec_info struct. */
static bool
vect_analyze_loop_2 (loop_vec_info loop_vinfo)
{
bool ok, slp = false;
int max_vf = MAX_VECTORIZATION_FACTOR;
int min_vf = 2;
unsigned int th;
unsigned int n_stmts = 0;
/* Find all data references in the loop (which correspond to vdefs/vuses)
and analyze their evolution in the loop. Also adjust the minimal
vectorization factor according to the loads and stores.
FORNOW: Handle only simple, array references, which
alignment can be forced, and aligned pointer-references. */
ok = vect_analyze_data_refs (loop_vinfo, NULL, &min_vf, &n_stmts);
if (!ok)
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"bad data references.\n");
return false;
}
/* Classify all cross-iteration scalar data-flow cycles.
Cross-iteration cycles caused by virtual phis are analyzed separately. */
vect_analyze_scalar_cycles (loop_vinfo);
vect_pattern_recog (loop_vinfo, NULL);
/* Analyze the access patterns of the data-refs in the loop (consecutive,
complex, etc.). FORNOW: Only handle consecutive access pattern. */
ok = vect_analyze_data_ref_accesses (loop_vinfo, NULL);
if (!ok)
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"bad data access.\n");
return false;
}
/* Data-flow analysis to detect stmts that do not need to be vectorized. */
ok = vect_mark_stmts_to_be_vectorized (loop_vinfo);
if (!ok)
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"unexpected pattern.\n");
return false;
}
/* Analyze data dependences between the data-refs in the loop
and adjust the maximum vectorization factor according to
the dependences.
FORNOW: fail at the first data dependence that we encounter. */
ok = vect_analyze_data_ref_dependences (loop_vinfo, &max_vf);
if (!ok
|| max_vf < min_vf)
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"bad data dependence.\n");
return false;
}
ok = vect_determine_vectorization_factor (loop_vinfo);
if (!ok)
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"can't determine vectorization factor.\n");
return false;
}
if (max_vf < LOOP_VINFO_VECT_FACTOR (loop_vinfo))
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"bad data dependence.\n");
return false;
}
/* Analyze the alignment of the data-refs in the loop.
Fail if a data reference is found that cannot be vectorized. */
ok = vect_analyze_data_refs_alignment (loop_vinfo, NULL);
if (!ok)
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"bad data alignment.\n");
return false;
}
/* Prune the list of ddrs to be tested at run-time by versioning for alias.
It is important to call pruning after vect_analyze_data_ref_accesses,
since we use grouping information gathered by interleaving analysis. */
ok = vect_prune_runtime_alias_test_list (loop_vinfo);
if (!ok)
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"number of versioning for alias "
"run-time tests exceeds %d "
"(--param vect-max-version-for-alias-checks)\n",
PARAM_VALUE (PARAM_VECT_MAX_VERSION_FOR_ALIAS_CHECKS));
return false;
}
/* This pass will decide on using loop versioning and/or loop peeling in
order to enhance the alignment of data references in the loop. */
ok = vect_enhance_data_refs_alignment (loop_vinfo);
if (!ok)
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"bad data alignment.\n");
return false;
}
/* Check the SLP opportunities in the loop, analyze and build SLP trees. */
ok = vect_analyze_slp (loop_vinfo, NULL, n_stmts);
if (ok)
{
/* Decide which possible SLP instances to SLP. */
slp = vect_make_slp_decision (loop_vinfo);
/* Find stmts that need to be both vectorized and SLPed. */
vect_detect_hybrid_slp (loop_vinfo);
}
else
return false;
/* Scan all the operations in the loop and make sure they are
vectorizable. */
ok = vect_analyze_loop_operations (loop_vinfo, slp);
if (!ok)
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"bad operation or unsupported loop bound.\n");
return false;
}
/* Decide whether we need to create an epilogue loop to handle
remaining scalar iterations. */
th = ((LOOP_VINFO_COST_MODEL_THRESHOLD (loop_vinfo) + 1)
/ LOOP_VINFO_VECT_FACTOR (loop_vinfo))
* LOOP_VINFO_VECT_FACTOR (loop_vinfo);
if (LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo)
&& LOOP_VINFO_PEELING_FOR_ALIGNMENT (loop_vinfo) > 0)
{
if (ctz_hwi (LOOP_VINFO_INT_NITERS (loop_vinfo)
- LOOP_VINFO_PEELING_FOR_ALIGNMENT (loop_vinfo))
< exact_log2 (LOOP_VINFO_VECT_FACTOR (loop_vinfo)))
LOOP_VINFO_PEELING_FOR_NITER (loop_vinfo) = true;
}
else if (LOOP_VINFO_PEELING_FOR_ALIGNMENT (loop_vinfo)
|| (tree_ctz (LOOP_VINFO_NITERS (loop_vinfo))
< (unsigned)exact_log2 (LOOP_VINFO_VECT_FACTOR (loop_vinfo))
/* In case of versioning, check if the maximum number of
iterations is greater than th. If they are identical,
the epilogue is unnecessary. */
&& ((!LOOP_REQUIRES_VERSIONING_FOR_ALIAS (loop_vinfo)
&& !LOOP_REQUIRES_VERSIONING_FOR_ALIGNMENT (loop_vinfo))
|| (unsigned HOST_WIDE_INT)max_stmt_executions_int
(LOOP_VINFO_LOOP (loop_vinfo)) > th)))
LOOP_VINFO_PEELING_FOR_NITER (loop_vinfo) = true;
/* If an epilogue loop is required make sure we can create one. */
if (LOOP_VINFO_PEELING_FOR_GAPS (loop_vinfo)
|| LOOP_VINFO_PEELING_FOR_NITER (loop_vinfo))
{
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location, "epilog loop required\n");
if (!vect_can_advance_ivs_p (loop_vinfo)
|| !slpeel_can_duplicate_loop_p (LOOP_VINFO_LOOP (loop_vinfo),
single_exit (LOOP_VINFO_LOOP
(loop_vinfo))))
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"not vectorized: can't create required "
"epilog loop\n");
return false;
}
}
return true;
}
/* Function vect_analyze_loop.
Apply a set of analyses on LOOP, and create a loop_vec_info struct
for it. The different analyses will record information in the
loop_vec_info struct. */
loop_vec_info
vect_analyze_loop (struct loop *loop)
{
loop_vec_info loop_vinfo;
unsigned int vector_sizes;
/* Autodetect first vector size we try. */
current_vector_size = 0;
vector_sizes = targetm.vectorize.autovectorize_vector_sizes ();
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"===== analyze_loop_nest =====\n");
if (loop_outer (loop)
&& loop_vec_info_for_loop (loop_outer (loop))
&& LOOP_VINFO_VECTORIZABLE_P (loop_vec_info_for_loop (loop_outer (loop))))
{
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"outer-loop already vectorized.\n");
return NULL;
}
while (1)
{
/* Check the CFG characteristics of the loop (nesting, entry/exit). */
loop_vinfo = vect_analyze_loop_form (loop);
if (!loop_vinfo)
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"bad loop form.\n");
return NULL;
}
if (vect_analyze_loop_2 (loop_vinfo))
{
LOOP_VINFO_VECTORIZABLE_P (loop_vinfo) = 1;
return loop_vinfo;
}
destroy_loop_vec_info (loop_vinfo, true);
vector_sizes &= ~current_vector_size;
if (vector_sizes == 0
|| current_vector_size == 0)
return NULL;
/* Try the next biggest vector size. */
current_vector_size = 1 << floor_log2 (vector_sizes);
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"***** Re-trying analysis with "
"vector size %d\n", current_vector_size);
}
}
/* Function reduction_code_for_scalar_code
Input:
CODE - tree_code of a reduction operations.
Output:
REDUC_CODE - the corresponding tree-code to be used to reduce the
vector of partial results into a single scalar result, or ERROR_MARK
if the operation is a supported reduction operation, but does not have
such a tree-code.
Return FALSE if CODE currently cannot be vectorized as reduction. */
static bool
reduction_code_for_scalar_code (enum tree_code code,
enum tree_code *reduc_code)
{
switch (code)
{
case MAX_EXPR:
*reduc_code = REDUC_MAX_EXPR;
return true;
case MIN_EXPR:
*reduc_code = REDUC_MIN_EXPR;
return true;
case PLUS_EXPR:
*reduc_code = REDUC_PLUS_EXPR;
return true;
case MULT_EXPR:
case MINUS_EXPR:
case BIT_IOR_EXPR:
case BIT_XOR_EXPR:
case BIT_AND_EXPR:
*reduc_code = ERROR_MARK;
return true;
default:
return false;
}
}
/* Error reporting helper for vect_is_simple_reduction below. GIMPLE statement
STMT is printed with a message MSG. */
static void
report_vect_op (int msg_type, gimple stmt, const char *msg)
{
dump_printf_loc (msg_type, vect_location, "%s", msg);
dump_gimple_stmt (msg_type, TDF_SLIM, stmt, 0);
dump_printf (msg_type, "\n");
}
/* Detect SLP reduction of the form:
#a1 = phi <a5, a0>
a2 = operation (a1)
a3 = operation (a2)
a4 = operation (a3)
a5 = operation (a4)
#a = phi <a5>
PHI is the reduction phi node (#a1 = phi <a5, a0> above)
FIRST_STMT is the first reduction stmt in the chain
(a2 = operation (a1)).
Return TRUE if a reduction chain was detected. */
static bool
vect_is_slp_reduction (loop_vec_info loop_info, gimple phi, gimple first_stmt)
{
struct loop *loop = (gimple_bb (phi))->loop_father;
struct loop *vect_loop = LOOP_VINFO_LOOP (loop_info);
enum tree_code code;
gimple current_stmt = NULL, loop_use_stmt = NULL, first, next_stmt;
stmt_vec_info use_stmt_info, current_stmt_info;
tree lhs;
imm_use_iterator imm_iter;
use_operand_p use_p;
int nloop_uses, size = 0, n_out_of_loop_uses;
bool found = false;
if (loop != vect_loop)
return false;
lhs = PHI_RESULT (phi);
code = gimple_assign_rhs_code (first_stmt);
while (1)
{
nloop_uses = 0;
n_out_of_loop_uses = 0;
FOR_EACH_IMM_USE_FAST (use_p, imm_iter, lhs)
{
gimple use_stmt = USE_STMT (use_p);
if (is_gimple_debug (use_stmt))
continue;
/* Check if we got back to the reduction phi. */
if (use_stmt == phi)
{
loop_use_stmt = use_stmt;
found = true;
break;
}
if (flow_bb_inside_loop_p (loop, gimple_bb (use_stmt)))
{
if (vinfo_for_stmt (use_stmt)
&& !STMT_VINFO_IN_PATTERN_P (vinfo_for_stmt (use_stmt)))
{
loop_use_stmt = use_stmt;
nloop_uses++;
}
}
else
n_out_of_loop_uses++;
/* There are can be either a single use in the loop or two uses in
phi nodes. */
if (nloop_uses > 1 || (n_out_of_loop_uses && nloop_uses))
return false;
}
if (found)
break;
/* We reached a statement with no loop uses. */
if (nloop_uses == 0)
return false;
/* This is a loop exit phi, and we haven't reached the reduction phi. */
if (gimple_code (loop_use_stmt) == GIMPLE_PHI)
return false;
if (!is_gimple_assign (loop_use_stmt)
|| code != gimple_assign_rhs_code (loop_use_stmt)
|| !flow_bb_inside_loop_p (loop, gimple_bb (loop_use_stmt)))
return false;
/* Insert USE_STMT into reduction chain. */
use_stmt_info = vinfo_for_stmt (loop_use_stmt);
if (current_stmt)
{
current_stmt_info = vinfo_for_stmt (current_stmt);
GROUP_NEXT_ELEMENT (current_stmt_info) = loop_use_stmt;
GROUP_FIRST_ELEMENT (use_stmt_info)
= GROUP_FIRST_ELEMENT (current_stmt_info);
}
else
GROUP_FIRST_ELEMENT (use_stmt_info) = loop_use_stmt;
lhs = gimple_assign_lhs (loop_use_stmt);
current_stmt = loop_use_stmt;
size++;
}
if (!found || loop_use_stmt != phi || size < 2)
return false;
/* Swap the operands, if needed, to make the reduction operand be the second
operand. */
lhs = PHI_RESULT (phi);
next_stmt = GROUP_FIRST_ELEMENT (vinfo_for_stmt (current_stmt));
while (next_stmt)
{
if (gimple_assign_rhs2 (next_stmt) == lhs)
{
tree op = gimple_assign_rhs1 (next_stmt);
gimple def_stmt = NULL;
if (TREE_CODE (op) == SSA_NAME)
def_stmt = SSA_NAME_DEF_STMT (op);
/* Check that the other def is either defined in the loop
("vect_internal_def"), or it's an induction (defined by a
loop-header phi-node). */
if (def_stmt
&& gimple_bb (def_stmt)
&& flow_bb_inside_loop_p (loop, gimple_bb (def_stmt))
&& (is_gimple_assign (def_stmt)
|| is_gimple_call (def_stmt)
|| STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def_stmt))
== vect_induction_def
|| (gimple_code (def_stmt) == GIMPLE_PHI
&& STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def_stmt))
== vect_internal_def
&& !is_loop_header_bb_p (gimple_bb (def_stmt)))))
{
lhs = gimple_assign_lhs (next_stmt);
next_stmt = GROUP_NEXT_ELEMENT (vinfo_for_stmt (next_stmt));
continue;
}
return false;
}
else
{
tree op = gimple_assign_rhs2 (next_stmt);
gimple def_stmt = NULL;
if (TREE_CODE (op) == SSA_NAME)
def_stmt = SSA_NAME_DEF_STMT (op);
/* Check that the other def is either defined in the loop
("vect_internal_def"), or it's an induction (defined by a
loop-header phi-node). */
if (def_stmt
&& gimple_bb (def_stmt)
&& flow_bb_inside_loop_p (loop, gimple_bb (def_stmt))
&& (is_gimple_assign (def_stmt)
|| is_gimple_call (def_stmt)
|| STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def_stmt))
== vect_induction_def
|| (gimple_code (def_stmt) == GIMPLE_PHI
&& STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def_stmt))
== vect_internal_def
&& !is_loop_header_bb_p (gimple_bb (def_stmt)))))
{
if (dump_enabled_p ())
{
dump_printf_loc (MSG_NOTE, vect_location, "swapping oprnds: ");
dump_gimple_stmt (MSG_NOTE, TDF_SLIM, next_stmt, 0);
dump_printf (MSG_NOTE, "\n");
}
swap_ssa_operands (next_stmt,
gimple_assign_rhs1_ptr (next_stmt),
gimple_assign_rhs2_ptr (next_stmt));
update_stmt (next_stmt);
if (CONSTANT_CLASS_P (gimple_assign_rhs1 (next_stmt)))
LOOP_VINFO_OPERANDS_SWAPPED (loop_info) = true;
}
else
return false;
}
lhs = gimple_assign_lhs (next_stmt);
next_stmt = GROUP_NEXT_ELEMENT (vinfo_for_stmt (next_stmt));
}
/* Save the chain for further analysis in SLP detection. */
first = GROUP_FIRST_ELEMENT (vinfo_for_stmt (current_stmt));
LOOP_VINFO_REDUCTION_CHAINS (loop_info).safe_push (first);
GROUP_SIZE (vinfo_for_stmt (first)) = size;
return true;
}
/* Function vect_is_simple_reduction_1
(1) Detect a cross-iteration def-use cycle that represents a simple
reduction computation. We look for the following pattern:
loop_header:
a1 = phi < a0, a2 >
a3 = ...
a2 = operation (a3, a1)
or
a3 = ...
loop_header:
a1 = phi < a0, a2 >
a2 = operation (a3, a1)
such that:
1. operation is commutative and associative and it is safe to
change the order of the computation (if CHECK_REDUCTION is true)
2. no uses for a2 in the loop (a2 is used out of the loop)
3. no uses of a1 in the loop besides the reduction operation
4. no uses of a1 outside the loop.
Conditions 1,4 are tested here.
Conditions 2,3 are tested in vect_mark_stmts_to_be_vectorized.
(2) Detect a cross-iteration def-use cycle in nested loops, i.e.,
nested cycles, if CHECK_REDUCTION is false.
(3) Detect cycles of phi nodes in outer-loop vectorization, i.e., double
reductions:
a1 = phi < a0, a2 >
inner loop (def of a3)
a2 = phi < a3 >
If MODIFY is true it tries also to rework the code in-place to enable
detection of more reduction patterns. For the time being we rewrite
"res -= RHS" into "rhs += -RHS" when it seems worthwhile.
*/
static gimple
vect_is_simple_reduction_1 (loop_vec_info loop_info, gimple phi,
bool check_reduction, bool *double_reduc,
bool modify)
{
struct loop *loop = (gimple_bb (phi))->loop_father;
struct loop *vect_loop = LOOP_VINFO_LOOP (loop_info);
edge latch_e = loop_latch_edge (loop);
tree loop_arg = PHI_ARG_DEF_FROM_EDGE (phi, latch_e);
gimple def_stmt, def1 = NULL, def2 = NULL;
enum tree_code orig_code, code;
tree op1, op2, op3 = NULL_TREE, op4 = NULL_TREE;
tree type;
int nloop_uses;
tree name;
imm_use_iterator imm_iter;
use_operand_p use_p;
bool phi_def;
*double_reduc = false;
/* If CHECK_REDUCTION is true, we assume inner-most loop vectorization,
otherwise, we assume outer loop vectorization. */
gcc_assert ((check_reduction && loop == vect_loop)
|| (!check_reduction && flow_loop_nested_p (vect_loop, loop)));
name = PHI_RESULT (phi);
/* ??? If there are no uses of the PHI result the inner loop reduction
won't be detected as possibly double-reduction by vectorizable_reduction
because that tries to walk the PHI arg from the preheader edge which
can be constant. See PR60382. */
if (has_zero_uses (name))
return NULL;
nloop_uses = 0;
FOR_EACH_IMM_USE_FAST (use_p, imm_iter, name)
{
gimple use_stmt = USE_STMT (use_p);
if (is_gimple_debug (use_stmt))
continue;
if (!flow_bb_inside_loop_p (loop, gimple_bb (use_stmt)))
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"intermediate value used outside loop.\n");
return NULL;
}
if (vinfo_for_stmt (use_stmt)
&& !is_pattern_stmt_p (vinfo_for_stmt (use_stmt)))
nloop_uses++;
if (nloop_uses > 1)
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"reduction used in loop.\n");
return NULL;
}
}
if (TREE_CODE (loop_arg) != SSA_NAME)
{
if (dump_enabled_p ())
{
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"reduction: not ssa_name: ");
dump_generic_expr (MSG_MISSED_OPTIMIZATION, TDF_SLIM, loop_arg);
dump_printf (MSG_MISSED_OPTIMIZATION, "\n");
}
return NULL;
}
def_stmt = SSA_NAME_DEF_STMT (loop_arg);
if (!def_stmt)
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"reduction: no def_stmt.\n");
return NULL;
}
if (!is_gimple_assign (def_stmt) && gimple_code (def_stmt) != GIMPLE_PHI)
{
if (dump_enabled_p ())
{
dump_gimple_stmt (MSG_NOTE, TDF_SLIM, def_stmt, 0);
dump_printf (MSG_NOTE, "\n");
}
return NULL;
}
if (is_gimple_assign (def_stmt))
{
name = gimple_assign_lhs (def_stmt);
phi_def = false;
}
else
{
name = PHI_RESULT (def_stmt);
phi_def = true;
}
nloop_uses = 0;
FOR_EACH_IMM_USE_FAST (use_p, imm_iter, name)
{
gimple use_stmt = USE_STMT (use_p);
if (is_gimple_debug (use_stmt))
continue;
if (flow_bb_inside_loop_p (loop, gimple_bb (use_stmt))
&& vinfo_for_stmt (use_stmt)
&& !is_pattern_stmt_p (vinfo_for_stmt (use_stmt)))
nloop_uses++;
if (nloop_uses > 1)
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"reduction used in loop.\n");
return NULL;
}
}
/* If DEF_STMT is a phi node itself, we expect it to have a single argument
defined in the inner loop. */
if (phi_def)
{
op1 = PHI_ARG_DEF (def_stmt, 0);
if (gimple_phi_num_args (def_stmt) != 1
|| TREE_CODE (op1) != SSA_NAME)
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"unsupported phi node definition.\n");
return NULL;
}
def1 = SSA_NAME_DEF_STMT (op1);
if (gimple_bb (def1)
&& flow_bb_inside_loop_p (loop, gimple_bb (def_stmt))
&& loop->inner
&& flow_bb_inside_loop_p (loop->inner, gimple_bb (def1))
&& is_gimple_assign (def1))
{
if (dump_enabled_p ())
report_vect_op (MSG_NOTE, def_stmt,
"detected double reduction: ");
*double_reduc = true;
return def_stmt;
}
return NULL;
}
code = orig_code = gimple_assign_rhs_code (def_stmt);
/* We can handle "res -= x[i]", which is non-associative by
simply rewriting this into "res += -x[i]". Avoid changing
gimple instruction for the first simple tests and only do this
if we're allowed to change code at all. */
if (code == MINUS_EXPR
&& modify
&& (op1 = gimple_assign_rhs1 (def_stmt))
&& TREE_CODE (op1) == SSA_NAME
&& SSA_NAME_DEF_STMT (op1) == phi)
code = PLUS_EXPR;
if (check_reduction
&& (!commutative_tree_code (code) || !associative_tree_code (code)))
{
if (dump_enabled_p ())
report_vect_op (MSG_MISSED_OPTIMIZATION, def_stmt,
"reduction: not commutative/associative: ");
return NULL;
}
if (get_gimple_rhs_class (code) != GIMPLE_BINARY_RHS)
{
if (code != COND_EXPR)
{
if (dump_enabled_p ())
report_vect_op (MSG_MISSED_OPTIMIZATION, def_stmt,
"reduction: not binary operation: ");
return NULL;
}
op3 = gimple_assign_rhs1 (def_stmt);
if (COMPARISON_CLASS_P (op3))
{
op4 = TREE_OPERAND (op3, 1);
op3 = TREE_OPERAND (op3, 0);
}
op1 = gimple_assign_rhs2 (def_stmt);
op2 = gimple_assign_rhs3 (def_stmt);
if (TREE_CODE (op1) != SSA_NAME && TREE_CODE (op2) != SSA_NAME)
{
if (dump_enabled_p ())
report_vect_op (MSG_MISSED_OPTIMIZATION, def_stmt,
"reduction: uses not ssa_names: ");
return NULL;
}
}
else
{
op1 = gimple_assign_rhs1 (def_stmt);
op2 = gimple_assign_rhs2 (def_stmt);
if (TREE_CODE (op1) != SSA_NAME && TREE_CODE (op2) != SSA_NAME)
{
if (dump_enabled_p ())
report_vect_op (MSG_MISSED_OPTIMIZATION, def_stmt,
"reduction: uses not ssa_names: ");
return NULL;
}
}
type = TREE_TYPE (gimple_assign_lhs (def_stmt));
if ((TREE_CODE (op1) == SSA_NAME
&& !types_compatible_p (type,TREE_TYPE (op1)))
|| (TREE_CODE (op2) == SSA_NAME
&& !types_compatible_p (type, TREE_TYPE (op2)))
|| (op3 && TREE_CODE (op3) == SSA_NAME
&& !types_compatible_p (type, TREE_TYPE (op3)))
|| (op4 && TREE_CODE (op4) == SSA_NAME
&& !types_compatible_p (type, TREE_TYPE (op4))))
{
if (dump_enabled_p ())
{
dump_printf_loc (MSG_NOTE, vect_location,
"reduction: multiple types: operation type: ");
dump_generic_expr (MSG_NOTE, TDF_SLIM, type);
dump_printf (MSG_NOTE, ", operands types: ");
dump_generic_expr (MSG_NOTE, TDF_SLIM,
TREE_TYPE (op1));
dump_printf (MSG_NOTE, ",");
dump_generic_expr (MSG_NOTE, TDF_SLIM,
TREE_TYPE (op2));
if (op3)
{
dump_printf (MSG_NOTE, ",");
dump_generic_expr (MSG_NOTE, TDF_SLIM,
TREE_TYPE (op3));
}
if (op4)
{
dump_printf (MSG_NOTE, ",");
dump_generic_expr (MSG_NOTE, TDF_SLIM,
TREE_TYPE (op4));
}
dump_printf (MSG_NOTE, "\n");
}
return NULL;
}
/* Check that it's ok to change the order of the computation.
Generally, when vectorizing a reduction we change the order of the
computation. This may change the behavior of the program in some
cases, so we need to check that this is ok. One exception is when
vectorizing an outer-loop: the inner-loop is executed sequentially,
and therefore vectorizing reductions in the inner-loop during
outer-loop vectorization is safe. */
/* CHECKME: check for !flag_finite_math_only too? */
if (SCALAR_FLOAT_TYPE_P (type) && !flag_associative_math
&& check_reduction)
{
/* Changing the order of operations changes the semantics. */
if (dump_enabled_p ())
report_vect_op (MSG_MISSED_OPTIMIZATION, def_stmt,
"reduction: unsafe fp math optimization: ");
return NULL;
}
else if (INTEGRAL_TYPE_P (type) && TYPE_OVERFLOW_TRAPS (type)
&& check_reduction)
{
/* Changing the order of operations changes the semantics. */
if (dump_enabled_p ())
report_vect_op (MSG_MISSED_OPTIMIZATION, def_stmt,
"reduction: unsafe int math optimization: ");
return NULL;
}
else if (SAT_FIXED_POINT_TYPE_P (type) && check_reduction)
{
/* Changing the order of operations changes the semantics. */
if (dump_enabled_p ())
report_vect_op (MSG_MISSED_OPTIMIZATION, def_stmt,
"reduction: unsafe fixed-point math optimization: ");
return NULL;
}
/* If we detected "res -= x[i]" earlier, rewrite it into
"res += -x[i]" now. If this turns out to be useless reassoc
will clean it up again. */
if (orig_code == MINUS_EXPR)
{
tree rhs = gimple_assign_rhs2 (def_stmt);
tree negrhs = make_ssa_name (TREE_TYPE (rhs));
gimple negate_stmt = gimple_build_assign (negrhs, NEGATE_EXPR, rhs);
gimple_stmt_iterator gsi = gsi_for_stmt (def_stmt);
set_vinfo_for_stmt (negate_stmt, new_stmt_vec_info (negate_stmt,
loop_info, NULL));
gsi_insert_before (&gsi, negate_stmt, GSI_NEW_STMT);
gimple_assign_set_rhs2 (def_stmt, negrhs);
gimple_assign_set_rhs_code (def_stmt, PLUS_EXPR);
update_stmt (def_stmt);
}
/* Reduction is safe. We're dealing with one of the following:
1) integer arithmetic and no trapv
2) floating point arithmetic, and special flags permit this optimization
3) nested cycle (i.e., outer loop vectorization). */
if (TREE_CODE (op1) == SSA_NAME)
def1 = SSA_NAME_DEF_STMT (op1);
if (TREE_CODE (op2) == SSA_NAME)
def2 = SSA_NAME_DEF_STMT (op2);
if (code != COND_EXPR
&& ((!def1 || gimple_nop_p (def1)) && (!def2 || gimple_nop_p (def2))))
{
if (dump_enabled_p ())
report_vect_op (MSG_NOTE, def_stmt, "reduction: no defs for operands: ");
return NULL;
}
/* Check that one def is the reduction def, defined by PHI,
the other def is either defined in the loop ("vect_internal_def"),
or it's an induction (defined by a loop-header phi-node). */
if (def2 && def2 == phi
&& (code == COND_EXPR
|| !def1 || gimple_nop_p (def1)
|| !flow_bb_inside_loop_p (loop, gimple_bb (def1))
|| (def1 && flow_bb_inside_loop_p (loop, gimple_bb (def1))
&& (is_gimple_assign (def1)
|| is_gimple_call (def1)
|| STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def1))
== vect_induction_def
|| (gimple_code (def1) == GIMPLE_PHI
&& STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def1))
== vect_internal_def
&& !is_loop_header_bb_p (gimple_bb (def1)))))))
{
if (dump_enabled_p ())
report_vect_op (MSG_NOTE, def_stmt, "detected reduction: ");
return def_stmt;
}
if (def1 && def1 == phi
&& (code == COND_EXPR
|| !def2 || gimple_nop_p (def2)
|| !flow_bb_inside_loop_p (loop, gimple_bb (def2))
|| (def2 && flow_bb_inside_loop_p (loop, gimple_bb (def2))
&& (is_gimple_assign (def2)
|| is_gimple_call (def2)
|| STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def2))
== vect_induction_def
|| (gimple_code (def2) == GIMPLE_PHI
&& STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def2))
== vect_internal_def
&& !is_loop_header_bb_p (gimple_bb (def2)))))))
{
if (check_reduction)
{
/* Swap operands (just for simplicity - so that the rest of the code
can assume that the reduction variable is always the last (second)
argument). */
if (dump_enabled_p ())
report_vect_op (MSG_NOTE, def_stmt,
"detected reduction: need to swap operands: ");
swap_ssa_operands (def_stmt, gimple_assign_rhs1_ptr (def_stmt),
gimple_assign_rhs2_ptr (def_stmt));
if (CONSTANT_CLASS_P (gimple_assign_rhs1 (def_stmt)))
LOOP_VINFO_OPERANDS_SWAPPED (loop_info) = true;
}
else
{
if (dump_enabled_p ())
report_vect_op (MSG_NOTE, def_stmt, "detected reduction: ");
}
return def_stmt;
}
/* Try to find SLP reduction chain. */
if (check_reduction && vect_is_slp_reduction (loop_info, phi, def_stmt))
{
if (dump_enabled_p ())
report_vect_op (MSG_NOTE, def_stmt,
"reduction: detected reduction chain: ");
return def_stmt;
}
if (dump_enabled_p ())
report_vect_op (MSG_MISSED_OPTIMIZATION, def_stmt,
"reduction: unknown pattern: ");
return NULL;
}
/* Wrapper around vect_is_simple_reduction_1, that won't modify code
in-place. Arguments as there. */
static gimple
vect_is_simple_reduction (loop_vec_info loop_info, gimple phi,
bool check_reduction, bool *double_reduc)
{
return vect_is_simple_reduction_1 (loop_info, phi, check_reduction,
double_reduc, false);
}
/* Wrapper around vect_is_simple_reduction_1, which will modify code
in-place if it enables detection of more reductions. Arguments
as there. */
gimple
vect_force_simple_reduction (loop_vec_info loop_info, gimple phi,
bool check_reduction, bool *double_reduc)
{
return vect_is_simple_reduction_1 (loop_info, phi, check_reduction,
double_reduc, true);
}
/* Calculate the cost of one scalar iteration of the loop. */
int
vect_get_single_scalar_iteration_cost (loop_vec_info loop_vinfo,
stmt_vector_for_cost *scalar_cost_vec)
{
struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
basic_block *bbs = LOOP_VINFO_BBS (loop_vinfo);
int nbbs = loop->num_nodes, factor, scalar_single_iter_cost = 0;
int innerloop_iters, i;
/* Count statements in scalar loop. Using this as scalar cost for a single
iteration for now.
TODO: Add outer loop support.
TODO: Consider assigning different costs to different scalar
statements. */
/* FORNOW. */
innerloop_iters = 1;
if (loop->inner)
innerloop_iters = 50; /* FIXME */
for (i = 0; i < nbbs; i++)
{
gimple_stmt_iterator si;
basic_block bb = bbs[i];
if (bb->loop_father == loop->inner)
factor = innerloop_iters;
else
factor = 1;
for (si = gsi_start_bb (bb); !gsi_end_p (si); gsi_next (&si))
{
gimple stmt = gsi_stmt (si);
stmt_vec_info stmt_info = vinfo_for_stmt (stmt);
if (!is_gimple_assign (stmt) && !is_gimple_call (stmt))
continue;
/* Skip stmts that are not vectorized inside the loop. */
if (stmt_info
&& !STMT_VINFO_RELEVANT_P (stmt_info)
&& (!STMT_VINFO_LIVE_P (stmt_info)
|| !VECTORIZABLE_CYCLE_DEF (STMT_VINFO_DEF_TYPE (stmt_info)))
&& !STMT_VINFO_IN_PATTERN_P (stmt_info))
continue;
vect_cost_for_stmt kind;
if (STMT_VINFO_DATA_REF (vinfo_for_stmt (stmt)))
{
if (DR_IS_READ (STMT_VINFO_DATA_REF (vinfo_for_stmt (stmt))))
kind = scalar_load;
else
kind = scalar_store;
}
else
kind = scalar_stmt;
scalar_single_iter_cost
+= record_stmt_cost (scalar_cost_vec, factor, kind,
NULL, 0, vect_prologue);
}
}
return scalar_single_iter_cost;
}
/* Calculate cost of peeling the loop PEEL_ITERS_PROLOGUE times. */
int
vect_get_known_peeling_cost (loop_vec_info loop_vinfo, int peel_iters_prologue,
int *peel_iters_epilogue,
stmt_vector_for_cost *scalar_cost_vec,
stmt_vector_for_cost *prologue_cost_vec,
stmt_vector_for_cost *epilogue_cost_vec)
{
int retval = 0;
int vf = LOOP_VINFO_VECT_FACTOR (loop_vinfo);
if (!LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo))
{
*peel_iters_epilogue = vf/2;
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"cost model: epilogue peel iters set to vf/2 "
"because loop iterations are unknown .\n");
/* If peeled iterations are known but number of scalar loop
iterations are unknown, count a taken branch per peeled loop. */
retval = record_stmt_cost (prologue_cost_vec, 1, cond_branch_taken,
NULL, 0, vect_prologue);
retval = record_stmt_cost (prologue_cost_vec, 1, cond_branch_taken,
NULL, 0, vect_epilogue);
}
else
{
int niters = LOOP_VINFO_INT_NITERS (loop_vinfo);
peel_iters_prologue = niters < peel_iters_prologue ?
niters : peel_iters_prologue;
*peel_iters_epilogue = (niters - peel_iters_prologue) % vf;
/* If we need to peel for gaps, but no peeling is required, we have to
peel VF iterations. */
if (LOOP_VINFO_PEELING_FOR_GAPS (loop_vinfo) && !*peel_iters_epilogue)
*peel_iters_epilogue = vf;
}
stmt_info_for_cost *si;
int j;
if (peel_iters_prologue)
FOR_EACH_VEC_ELT (*scalar_cost_vec, j, si)
retval += record_stmt_cost (prologue_cost_vec,
si->count * peel_iters_prologue,
si->kind, NULL, si->misalign,
vect_prologue);
if (*peel_iters_epilogue)
FOR_EACH_VEC_ELT (*scalar_cost_vec, j, si)
retval += record_stmt_cost (epilogue_cost_vec,
si->count * *peel_iters_epilogue,
si->kind, NULL, si->misalign,
vect_epilogue);
return retval;
}
/* Function vect_estimate_min_profitable_iters
Return the number of iterations required for the vector version of the
loop to be profitable relative to the cost of the scalar version of the
loop. */
static void
vect_estimate_min_profitable_iters (loop_vec_info loop_vinfo,
int *ret_min_profitable_niters,
int *ret_min_profitable_estimate)
{
int min_profitable_iters;
int min_profitable_estimate;
int peel_iters_prologue;
int peel_iters_epilogue;
unsigned vec_inside_cost = 0;
int vec_outside_cost = 0;
unsigned vec_prologue_cost = 0;
unsigned vec_epilogue_cost = 0;
int scalar_single_iter_cost = 0;
int scalar_outside_cost = 0;
int vf = LOOP_VINFO_VECT_FACTOR (loop_vinfo);
int npeel = LOOP_VINFO_PEELING_FOR_ALIGNMENT (loop_vinfo);
void *target_cost_data = LOOP_VINFO_TARGET_COST_DATA (loop_vinfo);
/* Cost model disabled. */
if (unlimited_cost_model (LOOP_VINFO_LOOP (loop_vinfo)))
{
dump_printf_loc (MSG_NOTE, vect_location, "cost model disabled.\n");
*ret_min_profitable_niters = 0;
*ret_min_profitable_estimate = 0;
return;
}
/* Requires loop versioning tests to handle misalignment. */
if (LOOP_REQUIRES_VERSIONING_FOR_ALIGNMENT (loop_vinfo))
{
/* FIXME: Make cost depend on complexity of individual check. */
unsigned len = LOOP_VINFO_MAY_MISALIGN_STMTS (loop_vinfo).length ();
(void) add_stmt_cost (target_cost_data, len, vector_stmt, NULL, 0,
vect_prologue);
dump_printf (MSG_NOTE,
"cost model: Adding cost of checks for loop "
"versioning to treat misalignment.\n");
}
/* Requires loop versioning with alias checks. */
if (LOOP_REQUIRES_VERSIONING_FOR_ALIAS (loop_vinfo))
{
/* FIXME: Make cost depend on complexity of individual check. */
unsigned len = LOOP_VINFO_COMP_ALIAS_DDRS (loop_vinfo).length ();
(void) add_stmt_cost (target_cost_data, len, vector_stmt, NULL, 0,
vect_prologue);
dump_printf (MSG_NOTE,
"cost model: Adding cost of checks for loop "
"versioning aliasing.\n");
}
if (LOOP_REQUIRES_VERSIONING_FOR_ALIGNMENT (loop_vinfo)
|| LOOP_REQUIRES_VERSIONING_FOR_ALIAS (loop_vinfo))
(void) add_stmt_cost (target_cost_data, 1, cond_branch_taken, NULL, 0,
vect_prologue);
/* Count statements in scalar loop. Using this as scalar cost for a single
iteration for now.
TODO: Add outer loop support.
TODO: Consider assigning different costs to different scalar
statements. */
auto_vec<stmt_info_for_cost> scalar_cost_vec;
scalar_single_iter_cost
= vect_get_single_scalar_iteration_cost (loop_vinfo, &scalar_cost_vec);
/* Add additional cost for the peeled instructions in prologue and epilogue
loop.
FORNOW: If we don't know the value of peel_iters for prologue or epilogue
at compile-time - we assume it's vf/2 (the worst would be vf-1).
TODO: Build an expression that represents peel_iters for prologue and
epilogue to be used in a run-time test. */
if (npeel < 0)
{
peel_iters_prologue = vf/2;
dump_printf (MSG_NOTE, "cost model: "
"prologue peel iters set to vf/2.\n");
/* If peeling for alignment is unknown, loop bound of main loop becomes
unknown. */
peel_iters_epilogue = vf/2;
dump_printf (MSG_NOTE, "cost model: "
"epilogue peel iters set to vf/2 because "
"peeling for alignment is unknown.\n");
/* If peeled iterations are unknown, count a taken branch and a not taken
branch per peeled loop. Even if scalar loop iterations are known,
vector iterations are not known since peeled prologue iterations are
not known. Hence guards remain the same. */
(void) add_stmt_cost (target_cost_data, 1, cond_branch_taken,
NULL, 0, vect_prologue);
(void) add_stmt_cost (target_cost_data, 1, cond_branch_not_taken,
NULL, 0, vect_prologue);
(void) add_stmt_cost (target_cost_data, 1, cond_branch_taken,
NULL, 0, vect_epilogue);
(void) add_stmt_cost (target_cost_data, 1, cond_branch_not_taken,
NULL, 0, vect_epilogue);
stmt_info_for_cost *si;
int j;
FOR_EACH_VEC_ELT (scalar_cost_vec, j, si)
{
struct _stmt_vec_info *stmt_info
= si->stmt ? vinfo_for_stmt (si->stmt) : NULL;
(void) add_stmt_cost (target_cost_data,
si->count * peel_iters_prologue,
si->kind, stmt_info, si->misalign,
vect_prologue);
(void) add_stmt_cost (target_cost_data,
si->count * peel_iters_epilogue,
si->kind, stmt_info, si->misalign,
vect_epilogue);
}
}
else
{
stmt_vector_for_cost prologue_cost_vec, epilogue_cost_vec;
stmt_info_for_cost *si;
int j;
void *data = LOOP_VINFO_TARGET_COST_DATA (loop_vinfo);
prologue_cost_vec.create (2);
epilogue_cost_vec.create (2);
peel_iters_prologue = npeel;
(void) vect_get_known_peeling_cost (loop_vinfo, peel_iters_prologue,
&peel_iters_epilogue,
&scalar_cost_vec,
&prologue_cost_vec,
&epilogue_cost_vec);
FOR_EACH_VEC_ELT (prologue_cost_vec, j, si)
{
struct _stmt_vec_info *stmt_info
= si->stmt ? vinfo_for_stmt (si->stmt) : NULL;
(void) add_stmt_cost (data, si->count, si->kind, stmt_info,
si->misalign, vect_prologue);
}
FOR_EACH_VEC_ELT (epilogue_cost_vec, j, si)
{
struct _stmt_vec_info *stmt_info
= si->stmt ? vinfo_for_stmt (si->stmt) : NULL;
(void) add_stmt_cost (data, si->count, si->kind, stmt_info,
si->misalign, vect_epilogue);
}
prologue_cost_vec.release ();
epilogue_cost_vec.release ();
}
/* FORNOW: The scalar outside cost is incremented in one of the
following ways:
1. The vectorizer checks for alignment and aliasing and generates
a condition that allows dynamic vectorization. A cost model
check is ANDED with the versioning condition. Hence scalar code
path now has the added cost of the versioning check.
if (cost > th & versioning_check)
jmp to vector code
Hence run-time scalar is incremented by not-taken branch cost.
2. The vectorizer then checks if a prologue is required. If the
cost model check was not done before during versioning, it has to
be done before the prologue check.
if (cost <= th)
prologue = scalar_iters
if (prologue == 0)
jmp to vector code
else
execute prologue
if (prologue == num_iters)
go to exit
Hence the run-time scalar cost is incremented by a taken branch,
plus a not-taken branch, plus a taken branch cost.
3. The vectorizer then checks if an epilogue is required. If the
cost model check was not done before during prologue check, it
has to be done with the epilogue check.
if (prologue == 0)
jmp to vector code
else
execute prologue
if (prologue == num_iters)
go to exit
vector code:
if ((cost <= th) | (scalar_iters-prologue-epilogue == 0))
jmp to epilogue
Hence the run-time scalar cost should be incremented by 2 taken
branches.
TODO: The back end may reorder the BBS's differently and reverse
conditions/branch directions. Change the estimates below to
something more reasonable. */
/* If the number of iterations is known and we do not do versioning, we can
decide whether to vectorize at compile time. Hence the scalar version
do not carry cost model guard costs. */
if (!LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo)
|| LOOP_REQUIRES_VERSIONING_FOR_ALIGNMENT (loop_vinfo)
|| LOOP_REQUIRES_VERSIONING_FOR_ALIAS (loop_vinfo))
{
/* Cost model check occurs at versioning. */
if (LOOP_REQUIRES_VERSIONING_FOR_ALIGNMENT (loop_vinfo)
|| LOOP_REQUIRES_VERSIONING_FOR_ALIAS (loop_vinfo))
scalar_outside_cost += vect_get_stmt_cost (cond_branch_not_taken);
else
{
/* Cost model check occurs at prologue generation. */
if (LOOP_VINFO_PEELING_FOR_ALIGNMENT (loop_vinfo) < 0)
scalar_outside_cost += 2 * vect_get_stmt_cost (cond_branch_taken)
+ vect_get_stmt_cost (cond_branch_not_taken);
/* Cost model check occurs at epilogue generation. */
else
scalar_outside_cost += 2 * vect_get_stmt_cost (cond_branch_taken);
}
}
/* Complete the target-specific cost calculations. */
finish_cost (LOOP_VINFO_TARGET_COST_DATA (loop_vinfo), &vec_prologue_cost,
&vec_inside_cost, &vec_epilogue_cost);
vec_outside_cost = (int)(vec_prologue_cost + vec_epilogue_cost);
if (dump_enabled_p ())
{
dump_printf_loc (MSG_NOTE, vect_location, "Cost model analysis: \n");
dump_printf (MSG_NOTE, " Vector inside of loop cost: %d\n",
vec_inside_cost);
dump_printf (MSG_NOTE, " Vector prologue cost: %d\n",
vec_prologue_cost);
dump_printf (MSG_NOTE, " Vector epilogue cost: %d\n",
vec_epilogue_cost);
dump_printf (MSG_NOTE, " Scalar iteration cost: %d\n",
scalar_single_iter_cost);
dump_printf (MSG_NOTE, " Scalar outside cost: %d\n",
scalar_outside_cost);
dump_printf (MSG_NOTE, " Vector outside cost: %d\n",
vec_outside_cost);
dump_printf (MSG_NOTE, " prologue iterations: %d\n",
peel_iters_prologue);
dump_printf (MSG_NOTE, " epilogue iterations: %d\n",
peel_iters_epilogue);
}
/* Calculate number of iterations required to make the vector version
profitable, relative to the loop bodies only. The following condition
must hold true:
SIC * niters + SOC > VIC * ((niters-PL_ITERS-EP_ITERS)/VF) + VOC
where
SIC = scalar iteration cost, VIC = vector iteration cost,
VOC = vector outside cost, VF = vectorization factor,
PL_ITERS = prologue iterations, EP_ITERS= epilogue iterations
SOC = scalar outside cost for run time cost model check. */
if ((scalar_single_iter_cost * vf) > (int) vec_inside_cost)
{
if (vec_outside_cost <= 0)
min_profitable_iters = 1;
else
{
min_profitable_iters = ((vec_outside_cost - scalar_outside_cost) * vf
- vec_inside_cost * peel_iters_prologue
- vec_inside_cost * peel_iters_epilogue)
/ ((scalar_single_iter_cost * vf)
- vec_inside_cost);
if ((scalar_single_iter_cost * vf * min_profitable_iters)
<= (((int) vec_inside_cost * min_profitable_iters)
+ (((int) vec_outside_cost - scalar_outside_cost) * vf)))
min_profitable_iters++;
}
}
/* vector version will never be profitable. */
else
{
if (LOOP_VINFO_LOOP (loop_vinfo)->force_vectorize)
warning_at (vect_location, OPT_Wopenmp_simd, "vectorization "
"did not happen for a simd loop");
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"cost model: the vector iteration cost = %d "
"divided by the scalar iteration cost = %d "
"is greater or equal to the vectorization factor = %d"
".\n",
vec_inside_cost, scalar_single_iter_cost, vf);
*ret_min_profitable_niters = -1;
*ret_min_profitable_estimate = -1;
return;
}
dump_printf (MSG_NOTE,
" Calculated minimum iters for profitability: %d\n",
min_profitable_iters);
min_profitable_iters =
min_profitable_iters < vf ? vf : min_profitable_iters;
/* Because the condition we create is:
if (niters <= min_profitable_iters)
then skip the vectorized loop. */
min_profitable_iters--;
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
" Runtime profitability threshold = %d\n",
min_profitable_iters);
*ret_min_profitable_niters = min_profitable_iters;
/* Calculate number of iterations required to make the vector version
profitable, relative to the loop bodies only.
Non-vectorized variant is SIC * niters and it must win over vector
variant on the expected loop trip count. The following condition must hold true:
SIC * niters > VIC * ((niters-PL_ITERS-EP_ITERS)/VF) + VOC + SOC */
if (vec_outside_cost <= 0)
min_profitable_estimate = 1;
else
{
min_profitable_estimate = ((vec_outside_cost + scalar_outside_cost) * vf
- vec_inside_cost * peel_iters_prologue
- vec_inside_cost * peel_iters_epilogue)
/ ((scalar_single_iter_cost * vf)
- vec_inside_cost);
}
min_profitable_estimate --;
min_profitable_estimate = MAX (min_profitable_estimate, min_profitable_iters);
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
" Static estimate profitability threshold = %d\n",
min_profitable_iters);
*ret_min_profitable_estimate = min_profitable_estimate;
}
/* Writes into SEL a mask for a vec_perm, equivalent to a vec_shr by OFFSET
vector elements (not bits) for a vector of mode MODE. */
static void
calc_vec_perm_mask_for_shift (enum machine_mode mode, unsigned int offset,
unsigned char *sel)
{
unsigned int i, nelt = GET_MODE_NUNITS (mode);
for (i = 0; i < nelt; i++)
sel[i] = (i + offset) & (2*nelt - 1);
}
/* Checks whether the target supports whole-vector shifts for vectors of mode
MODE. This is the case if _either_ the platform handles vec_shr_optab, _or_
it supports vec_perm_const with masks for all necessary shift amounts. */
static bool
have_whole_vector_shift (enum machine_mode mode)
{
if (optab_handler (vec_shr_optab, mode) != CODE_FOR_nothing)
return true;
if (direct_optab_handler (vec_perm_const_optab, mode) == CODE_FOR_nothing)
return false;
unsigned int i, nelt = GET_MODE_NUNITS (mode);
unsigned char *sel = XALLOCAVEC (unsigned char, nelt);
for (i = nelt/2; i >= 1; i/=2)
{
calc_vec_perm_mask_for_shift (mode, i, sel);
if (!can_vec_perm_p (mode, false, sel))
return false;
}
return true;
}
/* TODO: Close dependency between vect_model_*_cost and vectorizable_*
functions. Design better to avoid maintenance issues. */
/* Function vect_model_reduction_cost.
Models cost for a reduction operation, including the vector ops
generated within the strip-mine loop, the initial definition before
the loop, and the epilogue code that must be generated. */
static bool
vect_model_reduction_cost (stmt_vec_info stmt_info, enum tree_code reduc_code,
int ncopies)
{
int prologue_cost = 0, epilogue_cost = 0;
enum tree_code code;
optab optab;
tree vectype;
gimple stmt, orig_stmt;
tree reduction_op;
machine_mode mode;
loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info);
struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
void *target_cost_data = LOOP_VINFO_TARGET_COST_DATA (loop_vinfo);
/* Cost of reduction op inside loop. */
unsigned inside_cost = add_stmt_cost (target_cost_data, ncopies, vector_stmt,
stmt_info, 0, vect_body);
stmt = STMT_VINFO_STMT (stmt_info);
switch (get_gimple_rhs_class (gimple_assign_rhs_code (stmt)))
{
case GIMPLE_SINGLE_RHS:
gcc_assert (TREE_OPERAND_LENGTH (gimple_assign_rhs1 (stmt)) == ternary_op);
reduction_op = TREE_OPERAND (gimple_assign_rhs1 (stmt), 2);
break;
case GIMPLE_UNARY_RHS:
reduction_op = gimple_assign_rhs1 (stmt);
break;
case GIMPLE_BINARY_RHS:
reduction_op = gimple_assign_rhs2 (stmt);
break;
case GIMPLE_TERNARY_RHS:
reduction_op = gimple_assign_rhs3 (stmt);
break;
default:
gcc_unreachable ();
}
vectype = get_vectype_for_scalar_type (TREE_TYPE (reduction_op));
if (!vectype)
{
if (dump_enabled_p ())
{
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"unsupported data-type ");
dump_generic_expr (MSG_MISSED_OPTIMIZATION, TDF_SLIM,
TREE_TYPE (reduction_op));
dump_printf (MSG_MISSED_OPTIMIZATION, "\n");
}
return false;
}
mode = TYPE_MODE (vectype);
orig_stmt = STMT_VINFO_RELATED_STMT (stmt_info);
if (!orig_stmt)
orig_stmt = STMT_VINFO_STMT (stmt_info);
code = gimple_assign_rhs_code (orig_stmt);
/* Add in cost for initial definition. */
prologue_cost += add_stmt_cost (target_cost_data, 1, scalar_to_vec,
stmt_info, 0, vect_prologue);
/* Determine cost of epilogue code.
We have a reduction operator that will reduce the vector in one statement.
Also requires scalar extract. */
if (!nested_in_vect_loop_p (loop, orig_stmt))
{
if (reduc_code != ERROR_MARK)
{
epilogue_cost += add_stmt_cost (target_cost_data, 1, vector_stmt,
stmt_info, 0, vect_epilogue);
epilogue_cost += add_stmt_cost (target_cost_data, 1, vec_to_scalar,
stmt_info, 0, vect_epilogue);
}
else
{
int vec_size_in_bits = tree_to_uhwi (TYPE_SIZE (vectype));
tree bitsize =
TYPE_SIZE (TREE_TYPE (gimple_assign_lhs (orig_stmt)));
int element_bitsize = tree_to_uhwi (bitsize);
int nelements = vec_size_in_bits / element_bitsize;
optab = optab_for_tree_code (code, vectype, optab_default);
/* We have a whole vector shift available. */
if (VECTOR_MODE_P (mode)
&& optab_handler (optab, mode) != CODE_FOR_nothing
&& have_whole_vector_shift (mode))
{
/* Final reduction via vector shifts and the reduction operator.
Also requires scalar extract. */
epilogue_cost += add_stmt_cost (target_cost_data,
exact_log2 (nelements) * 2,
vector_stmt, stmt_info, 0,
vect_epilogue);
epilogue_cost += add_stmt_cost (target_cost_data, 1,
vec_to_scalar, stmt_info, 0,
vect_epilogue);
}
else
/* Use extracts and reduction op for final reduction. For N
elements, we have N extracts and N-1 reduction ops. */
epilogue_cost += add_stmt_cost (target_cost_data,
nelements + nelements - 1,
vector_stmt, stmt_info, 0,
vect_epilogue);
}
}
if (dump_enabled_p ())
dump_printf (MSG_NOTE,
"vect_model_reduction_cost: inside_cost = %d, "
"prologue_cost = %d, epilogue_cost = %d .\n", inside_cost,
prologue_cost, epilogue_cost);
return true;
}
/* Function vect_model_induction_cost.
Models cost for induction operations. */
static void
vect_model_induction_cost (stmt_vec_info stmt_info, int ncopies)
{
loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info);
void *target_cost_data = LOOP_VINFO_TARGET_COST_DATA (loop_vinfo);
unsigned inside_cost, prologue_cost;
/* loop cost for vec_loop. */
inside_cost = add_stmt_cost (target_cost_data, ncopies, vector_stmt,
stmt_info, 0, vect_body);
/* prologue cost for vec_init and vec_step. */
prologue_cost = add_stmt_cost (target_cost_data, 2, scalar_to_vec,
stmt_info, 0, vect_prologue);
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"vect_model_induction_cost: inside_cost = %d, "
"prologue_cost = %d .\n", inside_cost, prologue_cost);
}
/* Function get_initial_def_for_induction
Input:
STMT - a stmt that performs an induction operation in the loop.
IV_PHI - the initial value of the induction variable
Output:
Return a vector variable, initialized with the first VF values of
the induction variable. E.g., for an iv with IV_PHI='X' and
evolution S, for a vector of 4 units, we want to return:
[X, X + S, X + 2*S, X + 3*S]. */
static tree
get_initial_def_for_induction (gimple iv_phi)
{
stmt_vec_info stmt_vinfo = vinfo_for_stmt (iv_phi);
loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_vinfo);
struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
tree vectype;
int nunits;
edge pe = loop_preheader_edge (loop);
struct loop *iv_loop;
basic_block new_bb;
tree new_vec, vec_init, vec_step, t;
tree new_var;
tree new_name;
gimple init_stmt, new_stmt;
gphi *induction_phi;
tree induc_def, vec_def, vec_dest;
tree init_expr, step_expr;
int vf = LOOP_VINFO_VECT_FACTOR (loop_vinfo);
int i;
int ncopies;
tree expr;
stmt_vec_info phi_info = vinfo_for_stmt (iv_phi);
bool nested_in_vect_loop = false;
gimple_seq stmts = NULL;
imm_use_iterator imm_iter;
use_operand_p use_p;
gimple exit_phi;
edge latch_e;
tree loop_arg;
gimple_stmt_iterator si;
basic_block bb = gimple_bb (iv_phi);
tree stepvectype;
tree resvectype;
/* Is phi in an inner-loop, while vectorizing an enclosing outer-loop? */
if (nested_in_vect_loop_p (loop, iv_phi))
{
nested_in_vect_loop = true;
iv_loop = loop->inner;
}
else
iv_loop = loop;
gcc_assert (iv_loop == (gimple_bb (iv_phi))->loop_father);
latch_e = loop_latch_edge (iv_loop);
loop_arg = PHI_ARG_DEF_FROM_EDGE (iv_phi, latch_e);
step_expr = STMT_VINFO_LOOP_PHI_EVOLUTION_PART (phi_info);
gcc_assert (step_expr != NULL_TREE);
pe = loop_preheader_edge (iv_loop);
init_expr = PHI_ARG_DEF_FROM_EDGE (iv_phi,
loop_preheader_edge (iv_loop));
vectype = get_vectype_for_scalar_type (TREE_TYPE (init_expr));
resvectype = get_vectype_for_scalar_type (TREE_TYPE (PHI_RESULT (iv_phi)));
gcc_assert (vectype);
nunits = TYPE_VECTOR_SUBPARTS (vectype);
ncopies = vf / nunits;
gcc_assert (phi_info);
gcc_assert (ncopies >= 1);
/* Convert the step to the desired type. */
step_expr = force_gimple_operand (fold_convert (TREE_TYPE (vectype),
step_expr),
&stmts, true, NULL_TREE);
if (stmts)
{
new_bb = gsi_insert_seq_on_edge_immediate (pe, stmts);
gcc_assert (!new_bb);
}
/* Find the first insertion point in the BB. */
si = gsi_after_labels (bb);
/* Create the vector that holds the initial_value of the induction. */
if (nested_in_vect_loop)
{
/* iv_loop is nested in the loop to be vectorized. init_expr had already
been created during vectorization of previous stmts. We obtain it
from the STMT_VINFO_VEC_STMT of the defining stmt. */
vec_init = vect_get_vec_def_for_operand (init_expr, iv_phi, NULL);
/* If the initial value is not of proper type, convert it. */
if (!useless_type_conversion_p (vectype, TREE_TYPE (vec_init)))
{
new_stmt
= gimple_build_assign (vect_get_new_vect_var (vectype,
vect_simple_var,
"vec_iv_"),
VIEW_CONVERT_EXPR,
build1 (VIEW_CONVERT_EXPR, vectype,
vec_init));
vec_init = make_ssa_name (gimple_assign_lhs (new_stmt), new_stmt);
gimple_assign_set_lhs (new_stmt, vec_init);
new_bb = gsi_insert_on_edge_immediate (loop_preheader_edge (iv_loop),
new_stmt);
gcc_assert (!new_bb);
set_vinfo_for_stmt (new_stmt,
new_stmt_vec_info (new_stmt, loop_vinfo, NULL));
}
}
else
{
vec<constructor_elt, va_gc> *v;
/* iv_loop is the loop to be vectorized. Create:
vec_init = [X, X+S, X+2*S, X+3*S] (S = step_expr, X = init_expr) */
new_var = vect_get_new_vect_var (TREE_TYPE (vectype),
vect_scalar_var, "var_");
new_name = force_gimple_operand (fold_convert (TREE_TYPE (vectype),
init_expr),
&stmts, false, new_var);
if (stmts)
{
new_bb = gsi_insert_seq_on_edge_immediate (pe, stmts);
gcc_assert (!new_bb);
}
vec_alloc (v, nunits);
bool constant_p = is_gimple_min_invariant (new_name);
CONSTRUCTOR_APPEND_ELT (v, NULL_TREE, new_name);
for (i = 1; i < nunits; i++)
{
/* Create: new_name_i = new_name + step_expr */
new_name = fold_build2 (PLUS_EXPR, TREE_TYPE (new_name),
new_name, step_expr);
if (!is_gimple_min_invariant (new_name))
{
init_stmt = gimple_build_assign (new_var, new_name);
new_name = make_ssa_name (new_var, init_stmt);
gimple_assign_set_lhs (init_stmt, new_name);
new_bb = gsi_insert_on_edge_immediate (pe, init_stmt);
gcc_assert (!new_bb);
if (dump_enabled_p ())
{
dump_printf_loc (MSG_NOTE, vect_location,
"created new init_stmt: ");
dump_gimple_stmt (MSG_NOTE, TDF_SLIM, init_stmt, 0);
dump_printf (MSG_NOTE, "\n");
}
constant_p = false;
}
CONSTRUCTOR_APPEND_ELT (v, NULL_TREE, new_name);
}
/* Create a vector from [new_name_0, new_name_1, ..., new_name_nunits-1] */
if (constant_p)
new_vec = build_vector_from_ctor (vectype, v);
else
new_vec = build_constructor (vectype, v);
vec_init = vect_init_vector (iv_phi, new_vec, vectype, NULL);
}
/* Create the vector that holds the step of the induction. */
if (nested_in_vect_loop)
/* iv_loop is nested in the loop to be vectorized. Generate:
vec_step = [S, S, S, S] */
new_name = step_expr;
else
{
/* iv_loop is the loop to be vectorized. Generate:
vec_step = [VF*S, VF*S, VF*S, VF*S] */
if (SCALAR_FLOAT_TYPE_P (TREE_TYPE (step_expr)))
{
expr = build_int_cst (integer_type_node, vf);
expr = fold_convert (TREE_TYPE (step_expr), expr);
}
else
expr = build_int_cst (TREE_TYPE (step_expr), vf);
new_name = fold_build2 (MULT_EXPR, TREE_TYPE (step_expr),
expr, step_expr);
if (TREE_CODE (step_expr) == SSA_NAME)
new_name = vect_init_vector (iv_phi, new_name,
TREE_TYPE (step_expr), NULL);
}
t = unshare_expr (new_name);
gcc_assert (CONSTANT_CLASS_P (new_name)
|| TREE_CODE (new_name) == SSA_NAME);
stepvectype = get_vectype_for_scalar_type (TREE_TYPE (new_name));
gcc_assert (stepvectype);
new_vec = build_vector_from_val (stepvectype, t);
vec_step = vect_init_vector (iv_phi, new_vec, stepvectype, NULL);
/* Create the following def-use cycle:
loop prolog:
vec_init = ...
vec_step = ...
loop:
vec_iv = PHI <vec_init, vec_loop>
...
STMT
...
vec_loop = vec_iv + vec_step; */
/* Create the induction-phi that defines the induction-operand. */
vec_dest = vect_get_new_vect_var (vectype, vect_simple_var, "vec_iv_");
induction_phi = create_phi_node (vec_dest, iv_loop->header);
set_vinfo_for_stmt (induction_phi,
new_stmt_vec_info (induction_phi, loop_vinfo, NULL));
induc_def = PHI_RESULT (induction_phi);
/* Create the iv update inside the loop */
new_stmt = gimple_build_assign (vec_dest, PLUS_EXPR, induc_def, vec_step);
vec_def = make_ssa_name (vec_dest, new_stmt);
gimple_assign_set_lhs (new_stmt, vec_def);
gsi_insert_before (&si, new_stmt, GSI_SAME_STMT);
set_vinfo_for_stmt (new_stmt, new_stmt_vec_info (new_stmt, loop_vinfo,
NULL));
/* Set the arguments of the phi node: */
add_phi_arg (induction_phi, vec_init, pe, UNKNOWN_LOCATION);
add_phi_arg (induction_phi, vec_def, loop_latch_edge (iv_loop),
UNKNOWN_LOCATION);
/* In case that vectorization factor (VF) is bigger than the number
of elements that we can fit in a vectype (nunits), we have to generate
more than one vector stmt - i.e - we need to "unroll" the
vector stmt by a factor VF/nunits. For more details see documentation
in vectorizable_operation. */
if (ncopies > 1)
{
stmt_vec_info prev_stmt_vinfo;
/* FORNOW. This restriction should be relaxed. */
gcc_assert (!nested_in_vect_loop);
/* Create the vector that holds the step of the induction. */
if (SCALAR_FLOAT_TYPE_P (TREE_TYPE (step_expr)))
{
expr = build_int_cst (integer_type_node, nunits);
expr = fold_convert (TREE_TYPE (step_expr), expr);
}
else
expr = build_int_cst (TREE_TYPE (step_expr), nunits);
new_name = fold_build2 (MULT_EXPR, TREE_TYPE (step_expr),
expr, step_expr);
if (TREE_CODE (step_expr) == SSA_NAME)
new_name = vect_init_vector (iv_phi, new_name,
TREE_TYPE (step_expr), NULL);
t = unshare_expr (new_name);
gcc_assert (CONSTANT_CLASS_P (new_name)
|| TREE_CODE (new_name) == SSA_NAME);
new_vec = build_vector_from_val (stepvectype, t);
vec_step = vect_init_vector (iv_phi, new_vec, stepvectype, NULL);
vec_def = induc_def;
prev_stmt_vinfo = vinfo_for_stmt (induction_phi);
for (i = 1; i < ncopies; i++)
{
/* vec_i = vec_prev + vec_step */
new_stmt = gimple_build_assign (vec_dest, PLUS_EXPR,
vec_def, vec_step);
vec_def = make_ssa_name (vec_dest, new_stmt);
gimple_assign_set_lhs (new_stmt, vec_def);
gsi_insert_before (&si, new_stmt, GSI_SAME_STMT);
if (!useless_type_conversion_p (resvectype, vectype))
{
new_stmt
= gimple_build_assign
(vect_get_new_vect_var (resvectype, vect_simple_var,
"vec_iv_"),
VIEW_CONVERT_EXPR,
build1 (VIEW_CONVERT_EXPR, resvectype,
gimple_assign_lhs (new_stmt)));
gimple_assign_set_lhs (new_stmt,
make_ssa_name
(gimple_assign_lhs (new_stmt), new_stmt));
gsi_insert_before (&si, new_stmt, GSI_SAME_STMT);
}
set_vinfo_for_stmt (new_stmt,
new_stmt_vec_info (new_stmt, loop_vinfo, NULL));
STMT_VINFO_RELATED_STMT (prev_stmt_vinfo) = new_stmt;
prev_stmt_vinfo = vinfo_for_stmt (new_stmt);
}
}
if (nested_in_vect_loop)
{
/* Find the loop-closed exit-phi of the induction, and record
the final vector of induction results: */
exit_phi = NULL;
FOR_EACH_IMM_USE_FAST (use_p, imm_iter, loop_arg)
{
gimple use_stmt = USE_STMT (use_p);
if (is_gimple_debug (use_stmt))
continue;
if (!flow_bb_inside_loop_p (iv_loop, gimple_bb (use_stmt)))
{
exit_phi = use_stmt;
break;
}
}
if (exit_phi)
{
stmt_vec_info stmt_vinfo = vinfo_for_stmt (exit_phi);
/* FORNOW. Currently not supporting the case that an inner-loop induction
is not used in the outer-loop (i.e. only outside the outer-loop). */
gcc_assert (STMT_VINFO_RELEVANT_P (stmt_vinfo)
&& !STMT_VINFO_LIVE_P (stmt_vinfo));
STMT_VINFO_VEC_STMT (stmt_vinfo) = new_stmt;
if (dump_enabled_p ())
{
dump_printf_loc (MSG_NOTE, vect_location,
"vector of inductions after inner-loop:");
dump_gimple_stmt (MSG_NOTE, TDF_SLIM, new_stmt, 0);
dump_printf (MSG_NOTE, "\n");
}
}
}
if (dump_enabled_p ())
{
dump_printf_loc (MSG_NOTE, vect_location,
"transform induction: created def-use cycle: ");
dump_gimple_stmt (MSG_NOTE, TDF_SLIM, induction_phi, 0);
dump_printf (MSG_NOTE, "\n");
dump_gimple_stmt (MSG_NOTE, TDF_SLIM,
SSA_NAME_DEF_STMT (vec_def), 0);
dump_printf (MSG_NOTE, "\n");
}
STMT_VINFO_VEC_STMT (phi_info) = induction_phi;
if (!useless_type_conversion_p (resvectype, vectype))
{
new_stmt = gimple_build_assign (vect_get_new_vect_var (resvectype,
vect_simple_var,
"vec_iv_"),
VIEW_CONVERT_EXPR,
build1 (VIEW_CONVERT_EXPR, resvectype,
induc_def));
induc_def = make_ssa_name (gimple_assign_lhs (new_stmt), new_stmt);
gimple_assign_set_lhs (new_stmt, induc_def);
si = gsi_after_labels (bb);
gsi_insert_before (&si, new_stmt, GSI_SAME_STMT);
set_vinfo_for_stmt (new_stmt,
new_stmt_vec_info (new_stmt, loop_vinfo, NULL));
STMT_VINFO_RELATED_STMT (vinfo_for_stmt (new_stmt))
= STMT_VINFO_RELATED_STMT (vinfo_for_stmt (induction_phi));
}
return induc_def;
}
/* Function get_initial_def_for_reduction
Input:
STMT - a stmt that performs a reduction operation in the loop.
INIT_VAL - the initial value of the reduction variable
Output:
ADJUSTMENT_DEF - a tree that holds a value to be added to the final result
of the reduction (used for adjusting the epilog - see below).
Return a vector variable, initialized according to the operation that STMT
performs. This vector will be used as the initial value of the
vector of partial results.
Option1 (adjust in epilog): Initialize the vector as follows:
add/bit or/xor: [0,0,...,0,0]
mult/bit and: [1,1,...,1,1]
min/max/cond_expr: [init_val,init_val,..,init_val,init_val]
and when necessary (e.g. add/mult case) let the caller know
that it needs to adjust the result by init_val.
Option2: Initialize the vector as follows:
add/bit or/xor: [init_val,0,0,...,0]
mult/bit and: [init_val,1,1,...,1]
min/max/cond_expr: [init_val,init_val,...,init_val]
and no adjustments are needed.
For example, for the following code:
s = init_val;
for (i=0;i<n;i++)
s = s + a[i];
STMT is 's = s + a[i]', and the reduction variable is 's'.
For a vector of 4 units, we want to return either [0,0,0,init_val],
or [0,0,0,0] and let the caller know that it needs to adjust
the result at the end by 'init_val'.
FORNOW, we are using the 'adjust in epilog' scheme, because this way the
initialization vector is simpler (same element in all entries), if
ADJUSTMENT_DEF is not NULL, and Option2 otherwise.
A cost model should help decide between these two schemes. */
tree
get_initial_def_for_reduction (gimple stmt, tree init_val,
tree *adjustment_def)
{
stmt_vec_info stmt_vinfo = vinfo_for_stmt (stmt);
loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_vinfo);
struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
tree scalar_type = TREE_TYPE (init_val);
tree vectype = get_vectype_for_scalar_type (scalar_type);
int nunits;
enum tree_code code = gimple_assign_rhs_code (stmt);
tree def_for_init;
tree init_def;
tree *elts;
int i;
bool nested_in_vect_loop = false;
tree init_value;
REAL_VALUE_TYPE real_init_val = dconst0;
int int_init_val = 0;
gimple def_stmt = NULL;
gcc_assert (vectype);
nunits = TYPE_VECTOR_SUBPARTS (vectype);
gcc_assert (POINTER_TYPE_P (scalar_type) || INTEGRAL_TYPE_P (scalar_type)
|| SCALAR_FLOAT_TYPE_P (scalar_type));
if (nested_in_vect_loop_p (loop, stmt))
nested_in_vect_loop = true;
else
gcc_assert (loop == (gimple_bb (stmt))->loop_father);
/* In case of double reduction we only create a vector variable to be put
in the reduction phi node. The actual statement creation is done in
vect_create_epilog_for_reduction. */
if (adjustment_def && nested_in_vect_loop
&& TREE_CODE (init_val) == SSA_NAME
&& (def_stmt = SSA_NAME_DEF_STMT (init_val))
&& gimple_code (def_stmt) == GIMPLE_PHI
&& flow_bb_inside_loop_p (loop, gimple_bb (def_stmt))
&& vinfo_for_stmt (def_stmt)
&& STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def_stmt))
== vect_double_reduction_def)
{
*adjustment_def = NULL;
return vect_create_destination_var (init_val, vectype);
}
if (TREE_CONSTANT (init_val))
{
if (SCALAR_FLOAT_TYPE_P (scalar_type))
init_value = build_real (scalar_type, TREE_REAL_CST (init_val));
else
init_value = build_int_cst (scalar_type, TREE_INT_CST_LOW (init_val));
}
else
init_value = init_val;
/* In case of a nested reduction do not use an adjustment def as
that case is not supported by the epilogue generation correctly
if ncopies is not one. */
if (adjustment_def && nested_in_vect_loop)
{
*adjustment_def = NULL;
return vect_get_vec_def_for_operand (init_val, stmt, NULL);
}
switch (code)
{
case WIDEN_SUM_EXPR:
case DOT_PROD_EXPR:
case SAD_EXPR:
case PLUS_EXPR:
case MINUS_EXPR:
case BIT_IOR_EXPR:
case BIT_XOR_EXPR:
case MULT_EXPR:
case BIT_AND_EXPR:
/* ADJUSMENT_DEF is NULL when called from
vect_create_epilog_for_reduction to vectorize double reduction. */
if (adjustment_def)
*adjustment_def = init_val;
if (code == MULT_EXPR)
{
real_init_val = dconst1;
int_init_val = 1;
}
if (code == BIT_AND_EXPR)
int_init_val = -1;
if (SCALAR_FLOAT_TYPE_P (scalar_type))
def_for_init = build_real (scalar_type, real_init_val);
else
def_for_init = build_int_cst (scalar_type, int_init_val);
/* Create a vector of '0' or '1' except the first element. */
elts = XALLOCAVEC (tree, nunits);
for (i = nunits - 2; i >= 0; --i)
elts[i + 1] = def_for_init;
/* Option1: the first element is '0' or '1' as well. */
if (adjustment_def)
{
elts[0] = def_for_init;
init_def = build_vector (vectype, elts);
break;
}
/* Option2: the first element is INIT_VAL. */
elts[0] = init_val;
if (TREE_CONSTANT (init_val))
init_def = build_vector (vectype, elts);
else
{
vec<constructor_elt, va_gc> *v;
vec_alloc (v, nunits);
CONSTRUCTOR_APPEND_ELT (v, NULL_TREE, init_val);
for (i = 1; i < nunits; ++i)
CONSTRUCTOR_APPEND_ELT (v, NULL_TREE, elts[i]);
init_def = build_constructor (vectype, v);
}
break;
case MIN_EXPR:
case MAX_EXPR:
case COND_EXPR:
if (adjustment_def)
{
*adjustment_def = NULL_TREE;
init_def = vect_get_vec_def_for_operand (init_val, stmt, NULL);
break;
}
init_def = build_vector_from_val (vectype, init_value);
break;
default:
gcc_unreachable ();
}
return init_def;
}
/* Function vect_create_epilog_for_reduction
Create code at the loop-epilog to finalize the result of a reduction
computation.
VECT_DEFS is list of vector of partial results, i.e., the lhs's of vector
reduction statements.
STMT is the scalar reduction stmt that is being vectorized.
NCOPIES is > 1 in case the vectorization factor (VF) is bigger than the
number of elements that we can fit in a vectype (nunits). In this case
we have to generate more than one vector stmt - i.e - we need to "unroll"
the vector stmt by a factor VF/nunits. For more details see documentation
in vectorizable_operation.
REDUC_CODE is the tree-code for the epilog reduction.
REDUCTION_PHIS is a list of the phi-nodes that carry the reduction
computation.
REDUC_INDEX is the index of the operand in the right hand side of the
statement that is defined by REDUCTION_PHI.
DOUBLE_REDUC is TRUE if double reduction phi nodes should be handled.
SLP_NODE is an SLP node containing a group of reduction statements. The
first one in this group is STMT.
This function:
1. Creates the reduction def-use cycles: sets the arguments for
REDUCTION_PHIS:
The loop-entry argument is the vectorized initial-value of the reduction.
The loop-latch argument is taken from VECT_DEFS - the vector of partial
sums.
2. "Reduces" each vector of partial results VECT_DEFS into a single result,
by applying the operation specified by REDUC_CODE if available, or by
other means (whole-vector shifts or a scalar loop).
The function also creates a new phi node at the loop exit to preserve
loop-closed form, as illustrated below.
The flow at the entry to this function:
loop:
vec_def = phi <null, null> # REDUCTION_PHI
VECT_DEF = vector_stmt # vectorized form of STMT
s_loop = scalar_stmt # (scalar) STMT
loop_exit:
s_out0 = phi <s_loop> # (scalar) EXIT_PHI
use <s_out0>
use <s_out0>
The above is transformed by this function into:
loop:
vec_def = phi <vec_init, VECT_DEF> # REDUCTION_PHI
VECT_DEF = vector_stmt # vectorized form of STMT
s_loop = scalar_stmt # (scalar) STMT
loop_exit:
s_out0 = phi <s_loop> # (scalar) EXIT_PHI
v_out1 = phi <VECT_DEF> # NEW_EXIT_PHI
v_out2 = reduce <v_out1>
s_out3 = extract_field <v_out2, 0>
s_out4 = adjust_result <s_out3>
use <s_out4>
use <s_out4>
*/
static void
vect_create_epilog_for_reduction (vec<tree> vect_defs, gimple stmt,
int ncopies, enum tree_code reduc_code,
vec<gimple> reduction_phis,
int reduc_index, bool double_reduc,
slp_tree slp_node)
{
stmt_vec_info stmt_info = vinfo_for_stmt (stmt);
stmt_vec_info prev_phi_info;
tree vectype;
machine_mode mode;
loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info);
struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo), *outer_loop = NULL;
basic_block exit_bb;
tree scalar_dest;
tree scalar_type;
gimple new_phi = NULL, phi;
gimple_stmt_iterator exit_gsi;
tree vec_dest;
tree new_temp = NULL_TREE, new_dest, new_name, new_scalar_dest;
gimple epilog_stmt = NULL;
enum tree_code code = gimple_assign_rhs_code (stmt);
gimple exit_phi;
tree bitsize;
tree adjustment_def = NULL;
tree vec_initial_def = NULL;
tree reduction_op, expr, def;
tree orig_name, scalar_result;
imm_use_iterator imm_iter, phi_imm_iter;
use_operand_p use_p, phi_use_p;
gimple use_stmt, orig_stmt, reduction_phi = NULL;
bool nested_in_vect_loop = false;
auto_vec<gimple> new_phis;
auto_vec<gimple> inner_phis;
enum vect_def_type dt = vect_unknown_def_type;
int j, i;
auto_vec<tree> scalar_results;
unsigned int group_size = 1, k, ratio;
auto_vec<tree> vec_initial_defs;
auto_vec<gimple> phis;
bool slp_reduc = false;
tree new_phi_result;
gimple inner_phi = NULL;
if (slp_node)
group_size = SLP_TREE_SCALAR_STMTS (slp_node).length ();
if (nested_in_vect_loop_p (loop, stmt))
{
outer_loop = loop;
loop = loop->inner;
nested_in_vect_loop = true;
gcc_assert (!slp_node);
}
switch (get_gimple_rhs_class (gimple_assign_rhs_code (stmt)))
{
case GIMPLE_SINGLE_RHS:
gcc_assert (TREE_OPERAND_LENGTH (gimple_assign_rhs1 (stmt))
== ternary_op);
reduction_op = TREE_OPERAND (gimple_assign_rhs1 (stmt), reduc_index);
break;
case GIMPLE_UNARY_RHS:
reduction_op = gimple_assign_rhs1 (stmt);
break;
case GIMPLE_BINARY_RHS:
reduction_op = reduc_index ?
gimple_assign_rhs2 (stmt) : gimple_assign_rhs1 (stmt);
break;
case GIMPLE_TERNARY_RHS:
reduction_op = gimple_op (stmt, reduc_index + 1);
break;
default:
gcc_unreachable ();
}
vectype = get_vectype_for_scalar_type (TREE_TYPE (reduction_op));
gcc_assert (vectype);
mode = TYPE_MODE (vectype);
/* 1. Create the reduction def-use cycle:
Set the arguments of REDUCTION_PHIS, i.e., transform
loop:
vec_def = phi <null, null> # REDUCTION_PHI
VECT_DEF = vector_stmt # vectorized form of STMT
...
into:
loop:
vec_def = phi <vec_init, VECT_DEF> # REDUCTION_PHI
VECT_DEF = vector_stmt # vectorized form of STMT
...
(in case of SLP, do it for all the phis). */
/* Get the loop-entry arguments. */
enum vect_def_type initial_def_dt = vect_unknown_def_type;
if (slp_node)
vect_get_vec_defs (reduction_op, NULL_TREE, stmt, &vec_initial_defs,
NULL, slp_node, reduc_index);
else
{
/* Get at the scalar def before the loop, that defines the initial value
of the reduction variable. */
gimple def_stmt = SSA_NAME_DEF_STMT (reduction_op);
tree initial_def = PHI_ARG_DEF_FROM_EDGE (def_stmt,
loop_preheader_edge (loop));
vect_is_simple_use (initial_def, NULL, loop_vinfo, NULL,
&def_stmt, &initial_def, &initial_def_dt);
/* For the case of reduction, vect_get_vec_def_for_operand returns
the scalar def before the loop, that defines the initial value
of the reduction variable. */
vec_initial_def = vect_get_vec_def_for_operand (reduction_op, stmt,
&adjustment_def);
vec_initial_defs.create (1);
vec_initial_defs.quick_push (vec_initial_def);
}
/* Set phi nodes arguments. */
FOR_EACH_VEC_ELT (reduction_phis, i, phi)
{
tree vec_init_def, def;
gimple_seq stmts;
vec_init_def = force_gimple_operand (vec_initial_defs[i], &stmts,
true, NULL_TREE);
gsi_insert_seq_on_edge_immediate (loop_preheader_edge (loop), stmts);
def = vect_defs[i];
for (j = 0; j < ncopies; j++)
{
if (j != 0)
{
phi = STMT_VINFO_RELATED_STMT (vinfo_for_stmt (phi));
if (nested_in_vect_loop)
vec_init_def
= vect_get_vec_def_for_stmt_copy (initial_def_dt,
vec_init_def);
}
/* Set the loop-entry arg of the reduction-phi. */
add_phi_arg (as_a <gphi *> (phi), vec_init_def,
loop_preheader_edge (loop), UNKNOWN_LOCATION);
/* Set the loop-latch arg for the reduction-phi. */
if (j > 0)
def = vect_get_vec_def_for_stmt_copy (vect_unknown_def_type, def);
add_phi_arg (as_a <gphi *> (phi), def, loop_latch_edge (loop),
UNKNOWN_LOCATION);
if (dump_enabled_p ())
{
dump_printf_loc (MSG_NOTE, vect_location,
"transform reduction: created def-use cycle: ");
dump_gimple_stmt (MSG_NOTE, TDF_SLIM, phi, 0);
dump_printf (MSG_NOTE, "\n");
dump_gimple_stmt (MSG_NOTE, TDF_SLIM, SSA_NAME_DEF_STMT (def), 0);
dump_printf (MSG_NOTE, "\n");
}
}
}
/* 2. Create epilog code.
The reduction epilog code operates across the elements of the vector
of partial results computed by the vectorized loop.
The reduction epilog code consists of:
step 1: compute the scalar result in a vector (v_out2)
step 2: extract the scalar result (s_out3) from the vector (v_out2)
step 3: adjust the scalar result (s_out3) if needed.
Step 1 can be accomplished using one the following three schemes:
(scheme 1) using reduc_code, if available.
(scheme 2) using whole-vector shifts, if available.
(scheme 3) using a scalar loop. In this case steps 1+2 above are
combined.
The overall epilog code looks like this:
s_out0 = phi <s_loop> # original EXIT_PHI
v_out1 = phi <VECT_DEF> # NEW_EXIT_PHI
v_out2 = reduce <v_out1> # step 1
s_out3 = extract_field <v_out2, 0> # step 2
s_out4 = adjust_result <s_out3> # step 3
(step 3 is optional, and steps 1 and 2 may be combined).
Lastly, the uses of s_out0 are replaced by s_out4. */
/* 2.1 Create new loop-exit-phis to preserve loop-closed form:
v_out1 = phi <VECT_DEF>
Store them in NEW_PHIS. */
exit_bb = single_exit (loop)->dest;
prev_phi_info = NULL;
new_phis.create (vect_defs.length ());
FOR_EACH_VEC_ELT (vect_defs, i, def)
{
for (j = 0; j < ncopies; j++)
{
tree new_def = copy_ssa_name (def);
phi = create_phi_node (new_def, exit_bb);
set_vinfo_for_stmt (phi, new_stmt_vec_info (phi, loop_vinfo, NULL));
if (j == 0)
new_phis.quick_push (phi);
else
{
def = vect_get_vec_def_for_stmt_copy (dt, def);
STMT_VINFO_RELATED_STMT (prev_phi_info) = phi;
}
SET_PHI_ARG_DEF (phi, single_exit (loop)->dest_idx, def);
prev_phi_info = vinfo_for_stmt (phi);
}
}
/* The epilogue is created for the outer-loop, i.e., for the loop being
vectorized. Create exit phis for the outer loop. */
if (double_reduc)
{
loop = outer_loop;
exit_bb = single_exit (loop)->dest;
inner_phis.create (vect_defs.length ());
FOR_EACH_VEC_ELT (new_phis, i, phi)
{
tree new_result = copy_ssa_name (PHI_RESULT (phi));
gphi *outer_phi = create_phi_node (new_result, exit_bb);
SET_PHI_ARG_DEF (outer_phi, single_exit (loop)->dest_idx,
PHI_RESULT (phi));
set_vinfo_for_stmt (outer_phi, new_stmt_vec_info (outer_phi,
loop_vinfo, NULL));
inner_phis.quick_push (phi);
new_phis[i] = outer_phi;
prev_phi_info = vinfo_for_stmt (outer_phi);
while (STMT_VINFO_RELATED_STMT (vinfo_for_stmt (phi)))
{
phi = STMT_VINFO_RELATED_STMT (vinfo_for_stmt (phi));
new_result = copy_ssa_name (PHI_RESULT (phi));
outer_phi = create_phi_node (new_result, exit_bb);
SET_PHI_ARG_DEF (outer_phi, single_exit (loop)->dest_idx,
PHI_RESULT (phi));
set_vinfo_for_stmt (outer_phi, new_stmt_vec_info (outer_phi,
loop_vinfo, NULL));
STMT_VINFO_RELATED_STMT (prev_phi_info) = outer_phi;
prev_phi_info = vinfo_for_stmt (outer_phi);
}
}
}
exit_gsi = gsi_after_labels (exit_bb);
/* 2.2 Get the relevant tree-code to use in the epilog for schemes 2,3
(i.e. when reduc_code is not available) and in the final adjustment
code (if needed). Also get the original scalar reduction variable as
defined in the loop. In case STMT is a "pattern-stmt" (i.e. - it
represents a reduction pattern), the tree-code and scalar-def are
taken from the original stmt that the pattern-stmt (STMT) replaces.
Otherwise (it is a regular reduction) - the tree-code and scalar-def
are taken from STMT. */
orig_stmt = STMT_VINFO_RELATED_STMT (stmt_info);
if (!orig_stmt)
{
/* Regular reduction */
orig_stmt = stmt;
}
else
{
/* Reduction pattern */
stmt_vec_info stmt_vinfo = vinfo_for_stmt (orig_stmt);
gcc_assert (STMT_VINFO_IN_PATTERN_P (stmt_vinfo));
gcc_assert (STMT_VINFO_RELATED_STMT (stmt_vinfo) == stmt);
}
code = gimple_assign_rhs_code (orig_stmt);
/* For MINUS_EXPR the initial vector is [init_val,0,...,0], therefore,
partial results are added and not subtracted. */
if (code == MINUS_EXPR)
code = PLUS_EXPR;
scalar_dest = gimple_assign_lhs (orig_stmt);
scalar_type = TREE_TYPE (scalar_dest);
scalar_results.create (group_size);
new_scalar_dest = vect_create_destination_var (scalar_dest, NULL);
bitsize = TYPE_SIZE (scalar_type);
/* In case this is a reduction in an inner-loop while vectorizing an outer
loop - we don't need to extract a single scalar result at the end of the
inner-loop (unless it is double reduction, i.e., the use of reduction is
outside the outer-loop). The final vector of partial results will be used
in the vectorized outer-loop, or reduced to a scalar result at the end of
the outer-loop. */
if (nested_in_vect_loop && !double_reduc)
goto vect_finalize_reduction;
/* SLP reduction without reduction chain, e.g.,
# a1 = phi <a2, a0>
# b1 = phi <b2, b0>
a2 = operation (a1)
b2 = operation (b1) */
slp_reduc = (slp_node && !GROUP_FIRST_ELEMENT (vinfo_for_stmt (stmt)));
/* In case of reduction chain, e.g.,
# a1 = phi <a3, a0>
a2 = operation (a1)
a3 = operation (a2),
we may end up with more than one vector result. Here we reduce them to
one vector. */
if (GROUP_FIRST_ELEMENT (vinfo_for_stmt (stmt)))
{
tree first_vect = PHI_RESULT (new_phis[0]);
tree tmp;
gassign *new_vec_stmt = NULL;
vec_dest = vect_create_destination_var (scalar_dest, vectype);
for (k = 1; k < new_phis.length (); k++)
{
gimple next_phi = new_phis[k];
tree second_vect = PHI_RESULT (next_phi);
tmp = build2 (code, vectype, first_vect, second_vect);
new_vec_stmt = gimple_build_assign (vec_dest, tmp);
first_vect = make_ssa_name (vec_dest, new_vec_stmt);
gimple_assign_set_lhs (new_vec_stmt, first_vect);
gsi_insert_before (&exit_gsi, new_vec_stmt, GSI_SAME_STMT);
}
new_phi_result = first_vect;
if (new_vec_stmt)
{
new_phis.truncate (0);
new_phis.safe_push (new_vec_stmt);
}
}
else
new_phi_result = PHI_RESULT (new_phis[0]);
/* 2.3 Create the reduction code, using one of the three schemes described
above. In SLP we simply need to extract all the elements from the
vector (without reducing them), so we use scalar shifts. */
if (reduc_code != ERROR_MARK && !slp_reduc)
{
tree tmp;
tree vec_elem_type;
/*** Case 1: Create:
v_out2 = reduc_expr <v_out1> */
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"Reduce using direct vector reduction.\n");
vec_elem_type = TREE_TYPE (TREE_TYPE (new_phi_result));
if (!useless_type_conversion_p (scalar_type, vec_elem_type))
{
tree tmp_dest =
vect_create_destination_var (scalar_dest, vec_elem_type);
tmp = build1 (reduc_code, vec_elem_type, new_phi_result);
epilog_stmt = gimple_build_assign (tmp_dest, tmp);
new_temp = make_ssa_name (tmp_dest, epilog_stmt);
gimple_assign_set_lhs (epilog_stmt, new_temp);
gsi_insert_before (&exit_gsi, epilog_stmt, GSI_SAME_STMT);
tmp = build1 (NOP_EXPR, scalar_type, new_temp);
}
else
tmp = build1 (reduc_code, scalar_type, new_phi_result);
epilog_stmt = gimple_build_assign (new_scalar_dest, tmp);
new_temp = make_ssa_name (new_scalar_dest, epilog_stmt);
gimple_assign_set_lhs (epilog_stmt, new_temp);
gsi_insert_before (&exit_gsi, epilog_stmt, GSI_SAME_STMT);
scalar_results.safe_push (new_temp);
}
else
{
bool reduce_with_shift = have_whole_vector_shift (mode);
int element_bitsize = tree_to_uhwi (bitsize);
int vec_size_in_bits = tree_to_uhwi (TYPE_SIZE (vectype));
tree vec_temp;
/* Regardless of whether we have a whole vector shift, if we're
emulating the operation via tree-vect-generic, we don't want
to use it. Only the first round of the reduction is likely
to still be profitable via emulation. */
/* ??? It might be better to emit a reduction tree code here, so that
tree-vect-generic can expand the first round via bit tricks. */
if (!VECTOR_MODE_P (mode))
reduce_with_shift = false;
else
{
optab optab = optab_for_tree_code (code, vectype, optab_default);
if (optab_handler (optab, mode) == CODE_FOR_nothing)
reduce_with_shift = false;
}
if (reduce_with_shift && !slp_reduc)
{
int nelements = vec_size_in_bits / element_bitsize;
unsigned char *sel = XALLOCAVEC (unsigned char, nelements);
int elt_offset;
tree zero_vec = build_zero_cst (vectype);
/*** Case 2: Create:
for (offset = nelements/2; offset >= 1; offset/=2)
{
Create: va' = vec_shift <va, offset>
Create: va = vop <va, va'>
} */
tree rhs;
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"Reduce using vector shifts\n");
vec_dest = vect_create_destination_var (scalar_dest, vectype);
new_temp = new_phi_result;
for (elt_offset = nelements / 2;
elt_offset >= 1;
elt_offset /= 2)
{
calc_vec_perm_mask_for_shift (mode, elt_offset, sel);
tree mask = vect_gen_perm_mask_any (vectype, sel);
epilog_stmt = gimple_build_assign (vec_dest, VEC_PERM_EXPR,
new_temp, zero_vec, mask);
new_name = make_ssa_name (vec_dest, epilog_stmt);
gimple_assign_set_lhs (epilog_stmt, new_name);
gsi_insert_before (&exit_gsi, epilog_stmt, GSI_SAME_STMT);
epilog_stmt = gimple_build_assign (vec_dest, code, new_name,
new_temp);
new_temp = make_ssa_name (vec_dest, epilog_stmt);
gimple_assign_set_lhs (epilog_stmt, new_temp);
gsi_insert_before (&exit_gsi, epilog_stmt, GSI_SAME_STMT);
}
/* 2.4 Extract the final scalar result. Create:
s_out3 = extract_field <v_out2, bitpos> */
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"extract scalar result\n");
rhs = build3 (BIT_FIELD_REF, scalar_type, new_temp,
bitsize, bitsize_zero_node);
epilog_stmt = gimple_build_assign (new_scalar_dest, rhs);
new_temp = make_ssa_name (new_scalar_dest, epilog_stmt);
gimple_assign_set_lhs (epilog_stmt, new_temp);
gsi_insert_before (&exit_gsi, epilog_stmt, GSI_SAME_STMT);
scalar_results.safe_push (new_temp);
}
else
{
/*** Case 3: Create:
s = extract_field <v_out2, 0>
for (offset = element_size;
offset < vector_size;
offset += element_size;)
{
Create: s' = extract_field <v_out2, offset>
Create: s = op <s, s'> // For non SLP cases
} */
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"Reduce using scalar code.\n");
vec_size_in_bits = tree_to_uhwi (TYPE_SIZE (vectype));
FOR_EACH_VEC_ELT (new_phis, i, new_phi)
{
int bit_offset;
if (gimple_code (new_phi) == GIMPLE_PHI)
vec_temp = PHI_RESULT (new_phi);
else
vec_temp = gimple_assign_lhs (new_phi);
tree rhs = build3 (BIT_FIELD_REF, scalar_type, vec_temp, bitsize,
bitsize_zero_node);
epilog_stmt = gimple_build_assign (new_scalar_dest, rhs);
new_temp = make_ssa_name (new_scalar_dest, epilog_stmt);
gimple_assign_set_lhs (epilog_stmt, new_temp);
gsi_insert_before (&exit_gsi, epilog_stmt, GSI_SAME_STMT);
/* In SLP we don't need to apply reduction operation, so we just
collect s' values in SCALAR_RESULTS. */
if (slp_reduc)
scalar_results.safe_push (new_temp);
for (bit_offset = element_bitsize;
bit_offset < vec_size_in_bits;
bit_offset += element_bitsize)
{
tree bitpos = bitsize_int (bit_offset);
tree rhs = build3 (BIT_FIELD_REF, scalar_type, vec_temp,
bitsize, bitpos);
epilog_stmt = gimple_build_assign (new_scalar_dest, rhs);
new_name = make_ssa_name (new_scalar_dest, epilog_stmt);
gimple_assign_set_lhs (epilog_stmt, new_name);
gsi_insert_before (&exit_gsi, epilog_stmt, GSI_SAME_STMT);
if (slp_reduc)
{
/* In SLP we don't need to apply reduction operation, so
we just collect s' values in SCALAR_RESULTS. */
new_temp = new_name;
scalar_results.safe_push (new_name);
}
else
{
epilog_stmt = gimple_build_assign (new_scalar_dest, code,
new_name, new_temp);
new_temp = make_ssa_name (new_scalar_dest, epilog_stmt);
gimple_assign_set_lhs (epilog_stmt, new_temp);
gsi_insert_before (&exit_gsi, epilog_stmt, GSI_SAME_STMT);
}
}
}
/* The only case where we need to reduce scalar results in SLP, is
unrolling. If the size of SCALAR_RESULTS is greater than
GROUP_SIZE, we reduce them combining elements modulo
GROUP_SIZE. */
if (slp_reduc)
{
tree res, first_res, new_res;
gimple new_stmt;
/* Reduce multiple scalar results in case of SLP unrolling. */
for (j = group_size; scalar_results.iterate (j, &res);
j++)
{
first_res = scalar_results[j % group_size];
new_stmt = gimple_build_assign (new_scalar_dest, code,
first_res, res);
new_res = make_ssa_name (new_scalar_dest, new_stmt);
gimple_assign_set_lhs (new_stmt, new_res);
gsi_insert_before (&exit_gsi, new_stmt, GSI_SAME_STMT);
scalar_results[j % group_size] = new_res;
}
}
else
/* Not SLP - we have one scalar to keep in SCALAR_RESULTS. */
scalar_results.safe_push (new_temp);
}
}
vect_finalize_reduction:
if (double_reduc)
loop = loop->inner;
/* 2.5 Adjust the final result by the initial value of the reduction
variable. (When such adjustment is not needed, then
'adjustment_def' is zero). For example, if code is PLUS we create:
new_temp = loop_exit_def + adjustment_def */
if (adjustment_def)
{
gcc_assert (!slp_reduc);
if (nested_in_vect_loop)
{
new_phi = new_phis[0];
gcc_assert (TREE_CODE (TREE_TYPE (adjustment_def)) == VECTOR_TYPE);
expr = build2 (code, vectype, PHI_RESULT (new_phi), adjustment_def);
new_dest = vect_create_destination_var (scalar_dest, vectype);
}
else
{
new_temp = scalar_results[0];
gcc_assert (TREE_CODE (TREE_TYPE (adjustment_def)) != VECTOR_TYPE);
expr = build2 (code, scalar_type, new_temp, adjustment_def);
new_dest = vect_create_destination_var (scalar_dest, scalar_type);
}
epilog_stmt = gimple_build_assign (new_dest, expr);
new_temp = make_ssa_name (new_dest, epilog_stmt);
gimple_assign_set_lhs (epilog_stmt, new_temp);
gsi_insert_before (&exit_gsi, epilog_stmt, GSI_SAME_STMT);
if (nested_in_vect_loop)
{
set_vinfo_for_stmt (epilog_stmt,
new_stmt_vec_info (epilog_stmt, loop_vinfo,
NULL));
STMT_VINFO_RELATED_STMT (vinfo_for_stmt (epilog_stmt)) =
STMT_VINFO_RELATED_STMT (vinfo_for_stmt (new_phi));
if (!double_reduc)
scalar_results.quick_push (new_temp);
else
scalar_results[0] = new_temp;
}
else
scalar_results[0] = new_temp;
new_phis[0] = epilog_stmt;
}
/* 2.6 Handle the loop-exit phis. Replace the uses of scalar loop-exit
phis with new adjusted scalar results, i.e., replace use <s_out0>
with use <s_out4>.
Transform:
loop_exit:
s_out0 = phi <s_loop> # (scalar) EXIT_PHI
v_out1 = phi <VECT_DEF> # NEW_EXIT_PHI
v_out2 = reduce <v_out1>
s_out3 = extract_field <v_out2, 0>
s_out4 = adjust_result <s_out3>
use <s_out0>
use <s_out0>
into:
loop_exit:
s_out0 = phi <s_loop> # (scalar) EXIT_PHI
v_out1 = phi <VECT_DEF> # NEW_EXIT_PHI
v_out2 = reduce <v_out1>
s_out3 = extract_field <v_out2, 0>
s_out4 = adjust_result <s_out3>
use <s_out4>
use <s_out4> */
/* In SLP reduction chain we reduce vector results into one vector if
necessary, hence we set here GROUP_SIZE to 1. SCALAR_DEST is the LHS of
the last stmt in the reduction chain, since we are looking for the loop
exit phi node. */
if (GROUP_FIRST_ELEMENT (vinfo_for_stmt (stmt)))
{
scalar_dest = gimple_assign_lhs (
SLP_TREE_SCALAR_STMTS (slp_node)[group_size - 1]);
group_size = 1;
}
/* In SLP we may have several statements in NEW_PHIS and REDUCTION_PHIS (in
case that GROUP_SIZE is greater than vectorization factor). Therefore, we
need to match SCALAR_RESULTS with corresponding statements. The first
(GROUP_SIZE / number of new vector stmts) scalar results correspond to
the first vector stmt, etc.
(RATIO is equal to (GROUP_SIZE / number of new vector stmts)). */
if (group_size > new_phis.length ())
{
ratio = group_size / new_phis.length ();
gcc_assert (!(group_size % new_phis.length ()));
}
else
ratio = 1;
for (k = 0; k < group_size; k++)
{
if (k % ratio == 0)
{
epilog_stmt = new_phis[k / ratio];
reduction_phi = reduction_phis[k / ratio];
if (double_reduc)
inner_phi = inner_phis[k / ratio];
}
if (slp_reduc)
{
gimple current_stmt = SLP_TREE_SCALAR_STMTS (slp_node)[k];
orig_stmt = STMT_VINFO_RELATED_STMT (vinfo_for_stmt (current_stmt));
/* SLP statements can't participate in patterns. */
gcc_assert (!orig_stmt);
scalar_dest = gimple_assign_lhs (current_stmt);
}
phis.create (3);
/* Find the loop-closed-use at the loop exit of the original scalar
result. (The reduction result is expected to have two immediate uses -
one at the latch block, and one at the loop exit). */
FOR_EACH_IMM_USE_FAST (use_p, imm_iter, scalar_dest)
if (!flow_bb_inside_loop_p (loop, gimple_bb (USE_STMT (use_p)))
&& !is_gimple_debug (USE_STMT (use_p)))
phis.safe_push (USE_STMT (use_p));
/* While we expect to have found an exit_phi because of loop-closed-ssa
form we can end up without one if the scalar cycle is dead. */
FOR_EACH_VEC_ELT (phis, i, exit_phi)
{
if (outer_loop)
{
stmt_vec_info exit_phi_vinfo = vinfo_for_stmt (exit_phi);
gphi *vect_phi;
/* FORNOW. Currently not supporting the case that an inner-loop
reduction is not used in the outer-loop (but only outside the
outer-loop), unless it is double reduction. */
gcc_assert ((STMT_VINFO_RELEVANT_P (exit_phi_vinfo)
&& !STMT_VINFO_LIVE_P (exit_phi_vinfo))
|| double_reduc);
if (double_reduc)
STMT_VINFO_VEC_STMT (exit_phi_vinfo) = inner_phi;
else
STMT_VINFO_VEC_STMT (exit_phi_vinfo) = epilog_stmt;
if (!double_reduc
|| STMT_VINFO_DEF_TYPE (exit_phi_vinfo)
!= vect_double_reduction_def)
continue;
/* Handle double reduction:
stmt1: s1 = phi <s0, s2> - double reduction phi (outer loop)
stmt2: s3 = phi <s1, s4> - (regular) reduc phi (inner loop)
stmt3: s4 = use (s3) - (regular) reduc stmt (inner loop)
stmt4: s2 = phi <s4> - double reduction stmt (outer loop)
At that point the regular reduction (stmt2 and stmt3) is
already vectorized, as well as the exit phi node, stmt4.
Here we vectorize the phi node of double reduction, stmt1, and
update all relevant statements. */
/* Go through all the uses of s2 to find double reduction phi
node, i.e., stmt1 above. */
orig_name = PHI_RESULT (exit_phi);
FOR_EACH_IMM_USE_STMT (use_stmt, imm_iter, orig_name)
{
stmt_vec_info use_stmt_vinfo;
stmt_vec_info new_phi_vinfo;
tree vect_phi_init, preheader_arg, vect_phi_res, init_def;
basic_block bb = gimple_bb (use_stmt);
gimple use;
/* Check that USE_STMT is really double reduction phi
node. */
if (gimple_code (use_stmt) != GIMPLE_PHI
|| gimple_phi_num_args (use_stmt) != 2
|| bb->loop_father != outer_loop)
continue;
use_stmt_vinfo = vinfo_for_stmt (use_stmt);
if (!use_stmt_vinfo
|| STMT_VINFO_DEF_TYPE (use_stmt_vinfo)
!= vect_double_reduction_def)
continue;
/* Create vector phi node for double reduction:
vs1 = phi <vs0, vs2>
vs1 was created previously in this function by a call to
vect_get_vec_def_for_operand and is stored in
vec_initial_def;
vs2 is defined by INNER_PHI, the vectorized EXIT_PHI;
vs0 is created here. */
/* Create vector phi node. */
vect_phi = create_phi_node (vec_initial_def, bb);
new_phi_vinfo = new_stmt_vec_info (vect_phi,
loop_vec_info_for_loop (outer_loop), NULL);
set_vinfo_for_stmt (vect_phi, new_phi_vinfo);
/* Create vs0 - initial def of the double reduction phi. */
preheader_arg = PHI_ARG_DEF_FROM_EDGE (use_stmt,
loop_preheader_edge (outer_loop));
init_def = get_initial_def_for_reduction (stmt,
preheader_arg, NULL);
vect_phi_init = vect_init_vector (use_stmt, init_def,
vectype, NULL);
/* Update phi node arguments with vs0 and vs2. */
add_phi_arg (vect_phi, vect_phi_init,
loop_preheader_edge (outer_loop),
UNKNOWN_LOCATION);
add_phi_arg (vect_phi, PHI_RESULT (inner_phi),
loop_latch_edge (outer_loop), UNKNOWN_LOCATION);
if (dump_enabled_p ())
{
dump_printf_loc (MSG_NOTE, vect_location,
"created double reduction phi node: ");
dump_gimple_stmt (MSG_NOTE, TDF_SLIM, vect_phi, 0);
dump_printf (MSG_NOTE, "\n");
}
vect_phi_res = PHI_RESULT (vect_phi);
/* Replace the use, i.e., set the correct vs1 in the regular
reduction phi node. FORNOW, NCOPIES is always 1, so the
loop is redundant. */
use = reduction_phi;
for (j = 0; j < ncopies; j++)
{
edge pr_edge = loop_preheader_edge (loop);
SET_PHI_ARG_DEF (use, pr_edge->dest_idx, vect_phi_res);
use = STMT_VINFO_RELATED_STMT (vinfo_for_stmt (use));
}
}
}
}
phis.release ();
if (nested_in_vect_loop)
{
if (double_reduc)
loop = outer_loop;
else
continue;
}
phis.create (3);
/* Find the loop-closed-use at the loop exit of the original scalar
result. (The reduction result is expected to have two immediate uses,
one at the latch block, and one at the loop exit). For double
reductions we are looking for exit phis of the outer loop. */
FOR_EACH_IMM_USE_FAST (use_p, imm_iter, scalar_dest)
{
if (!flow_bb_inside_loop_p (loop, gimple_bb (USE_STMT (use_p))))
{
if (!is_gimple_debug (USE_STMT (use_p)))
phis.safe_push (USE_STMT (use_p));
}
else
{
if (double_reduc && gimple_code (USE_STMT (use_p)) == GIMPLE_PHI)
{
tree phi_res = PHI_RESULT (USE_STMT (use_p));
FOR_EACH_IMM_USE_FAST (phi_use_p, phi_imm_iter, phi_res)
{
if (!flow_bb_inside_loop_p (loop,
gimple_bb (USE_STMT (phi_use_p)))
&& !is_gimple_debug (USE_STMT (phi_use_p)))
phis.safe_push (USE_STMT (phi_use_p));
}
}
}
}
FOR_EACH_VEC_ELT (phis, i, exit_phi)
{
/* Replace the uses: */
orig_name = PHI_RESULT (exit_phi);
scalar_result = scalar_results[k];
FOR_EACH_IMM_USE_STMT (use_stmt, imm_iter, orig_name)
FOR_EACH_IMM_USE_ON_STMT (use_p, imm_iter)
SET_USE (use_p, scalar_result);
}
phis.release ();
}
}
/* Function vectorizable_reduction.
Check if STMT performs a reduction operation that can be vectorized.
If VEC_STMT is also passed, vectorize the STMT: create a vectorized
stmt to replace it, put it in VEC_STMT, and insert it at GSI.
Return FALSE if not a vectorizable STMT, TRUE otherwise.
This function also handles reduction idioms (patterns) that have been
recognized in advance during vect_pattern_recog. In this case, STMT may be
of this form:
X = pattern_expr (arg0, arg1, ..., X)
and it's STMT_VINFO_RELATED_STMT points to the last stmt in the original
sequence that had been detected and replaced by the pattern-stmt (STMT).
In some cases of reduction patterns, the type of the reduction variable X is
different than the type of the other arguments of STMT.
In such cases, the vectype that is used when transforming STMT into a vector
stmt is different than the vectype that is used to determine the
vectorization factor, because it consists of a different number of elements
than the actual number of elements that are being operated upon in parallel.
For example, consider an accumulation of shorts into an int accumulator.
On some targets it's possible to vectorize this pattern operating on 8
shorts at a time (hence, the vectype for purposes of determining the
vectorization factor should be V8HI); on the other hand, the vectype that
is used to create the vector form is actually V4SI (the type of the result).
Upon entry to this function, STMT_VINFO_VECTYPE records the vectype that
indicates what is the actual level of parallelism (V8HI in the example), so
that the right vectorization factor would be derived. This vectype
corresponds to the type of arguments to the reduction stmt, and should *NOT*
be used to create the vectorized stmt. The right vectype for the vectorized
stmt is obtained from the type of the result X:
get_vectype_for_scalar_type (TREE_TYPE (X))
This means that, contrary to "regular" reductions (or "regular" stmts in
general), the following equation:
STMT_VINFO_VECTYPE == get_vectype_for_scalar_type (TREE_TYPE (X))
does *NOT* necessarily hold for reduction patterns. */
bool
vectorizable_reduction (gimple stmt, gimple_stmt_iterator *gsi,
gimple *vec_stmt, slp_tree slp_node)
{
tree vec_dest;
tree scalar_dest;
tree loop_vec_def0 = NULL_TREE, loop_vec_def1 = NULL_TREE;
stmt_vec_info stmt_info = vinfo_for_stmt (stmt);
tree vectype_out = STMT_VINFO_VECTYPE (stmt_info);
tree vectype_in = NULL_TREE;
loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info);
struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
enum tree_code code, orig_code, epilog_reduc_code;
machine_mode vec_mode;
int op_type;
optab optab, reduc_optab;
tree new_temp = NULL_TREE;
tree def;
gimple def_stmt;
enum vect_def_type dt;
gphi *new_phi = NULL;
tree scalar_type;
bool is_simple_use;
gimple orig_stmt;
stmt_vec_info orig_stmt_info;
tree expr = NULL_TREE;
int i;
int ncopies;
int epilog_copies;
stmt_vec_info prev_stmt_info, prev_phi_info;
bool single_defuse_cycle = false;
tree reduc_def = NULL_TREE;
gimple new_stmt = NULL;
int j;
tree ops[3];
bool nested_cycle = false, found_nested_cycle_def = false;
gimple reduc_def_stmt = NULL;
/* The default is that the reduction variable is the last in statement. */
int reduc_index = 2;
bool double_reduc = false, dummy;
basic_block def_bb;
struct loop * def_stmt_loop, *outer_loop = NULL;
tree def_arg;
gimple def_arg_stmt;
auto_vec<tree> vec_oprnds0;
auto_vec<tree> vec_oprnds1;
auto_vec<tree> vect_defs;
auto_vec<gimple> phis;
int vec_num;
tree def0, def1, tem, op0, op1 = NULL_TREE;
/* In case of reduction chain we switch to the first stmt in the chain, but
we don't update STMT_INFO, since only the last stmt is marked as reduction
and has reduction properties. */
if (GROUP_FIRST_ELEMENT (vinfo_for_stmt (stmt)))
stmt = GROUP_FIRST_ELEMENT (stmt_info);
if (nested_in_vect_loop_p (loop, stmt))
{
outer_loop = loop;
loop = loop->inner;
nested_cycle = true;
}
/* 1. Is vectorizable reduction? */
/* Not supportable if the reduction variable is used in the loop, unless
it's a reduction chain. */
if (STMT_VINFO_RELEVANT (stmt_info) > vect_used_in_outer
&& !GROUP_FIRST_ELEMENT (stmt_info))
return false;
/* Reductions that are not used even in an enclosing outer-loop,
are expected to be "live" (used out of the loop). */
if (STMT_VINFO_RELEVANT (stmt_info) == vect_unused_in_scope
&& !STMT_VINFO_LIVE_P (stmt_info))
return false;
/* Make sure it was already recognized as a reduction computation. */
if (STMT_VINFO_DEF_TYPE (stmt_info) != vect_reduction_def
&& STMT_VINFO_DEF_TYPE (stmt_info) != vect_nested_cycle)
return false;
/* 2. Has this been recognized as a reduction pattern?
Check if STMT represents a pattern that has been recognized
in earlier analysis stages. For stmts that represent a pattern,
the STMT_VINFO_RELATED_STMT field records the last stmt in
the original sequence that constitutes the pattern. */
orig_stmt = STMT_VINFO_RELATED_STMT (stmt_info);
if (orig_stmt)
{
orig_stmt_info = vinfo_for_stmt (orig_stmt);
gcc_assert (STMT_VINFO_IN_PATTERN_P (orig_stmt_info));
gcc_assert (!STMT_VINFO_IN_PATTERN_P (stmt_info));
}
/* 3. Check the operands of the operation. The first operands are defined
inside the loop body. The last operand is the reduction variable,
which is defined by the loop-header-phi. */
gcc_assert (is_gimple_assign (stmt));
/* Flatten RHS. */
switch (get_gimple_rhs_class (gimple_assign_rhs_code (stmt)))
{
case GIMPLE_SINGLE_RHS:
op_type = TREE_OPERAND_LENGTH (gimple_assign_rhs1 (stmt));
if (op_type == ternary_op)
{
tree rhs = gimple_assign_rhs1 (stmt);
ops[0] = TREE_OPERAND (rhs, 0);
ops[1] = TREE_OPERAND (rhs, 1);
ops[2] = TREE_OPERAND (rhs, 2);
code = TREE_CODE (rhs);
}
else
return false;
break;
case GIMPLE_BINARY_RHS:
code = gimple_assign_rhs_code (stmt);
op_type = TREE_CODE_LENGTH (code);
gcc_assert (op_type == binary_op);
ops[0] = gimple_assign_rhs1 (stmt);
ops[1] = gimple_assign_rhs2 (stmt);
break;
case GIMPLE_TERNARY_RHS:
code = gimple_assign_rhs_code (stmt);
op_type = TREE_CODE_LENGTH (code);
gcc_assert (op_type == ternary_op);
ops[0] = gimple_assign_rhs1 (stmt);
ops[1] = gimple_assign_rhs2 (stmt);
ops[2] = gimple_assign_rhs3 (stmt);
break;
case GIMPLE_UNARY_RHS:
return false;
default:
gcc_unreachable ();
}
if (code == COND_EXPR && slp_node)
return false;
scalar_dest = gimple_assign_lhs (stmt);
scalar_type = TREE_TYPE (scalar_dest);
if (!POINTER_TYPE_P (scalar_type) && !INTEGRAL_TYPE_P (scalar_type)
&& !SCALAR_FLOAT_TYPE_P (scalar_type))
return false;
/* Do not try to vectorize bit-precision reductions. */
if ((TYPE_PRECISION (scalar_type)
!= GET_MODE_PRECISION (TYPE_MODE (scalar_type))))
return false;
/* All uses but the last are expected to be defined in the loop.
The last use is the reduction variable. In case of nested cycle this
assumption is not true: we use reduc_index to record the index of the
reduction variable. */
for (i = 0; i < op_type - 1; i++)
{
/* The condition of COND_EXPR is checked in vectorizable_condition(). */
if (i == 0 && code == COND_EXPR)
continue;
is_simple_use = vect_is_simple_use_1 (ops[i], stmt, loop_vinfo, NULL,
&def_stmt, &def, &dt, &tem);
if (!vectype_in)
vectype_in = tem;
gcc_assert (is_simple_use);
if (dt != vect_internal_def
&& dt != vect_external_def
&& dt != vect_constant_def
&& dt != vect_induction_def
&& !(dt == vect_nested_cycle && nested_cycle))
return false;
if (dt == vect_nested_cycle)
{
found_nested_cycle_def = true;
reduc_def_stmt = def_stmt;
reduc_index = i;
}
}
is_simple_use = vect_is_simple_use_1 (ops[i], stmt, loop_vinfo, NULL,
&def_stmt, &def, &dt, &tem);
if (!vectype_in)
vectype_in = tem;
gcc_assert (is_simple_use);
if (!found_nested_cycle_def)
reduc_def_stmt = def_stmt;
if (reduc_def_stmt && gimple_code (reduc_def_stmt) != GIMPLE_PHI)
return false;
if (!(dt == vect_reduction_def
|| dt == vect_nested_cycle
|| ((dt == vect_internal_def || dt == vect_external_def
|| dt == vect_constant_def || dt == vect_induction_def)
&& nested_cycle && found_nested_cycle_def)))
{
/* For pattern recognized stmts, orig_stmt might be a reduction,
but some helper statements for the pattern might not, or
might be COND_EXPRs with reduction uses in the condition. */
gcc_assert (orig_stmt);
return false;
}
if (orig_stmt)
gcc_assert (orig_stmt == vect_is_simple_reduction (loop_vinfo,
reduc_def_stmt,
!nested_cycle,
&dummy));
else
{
gimple tmp = vect_is_simple_reduction (loop_vinfo, reduc_def_stmt,
!nested_cycle, &dummy);
/* We changed STMT to be the first stmt in reduction chain, hence we
check that in this case the first element in the chain is STMT. */
gcc_assert (stmt == tmp
|| GROUP_FIRST_ELEMENT (vinfo_for_stmt (tmp)) == stmt);
}
if (STMT_VINFO_LIVE_P (vinfo_for_stmt (reduc_def_stmt)))
return false;
if (slp_node || PURE_SLP_STMT (stmt_info))
ncopies = 1;
else
ncopies = (LOOP_VINFO_VECT_FACTOR (loop_vinfo)
/ TYPE_VECTOR_SUBPARTS (vectype_in));
gcc_assert (ncopies >= 1);
vec_mode = TYPE_MODE (vectype_in);
if (code == COND_EXPR)
{
if (!vectorizable_condition (stmt, gsi, NULL, ops[reduc_index], 0, NULL))
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"unsupported condition in reduction\n");
return false;
}
}
else
{
/* 4. Supportable by target? */
if (code == LSHIFT_EXPR || code == RSHIFT_EXPR
|| code == LROTATE_EXPR || code == RROTATE_EXPR)
{
/* Shifts and rotates are only supported by vectorizable_shifts,
not vectorizable_reduction. */
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"unsupported shift or rotation.\n");
return false;
}
/* 4.1. check support for the operation in the loop */
optab = optab_for_tree_code (code, vectype_in, optab_default);
if (!optab)
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"no optab.\n");
return false;
}
if (optab_handler (optab, vec_mode) == CODE_FOR_nothing)
{
if (dump_enabled_p ())
dump_printf (MSG_NOTE, "op not supported by target.\n");
if (GET_MODE_SIZE (vec_mode) != UNITS_PER_WORD
|| LOOP_VINFO_VECT_FACTOR (loop_vinfo)
< vect_min_worthwhile_factor (code))
return false;
if (dump_enabled_p ())
dump_printf (MSG_NOTE, "proceeding using word mode.\n");
}
/* Worthwhile without SIMD support? */
if (!VECTOR_MODE_P (TYPE_MODE (vectype_in))
&& LOOP_VINFO_VECT_FACTOR (loop_vinfo)
< vect_min_worthwhile_factor (code))
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"not worthwhile without SIMD support.\n");
return false;
}
}
/* 4.2. Check support for the epilog operation.
If STMT represents a reduction pattern, then the type of the
reduction variable may be different than the type of the rest
of the arguments. For example, consider the case of accumulation
of shorts into an int accumulator; The original code:
S1: int_a = (int) short_a;
orig_stmt-> S2: int_acc = plus <int_a ,int_acc>;
was replaced with:
STMT: int_acc = widen_sum <short_a, int_acc>
This means that:
1. The tree-code that is used to create the vector operation in the
epilog code (that reduces the partial results) is not the
tree-code of STMT, but is rather the tree-code of the original
stmt from the pattern that STMT is replacing. I.e, in the example
above we want to use 'widen_sum' in the loop, but 'plus' in the
epilog.
2. The type (mode) we use to check available target support
for the vector operation to be created in the *epilog*, is
determined by the type of the reduction variable (in the example
above we'd check this: optab_handler (plus_optab, vect_int_mode])).
However the type (mode) we use to check available target support
for the vector operation to be created *inside the loop*, is
determined by the type of the other arguments to STMT (in the
example we'd check this: optab_handler (widen_sum_optab,
vect_short_mode)).
This is contrary to "regular" reductions, in which the types of all
the arguments are the same as the type of the reduction variable.
For "regular" reductions we can therefore use the same vector type
(and also the same tree-code) when generating the epilog code and
when generating the code inside the loop. */
if (orig_stmt)
{
/* This is a reduction pattern: get the vectype from the type of the
reduction variable, and get the tree-code from orig_stmt. */
orig_code = gimple_assign_rhs_code (orig_stmt);
gcc_assert (vectype_out);
vec_mode = TYPE_MODE (vectype_out);
}
else
{
/* Regular reduction: use the same vectype and tree-code as used for
the vector code inside the loop can be used for the epilog code. */
orig_code = code;
}
if (nested_cycle)
{
def_bb = gimple_bb (reduc_def_stmt);
def_stmt_loop = def_bb->loop_father;
def_arg = PHI_ARG_DEF_FROM_EDGE (reduc_def_stmt,
loop_preheader_edge (def_stmt_loop));
if (TREE_CODE (def_arg) == SSA_NAME
&& (def_arg_stmt = SSA_NAME_DEF_STMT (def_arg))
&& gimple_code (def_arg_stmt) == GIMPLE_PHI
&& flow_bb_inside_loop_p (outer_loop, gimple_bb (def_arg_stmt))
&& vinfo_for_stmt (def_arg_stmt)
&& STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def_arg_stmt))
== vect_double_reduction_def)
double_reduc = true;
}
epilog_reduc_code = ERROR_MARK;
if (reduction_code_for_scalar_code (orig_code, &epilog_reduc_code))
{
reduc_optab = optab_for_tree_code (epilog_reduc_code, vectype_out,
optab_default);
if (!reduc_optab)
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"no optab for reduction.\n");
epilog_reduc_code = ERROR_MARK;
}
else if (optab_handler (reduc_optab, vec_mode) == CODE_FOR_nothing)
{
optab = scalar_reduc_to_vector (reduc_optab, vectype_out);
if (optab_handler (optab, vec_mode) == CODE_FOR_nothing)
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"reduc op not supported by target.\n");
epilog_reduc_code = ERROR_MARK;
}
}
}
else
{
if (!nested_cycle || double_reduc)
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"no reduc code for scalar code.\n");
return false;
}
}
if (double_reduc && ncopies > 1)
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"multiple types in double reduction\n");
return false;
}
/* In case of widenning multiplication by a constant, we update the type
of the constant to be the type of the other operand. We check that the
constant fits the type in the pattern recognition pass. */
if (code == DOT_PROD_EXPR
&& !types_compatible_p (TREE_TYPE (ops[0]), TREE_TYPE (ops[1])))
{
if (TREE_CODE (ops[0]) == INTEGER_CST)
ops[0] = fold_convert (TREE_TYPE (ops[1]), ops[0]);
else if (TREE_CODE (ops[1]) == INTEGER_CST)
ops[1] = fold_convert (TREE_TYPE (ops[0]), ops[1]);
else
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"invalid types in dot-prod\n");
return false;
}
}
if (!vec_stmt) /* transformation not required. */
{
if (!vect_model_reduction_cost (stmt_info, epilog_reduc_code, ncopies))
return false;
STMT_VINFO_TYPE (stmt_info) = reduc_vec_info_type;
return true;
}
/** Transform. **/
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location, "transform reduction.\n");
/* FORNOW: Multiple types are not supported for condition. */
if (code == COND_EXPR)
gcc_assert (ncopies == 1);
/* Create the destination vector */
vec_dest = vect_create_destination_var (scalar_dest, vectype_out);
/* In case the vectorization factor (VF) is bigger than the number
of elements that we can fit in a vectype (nunits), we have to generate
more than one vector stmt - i.e - we need to "unroll" the
vector stmt by a factor VF/nunits. For more details see documentation
in vectorizable_operation. */
/* If the reduction is used in an outer loop we need to generate
VF intermediate results, like so (e.g. for ncopies=2):
r0 = phi (init, r0)
r1 = phi (init, r1)
r0 = x0 + r0;
r1 = x1 + r1;
(i.e. we generate VF results in 2 registers).
In this case we have a separate def-use cycle for each copy, and therefore
for each copy we get the vector def for the reduction variable from the
respective phi node created for this copy.
Otherwise (the reduction is unused in the loop nest), we can combine
together intermediate results, like so (e.g. for ncopies=2):
r = phi (init, r)
r = x0 + r;
r = x1 + r;
(i.e. we generate VF/2 results in a single register).
In this case for each copy we get the vector def for the reduction variable
from the vectorized reduction operation generated in the previous iteration.
*/
if (STMT_VINFO_RELEVANT (stmt_info) == vect_unused_in_scope)
{
single_defuse_cycle = true;
epilog_copies = 1;
}
else
epilog_copies = ncopies;
prev_stmt_info = NULL;
prev_phi_info = NULL;
if (slp_node)
{
vec_num = SLP_TREE_NUMBER_OF_VEC_STMTS (slp_node);
gcc_assert (TYPE_VECTOR_SUBPARTS (vectype_out)
== TYPE_VECTOR_SUBPARTS (vectype_in));
}
else
{
vec_num = 1;
vec_oprnds0.create (1);
if (op_type == ternary_op)
vec_oprnds1.create (1);
}
phis.create (vec_num);
vect_defs.create (vec_num);
if (!slp_node)
vect_defs.quick_push (NULL_TREE);
for (j = 0; j < ncopies; j++)
{
if (j == 0 || !single_defuse_cycle)
{
for (i = 0; i < vec_num; i++)
{
/* Create the reduction-phi that defines the reduction
operand. */
new_phi = create_phi_node (vec_dest, loop->header);
set_vinfo_for_stmt (new_phi,
new_stmt_vec_info (new_phi, loop_vinfo,
NULL));
if (j == 0 || slp_node)
phis.quick_push (new_phi);
}
}
if (code == COND_EXPR)
{
gcc_assert (!slp_node);
vectorizable_condition (stmt, gsi, vec_stmt,
PHI_RESULT (phis[0]),
reduc_index, NULL);
/* Multiple types are not supported for condition. */
break;
}
/* Handle uses. */
if (j == 0)
{
op0 = ops[!reduc_index];
if (op_type == ternary_op)
{
if (reduc_index == 0)
op1 = ops[2];
else
op1 = ops[1];
}
if (slp_node)
vect_get_vec_defs (op0, op1, stmt, &vec_oprnds0, &vec_oprnds1,
slp_node, -1);
else
{
loop_vec_def0 = vect_get_vec_def_for_operand (ops[!reduc_index],
stmt, NULL);
vec_oprnds0.quick_push (loop_vec_def0);
if (op_type == ternary_op)
{
loop_vec_def1 = vect_get_vec_def_for_operand (op1, stmt,
NULL);
vec_oprnds1.quick_push (loop_vec_def1);
}
}
}
else
{
if (!slp_node)
{
enum vect_def_type dt;
gimple dummy_stmt;
tree dummy;
vect_is_simple_use (ops[!reduc_index], stmt, loop_vinfo, NULL,
&dummy_stmt, &dummy, &dt);
loop_vec_def0 = vect_get_vec_def_for_stmt_copy (dt,
loop_vec_def0);
vec_oprnds0[0] = loop_vec_def0;
if (op_type == ternary_op)
{
vect_is_simple_use (op1, stmt, loop_vinfo, NULL, &dummy_stmt,
&dummy, &dt);
loop_vec_def1 = vect_get_vec_def_for_stmt_copy (dt,
loop_vec_def1);
vec_oprnds1[0] = loop_vec_def1;
}
}
if (single_defuse_cycle)
reduc_def = gimple_assign_lhs (new_stmt);
STMT_VINFO_RELATED_STMT (prev_phi_info) = new_phi;
}
FOR_EACH_VEC_ELT (vec_oprnds0, i, def0)
{
if (slp_node)
reduc_def = PHI_RESULT (phis[i]);
else
{
if (!single_defuse_cycle || j == 0)
reduc_def = PHI_RESULT (new_phi);
}
def1 = ((op_type == ternary_op)
? vec_oprnds1[i] : NULL);
if (op_type == binary_op)
{
if (reduc_index == 0)
expr = build2 (code, vectype_out, reduc_def, def0);
else
expr = build2 (code, vectype_out, def0, reduc_def);
}
else
{
if (reduc_index == 0)
expr = build3 (code, vectype_out, reduc_def, def0, def1);
else
{
if (reduc_index == 1)
expr = build3 (code, vectype_out, def0, reduc_def, def1);
else
expr = build3 (code, vectype_out, def0, def1, reduc_def);
}
}
new_stmt = gimple_build_assign (vec_dest, expr);
new_temp = make_ssa_name (vec_dest, new_stmt);
gimple_assign_set_lhs (new_stmt, new_temp);
vect_finish_stmt_generation (stmt, new_stmt, gsi);
if (slp_node)
{
SLP_TREE_VEC_STMTS (slp_node).quick_push (new_stmt);
vect_defs.quick_push (new_temp);
}
else
vect_defs[0] = new_temp;
}
if (slp_node)
continue;
if (j == 0)
STMT_VINFO_VEC_STMT (stmt_info) = *vec_stmt = new_stmt;
else
STMT_VINFO_RELATED_STMT (prev_stmt_info) = new_stmt;
prev_stmt_info = vinfo_for_stmt (new_stmt);
prev_phi_info = vinfo_for_stmt (new_phi);
}
/* Finalize the reduction-phi (set its arguments) and create the
epilog reduction code. */
if ((!single_defuse_cycle || code == COND_EXPR) && !slp_node)
{
new_temp = gimple_assign_lhs (*vec_stmt);
vect_defs[0] = new_temp;
}
vect_create_epilog_for_reduction (vect_defs, stmt, epilog_copies,
epilog_reduc_code, phis, reduc_index,
double_reduc, slp_node);
return true;
}
/* Function vect_min_worthwhile_factor.
For a loop where we could vectorize the operation indicated by CODE,
return the minimum vectorization factor that makes it worthwhile
to use generic vectors. */
int
vect_min_worthwhile_factor (enum tree_code code)
{
switch (code)
{
case PLUS_EXPR:
case MINUS_EXPR:
case NEGATE_EXPR:
return 4;
case BIT_AND_EXPR:
case BIT_IOR_EXPR:
case BIT_XOR_EXPR:
case BIT_NOT_EXPR:
return 2;
default:
return INT_MAX;
}
}
/* Function vectorizable_induction
Check if PHI performs an induction computation that can be vectorized.
If VEC_STMT is also passed, vectorize the induction PHI: create a vectorized
phi to replace it, put it in VEC_STMT, and add it to the same basic block.
Return FALSE if not a vectorizable STMT, TRUE otherwise. */
bool
vectorizable_induction (gimple phi, gimple_stmt_iterator *gsi ATTRIBUTE_UNUSED,
gimple *vec_stmt)
{
stmt_vec_info stmt_info = vinfo_for_stmt (phi);
tree vectype = STMT_VINFO_VECTYPE (stmt_info);
loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info);
struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
int nunits = TYPE_VECTOR_SUBPARTS (vectype);
int ncopies = LOOP_VINFO_VECT_FACTOR (loop_vinfo) / nunits;
tree vec_def;
gcc_assert (ncopies >= 1);
/* FORNOW. These restrictions should be relaxed. */
if (nested_in_vect_loop_p (loop, phi))
{
imm_use_iterator imm_iter;
use_operand_p use_p;
gimple exit_phi;
edge latch_e;
tree loop_arg;
if (ncopies > 1)
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"multiple types in nested loop.\n");
return false;
}
exit_phi = NULL;
latch_e = loop_latch_edge (loop->inner);
loop_arg = PHI_ARG_DEF_FROM_EDGE (phi, latch_e);
FOR_EACH_IMM_USE_FAST (use_p, imm_iter, loop_arg)
{
gimple use_stmt = USE_STMT (use_p);
if (is_gimple_debug (use_stmt))
continue;
if (!flow_bb_inside_loop_p (loop->inner, gimple_bb (use_stmt)))
{
exit_phi = use_stmt;
break;
}
}
if (exit_phi)
{
stmt_vec_info exit_phi_vinfo = vinfo_for_stmt (exit_phi);
if (!(STMT_VINFO_RELEVANT_P (exit_phi_vinfo)
&& !STMT_VINFO_LIVE_P (exit_phi_vinfo)))
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"inner-loop induction only used outside "
"of the outer vectorized loop.\n");
return false;
}
}
}
if (!STMT_VINFO_RELEVANT_P (stmt_info))
return false;
/* FORNOW: SLP not supported. */
if (STMT_SLP_TYPE (stmt_info))
return false;
gcc_assert (STMT_VINFO_DEF_TYPE (stmt_info) == vect_induction_def);
if (gimple_code (phi) != GIMPLE_PHI)
return false;
if (!vec_stmt) /* transformation not required. */
{
STMT_VINFO_TYPE (stmt_info) = induc_vec_info_type;
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"=== vectorizable_induction ===\n");
vect_model_induction_cost (stmt_info, ncopies);
return true;
}
/** Transform. **/
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location, "transform induction phi.\n");
vec_def = get_initial_def_for_induction (phi);
*vec_stmt = SSA_NAME_DEF_STMT (vec_def);
return true;
}
/* Function vectorizable_live_operation.
STMT computes a value that is used outside the loop. Check if
it can be supported. */
bool
vectorizable_live_operation (gimple stmt,
gimple_stmt_iterator *gsi ATTRIBUTE_UNUSED,
gimple *vec_stmt)
{
stmt_vec_info stmt_info = vinfo_for_stmt (stmt);
loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info);
struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
int i;
int op_type;
tree op;
tree def;
gimple def_stmt;
enum vect_def_type dt;
enum tree_code code;
enum gimple_rhs_class rhs_class;
gcc_assert (STMT_VINFO_LIVE_P (stmt_info));
if (STMT_VINFO_DEF_TYPE (stmt_info) == vect_reduction_def)
return false;
if (!is_gimple_assign (stmt))
{
if (gimple_call_internal_p (stmt)
&& gimple_call_internal_fn (stmt) == IFN_GOMP_SIMD_LANE
&& gimple_call_lhs (stmt)
&& loop->simduid
&& TREE_CODE (gimple_call_arg (stmt, 0)) == SSA_NAME
&& loop->simduid
== SSA_NAME_VAR (gimple_call_arg (stmt, 0)))
{
edge e = single_exit (loop);
basic_block merge_bb = e->dest;
imm_use_iterator imm_iter;
use_operand_p use_p;
tree lhs = gimple_call_lhs (stmt);
FOR_EACH_IMM_USE_FAST (use_p, imm_iter, lhs)
{
gimple use_stmt = USE_STMT (use_p);
if (gimple_code (use_stmt) == GIMPLE_PHI
&& gimple_bb (use_stmt) == merge_bb)
{
if (vec_stmt)
{
tree vfm1
= build_int_cst (unsigned_type_node,
loop_vinfo->vectorization_factor - 1);
SET_PHI_ARG_DEF (use_stmt, e->dest_idx, vfm1);
}
return true;
}
}
}
return false;
}
if (TREE_CODE (gimple_assign_lhs (stmt)) != SSA_NAME)
return false;
/* FORNOW. CHECKME. */
if (nested_in_vect_loop_p (loop, stmt))
return false;
code = gimple_assign_rhs_code (stmt);
op_type = TREE_CODE_LENGTH (code);
rhs_class = get_gimple_rhs_class (code);
gcc_assert (rhs_class != GIMPLE_UNARY_RHS || op_type == unary_op);
gcc_assert (rhs_class != GIMPLE_BINARY_RHS || op_type == binary_op);
/* FORNOW: support only if all uses are invariant. This means
that the scalar operations can remain in place, unvectorized.
The original last scalar value that they compute will be used. */
for (i = 0; i < op_type; i++)
{
if (rhs_class == GIMPLE_SINGLE_RHS)
op = TREE_OPERAND (gimple_op (stmt, 1), i);
else
op = gimple_op (stmt, i + 1);
if (op
&& !vect_is_simple_use (op, stmt, loop_vinfo, NULL, &def_stmt, &def,
&dt))
{
if (dump_enabled_p ())
dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
"use not simple.\n");
return false;
}
if (dt != vect_external_def && dt != vect_constant_def)
return false;
}
/* No transformation is required for the cases we currently support. */
return true;
}
/* Kill any debug uses outside LOOP of SSA names defined in STMT. */
static void
vect_loop_kill_debug_uses (struct loop *loop, gimple stmt)
{
ssa_op_iter op_iter;
imm_use_iterator imm_iter;
def_operand_p def_p;
gimple ustmt;
FOR_EACH_PHI_OR_STMT_DEF (def_p, stmt, op_iter, SSA_OP_DEF)
{
FOR_EACH_IMM_USE_STMT (ustmt, imm_iter, DEF_FROM_PTR (def_p))
{
basic_block bb;
if (!is_gimple_debug (ustmt))
continue;
bb = gimple_bb (ustmt);
if (!flow_bb_inside_loop_p (loop, bb))
{
if (gimple_debug_bind_p (ustmt))
{
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"killing debug use\n");
gimple_debug_bind_reset_value (ustmt);
update_stmt (ustmt);
}
else
gcc_unreachable ();
}
}
}
}
/* This function builds ni_name = number of iterations. Statements
are emitted on the loop preheader edge. */
static tree
vect_build_loop_niters (loop_vec_info loop_vinfo)
{
tree ni = unshare_expr (LOOP_VINFO_NITERS (loop_vinfo));
if (TREE_CODE (ni) == INTEGER_CST)
return ni;
else
{
tree ni_name, var;
gimple_seq stmts = NULL;
edge pe = loop_preheader_edge (LOOP_VINFO_LOOP (loop_vinfo));
var = create_tmp_var (TREE_TYPE (ni), "niters");
ni_name = force_gimple_operand (ni, &stmts, false, var);
if (stmts)
gsi_insert_seq_on_edge_immediate (pe, stmts);
return ni_name;
}
}
/* This function generates the following statements:
ni_name = number of iterations loop executes
ratio = ni_name / vf
ratio_mult_vf_name = ratio * vf
and places them on the loop preheader edge. */
static void
vect_generate_tmps_on_preheader (loop_vec_info loop_vinfo,
tree ni_name,
tree *ratio_mult_vf_name_ptr,
tree *ratio_name_ptr)
{
tree ni_minus_gap_name;
tree var;
tree ratio_name;
tree ratio_mult_vf_name;
int vf = LOOP_VINFO_VECT_FACTOR (loop_vinfo);
edge pe = loop_preheader_edge (LOOP_VINFO_LOOP (loop_vinfo));
tree log_vf;
log_vf = build_int_cst (TREE_TYPE (ni_name), exact_log2 (vf));
/* If epilogue loop is required because of data accesses with gaps, we
subtract one iteration from the total number of iterations here for
correct calculation of RATIO. */
if (LOOP_VINFO_PEELING_FOR_GAPS (loop_vinfo))
{
ni_minus_gap_name = fold_build2 (MINUS_EXPR, TREE_TYPE (ni_name),
ni_name,
build_one_cst (TREE_TYPE (ni_name)));
if (!is_gimple_val (ni_minus_gap_name))
{
var = create_tmp_var (TREE_TYPE (ni_name), "ni_gap");
gimple stmts = NULL;
ni_minus_gap_name = force_gimple_operand (ni_minus_gap_name, &stmts,
true, var);
gsi_insert_seq_on_edge_immediate (pe, stmts);
}
}
else
ni_minus_gap_name = ni_name;
/* Create: ratio = ni >> log2(vf) */
/* ??? As we have ni == number of latch executions + 1, ni could
have overflown to zero. So avoid computing ratio based on ni
but compute it using the fact that we know ratio will be at least
one, thus via (ni - vf) >> log2(vf) + 1. */
ratio_name
= fold_build2 (PLUS_EXPR, TREE_TYPE (ni_name),
fold_build2 (RSHIFT_EXPR, TREE_TYPE (ni_name),
fold_build2 (MINUS_EXPR, TREE_TYPE (ni_name),
ni_minus_gap_name,
build_int_cst
(TREE_TYPE (ni_name), vf)),
log_vf),
build_int_cst (TREE_TYPE (ni_name), 1));
if (!is_gimple_val (ratio_name))
{
var = create_tmp_var (TREE_TYPE (ni_name), "bnd");
gimple stmts = NULL;
ratio_name = force_gimple_operand (ratio_name, &stmts, true, var);
gsi_insert_seq_on_edge_immediate (pe, stmts);
}
*ratio_name_ptr = ratio_name;
/* Create: ratio_mult_vf = ratio << log2 (vf). */
if (ratio_mult_vf_name_ptr)
{
ratio_mult_vf_name = fold_build2 (LSHIFT_EXPR, TREE_TYPE (ratio_name),
ratio_name, log_vf);
if (!is_gimple_val (ratio_mult_vf_name))
{
var = create_tmp_var (TREE_TYPE (ni_name), "ratio_mult_vf");
gimple stmts = NULL;
ratio_mult_vf_name = force_gimple_operand (ratio_mult_vf_name, &stmts,
true, var);
gsi_insert_seq_on_edge_immediate (pe, stmts);
}
*ratio_mult_vf_name_ptr = ratio_mult_vf_name;
}
return;
}
/* Function vect_transform_loop.
The analysis phase has determined that the loop is vectorizable.
Vectorize the loop - created vectorized stmts to replace the scalar
stmts in the loop, and update the loop exit condition. */
void
vect_transform_loop (loop_vec_info loop_vinfo)
{
struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
basic_block *bbs = LOOP_VINFO_BBS (loop_vinfo);
int nbbs = loop->num_nodes;
int i;
tree ratio = NULL;
int vectorization_factor = LOOP_VINFO_VECT_FACTOR (loop_vinfo);
bool grouped_store;
bool slp_scheduled = false;
gimple stmt, pattern_stmt;
gimple_seq pattern_def_seq = NULL;
gimple_stmt_iterator pattern_def_si = gsi_none ();
bool transform_pattern_stmt = false;
bool check_profitability = false;
int th;
/* Record number of iterations before we started tampering with the profile. */
gcov_type expected_iterations = expected_loop_iterations_unbounded (loop);
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location, "=== vec_transform_loop ===\n");
/* If profile is inprecise, we have chance to fix it up. */
if (LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo))
expected_iterations = LOOP_VINFO_INT_NITERS (loop_vinfo);
/* Use the more conservative vectorization threshold. If the number
of iterations is constant assume the cost check has been performed
by our caller. If the threshold makes all loops profitable that
run at least the vectorization factor number of times checking
is pointless, too. */
th = LOOP_VINFO_COST_MODEL_THRESHOLD (loop_vinfo);
if (th >= LOOP_VINFO_VECT_FACTOR (loop_vinfo) - 1
&& !LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo))
{
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"Profitability threshold is %d loop iterations.\n",
th);
check_profitability = true;
}
/* Version the loop first, if required, so the profitability check
comes first. */
if (LOOP_REQUIRES_VERSIONING_FOR_ALIGNMENT (loop_vinfo)
|| LOOP_REQUIRES_VERSIONING_FOR_ALIAS (loop_vinfo))
{
vect_loop_versioning (loop_vinfo, th, check_profitability);
check_profitability = false;
}
tree ni_name = vect_build_loop_niters (loop_vinfo);
LOOP_VINFO_NITERS_UNCHANGED (loop_vinfo) = ni_name;
/* Peel the loop if there are data refs with unknown alignment.
Only one data ref with unknown store is allowed. */
if (LOOP_VINFO_PEELING_FOR_ALIGNMENT (loop_vinfo))
{
vect_do_peeling_for_alignment (loop_vinfo, ni_name,
th, check_profitability);
check_profitability = false;
/* The above adjusts LOOP_VINFO_NITERS, so cause ni_name to
be re-computed. */
ni_name = NULL_TREE;
}
/* If the loop has a symbolic number of iterations 'n' (i.e. it's not a
compile time constant), or it is a constant that doesn't divide by the
vectorization factor, then an epilog loop needs to be created.
We therefore duplicate the loop: the original loop will be vectorized,
and will compute the first (n/VF) iterations. The second copy of the loop
will remain scalar and will compute the remaining (n%VF) iterations.
(VF is the vectorization factor). */
if (LOOP_VINFO_PEELING_FOR_NITER (loop_vinfo)
|| LOOP_VINFO_PEELING_FOR_GAPS (loop_vinfo))
{
tree ratio_mult_vf;
if (!ni_name)
ni_name = vect_build_loop_niters (loop_vinfo);
vect_generate_tmps_on_preheader (loop_vinfo, ni_name, &ratio_mult_vf,
&ratio);
vect_do_peeling_for_loop_bound (loop_vinfo, ni_name, ratio_mult_vf,
th, check_profitability);
}
else if (LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo))
ratio = build_int_cst (TREE_TYPE (LOOP_VINFO_NITERS (loop_vinfo)),
LOOP_VINFO_INT_NITERS (loop_vinfo) / vectorization_factor);
else
{
if (!ni_name)
ni_name = vect_build_loop_niters (loop_vinfo);
vect_generate_tmps_on_preheader (loop_vinfo, ni_name, NULL, &ratio);
}
/* 1) Make sure the loop header has exactly two entries
2) Make sure we have a preheader basic block. */
gcc_assert (EDGE_COUNT (loop->header->preds) == 2);
split_edge (loop_preheader_edge (loop));
/* FORNOW: the vectorizer supports only loops which body consist
of one basic block (header + empty latch). When the vectorizer will
support more involved loop forms, the order by which the BBs are
traversed need to be reconsidered. */
for (i = 0; i < nbbs; i++)
{
basic_block bb = bbs[i];
stmt_vec_info stmt_info;
for (gphi_iterator si = gsi_start_phis (bb); !gsi_end_p (si);
gsi_next (&si))
{
gphi *phi = si.phi ();
if (dump_enabled_p ())
{
dump_printf_loc (MSG_NOTE, vect_location,
"------>vectorizing phi: ");
dump_gimple_stmt (MSG_NOTE, TDF_SLIM, phi, 0);
dump_printf (MSG_NOTE, "\n");
}
stmt_info = vinfo_for_stmt (phi);
if (!stmt_info)
continue;
if (MAY_HAVE_DEBUG_STMTS && !STMT_VINFO_LIVE_P (stmt_info))
vect_loop_kill_debug_uses (loop, phi);
if (!STMT_VINFO_RELEVANT_P (stmt_info)
&& !STMT_VINFO_LIVE_P (stmt_info))
continue;
if (STMT_VINFO_VECTYPE (stmt_info)
&& (TYPE_VECTOR_SUBPARTS (STMT_VINFO_VECTYPE (stmt_info))
!= (unsigned HOST_WIDE_INT) vectorization_factor)
&& dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location, "multiple-types.\n");
if (STMT_VINFO_DEF_TYPE (stmt_info) == vect_induction_def)
{
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location, "transform phi.\n");
vect_transform_stmt (phi, NULL, NULL, NULL, NULL);
}
}
pattern_stmt = NULL;
for (gimple_stmt_iterator si = gsi_start_bb (bb);
!gsi_end_p (si) || transform_pattern_stmt;)
{
bool is_store;
if (transform_pattern_stmt)
stmt = pattern_stmt;
else
{
stmt = gsi_stmt (si);
/* During vectorization remove existing clobber stmts. */
if (gimple_clobber_p (stmt))
{
unlink_stmt_vdef (stmt);
gsi_remove (&si, true);
release_defs (stmt);
continue;
}
}
if (dump_enabled_p ())
{
dump_printf_loc (MSG_NOTE, vect_location,
"------>vectorizing statement: ");
dump_gimple_stmt (MSG_NOTE, TDF_SLIM, stmt, 0);
dump_printf (MSG_NOTE, "\n");
}
stmt_info = vinfo_for_stmt (stmt);
/* vector stmts created in the outer-loop during vectorization of
stmts in an inner-loop may not have a stmt_info, and do not
need to be vectorized. */
if (!stmt_info)
{
gsi_next (&si);
continue;
}
if (MAY_HAVE_DEBUG_STMTS && !STMT_VINFO_LIVE_P (stmt_info))
vect_loop_kill_debug_uses (loop, stmt);
if (!STMT_VINFO_RELEVANT_P (stmt_info)
&& !STMT_VINFO_LIVE_P (stmt_info))
{
if (STMT_VINFO_IN_PATTERN_P (stmt_info)
&& (pattern_stmt = STMT_VINFO_RELATED_STMT (stmt_info))
&& (STMT_VINFO_RELEVANT_P (vinfo_for_stmt (pattern_stmt))
|| STMT_VINFO_LIVE_P (vinfo_for_stmt (pattern_stmt))))
{
stmt = pattern_stmt;
stmt_info = vinfo_for_stmt (stmt);
}
else
{
gsi_next (&si);
continue;
}
}
else if (STMT_VINFO_IN_PATTERN_P (stmt_info)
&& (pattern_stmt = STMT_VINFO_RELATED_STMT (stmt_info))
&& (STMT_VINFO_RELEVANT_P (vinfo_for_stmt (pattern_stmt))
|| STMT_VINFO_LIVE_P (vinfo_for_stmt (pattern_stmt))))
transform_pattern_stmt = true;
/* If pattern statement has def stmts, vectorize them too. */
if (is_pattern_stmt_p (stmt_info))
{
if (pattern_def_seq == NULL)
{
pattern_def_seq = STMT_VINFO_PATTERN_DEF_SEQ (stmt_info);
pattern_def_si = gsi_start (pattern_def_seq);
}
else if (!gsi_end_p (pattern_def_si))
gsi_next (&pattern_def_si);
if (pattern_def_seq != NULL)
{
gimple pattern_def_stmt = NULL;
stmt_vec_info pattern_def_stmt_info = NULL;
while (!gsi_end_p (pattern_def_si))
{
pattern_def_stmt = gsi_stmt (pattern_def_si);
pattern_def_stmt_info
= vinfo_for_stmt (pattern_def_stmt);
if (STMT_VINFO_RELEVANT_P (pattern_def_stmt_info)
|| STMT_VINFO_LIVE_P (pattern_def_stmt_info))
break;
gsi_next (&pattern_def_si);
}
if (!gsi_end_p (pattern_def_si))
{
if (dump_enabled_p ())
{
dump_printf_loc (MSG_NOTE, vect_location,
"==> vectorizing pattern def "
"stmt: ");
dump_gimple_stmt (MSG_NOTE, TDF_SLIM,
pattern_def_stmt, 0);
dump_printf (MSG_NOTE, "\n");
}
stmt = pattern_def_stmt;
stmt_info = pattern_def_stmt_info;
}
else
{
pattern_def_si = gsi_none ();
transform_pattern_stmt = false;
}
}
else
transform_pattern_stmt = false;
}
if (STMT_VINFO_VECTYPE (stmt_info))
{
unsigned int nunits
= (unsigned int)
TYPE_VECTOR_SUBPARTS (STMT_VINFO_VECTYPE (stmt_info));
if (!STMT_SLP_TYPE (stmt_info)
&& nunits != (unsigned int) vectorization_factor
&& dump_enabled_p ())
/* For SLP VF is set according to unrolling factor, and not
to vector size, hence for SLP this print is not valid. */
dump_printf_loc (MSG_NOTE, vect_location, "multiple-types.\n");
}
/* SLP. Schedule all the SLP instances when the first SLP stmt is
reached. */
if (STMT_SLP_TYPE (stmt_info))
{
if (!slp_scheduled)
{
slp_scheduled = true;
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location,
"=== scheduling SLP instances ===\n");
vect_schedule_slp (loop_vinfo, NULL);
}
/* Hybrid SLP stmts must be vectorized in addition to SLP. */
if (!vinfo_for_stmt (stmt) || PURE_SLP_STMT (stmt_info))
{
if (!transform_pattern_stmt && gsi_end_p (pattern_def_si))
{
pattern_def_seq = NULL;
gsi_next (&si);
}
continue;
}
}
/* -------- vectorize statement ------------ */
if (dump_enabled_p ())
dump_printf_loc (MSG_NOTE, vect_location, "transform statement.\n");
grouped_store = false;
is_store = vect_transform_stmt (stmt, &si, &grouped_store, NULL, NULL);
if (is_store)
{
if (STMT_VINFO_GROUPED_ACCESS (stmt_info))
{
/* Interleaving. If IS_STORE is TRUE, the vectorization of the
interleaving chain was completed - free all the stores in
the chain. */
gsi_next (&si);
vect_remove_stores (GROUP_FIRST_ELEMENT (stmt_info));
}
else
{
/* Free the attached stmt_vec_info and remove the stmt. */
gimple store = gsi_stmt (si);
free_stmt_vec_info (store);
unlink_stmt_vdef (store);
gsi_remove (&si, true);
release_defs (store);
}
/* Stores can only appear at the end of pattern statements. */
gcc_assert (!transform_pattern_stmt);
pattern_def_seq = NULL;
}
else if (!transform_pattern_stmt && gsi_end_p (pattern_def_si))
{
pattern_def_seq = NULL;
gsi_next (&si);
}
} /* stmts in BB */
} /* BBs in loop */
slpeel_make_loop_iterate_ntimes (loop, ratio);
/* Reduce loop iterations by the vectorization factor. */
scale_loop_profile (loop, GCOV_COMPUTE_SCALE (1, vectorization_factor),
expected_iterations / vectorization_factor);
loop->nb_iterations_upper_bound
= wi::udiv_floor (loop->nb_iterations_upper_bound, vectorization_factor);
if (LOOP_VINFO_PEELING_FOR_GAPS (loop_vinfo)
&& loop->nb_iterations_upper_bound != 0)
loop->nb_iterations_upper_bound = loop->nb_iterations_upper_bound - 1;
if (loop->any_estimate)
{
loop->nb_iterations_estimate
= wi::udiv_floor (loop->nb_iterations_estimate, vectorization_factor);
if (LOOP_VINFO_PEELING_FOR_GAPS (loop_vinfo)
&& loop->nb_iterations_estimate != 0)
loop->nb_iterations_estimate = loop->nb_iterations_estimate - 1;
}
if (dump_enabled_p ())
{
dump_printf_loc (MSG_NOTE, vect_location,
"LOOP VECTORIZED\n");
if (loop->inner)
dump_printf_loc (MSG_NOTE, vect_location,
"OUTER LOOP VECTORIZED\n");
dump_printf (MSG_NOTE, "\n");
}
}
|
Parallelizer.h | // This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2010 Gael Guennebaud <gael.guennebaud@inria.fr>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
#ifndef EIGEN_PARALLELIZER_H
#define EIGEN_PARALLELIZER_H
namespace Eigen {
namespace internal {
/** \internal */
inline void manage_multi_threading(Action action, int* v) {
static int m_maxThreads = -1;
EIGEN_UNUSED_VARIABLE(m_maxThreads);
if (action == SetAction) {
eigen_internal_assert(v != 0);
m_maxThreads = *v;
} else if (action == GetAction) {
eigen_internal_assert(v != 0);
#ifdef EIGEN_HAS_OPENMP
if (m_maxThreads > 0)
*v = m_maxThreads;
else
*v = omp_get_max_threads();
#else
*v = 1;
#endif
} else {
eigen_internal_assert(false);
}
}
} // namespace internal
/** Must be call first when calling Eigen from multiple threads */
inline void initParallel() {
int nbt;
internal::manage_multi_threading(GetAction, &nbt);
std::ptrdiff_t l1, l2, l3;
internal::manage_caching_sizes(GetAction, &l1, &l2, &l3);
}
/** \returns the max number of threads reserved for Eigen
* \sa setNbThreads */
inline int nbThreads() {
int ret;
internal::manage_multi_threading(GetAction, &ret);
return ret;
}
/** Sets the max number of threads reserved for Eigen
* \sa nbThreads */
inline void setNbThreads(int v) { internal::manage_multi_threading(SetAction, &v); }
namespace internal {
template <typename Index> struct GemmParallelInfo {
GemmParallelInfo() : sync(-1), users(0), lhs_start(0), lhs_length(0) {}
Index volatile sync;
int volatile users;
Index lhs_start;
Index lhs_length;
};
template <bool Condition, typename Functor, typename Index>
void parallelize_gemm(const Functor& func, Index rows, Index cols, Index depth,
bool transpose) {
// TODO when EIGEN_USE_BLAS is defined,
// we should still enable OMP for other scalar types
#if !(defined(EIGEN_HAS_OPENMP)) || defined(EIGEN_USE_BLAS)
// FIXME the transpose variable is only needed to properly split
// the matrix product when multithreading is enabled. This is a temporary
// fix to support row-major destination matrices. This whole
// parallelizer mechanism has to be redisigned anyway.
EIGEN_UNUSED_VARIABLE(depth);
EIGEN_UNUSED_VARIABLE(transpose);
func(0, rows, 0, cols);
#else
// Dynamically check whether we should enable or disable OpenMP.
// The conditions are:
// - the max number of threads we can create is greater than 1
// - we are not already in a parallel code
// - the sizes are large enough
// compute the maximal number of threads from the size of the product:
// This first heuristic takes into account that the product kernel is fully optimized when working with nr columns at once.
Index size = transpose ? rows : cols;
Index pb_max_threads = std::max<Index>(1, size / Functor::Traits::nr);
// compute the maximal number of threads from the total amount of work:
double work = static_cast<double>(rows) * static_cast<double>(cols) *
static_cast<double>(depth);
double kMinTaskSize = 50000; // FIXME improve this heuristic.
pb_max_threads =
std::max<Index>(1, std::min<Index>(pb_max_threads, work / kMinTaskSize));
// compute the number of threads we are going to use
Index threads = std::min<Index>(nbThreads(), pb_max_threads);
// if multi-threading is explicitely disabled, not useful, or if we already are in a parallel session,
// then abort multi-threading
// FIXME omp_get_num_threads()>1 only works for openmp, what if the user does not use openmp?
if ((!Condition) || (threads == 1) || (omp_get_num_threads() > 1))
return func(0, rows, 0, cols);
Eigen::initParallel();
func.initParallelSession(threads);
if (transpose) std::swap(rows, cols);
ei_declare_aligned_stack_constructed_variable(GemmParallelInfo<Index>, info, threads,
0);
int errorCount = 0;
#pragma omp parallel num_threads(threads) reduction(+ : errorCount)
{
Index i = omp_get_thread_num();
// Note that the actual number of threads might be lower than the number of request ones.
Index actual_threads = omp_get_num_threads();
Index blockCols = (cols / actual_threads) & ~Index(0x3);
Index blockRows = (rows / actual_threads);
blockRows = (blockRows / Functor::Traits::mr) * Functor::Traits::mr;
Index r0 = i * blockRows;
Index actualBlockRows = (i + 1 == actual_threads) ? rows - r0 : blockRows;
Index c0 = i * blockCols;
Index actualBlockCols = (i + 1 == actual_threads) ? cols - c0 : blockCols;
info[i].lhs_start = r0;
info[i].lhs_length = actualBlockRows;
EIGEN_TRY {
if (transpose)
func(c0, actualBlockCols, 0, rows, info);
else
func(0, rows, c0, actualBlockCols, info);
}
EIGEN_CATCH(...) { ++errorCount; }
}
//if (errorCount) EIGEN_THROW_X(Eigen::eigen_assert_exception());
// CRAAM(marek): this seems to be an upstream bug, should be fixed in 3.3.9)
eigen_assert(errorCount == 0);
#endif
}
} // end namespace internal
} // end namespace Eigen
#endif // EIGEN_PARALLELIZER_H
|
Example1.c | //#include <stdio.h>
//#include <omp.h>
//#include <conio.h>
//
//int main(int argc, char *argv[])
//{
// int tid,tsize;
// tid = omp_get_thread_num();
// printf("Thread Number = %d \n", tid);
// tsize = omp_get_num_threads();
// printf("Number of Threads = %d \n", tsize);
// omp_set_num_threads(8);
//
//#pragma omp parallel
// {
// tid = omp_get_thread_num();
// tsize = omp_get_num_threads();
//
// printf("Hello Thread = %d / %d\n", tid, tsize);
// }
// tid = omp_get_thread_num();
// printf("Thread %d is done. \n", tid);
//
// _getch(); // for keep console from <conio.h> library
// return 0;
//} |
scheduled_clauseModificado.c | #include <stdio.h>
#include <stdlib.h>
#ifdef _OPENMP
#include <omp.h>
#else
#define omp_get_thread_num()0
#endif
main(int argc, char **argv){
int i,n=200,chunk,a[n],suma=0;
if(argc<3){
fprintf(stderr,"\nFalta iteraciones o chunk\n");
exit(-1);
}
n= atoi(argv[1]); if(n>200) n=200; chunk=atoi(argv[2]);
for(i=0;i<n;i++) a[i]=i;
#pragma omp parallel for firstprivate(suma)\
lastprivate(suma) schedule(dynamic,chunk)
for(i=0;i<n;i++){
suma=suma+ a[i];
printf("thread %d suma a [%d] suma=%d\n", omp_get_thread_num(),i,suma);
printf("Valor de la variable dyn-var: %d \n",omp_get_dynamic());
printf("Valor de la variable nthreads_var: %d\n",omp_get_max_threads());
printf("Valor de la variable thread_limit-var: %d\n", omp_get_thread_limit()); //suponemos versión 3.0 de openMP
//printf("Valor de la variable run-sched-var: %d\n",omp_get_schedule(n,chunk));
}
printf("\nFuera de 'parallel for' suma=%d\n",suma);
printf("Valor de la variable dyn-var: %d\n",omp_get_dynamic());
printf("Valor de la variable nthreads_var: %d\n",omp_get_max_threads());
printf("Valor de la variable thread_limit-var: %d\n",omp_get_thread_limit()); //suponemos versión 3.0 de openMP
//printf("Valor de la variable run-sched-var: ",omp_get_schedule(n,chunk));
} |
target_update-2.c | /* { dg-do run } */
#include <stdlib.h>
const int MAX = 1800;
void check (int *a, int *b, int N)
{
int i;
for (i = 0; i < N; i++)
if (a[i] != b[i])
abort ();
}
void init (int *a1, int *a2, int N)
{
int i, s = -1;
for (i = 0; i < N; i++)
{
a1[i] = s;
a2[i] = i;
s = -s;
}
}
int maybe_init_again (int *a, int N)
{
int i;
for (i = 0; i < N; i++)
a[i] = i;
return 1;
}
void vec_mult_ref (int *p, int *v1, int *v2, int N)
{
int i;
init (v1, v2, N);
for (i = 0; i < N; i++)
p[i] = v1[i] * v2[i];
maybe_init_again (v1, N);
maybe_init_again (v2, N);
for (i = 0; i < N; i++)
p[i] = p[i] + (v1[i] * v2[i]);
}
void vec_mult (int *p, int *v1, int *v2, int N)
{
int i;
init (v1, v2, N);
#pragma omp target data map(to: v1[:N], v2[:N]) map(from: p[0:N])
{
int changed;
#pragma omp target
#pragma omp parallel for
for (i = 0; i < N; i++)
p[i] = v1[i] * v2[i];
changed = maybe_init_again (v1, N);
#pragma omp target update if (changed) to(v1[:N])
changed = maybe_init_again (v2, N);
#pragma omp target update if (changed) to(v2[:N])
#pragma omp target
#pragma omp parallel for
for (i = 0; i < N; i++)
p[i] = p[i] + (v1[i] * v2[i]);
}
}
int main ()
{
int *p = (int *) malloc (MAX * sizeof (int));
int *p1 = (int *) malloc (MAX * sizeof (int));
int *v1 = (int *) malloc (MAX * sizeof (int));
int *v2 = (int *) malloc (MAX * sizeof (int));
vec_mult_ref (p, v1, v2, MAX);
vec_mult (p1, v1, v2, MAX);
check (p, p1, MAX);
free (p);
free (p1);
free (v1);
free (v2);
return 0;
}
|
charging.c | /*
* Copyright 2019 <Benjamin Santos> <caos21@gmail.com>
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
*/
#include "charging.h"
int fcharging(double t, double *n, double *dndt, void *data) {
struct collision_data *mcd;
mcd = (struct collision_data *)data;
short l = mcd->l;
short nchrgs = mcd->nchrgs;
short q = 0;
for (q = 0; q < nchrgs - 1; ++q) {
dndt[q] =
((mcd->ifreq[l][q - 1] + mcd->with_tunnel * mcd->tfreq[l][q - 1]) *
n[q - 1] +
mcd->efreq[l][q + 1] * n[q + 1] -
n[q] * ((mcd->ifreq[l][q] + mcd->with_tunnel * mcd->tfreq[l][q]) +
mcd->efreq[l][q]));
}
q = 0;
dndt[q] = (mcd->efreq[l][q + 1] * n[q + 1] -
n[q] * ((mcd->ifreq[l][q] + mcd->with_tunnel * mcd->tfreq[l][q])));
q = nchrgs - 1;
dndt[q] = ((mcd->ifreq[l][q - 1] + mcd->with_tunnel * mcd->tfreq[l][q - 1]) *
n[q - 1] -
n[q] * mcd->efreq[l][q]);
return 0;
}
int charging_step(double time, double delta_t, void *pdata, void *cdata) {
struct plasma_data *mpd = pdata;
struct collision_data *mcd = cdata;
short nchrgs = mcd->nchrgs;
short nvols = mpd->nvols;
#pragma omp parallel for schedule(static) default(none) shared(nvols, nchrgs, mcd, mpd, time, delta_t, stderr)
for (short l = 0; l < nvols; ++l) {
struct collision_data local_mcd;
local_mcd.l = l;
local_mcd.nchrgs = nchrgs;
local_mcd.with_tunnel = mcd->with_tunnel;
local_mcd.efreq = mcd->efreq;
local_mcd.ifreq = mcd->ifreq;
local_mcd.tfreq = mcd->tfreq;
double tin = time;
double tout = time + delta_t;
double atol[nchrgs], rtol[nchrgs], nqdens[nchrgs];
for (short q = 0; q < nchrgs; ++q) {
nqdens[q] = mpd->pdens[l][q];
atol[q] = 1.0e-3;
rtol[q] = 1.0e-3;
}
struct lsoda_opt_t opt = {0};
opt.ixpr = 0; // additional printing
opt.rtol = rtol; // relative tolerance
opt.atol = atol; // absolute tolerance
opt.itask = 1; // normal integration
opt.mxstep = 100000000; // max steps
struct lsoda_context_t ctx = {
.function = fcharging,
.data = &local_mcd,
.neq = (int)(nchrgs),
.state = 1,
};
lsoda_prepare(&ctx, &opt);
// integrate
lsoda(&ctx, nqdens, &tin, tout);
if (ctx.state <= 0) {
fprintf(stderr, "\n------------------------------------");
fprintf(stderr, "\n[ee] LSODA error in charging");
fprintf(stderr, "\n[ee] error istate = %d", ctx.state);
fprintf(stderr, "\n[ii] volume section = %d ", l);
fprintf(stderr, "\n[ii] min dtq = %f ", opt.hmin);
fprintf(stderr, "\n[ii] h0 = %f ", opt.h0);
fprintf(stderr, "\n[ii] time = %f", time);
fprintf(stderr, "\n[ii] delta_t = %f", delta_t);
fprintf(stderr, "\n------------------------------------\n");
exit(0);
}
lsoda_free(&ctx);
for (short q = 0; q < nchrgs; ++q) {
mpd->ndens[l][q] = (nqdens[q] > 0 ? nqdens[q] : 0.0);
mpd->qrate2d[l][q] = (mpd->ndens[l][q] - mpd->pdens[l][q]) / delta_t;
}
}
return 0;
}
|
DRB045-doall1-orig-no.c | /*
Copyright (c) 2017, Lawrence Livermore National Security, LLC.
Produced at the Lawrence Livermore National Laboratory
Written by Chunhua Liao, Pei-Hung Lin, Joshua Asplund,
Markus Schordan, and Ian Karlin
(email: liao6@llnl.gov, lin32@llnl.gov, asplund1@llnl.gov,
schordan1@llnl.gov, karlin1@llnl.gov)
LLNL-CODE-732144
All rights reserved.
This file is part of DataRaceBench. For details, see
https://github.com/LLNL/dataracebench. Please also see the LICENSE file
for our additional BSD notice.
Redistribution and use in source and binary forms, with
or without modification, are permitted provided that the following
conditions are met:
* Redistributions of source code must retain the above copyright
notice, this list of conditions and the disclaimer below.
* Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the disclaimer (as noted below)
in the documentation and/or other materials provided with the
distribution.
* Neither the name of the LLNS/LLNL nor the names of its contributors
may be used to endorse or promote products derived from this
software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND
CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES,
INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL LAWRENCE LIVERMORE NATIONAL
SECURITY, LLC, THE U.S. DEPARTMENT OF ENERGY OR CONTRIBUTORS BE
LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY,
OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING
IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF
THE POSSIBILITY OF SUCH DAMAGE.
*/
#include <stdio.h>
#include <stdlib.h>
/*
Simplest one dimension array computation
*/
#include <omp.h>
int a[100];
int main()
{
int i;
#pragma omp parallel for private (i)
for (i = 0; i <= 99; i += 1) {
a[i] = i;
}
#pragma omp parallel for private (i)
for (i = 0; i <= 99; i += 1) {
a[i] = a[i] + 1;
}
for (i = 0; i <= 99; i += 1) {
printf("%d\n",a[i]);
}
return 0;
}
|
resource_manager.h | // -----------------------------------------------------------------------------
//
// Copyright (C) 2021 CERN & Newcastle University for the benefit of the
// BioDynaMo collaboration. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
//
// See the LICENSE file distributed with this work for details.
// See the NOTICE file distributed with this work for additional information
// regarding copyright ownership.
//
// -----------------------------------------------------------------------------
#ifndef CORE_RESOURCE_MANAGER_H_
#define CORE_RESOURCE_MANAGER_H_
#include <omp.h>
#include <sched.h>
#include <algorithm>
#include <cmath>
#include <limits>
#include <memory>
#include <ostream>
#include <set>
#include <string>
#include <unordered_map>
#include <utility>
#include <vector>
#include "core/agent/agent.h"
#include "core/agent/agent_handle.h"
#include "core/agent/agent_uid.h"
#include "core/agent/agent_uid_generator.h"
#include "core/container/agent_uid_map.h"
#include "core/diffusion/diffusion_grid.h"
#include "core/functor.h"
#include "core/operation/operation.h"
#include "core/simulation.h"
#include "core/type_index.h"
#include "core/util/numa.h"
#include "core/util/root.h"
#include "core/util/thread_info.h"
#include "core/util/type.h"
namespace bdm {
/// ResourceManager stores agents and diffusion grids and provides
/// methods to add, remove, and access them. Agents are uniquely identified
/// by their AgentUid, and AgentHandle. An AgentHandle might change during the
/// simulation.
class ResourceManager {
public:
explicit ResourceManager(TRootIOCtor* r) {}
ResourceManager();
virtual ~ResourceManager();
ResourceManager& operator=(ResourceManager&& other) {
if (agents_.size() != other.agents_.size()) {
Log::Fatal(
"Restored ResourceManager has different number of NUMA nodes.");
}
for (auto& el : diffusion_grids_) {
delete el.second;
}
for (auto& numa_agents : agents_) {
for (auto* agent : numa_agents) {
delete agent;
}
}
agents_ = std::move(other.agents_);
agents_lb_.resize(agents_.size());
diffusion_grids_ = std::move(other.diffusion_grids_);
RebuildAgentUidMap();
// restore type_index_
if (type_index_) {
for (auto& numa_agents : agents_) {
for (auto* agent : numa_agents) {
type_index_->Add(agent);
}
}
}
return *this;
}
void RebuildAgentUidMap() {
// rebuild uid_ah_map_
uid_ah_map_.clear();
auto* agent_uid_generator = Simulation::GetActive()->GetAgentUidGenerator();
uid_ah_map_.resize(agent_uid_generator->GetHighestIndex() + 1);
for (unsigned n = 0; n < agents_.size(); ++n) {
for (unsigned i = 0; i < agents_[n].size(); ++i) {
auto* agent = agents_[n][i];
this->uid_ah_map_.Insert(agent->GetUid(), AgentHandle(n, i));
}
}
}
Agent* GetAgent(const AgentUid& uid) {
if (!uid_ah_map_.Contains(uid)) {
return nullptr;
}
auto& ah = uid_ah_map_[uid];
return agents_[ah.GetNumaNode()][ah.GetElementIdx()];
}
Agent* GetAgent(AgentHandle ah) {
return agents_[ah.GetNumaNode()][ah.GetElementIdx()];
}
AgentHandle GetAgentHandle(const AgentUid& uid) { return uid_ah_map_[uid]; }
void AddDiffusionGrid(DiffusionGrid* dgrid) {
uint64_t substance_id = dgrid->GetSubstanceId();
auto search = diffusion_grids_.find(substance_id);
if (search != diffusion_grids_.end()) {
Log::Fatal("ResourceManager::AddDiffusionGrid",
"You tried to add a diffusion grid with an already existing "
"substance id. Please choose a different substance id.");
} else {
diffusion_grids_[substance_id] = dgrid;
}
}
void RemoveDiffusionGrid(size_t substance_id) {
auto search = diffusion_grids_.find(substance_id);
if (search != diffusion_grids_.end()) {
delete search->second;
diffusion_grids_.erase(search);
} else {
Log::Error("ResourceManager::RemoveDiffusionGrid",
"You tried to remove a diffusion grid that does not exist.");
}
}
/// Return the diffusion grid which holds the substance of specified id
DiffusionGrid* GetDiffusionGrid(size_t substance_id) const {
if (substance_id >= diffusion_grids_.size()) {
Log::Error("DiffusionGrid::GetDiffusionGrid",
"You tried to request diffusion grid '", substance_id,
"', but it does not exist! Make sure that it's the correct id "
"correctly and that the diffusion grid is registered.");
return nullptr;
}
return diffusion_grids_.at(substance_id);
}
/// Return the diffusion grid which holds the substance of specified name
/// Caution: using this function in a tight loop will result in a slow
/// simulation. Use `GetDiffusionGrid(size_t)` in those cases.
DiffusionGrid* GetDiffusionGrid(std::string substance_name) const {
for (auto& el : diffusion_grids_) {
auto& dg = el.second;
if (dg->GetSubstanceName() == substance_name) {
return dg;
}
}
Log::Error("DiffusionGrid::GetDiffusionGrid",
"You tried to request a diffusion grid named '", substance_name,
"', but it does not exist! Make sure that it's spelled "
"correctly and that the diffusion grid is registered.");
return nullptr;
}
/// Execute the given functor for all diffusion grids
/// rm->ForEachDiffusionGrid([](DiffusionGrid* dgrid) {
/// ...
/// });
template <typename TFunctor>
void ForEachDiffusionGrid(TFunctor&& f) const {
for (auto& el : diffusion_grids_) {
f(el.second);
}
}
/// Returns the total number of agents if numa_node == -1
/// Otherwise the number of agents in the specific numa node
size_t GetNumAgents(int numa_node = -1) const {
if (numa_node == -1) {
size_t num_agents = 0;
for (auto& numa_agents : agents_) {
num_agents += numa_agents.size();
}
return num_agents;
} else {
return agents_[numa_node].size();
}
}
/// Call a function for all or a subset of agents in the simulation.
/// @param function that will be called for each agent
/// @param filter if specified, `function` will only be called for agents
/// for which `filter(agent)` evaluates to true.
///
/// rm->ForEachAgent([](Agent* a) {
/// std::cout << a->GetUid() << std::endl;
/// });
virtual void ForEachAgent(const std::function<void(Agent*)>& function,
Functor<bool, Agent*>* filter = nullptr) {
for (auto& numa_agents : agents_) {
for (auto* agent : numa_agents) {
if (!filter || (filter && (*filter)(agent))) {
function(agent);
}
}
}
}
virtual void ForEachAgent(
const std::function<void(Agent*, AgentHandle)>& function,
Functor<bool, Agent*>* filter = nullptr) {
for (uint64_t n = 0; n < agents_.size(); ++n) {
auto& numa_agents = agents_[n];
for (uint64_t i = 0; i < numa_agents.size(); ++i) {
auto* a = numa_agents[i];
if (!filter || (filter && (*filter)(a))) {
function(a, AgentHandle(n, i));
}
}
}
}
/// Call a function for all or a subset of agents in the simulation.
/// @param function that will be called for each agent
/// @param filter if specified, `function` will only be called for agents
/// for which `filter(agent)` evaluates to true.
/// Function invocations are parallelized.\n
/// Uses static scheduling.
/// \see ForEachAgent
virtual void ForEachAgentParallel(Functor<void, Agent*>& function,
Functor<bool, Agent*>* filter = nullptr);
/// Call an operation for all or a subset of agents in the simulation.
/// Function invocations are parallelized.\n
/// Uses static scheduling.
/// \see ForEachAgent
virtual void ForEachAgentParallel(Operation& op,
Functor<bool, Agent*>* filter = nullptr);
virtual void ForEachAgentParallel(
Functor<void, Agent*, AgentHandle>& function,
Functor<bool, Agent*>* filter = nullptr);
/// Call a function for all or a subset of agents in the simulation.
/// Function invocations are parallelized.\n
/// Uses dynamic scheduling and work stealing. Batch size controlled by
/// `chunk`.
/// \param chunk number of agents that are assigned to a thread (batch
/// size)
/// \see ForEachAgent
virtual void ForEachAgentParallel(
uint64_t chunk, Functor<void, Agent*, AgentHandle>& function,
Functor<bool, Agent*>* filter = nullptr);
/// Reserves enough memory to hold `capacity` number of agents for
/// each numa domain.
void Reserve(size_t capacity) {
for (auto& numa_agents : agents_) {
numa_agents.reserve(capacity);
}
if (type_index_) {
type_index_->Reserve(capacity);
}
}
/// Resize `agents_[numa_node]` such that it holds `current + additional`
/// elements after this call.
/// Returns the size after
uint64_t GrowAgentContainer(size_t additional, size_t numa_node) {
if (additional == 0) {
return agents_[numa_node].size();
}
auto current = agents_[numa_node].size();
if (current + additional < agents_[numa_node].size()) {
agents_[numa_node].reserve((current + additional) * 1.5);
}
agents_[numa_node].resize(current + additional);
return current;
}
/// Returns true if an agent with the given uid is stored in this
/// ResourceManager.
bool ContainsAgent(const AgentUid& uid) const {
return uid_ah_map_.Contains(uid);
}
/// Remove all agents
/// NB: This method is not thread-safe! This function invalidates
/// agent references pointing into the ResourceManager. AgentPointer are
/// not affected.
void ClearAgents() {
uid_ah_map_.clear();
for (auto& numa_agents : agents_) {
for (auto* agent : numa_agents) {
delete agent;
}
numa_agents.clear();
}
if (type_index_) {
type_index_->Clear();
}
}
/// Reorder agents such that, agents are distributed to NUMA
/// nodes. Nearby agents will be moved to the same NUMA node.
virtual void LoadBalance();
void DebugNuma() const;
/// NB: This method is not thread-safe! This function might invalidate
/// agent references pointing into the ResourceManager. AgentPointer are
/// not affected.
void AddAgent(Agent* agent, // NOLINT
typename AgentHandle::NumaNode_t numa_node = 0) {
auto uid = agent->GetUid();
if (uid.GetIndex() >= uid_ah_map_.size()) {
uid_ah_map_.resize(uid.GetIndex() + 1);
}
agents_[numa_node].push_back(agent);
uid_ah_map_.Insert(uid,
AgentHandle(numa_node, agents_[numa_node].size() - 1));
if (type_index_) {
type_index_->Add(agent);
}
}
void ResizeAgentUidMap() {
auto* agent_uid_generator = Simulation::GetActive()->GetAgentUidGenerator();
auto highest_idx = agent_uid_generator->GetHighestIndex();
auto new_size = highest_idx * 1.5 + 1;
if (highest_idx >= uid_ah_map_.size()) {
uid_ah_map_.resize(new_size);
}
if (type_index_) {
type_index_->Reserve(new_size);
}
}
virtual void EndOfIteration() {
// Check if SoUiD defragmentation should be turned on or off
double utilization = static_cast<double>(GetNumAgents()) /
static_cast<double>(uid_ah_map_.size());
auto* sim = Simulation::GetActive();
auto* param = sim->GetParam();
if (utilization < param->agent_uid_defragmentation_low_watermark) {
sim->GetAgentUidGenerator()->EnableDefragmentation(&uid_ah_map_);
} else if (utilization > param->agent_uid_defragmentation_high_watermark) {
sim->GetAgentUidGenerator()->DisableDefragmentation();
}
}
/// Adds `new_agents` to `agents_[numa_node]`. `offset` specifies
/// the index at which the first element is inserted. Agents are inserted
/// consecutively. This methos is thread safe only if insertion intervals do
/// not overlap!
virtual void AddAgents(typename AgentHandle::NumaNode_t numa_node,
uint64_t offset,
const std::vector<Agent*>& new_agents) {
uint64_t i = 0;
for (auto* agent : new_agents) {
auto uid = agent->GetUid();
uid_ah_map_.Insert(uid, AgentHandle(numa_node, offset + i));
agents_[numa_node][offset + i] = agent;
i++;
}
if (type_index_) {
#pragma omp critical
for (auto* agent : new_agents) {
type_index_->Add(agent);
}
}
}
/// Removes the agent with the given uid.\n
/// NB: This method is not thread-safe! This function invalidates
/// agent references pointing into the ResourceManager. AgentPointer are
/// not affected.
void RemoveAgent(const AgentUid& uid) {
// remove from map
if (uid_ah_map_.Contains(uid)) {
auto ah = uid_ah_map_[uid];
uid_ah_map_.Remove(uid);
// remove from vector
auto& numa_agents = agents_[ah.GetNumaNode()];
Agent* agent = nullptr;
if (ah.GetElementIdx() == numa_agents.size() - 1) {
agent = numa_agents.back();
numa_agents.pop_back();
} else {
// swap
agent = numa_agents[ah.GetElementIdx()];
auto* reordered = numa_agents.back();
numa_agents[ah.GetElementIdx()] = reordered;
numa_agents.pop_back();
uid_ah_map_.Insert(reordered->GetUid(), ah);
}
if (type_index_) {
type_index_->Remove(agent);
}
delete agent;
}
}
// \param uids: one vector for each thread containing one vector for each numa
// node
void RemoveAgents(const std::vector<std::vector<AgentUid>*>& uids);
const TypeIndex* GetTypeIndex() const { return type_index_; }
protected:
/// Maps an AgentUid to its storage location in `agents_` \n
AgentUidMap<AgentHandle> uid_ah_map_ = AgentUidMap<AgentHandle>(100u); //!
/// Pointer container for all agents
std::vector<std::vector<Agent*>> agents_;
/// Container used during load balancing
std::vector<std::vector<Agent*>> agents_lb_; //!
/// Maps a diffusion grid ID to the pointer to the diffusion grid
std::unordered_map<uint64_t, DiffusionGrid*> diffusion_grids_;
ThreadInfo* thread_info_ = ThreadInfo::GetInstance(); //!
TypeIndex* type_index_ = nullptr;
struct ParallelRemovalAuxData {
std::vector<std::vector<uint64_t>> to_right;
std::vector<std::vector<uint64_t>> not_to_left;
};
/// auxiliary data required for parallel agent removal
ParallelRemovalAuxData parallel_remove_; //!
friend class SimulationBackup;
friend std::ostream& operator<<(std::ostream& os, const ResourceManager& rm);
BDM_CLASS_DEF_NV(ResourceManager, 2);
};
inline std::ostream& operator<<(std::ostream& os, const ResourceManager& rm) {
os << "\033[1mAgents per numa node\033[0m" << std::endl;
uint64_t cnt = 0;
for (auto& numa_agents : rm.agents_) {
os << "numa node " << cnt++ << " -> size: " << numa_agents.size()
<< std::endl;
}
return os;
}
} // namespace bdm
#endif // CORE_RESOURCE_MANAGER_H_
|
jacobi-ompacc-opt1.c | // An optimization on top of naive coding:
// promoting data handling outside the while loop
#include <stdio.h>
#include <math.h>
#ifdef _OPENMP
#include <omp.h>
#endif
// Add timing support
#include <sys/time.h>
double time_stamp()
{
struct timeval t;
double time;
gettimeofday(&t, NULL);
time = t.tv_sec + 1.0e-6*t.tv_usec;
return time;
}
double time1, time2;
void driver(void);
void initialize(void);
void jacobi(void);
void error_check(void);
/************************************************************
* program to solve a finite difference
* discretization of Helmholtz equation :
* (d2/dx2)u + (d2/dy2)u - alpha u = f
* using Jacobi iterative method.
*
* Modified: Sanjiv Shah, Kuck and Associates, Inc. (KAI), 1998
* Author: Joseph Robicheaux, Kuck and Associates, Inc. (KAI), 1998
*
* This c version program is translated by
* Chunhua Liao, University of Houston, Jan, 2005
*
* Directives are used in this code to achieve parallelism.
* All do loops are parallelized with default 'static' scheduling.
*
* Input : n - grid dimension in x direction
* m - grid dimension in y direction
* alpha - Helmholtz constant (always greater than 0.0)
* tol - error tolerance for iterative solver
* relax - Successice over relaxation parameter
* mits - Maximum iterations for iterative solver
*
* On output
* : u(n,m) - Dependent variable (solutions)
* : f(n,m) - Right hand side function
*************************************************************/
#define MSIZE 512
int n,m,mits;
#define REAL float // flexible between float and double
REAL tol,relax=1.0,alpha=0.0543;
REAL u[MSIZE][MSIZE],f[MSIZE][MSIZE],uold[MSIZE][MSIZE];
REAL dx,dy;
int main (void)
{
// float toler;
/* printf("Input n,m (< %d) - grid dimension in x,y direction:\n",MSIZE);
scanf ("%d",&n);
scanf ("%d",&m);
printf("Input tol - error tolerance for iterative solver\n");
scanf("%f",&toler);
tol=(double)toler;
printf("Input mits - Maximum iterations for solver\n");
scanf("%d",&mits);
*/
n=MSIZE;
m=MSIZE;
tol=0.0000000001;
mits=5000;
#if 0 // Not yet support concurrent CPU and GPU threads
#ifdef _OPENMP
#pragma omp parallel
{
#pragma omp single
printf("Running using %d threads...\n",omp_get_num_threads());
}
#endif
#endif
driver ( ) ;
return 0;
}
/*************************************************************
* Subroutine driver ()
* This is where the arrays are allocated and initialzed.
*
* Working varaibles/arrays
* dx - grid spacing in x direction
* dy - grid spacing in y direction
*************************************************************/
void driver( )
{
initialize();
time1 = time_stamp();
/* Solve Helmholtz equation */
jacobi ();
time2 = time_stamp();
printf("------------------------\n");
printf("Execution time = %f\n",time2-time1);
/* error_check (n,m,alpha,dx,dy,u,f)*/
error_check ( );
}
/* subroutine initialize (n,m,alpha,dx,dy,u,f)
******************************************************
* Initializes data
* Assumes exact solution is u(x,y) = (1-x^2)*(1-y^2)
*
******************************************************/
void initialize( )
{
int i,j, xx,yy;
//double PI=3.1415926;
dx = 2.0 / (n-1);
dy = 2.0 / (m-1);
/* Initialize initial condition and RHS */
//#pragma omp parallel for private(xx,yy,j,i)
for (i=0;i<n;i++)
for (j=0;j<m;j++)
{
xx =(int)( -1.0 + dx * (i-1));
yy = (int)(-1.0 + dy * (j-1)) ;
u[i][j] = 0.0;
f[i][j] = -1.0*alpha *(1.0-xx*xx)*(1.0-yy*yy)\
- 2.0*(1.0-xx*xx)-2.0*(1.0-yy*yy);
}
}
/* subroutine jacobi (n,m,dx,dy,alpha,omega,u,f,tol,maxit)
******************************************************************
* Subroutine HelmholtzJ
* Solves poisson equation on rectangular grid assuming :
* (1) Uniform discretization in each direction, and
* (2) Dirichlect boundary conditions
*
* Jacobi method is used in this routine
*
* Input : n,m Number of grid points in the X/Y directions
* dx,dy Grid spacing in the X/Y directions
* alpha Helmholtz eqn. coefficient
* omega Relaxation factor
* f(n,m) Right hand side function
* u(n,m) Dependent variable/Solution
* tol Tolerance for iterative solver
* maxit Maximum number of iterations
*
* Output : u(n,m) - Solution
*****************************************************************/
void jacobi( )
{
REAL omega;
int i,j,k;
REAL error,resid,ax,ay,b;
// double error_local;
// float ta,tb,tc,td,te,ta1,ta2,tb1,tb2,tc1,tc2,td1,td2;
// float te1,te2;
// float second;
omega=relax;
/*
* Initialize coefficients */
ax = 1.0/(dx*dx); /* X-direction coef */
ay = 1.0/(dy*dy); /* Y-direction coef */
b = -2.0/(dx*dx)-2.0/(dy*dy) - alpha; /* Central coeff */
error = 10.0 * tol;
k = 1;
// An optimization on top of naive coding: promoting data handling outside the while loop
// data properties may change since the scope is bigger:
#pragma omp target data map(in:n, m, omega, ax, ay, b, f[0:n][0:m]) map(inout:u[0:n][0:m]) map(alloc:uold[0:n][0:m])
while ((k<=mits)&&(error>tol))
{
error = 0.0;
/* Copy new solution into old */
//#pragma omp parallel
// {
#pragma omp target //map(in:n, m, u[0:n][0:m]) map(out:uold[0:n][0:m])
#pragma omp parallel for private(j,i)
for(i=0;i<n;i++)
for(j=0;j<m;j++)
uold[i][j] = u[i][j];
#pragma omp target //map(in:n, m, omega, ax, ay, b, f[0:n][0:m], uold[0:n][0:m]) map(out:u[0:n][0:m])
#pragma omp parallel for private(resid,j,i) reduction(+:error) // nowait
for (i=1;i<(n-1);i++)
for (j=1;j<(m-1);j++)
{
resid = (ax*(uold[i-1][j] + uold[i+1][j])\
+ ay*(uold[i][j-1] + uold[i][j+1])+ b * uold[i][j] - f[i][j])/b;
u[i][j] = uold[i][j] - omega * resid;
error = error + resid*resid ;
}
// }
/* omp end parallel */
/* Error check */
if (k%500==0)
printf("Finished %d iteration with error =%f\n",k, error);
error = sqrt(error)/(n*m);
k = k + 1;
} /* End iteration loop */
printf("Total Number of Iterations:%d\n",k);
printf("Residual:%E\n", error);
}
/* subroutine error_check (n,m,alpha,dx,dy,u,f)
implicit none
************************************************************
* Checks error between numerical and exact solution
*
************************************************************/
void error_check ( )
{
int i,j;
REAL xx,yy,temp,error;
dx = 2.0 / (n-1);
dy = 2.0 / (m-1);
error = 0.0 ;
//#pragma omp parallel for private(xx,yy,temp,j,i) reduction(+:error)
for (i=0;i<n;i++)
for (j=0;j<m;j++)
{
xx = -1.0 + dx * (i-1);
yy = -1.0 + dy * (j-1);
temp = u[i][j] - (1.0-xx*xx)*(1.0-yy*yy);
error = error + temp*temp;
}
error = sqrt(error)/(n*m);
printf("Solution Error :%E \n",error);
}
|
fpForestClassificationBase.h | #ifndef fpForestClassification_h
#define fpForestClassification_h
#include "../../../baseFunctions/fpForestBase.h"
#include <vector>
#include <stdio.h>
#include <ctime>
#include <chrono>
#include <cstdlib>
#include <omp.h>
#include "rfTree.h"
#include <map>
namespace fp {
template <typename T>
class fpForestClassificationBase : public fpForestBase<T>
{
protected:
std::vector<rfTree<T> > trees;
int numCorrect = 0;
int numOOB = 0;
std::map<std::pair<int, int>, double> pairMat;
public:
fpDisplayProgress printProgress;
// using fpForestBase<T>::fpForestBase;
~fpForestClassificationBase(){}
inline void printForestType(){
std::cout << "This is a basic classification forest.\n";
}
inline void changeForestSize(){
trees.resize(fpSingleton::getSingleton().returnNumTrees());
}
inline void growTrees(){
#pragma omp parallel for num_threads(fpSingleton::getSingleton().returnNumThreads())
for(unsigned int i = 0; i < trees.size(); ++i){
printProgress.displayProgress(i);
trees[i].growTree();
}
std::cout << "\n"<< std::flush;
}
inline void checkParameters(){
//TODO: check parameters to make sure they make sense for this forest type.
;
}
inline std::map<std::string, float> calcTreeStats(){
// rewrite as a struct in a top level header file.
int maxDepth=0;
int totalLeafNodes=0;
int totalLeafDepth=0;
int tempMaxDepth;
for(int i = 0; i < fpSingleton::getSingleton().returnNumTrees(); ++i){
tempMaxDepth = trees[i].returnMaxDepth();
maxDepth = ((maxDepth < tempMaxDepth) ? tempMaxDepth : maxDepth);
totalLeafNodes += trees[i].returnNumLeafNodes();
totalLeafDepth += trees[i].returnLeafDepthSum();
}
std::map<std::string, float> treeStats;
treeStats["maxDepth"] = (float) maxDepth;
treeStats["totalLeafDepth"] = (float) totalLeafDepth;
treeStats["totalLeafNodes"] = (float) totalLeafNodes;
treeStats["OOBaccuracy"] = reportOOB();
return treeStats;
}
inline void treeStats(){
std::map<std::string, float> treeStats = calcTreeStats();
std::cout << "max depth: " << treeStats["maxDepth"] << "\n";
std::cout << "avg depth: " << float(treeStats["totalLeafDepth"])/float(treeStats["totalLeafNodes"]) << "\n";
std::cout << "num leaf nodes: " << treeStats["totalLeafNodes"] << "\n";
std::cout << "avg num leaf nodes per tree: " << treeStats["totalLeafNodes"]/fpSingleton::getSingleton().returnNumTrees() << "\n";
std::cout << "OOB Accuracy: " << treeStats["OOBaccuracy"] << "\n";
}
void printTree0(){
trees[0].printTree();
}
void growForest(){
// checkParameters();
changeForestSize();
growTrees();
treeStats();
}
inline int predictClass(int observationNumber){
std::vector<int> classTally(fpSingleton::getSingleton().returnNumClasses(),0);
for(int i = 0; i < fpSingleton::getSingleton().returnNumTrees(); ++i){
++classTally[trees[i].predictObservation(observationNumber)];
}
int bestClass = 0;
for(int j = 1; j < fpSingleton::getSingleton().returnNumClasses(); ++j){
if(classTally[bestClass] < classTally[j]){
bestClass = j;
}
}
return bestClass;
}
inline std::map<std::pair<int, int>, double> returnPairMat(){
return pairMat;
}
inline int predictClass(const T* observation){
/*
std::vector<int> classTally(fpSingleton::getSingleton().returnNumClasses(),0);
for(int i = 0; i < fpSingleton::getSingleton().returnNumTrees(); ++i){
++classTally[trees[i].predictObservation(observation)];
}
int bestClass = 0;
for(int j = 1; j < fpSingleton::getSingleton().returnNumClasses(); ++j){
if(classTally[bestClass] < classTally[j]){
bestClass = j;
}
}
return bestClass;
*/
return 0;
}
inline int predictClass(std::vector<T>& observation){
std::vector<int> classTally(fpSingleton::getSingleton().returnNumClasses(),0);
for(int i = 0; i < fpSingleton::getSingleton().returnNumTrees(); ++i){
++classTally[trees[i].predictObservation(observation)];
}
int bestClass = 0;
for(int j = 1; j < fpSingleton::getSingleton().returnNumClasses(); ++j){
if(classTally[bestClass] < classTally[j]){
bestClass = j;
}
}
return bestClass;
}
inline std::vector<int> predictClassPost(std::vector<T>& observation){
std::vector<int> classTally(fpSingleton::getSingleton().returnNumClasses(),0);
for(int i = 0; i < fpSingleton::getSingleton().returnNumTrees(); ++i){
++classTally[trees[i].predictObservation(observation)];
}
return classTally;
}
inline float testForest(){
int numTried = 0;
int numWrong = 0;
for (int i = 0; i <fpSingleton::getSingleton().returnNumObservations();i++){
++numTried;
int predClass = predictClass(i);
if(predClass != fpSingleton::getSingleton().returnTestLabel(i)){
++numWrong;
}
}
std::cout << "\nnumWrong= " << numWrong << "\n";
return (float)numWrong/(float)numTried;
}
inline float reportOOB(){
int numCorrect = 0;
int numOOB = 0;
float oobAccuracy = 0;
std::map<int, int> oobBestClass;
// A vector of vectors (numObs X numClasses) for storing
// the class tallies.
std::vector<std::vector<int>> oobClassVotes(fpSingleton::getSingleton().returnNumObservations(), std::vector<int>(fpSingleton::getSingleton().returnNumClasses(), 0));
// Iterate over trees to get oob points and add up their
// class votes. returnOOBvotes is an n x 2 vector with
// <(oobID, treeVote)>.
for (auto& ti : trees){
for (auto j : ti.returnOOBvotes()){
// increment the vote for class j[1] for
// oob_point j[0].
oobClassVotes[j[0]][j[1]] += 1;
}
}
// Iterate over "rows" and calculate the bestClass.
for (unsigned int i = 0; i < oobClassVotes.size(); i++){
if(std::any_of(oobClassVotes[i].begin(), oobClassVotes[i].end(), [](int i) {return i>0;})){
// This will pick the lower class value if there
// is a tie. (same as in the predict methods).
// TODO: flip a coin for tie-breaking.
oobBestClass[i] = std::distance(oobClassVotes[i].begin(), std::max_element(oobClassVotes[i].begin(), oobClassVotes[i].end()));
numOOB++;
// using distance is a way to get the index of
// the max value in the vector.
// http://www.cplusplus.com/forum/beginner/212806/#msg994102
}
}
for (auto& i : oobBestClass){
// Tally the number of correct predictions.
// i.first is the observation index.
// i.second is the predicted class.
if(fpSingleton::getSingleton().returnLabel(i.first) == i.second){
numCorrect++;
}
}
this->numCorrect = numCorrect;
this->numOOB = numOOB;
oobAccuracy = (float) numCorrect / (float) numOOB;
return oobAccuracy;
}
/*
* testing functions -- not to be used in production
*/
inline std::vector<std::vector<T> > testOneTreeOOB(){
std::vector<std::vector<T> > dataValues;
std::vector<int> oobIndices;
std::map<int, int> oobBestClass;
// A vector of vectors (numObs X numClasses) for storing
// the class tallies.
std::vector<std::vector<int>> oobClassVotes(fpSingleton::getSingleton().returnNumObservations(), std::vector<int>(fpSingleton::getSingleton().returnNumClasses(), 0));
// Iterate over trees to get oob points and add up their
// class votes.
for (unsigned int i = 0; i < trees.size(); i++){
for (auto j : trees[i].returnOOBvotes()){
oobClassVotes[j[0]][j[1]] += 1;
}
}
// Iterate over "rows" and calculate the bestClass.
for (unsigned int i = 0; i < oobClassVotes.size(); i++){
if(!std::all_of(oobClassVotes[i].begin(), oobClassVotes[i].end(), [](int i) {return i==0;})){
// This will pick the lower class value if there
// is a tie. (same as in the predict methods).
// TODO: flip a coin for tie-breaking.
oobIndices.push_back(i);
}
}
for(auto& i : oobIndices){
std::vector<T> tmp;
for(int j = 0; j < fpSingleton::getSingleton().returnNumFeatures(); j++){
tmp.push_back(fpSingleton::getSingleton().returnFeatureVal(j, i));
}
dataValues.push_back(tmp);
}
return dataValues;
}
inline std::vector<int> testOneTreeOOBind(){
std::vector<int> oobIndices;
std::map<int, int> oobBestClass;
// A vector of vectors (numObs X numClasses) for storing
// the class tallies.
std::vector<std::vector<int>> oobClassVotes(fpSingleton::getSingleton().returnNumObservations(), std::vector<int>(fpSingleton::getSingleton().returnNumClasses(), 0));
// Iterate over trees to get oob points and add up their
// class votes.
for (unsigned int i = 0; i < trees.size(); i++){
for (auto j : trees[i].returnOOBvotes()){
oobClassVotes[j[0]][j[1]] += 1;
}
}
// Iterate over "rows" and calculate the bestClass.
for (unsigned int i = 0; i < oobClassVotes.size(); i++){
if(!std::all_of(oobClassVotes[i].begin(), oobClassVotes[i].end(), [](int i) {return i==0;})){
// This will pick the lower class value if there
// is a tie. (same as in the predict methods).
// TODO: flip a coin for tie-breaking.
oobIndices.push_back(i);
}
}
return oobIndices;
}
inline std::map<std::string, int> testReturnNumCorrectAndNumOOB(){
std::map<std::string, int> retVal;
retVal["numCorrect"] = numCorrect;
retVal["numOOB"] = numOOB;
return retVal;
}
};
}// namespace fp
#endif //fpForestClassification_h
|
par_coarsen.c | /******************************************************************************
* Copyright 1998-2019 Lawrence Livermore National Security, LLC and other
* HYPRE Project Developers. See the top-level COPYRIGHT file for details.
*
* SPDX-License-Identifier: (Apache-2.0 OR MIT)
******************************************************************************/
/******************************************************************************
*
*****************************************************************************/
/* following should be in a header file */
#include "_hypre_parcsr_ls.h"
/*==========================================================================*/
/*==========================================================================*/
/**
Selects a coarse "grid" based on the graph of a matrix.
Notes:
\begin{itemize}
\item The underlying matrix storage scheme is a hypre_ParCSR matrix.
\item The routine returns the following:
\begin{itemize}
\item S - a ParCSR matrix representing the "strength matrix". This is
used in the "build interpolation" routine.
\item CF\_marker - an array indicating both C-pts (value = 1) and
F-pts (value = -1)
\end{itemize}
\item We define the following temporary storage:
\begin{itemize}
\item measure\_array - an array containing the "measures" for each
of the fine-grid points
\item graph\_array - an array containing the list of points in the
"current subgraph" being considered in the coarsening process.
\end{itemize}
\item The graph of the "strength matrix" for A is a subgraph of the
graph of A, but requires nonsymmetric storage even if A is
symmetric. This is because of the directional nature of the
"strengh of dependence" notion (see below). Since we are using
nonsymmetric storage for A right now, this is not a problem. If we
ever add the ability to store A symmetrically, then we could store
the strength graph as floats instead of doubles to save space.
\item This routine currently "compresses" the strength matrix. We
should consider the possibility of defining this matrix to have the
same "nonzero structure" as A. To do this, we could use the same
A\_i and A\_j arrays, and would need only define the S\_data array.
There are several pros and cons to discuss.
\end{itemize}
Terminology:
\begin{itemize}
\item Ruge's terminology: A point is "strongly connected to" $j$, or
"strongly depends on" $j$, if $-a_ij >= \theta max_{l != j} \{-a_il\}$.
\item Here, we retain some of this terminology, but with a more
generalized notion of "strength". We also retain the "natural"
graph notation for representing the directed graph of a matrix.
That is, the nonzero entry $a_ij$ is represented as: i --> j. In
the strength matrix, S, the entry $s_ij$ is also graphically denoted
as above, and means both of the following:
\begin{itemize}
\item $i$ "depends on" $j$ with "strength" $s_ij$
\item $j$ "influences" $i$ with "strength" $s_ij$
\end{itemize}
\end{itemize}
{\bf Input files:}
_hypre_parcsr_ls.h
@return Error code.
@param A [IN]
coefficient matrix
@param strength_threshold [IN]
threshold parameter used to define strength
@param S_ptr [OUT]
strength matrix
@param CF_marker_ptr [IN/OUT]
array indicating C/F points
@see */
/*--------------------------------------------------------------------------*/
#define C_PT 1
#define F_PT -1
#define SF_PT -3
#define COMMON_C_PT 2
#define Z_PT -2
HYPRE_Int
hypre_BoomerAMGCoarsen( hypre_ParCSRMatrix *S,
hypre_ParCSRMatrix *A,
HYPRE_Int CF_init,
HYPRE_Int debug_flag,
HYPRE_Int **CF_marker_ptr)
{
MPI_Comm comm = hypre_ParCSRMatrixComm(S);
hypre_ParCSRCommPkg *comm_pkg = hypre_ParCSRMatrixCommPkg(S);
hypre_ParCSRCommHandle *comm_handle;
hypre_CSRMatrix *S_diag = hypre_ParCSRMatrixDiag(S);
HYPRE_Int *S_diag_i = hypre_CSRMatrixI(S_diag);
HYPRE_Int *S_diag_j = hypre_CSRMatrixJ(S_diag);
hypre_CSRMatrix *S_offd = hypre_ParCSRMatrixOffd(S);
HYPRE_Int *S_offd_i = hypre_CSRMatrixI(S_offd);
HYPRE_Int *S_offd_j = NULL;
HYPRE_BigInt *col_map_offd = hypre_ParCSRMatrixColMapOffd(S);
HYPRE_Int num_variables = hypre_CSRMatrixNumRows(S_diag);
HYPRE_BigInt col_1 = hypre_ParCSRMatrixFirstColDiag(S);
HYPRE_BigInt col_n = col_1 + (HYPRE_BigInt)hypre_CSRMatrixNumCols(S_diag);
HYPRE_Int num_cols_offd = 0;
hypre_CSRMatrix *S_ext;
HYPRE_Int *S_ext_i = NULL;
HYPRE_BigInt *S_ext_j = NULL;
HYPRE_Int num_sends = 0;
HYPRE_Int *int_buf_data;
HYPRE_Real *buf_data;
HYPRE_Int *CF_marker;
HYPRE_Int *CF_marker_offd;
HYPRE_Real *measure_array;
HYPRE_Int *graph_array;
HYPRE_Int *graph_array_offd;
HYPRE_Int graph_size;
HYPRE_BigInt big_graph_size;
HYPRE_Int graph_offd_size;
HYPRE_BigInt global_graph_size;
HYPRE_Int i, j, k, kc, jS, kS, ig, elmt;
HYPRE_Int index, start, my_id, num_procs, jrow, cnt, nnzrow;
HYPRE_Int use_commpkg_A = 0;
HYPRE_Int break_var = 1;
HYPRE_Real wall_time;
HYPRE_Int iter = 0;
HYPRE_BigInt big_k;
#if 0 /* debugging */
char filename[256];
FILE *fp;
HYPRE_Int iter = 0;
#endif
/*--------------------------------------------------------------
* Compute a ParCSR strength matrix, S.
*
* For now, the "strength" of dependence/influence is defined in
* the following way: i depends on j if
* aij > hypre_max (k != i) aik, aii < 0
* or
* aij < hypre_min (k != i) aik, aii >= 0
* Then S_ij = 1, else S_ij = 0.
*
* NOTE: the entries are negative initially, corresponding
* to "unaccounted-for" dependence.
*----------------------------------------------------------------*/
S_ext = NULL;
if (debug_flag == 3) wall_time = time_getWallclockSeconds();
hypre_MPI_Comm_size(comm,&num_procs);
hypre_MPI_Comm_rank(comm,&my_id);
if (!comm_pkg)
{
use_commpkg_A = 1;
comm_pkg = hypre_ParCSRMatrixCommPkg(A);
}
if (!comm_pkg)
{
hypre_MatvecCommPkgCreate(A);
comm_pkg = hypre_ParCSRMatrixCommPkg(A);
}
num_sends = hypre_ParCSRCommPkgNumSends(comm_pkg);
int_buf_data = hypre_CTAlloc(HYPRE_Int, hypre_ParCSRCommPkgSendMapStart(comm_pkg,
num_sends), HYPRE_MEMORY_HOST);
buf_data = hypre_CTAlloc(HYPRE_Real, hypre_ParCSRCommPkgSendMapStart(comm_pkg,
num_sends), HYPRE_MEMORY_HOST);
num_cols_offd = hypre_CSRMatrixNumCols(S_offd);
S_diag_j = hypre_CSRMatrixJ(S_diag);
if (num_cols_offd)
{
S_offd_j = hypre_CSRMatrixJ(S_offd);
}
/*----------------------------------------------------------
* Compute the measures
*
* The measures are currently given by the column sums of S.
* Hence, measure_array[i] is the number of influences
* of variable i.
*
* The measures are augmented by a random number
* between 0 and 1.
*----------------------------------------------------------*/
measure_array = hypre_CTAlloc(HYPRE_Real, num_variables+num_cols_offd, HYPRE_MEMORY_HOST);
for (i=0; i < S_offd_i[num_variables]; i++)
{
measure_array[num_variables + S_offd_j[i]] += 1.0;
}
if (num_procs > 1)
comm_handle = hypre_ParCSRCommHandleCreate(2, comm_pkg,
&measure_array[num_variables], buf_data);
for (i=0; i < S_diag_i[num_variables]; i++)
{
measure_array[S_diag_j[i]] += 1.0;
}
if (num_procs > 1)
hypre_ParCSRCommHandleDestroy(comm_handle);
index = 0;
for (i=0; i < num_sends; i++)
{
start = hypre_ParCSRCommPkgSendMapStart(comm_pkg, i);
for (j=start; j < hypre_ParCSRCommPkgSendMapStart(comm_pkg, i+1); j++)
measure_array[hypre_ParCSRCommPkgSendMapElmt(comm_pkg,j)]
+= buf_data[index++];
}
for (i=num_variables; i < num_variables+num_cols_offd; i++)
{
measure_array[i] = 0;
}
/* this augments the measures */
if (CF_init == 2)
hypre_BoomerAMGIndepSetInit(S, measure_array, 1);
else
hypre_BoomerAMGIndepSetInit(S, measure_array, 0);
/*---------------------------------------------------
* Initialize the graph array
* graph_array contains interior points in elements 0 ... num_variables-1
* followed by boundary values
*---------------------------------------------------*/
graph_array = hypre_CTAlloc(HYPRE_Int, num_variables, HYPRE_MEMORY_HOST);
if (num_cols_offd)
graph_array_offd = hypre_CTAlloc(HYPRE_Int, num_cols_offd, HYPRE_MEMORY_HOST);
else
graph_array_offd = NULL;
/* initialize measure array and graph array */
for (ig = 0; ig < num_cols_offd; ig++)
graph_array_offd[ig] = ig;
/*---------------------------------------------------
* Initialize the C/F marker array
* C/F marker array contains interior points in elements 0 ...
* num_variables-1 followed by boundary values
*---------------------------------------------------*/
graph_offd_size = num_cols_offd;
/* Allocate CF_marker if not done before */
if (*CF_marker_ptr == NULL)
{
*CF_marker_ptr = hypre_CTAlloc(HYPRE_Int, num_variables, HYPRE_MEMORY_HOST);
}
CF_marker = *CF_marker_ptr;
if (CF_init == 1)
{
cnt = 0;
for (i = 0; i < num_variables; i++)
{
if ( CF_marker[i] != SF_PT )
{
if ( (S_offd_i[i+1] - S_offd_i[i]) > 0 ||
(CF_marker[i] == F_PT) )
{
CF_marker[i] = 0;
}
if ( CF_marker[i] == Z_PT)
{
if ( (S_diag_i[i+1] - S_diag_i[i]) > 0 ||
(measure_array[i] >= 1.0) )
{
CF_marker[i] = 0;
graph_array[cnt++] = i;
}
else
{
CF_marker[i] = F_PT;
}
}
else
{
graph_array[cnt++] = i;
}
}
else
{
measure_array[i] = 0;
}
}
}
else
{
cnt = 0;
for (i = 0; i < num_variables; i++)
{
if ( CF_marker[i] != SF_PT )
{
CF_marker[i] = 0;
nnzrow = (S_diag_i[i+1] - S_diag_i[i]) + (S_offd_i[i+1] - S_offd_i[i]);
if (nnzrow == 0)
{
CF_marker[i] = SF_PT;
measure_array[i] = 0;
}
else
{
graph_array[cnt++] = i;
}
}
else
{
measure_array[i] = 0;
}
}
}
graph_size = cnt;
if (num_cols_offd)
CF_marker_offd = hypre_CTAlloc(HYPRE_Int, num_cols_offd, HYPRE_MEMORY_HOST);
else
CF_marker_offd = NULL;
for (i=0; i < num_cols_offd; i++)
CF_marker_offd[i] = 0;
/*---------------------------------------------------
* Loop until all points are either fine or coarse.
*---------------------------------------------------*/
if (num_procs > 1)
{
if (use_commpkg_A)
S_ext = hypre_ParCSRMatrixExtractBExt(S,A,0);
else
S_ext = hypre_ParCSRMatrixExtractBExt(S,S,0);
S_ext_i = hypre_CSRMatrixI(S_ext);
S_ext_j = hypre_CSRMatrixBigJ(S_ext);
}
/* compress S_ext and convert column numbers*/
index = 0;
for (i=0; i < num_cols_offd; i++)
{
for (j=S_ext_i[i]; j < S_ext_i[i+1]; j++)
{
big_k = S_ext_j[j];
if (big_k >= col_1 && big_k < col_n)
{
S_ext_j[index++] = big_k - col_1;
}
else
{
kc = hypre_BigBinarySearch(col_map_offd,big_k,num_cols_offd);
if (kc > -1) S_ext_j[index++] = (HYPRE_BigInt)(-kc-1);
}
}
S_ext_i[i] = index;
}
for (i = num_cols_offd; i > 0; i--)
S_ext_i[i] = S_ext_i[i-1];
if (num_procs > 1) S_ext_i[0] = 0;
if (debug_flag == 3)
{
wall_time = time_getWallclockSeconds() - wall_time;
hypre_printf("Proc = %d Initialize CLJP phase = %f\n",
my_id, wall_time);
}
while (1)
{
/*------------------------------------------------
* Exchange boundary data, i.i. get measures and S_ext_data
*------------------------------------------------*/
if (num_procs > 1)
comm_handle = hypre_ParCSRCommHandleCreate(2, comm_pkg,
&measure_array[num_variables], buf_data);
if (num_procs > 1)
hypre_ParCSRCommHandleDestroy(comm_handle);
index = 0;
for (i=0; i < num_sends; i++)
{
start = hypre_ParCSRCommPkgSendMapStart(comm_pkg, i);
for (j=start; j < hypre_ParCSRCommPkgSendMapStart(comm_pkg, i+1); j++)
measure_array[hypre_ParCSRCommPkgSendMapElmt(comm_pkg,j)]
+= buf_data[index++];
}
/*------------------------------------------------
* Set F-pts and update subgraph
*------------------------------------------------*/
if (iter || (CF_init != 1))
{
for (ig = 0; ig < graph_size; ig++)
{
i = graph_array[ig];
if ( (CF_marker[i] != C_PT) && (measure_array[i] < 1) )
{
/* set to be an F-pt */
CF_marker[i] = F_PT;
/* make sure all dependencies have been accounted for */
for (jS = S_diag_i[i]; jS < S_diag_i[i+1]; jS++)
{
if (S_diag_j[jS] > -1)
{
CF_marker[i] = 0;
}
}
for (jS = S_offd_i[i]; jS < S_offd_i[i+1]; jS++)
{
if (S_offd_j[jS] > -1)
{
CF_marker[i] = 0;
}
}
}
if (CF_marker[i])
{
measure_array[i] = 0;
/* take point out of the subgraph */
graph_size--;
graph_array[ig] = graph_array[graph_size];
graph_array[graph_size] = i;
ig--;
}
}
}
/*------------------------------------------------
* Exchange boundary data, i.i. get measures
*------------------------------------------------*/
if (debug_flag == 3) wall_time = time_getWallclockSeconds();
index = 0;
for (i = 0; i < num_sends; i++)
{
start = hypre_ParCSRCommPkgSendMapStart(comm_pkg, i);
for (j = start; j < hypre_ParCSRCommPkgSendMapStart(comm_pkg, i+1); j++)
{
jrow = hypre_ParCSRCommPkgSendMapElmt(comm_pkg,j);
buf_data[index++] = measure_array[jrow];
}
}
if (num_procs > 1)
{
comm_handle = hypre_ParCSRCommHandleCreate(1, comm_pkg, buf_data,
&measure_array[num_variables]);
hypre_ParCSRCommHandleDestroy(comm_handle);
}
/*------------------------------------------------
* Debugging:
*
* Uncomment the sections of code labeled
* "debugging" to generate several files that
* can be visualized using the `coarsen.m'
* matlab routine.
*------------------------------------------------*/
#if 0 /* debugging */
/* print out measures */
hypre_sprintf(filename, "coarsen.out.measures.%04d", iter);
fp = fopen(filename, "w");
for (i = 0; i < num_variables; i++)
{
hypre_fprintf(fp, "%f\n", measure_array[i]);
}
fclose(fp);
/* print out strength matrix */
hypre_sprintf(filename, "coarsen.out.strength.%04d", iter);
hypre_CSRMatrixPrint(S, filename);
/* print out C/F marker */
hypre_sprintf(filename, "coarsen.out.CF.%04d", iter);
fp = fopen(filename, "w");
for (i = 0; i < num_variables; i++)
{
hypre_fprintf(fp, "%d\n", CF_marker[i]);
}
fclose(fp);
iter++;
#endif
/*------------------------------------------------
* Test for convergence
*------------------------------------------------*/
big_graph_size = (HYPRE_BigInt) graph_size;
hypre_MPI_Allreduce(&big_graph_size,&global_graph_size,1,HYPRE_MPI_BIG_INT,hypre_MPI_SUM,comm);
if (global_graph_size == 0)
break;
/*------------------------------------------------
* Pick an independent set of points with
* maximal measure.
*------------------------------------------------*/
if (iter || (CF_init != 1))
{
hypre_BoomerAMGIndepSet(S, measure_array, graph_array,
graph_size,
graph_array_offd, graph_offd_size,
CF_marker, CF_marker_offd);
if (num_procs > 1)
{
comm_handle = hypre_ParCSRCommHandleCreate(12, comm_pkg,
CF_marker_offd, int_buf_data);
hypre_ParCSRCommHandleDestroy(comm_handle);
}
index = 0;
for (i = 0; i < num_sends; i++)
{
start = hypre_ParCSRCommPkgSendMapStart(comm_pkg, i);
for (j=start; j < hypre_ParCSRCommPkgSendMapStart(comm_pkg,i+1);j++) {
elmt = hypre_ParCSRCommPkgSendMapElmt(comm_pkg,j);
if (!int_buf_data[index++] && CF_marker[elmt] > 0)
{
CF_marker[elmt] = 0;
}
}
}
}
iter++;
/*------------------------------------------------
* Exchange boundary data for CF_marker
*------------------------------------------------*/
index = 0;
for (i = 0; i < num_sends; i++)
{
start = hypre_ParCSRCommPkgSendMapStart(comm_pkg, i);
for (j = start; j < hypre_ParCSRCommPkgSendMapStart(comm_pkg, i+1); j++)
{
elmt = hypre_ParCSRCommPkgSendMapElmt(comm_pkg,j);
int_buf_data[index++] = CF_marker[elmt];
}
}
if (num_procs > 1)
{
comm_handle = hypre_ParCSRCommHandleCreate(11, comm_pkg, int_buf_data,
CF_marker_offd);
hypre_ParCSRCommHandleDestroy(comm_handle);
}
for (ig = 0; ig < graph_offd_size; ig++)
{
i = graph_array_offd[ig];
if (CF_marker_offd[i] < 0)
{
/* take point out of the subgraph */
graph_offd_size--;
graph_array_offd[ig] = graph_array_offd[graph_offd_size];
graph_array_offd[graph_offd_size] = i;
ig--;
}
}
if (debug_flag == 3)
{
wall_time = time_getWallclockSeconds() - wall_time;
hypre_printf("Proc = %d iter %d comm. and subgraph update = %f\n",
my_id, iter, wall_time);
}
/*------------------------------------------------
* Set C_pts and apply heuristics.
*------------------------------------------------*/
for (i=num_variables; i < num_variables+num_cols_offd; i++)
{
measure_array[i] = 0;
}
if (debug_flag == 3) wall_time = time_getWallclockSeconds();
for (ig = 0; ig < graph_size; ig++)
{
i = graph_array[ig];
/*---------------------------------------------
* Heuristic: C-pts don't interpolate from
* neighbors that influence them.
*---------------------------------------------*/
if (CF_marker[i] > 0)
{
/* set to be a C-pt */
CF_marker[i] = C_PT;
for (jS = S_diag_i[i]; jS < S_diag_i[i+1]; jS++)
{
j = S_diag_j[jS];
if (j > -1)
{
/* "remove" edge from S */
S_diag_j[jS] = -S_diag_j[jS]-1;
/* decrement measures of unmarked neighbors */
if (!CF_marker[j])
{
measure_array[j]--;
}
}
}
for (jS = S_offd_i[i]; jS < S_offd_i[i+1]; jS++)
{
j = S_offd_j[jS];
if (j > -1)
{
/* "remove" edge from S */
S_offd_j[jS] = -S_offd_j[jS]-1;
/* decrement measures of unmarked neighbors */
if (!CF_marker_offd[j])
{
measure_array[j+num_variables]--;
}
}
}
}
else
{
/* marked dependencies */
for (jS = S_diag_i[i]; jS < S_diag_i[i+1]; jS++)
{
j = S_diag_j[jS];
if (j < 0) j = -j-1;
if (CF_marker[j] > 0)
{
if (S_diag_j[jS] > -1)
{
/* "remove" edge from S */
S_diag_j[jS] = -S_diag_j[jS]-1;
}
/* IMPORTANT: consider all dependencies */
/* temporarily modify CF_marker */
CF_marker[j] = COMMON_C_PT;
}
else if (CF_marker[j] == SF_PT)
{
if (S_diag_j[jS] > -1)
{
/* "remove" edge from S */
S_diag_j[jS] = -S_diag_j[jS]-1;
}
}
}
for (jS = S_offd_i[i]; jS < S_offd_i[i+1]; jS++)
{
j = S_offd_j[jS];
if (j < 0) j = -j-1;
if (CF_marker_offd[j] > 0)
{
if (S_offd_j[jS] > -1)
{
/* "remove" edge from S */
S_offd_j[jS] = -S_offd_j[jS]-1;
}
/* IMPORTANT: consider all dependencies */
/* temporarily modify CF_marker */
CF_marker_offd[j] = COMMON_C_PT;
}
else if (CF_marker_offd[j] == SF_PT)
{
if (S_offd_j[jS] > -1)
{
/* "remove" edge from S */
S_offd_j[jS] = -S_offd_j[jS]-1;
}
}
}
/* unmarked dependencies */
for (jS = S_diag_i[i]; jS < S_diag_i[i+1]; jS++)
{
if (S_diag_j[jS] > -1)
{
j = S_diag_j[jS];
break_var = 1;
/* check for common C-pt */
for (kS = S_diag_i[j]; kS < S_diag_i[j+1]; kS++)
{
k = S_diag_j[kS];
if (k < 0) k = -k-1;
/* IMPORTANT: consider all dependencies */
if (CF_marker[k] == COMMON_C_PT)
{
/* "remove" edge from S and update measure*/
S_diag_j[jS] = -S_diag_j[jS]-1;
measure_array[j]--;
break_var = 0;
break;
}
}
if (break_var)
{
for (kS = S_offd_i[j]; kS < S_offd_i[j+1]; kS++)
{
k = S_offd_j[kS];
if (k < 0) k = -k-1;
/* IMPORTANT: consider all dependencies */
if ( CF_marker_offd[k] == COMMON_C_PT)
{
/* "remove" edge from S and update measure*/
S_diag_j[jS] = -S_diag_j[jS]-1;
measure_array[j]--;
break;
}
}
}
}
}
for (jS = S_offd_i[i]; jS < S_offd_i[i+1]; jS++)
{
if (S_offd_j[jS] > -1)
{
j = S_offd_j[jS];
/* check for common C-pt */
for (kS = S_ext_i[j]; kS < S_ext_i[j+1]; kS++)
{
k = (HYPRE_Int)S_ext_j[kS];
if (k >= 0)
{
/* IMPORTANT: consider all dependencies */
if (CF_marker[k] == COMMON_C_PT)
{
/* "remove" edge from S and update measure*/
S_offd_j[jS] = -S_offd_j[jS]-1;
measure_array[j+num_variables]--;
break;
}
}
else
{
kc = -k-1;
if (kc > -1 && CF_marker_offd[kc] == COMMON_C_PT)
{
/* "remove" edge from S and update measure*/
S_offd_j[jS] = -S_offd_j[jS]-1;
measure_array[j+num_variables]--;
break;
}
}
}
}
}
}
/* reset CF_marker */
for (jS = S_diag_i[i]; jS < S_diag_i[i+1]; jS++)
{
j = S_diag_j[jS];
if (j < 0) j = -j-1;
if (CF_marker[j] == COMMON_C_PT)
{
CF_marker[j] = C_PT;
}
}
for (jS = S_offd_i[i]; jS < S_offd_i[i+1]; jS++)
{
j = S_offd_j[jS];
if (j < 0) j = -j-1;
if (CF_marker_offd[j] == COMMON_C_PT)
{
CF_marker_offd[j] = C_PT;
}
}
}
if (debug_flag == 3)
{
wall_time = time_getWallclockSeconds() - wall_time;
hypre_printf("Proc = %d CLJP phase = %f graph_size = %d nc_offd = %d\n",
my_id, wall_time, graph_size, num_cols_offd);
}
}
/*---------------------------------------------------
* Clean up and return
*---------------------------------------------------*/
/* Reset S_matrix */
for (i=0; i < S_diag_i[num_variables]; i++)
{
if (S_diag_j[i] < 0)
S_diag_j[i] = -S_diag_j[i]-1;
}
for (i=0; i < S_offd_i[num_variables]; i++)
{
if (S_offd_j[i] < 0)
S_offd_j[i] = -S_offd_j[i]-1;
}
/*for (i=0; i < num_variables; i++)
if (CF_marker[i] == SF_PT) CF_marker[i] = F_PT;*/
hypre_TFree(measure_array, HYPRE_MEMORY_HOST);
hypre_TFree(graph_array, HYPRE_MEMORY_HOST);
if (num_cols_offd) hypre_TFree(graph_array_offd, HYPRE_MEMORY_HOST);
hypre_TFree(buf_data, HYPRE_MEMORY_HOST);
hypre_TFree(int_buf_data, HYPRE_MEMORY_HOST);
hypre_TFree(CF_marker_offd, HYPRE_MEMORY_HOST);
if (num_procs > 1) hypre_CSRMatrixDestroy(S_ext);
return hypre_error_flag;
}
/*==========================================================================
* Ruge's coarsening algorithm
*==========================================================================*/
#define C_PT 1
#define F_PT -1
#define Z_PT -2
#define SF_PT -3 /* special fine points */
#define SC_PT 3 /* special coarse points */
#define UNDECIDED 0
/**************************************************************
*
* Ruge Coarsening routine
*
**************************************************************/
HYPRE_Int
hypre_BoomerAMGCoarsenRuge( hypre_ParCSRMatrix *S,
hypre_ParCSRMatrix *A,
HYPRE_Int measure_type,
HYPRE_Int coarsen_type,
HYPRE_Int cut_factor,
HYPRE_Int debug_flag,
HYPRE_Int **CF_marker_ptr)
{
MPI_Comm comm = hypre_ParCSRMatrixComm(S);
hypre_ParCSRCommPkg *comm_pkg = hypre_ParCSRMatrixCommPkg(S);
hypre_ParCSRCommHandle *comm_handle;
hypre_CSRMatrix *A_diag = hypre_ParCSRMatrixDiag(A);
hypre_CSRMatrix *S_diag = hypre_ParCSRMatrixDiag(S);
hypre_CSRMatrix *A_offd = hypre_ParCSRMatrixOffd(A);
hypre_CSRMatrix *S_offd = hypre_ParCSRMatrixOffd(S);
HYPRE_Int *A_i = hypre_CSRMatrixI(A_diag);
HYPRE_Int *S_i = hypre_CSRMatrixI(S_diag);
HYPRE_Int *S_j = hypre_CSRMatrixJ(S_diag);
HYPRE_Int *A_offd_i = hypre_CSRMatrixI(A_offd);
HYPRE_Int *S_offd_i = hypre_CSRMatrixI(S_offd);
HYPRE_Int *S_offd_j = NULL;
HYPRE_Int num_variables = hypre_CSRMatrixNumRows(S_diag);
HYPRE_Int num_cols_offd = hypre_CSRMatrixNumCols(S_offd);
HYPRE_BigInt *col_map_offd = hypre_ParCSRMatrixColMapOffd(S);
HYPRE_BigInt num_nonzeros = hypre_ParCSRMatrixNumNonzeros(A);
HYPRE_BigInt global_num_rows = hypre_ParCSRMatrixGlobalNumRows(A);
HYPRE_Int avg_nnzrow;
hypre_CSRMatrix *S_ext = NULL;
HYPRE_Int *S_ext_i = NULL;
HYPRE_BigInt *S_ext_j = NULL;
hypre_CSRMatrix *ST;
HYPRE_Int *ST_i;
HYPRE_Int *ST_j;
HYPRE_Int *CF_marker;
HYPRE_Int *CF_marker_offd = NULL;
HYPRE_Int ci_tilde = -1;
HYPRE_Int ci_tilde_mark = -1;
HYPRE_Int ci_tilde_offd = -1;
HYPRE_Int ci_tilde_offd_mark = -1;
HYPRE_Int *measure_array;
HYPRE_Int *graph_array;
HYPRE_Int *int_buf_data = NULL;
HYPRE_Int *ci_array = NULL;
HYPRE_BigInt big_k;
HYPRE_Int i, j, k, jS;
HYPRE_Int ji, jj, jk, jm, index;
HYPRE_Int set_empty = 1;
HYPRE_Int C_i_nonempty = 0;
HYPRE_Int cut, nnzrow;
HYPRE_Int num_procs, my_id;
HYPRE_Int num_sends = 0;
HYPRE_BigInt first_col;
HYPRE_Int start;
HYPRE_BigInt col_0, col_n;
hypre_LinkList LoL_head;
hypre_LinkList LoL_tail;
HYPRE_Int *lists, *where;
HYPRE_Int measure, new_meas;
HYPRE_Int meas_type = 0;
HYPRE_Int agg_2 = 0;
HYPRE_Int num_left, elmt;
HYPRE_Int nabor, nabor_two;
HYPRE_Int use_commpkg_A = 0;
HYPRE_Int break_var = 0;
HYPRE_Int f_pnt = F_PT;
HYPRE_Real wall_time;
if (coarsen_type < 0)
{
coarsen_type = -coarsen_type;
}
if (measure_type == 1 || measure_type == 4)
{
meas_type = 1;
}
if (measure_type == 4 || measure_type == 3)
{
agg_2 = 1;
}
/*-------------------------------------------------------
* Initialize the C/F marker, LoL_head, LoL_tail arrays
*-------------------------------------------------------*/
LoL_head = NULL;
LoL_tail = NULL;
lists = hypre_CTAlloc(HYPRE_Int, num_variables, HYPRE_MEMORY_HOST);
where = hypre_CTAlloc(HYPRE_Int, num_variables, HYPRE_MEMORY_HOST);
#if 0 /* debugging */
char filename[256];
FILE *fp;
HYPRE_Int iter = 0;
#endif
/*--------------------------------------------------------------
* Compute a CSR strength matrix, S.
*
* For now, the "strength" of dependence/influence is defined in
* the following way: i depends on j if
* aij > hypre_max (k != i) aik, aii < 0
* or
* aij < hypre_min (k != i) aik, aii >= 0
* Then S_ij = 1, else S_ij = 0.
*
* NOTE: the entries are negative initially, corresponding
* to "unaccounted-for" dependence.
*----------------------------------------------------------------*/
if (debug_flag == 3) wall_time = time_getWallclockSeconds();
first_col = hypre_ParCSRMatrixFirstColDiag(S);
col_0 = first_col-1;
col_n = col_0+(HYPRE_BigInt)num_variables;
hypre_MPI_Comm_size(comm,&num_procs);
hypre_MPI_Comm_rank(comm,&my_id);
if (!comm_pkg)
{
use_commpkg_A = 1;
comm_pkg = hypre_ParCSRMatrixCommPkg(A);
}
if (!comm_pkg)
{
hypre_MatvecCommPkgCreate(A);
comm_pkg = hypre_ParCSRMatrixCommPkg(A);
}
num_sends = hypre_ParCSRCommPkgNumSends(comm_pkg);
if (num_cols_offd)
{
S_offd_j = hypre_CSRMatrixJ(S_offd);
}
jS = S_i[num_variables];
ST = hypre_CSRMatrixCreate(num_variables, num_variables, jS);
hypre_CSRMatrixMemoryLocation(ST) = HYPRE_MEMORY_HOST;
ST_i = hypre_CTAlloc(HYPRE_Int, num_variables+1, HYPRE_MEMORY_HOST);
ST_j = hypre_CTAlloc(HYPRE_Int, jS, HYPRE_MEMORY_HOST);
hypre_CSRMatrixI(ST) = ST_i;
hypre_CSRMatrixJ(ST) = ST_j;
/*----------------------------------------------------------
* generate transpose of S, ST
*----------------------------------------------------------*/
for (i=0; i <= num_variables; i++)
{
ST_i[i] = 0;
}
for (i=0; i < jS; i++)
{
ST_i[S_j[i]+1]++;
}
for (i=0; i < num_variables; i++)
{
ST_i[i+1] += ST_i[i];
}
for (i=0; i < num_variables; i++)
{
for (j=S_i[i]; j < S_i[i+1]; j++)
{
index = S_j[j];
ST_j[ST_i[index]] = i;
ST_i[index]++;
}
}
for (i = num_variables; i > 0; i--)
{
ST_i[i] = ST_i[i-1];
}
ST_i[0] = 0;
/*----------------------------------------------------------
* Compute the measures
*
* The measures are given by the row sums of ST.
* Hence, measure_array[i] is the number of influences
* of variable i.
* correct actual measures through adding influences from
* neighbor processors
*----------------------------------------------------------*/
measure_array = hypre_CTAlloc(HYPRE_Int, num_variables, HYPRE_MEMORY_HOST);
for (i = 0; i < num_variables; i++)
{
measure_array[i] = ST_i[i+1]-ST_i[i];
}
/* special case for Falgout coarsening */
if (coarsen_type == 6)
{
f_pnt = Z_PT;
coarsen_type = 1;
}
if (coarsen_type == 10)
{
f_pnt = Z_PT;
coarsen_type = 11;
}
if ((meas_type || (coarsen_type != 1 && coarsen_type != 11)) && num_procs > 1)
{
if (use_commpkg_A)
S_ext = hypre_ParCSRMatrixExtractBExt(S,A,0);
else
S_ext = hypre_ParCSRMatrixExtractBExt(S,S,0);
S_ext_i = hypre_CSRMatrixI(S_ext);
S_ext_j = hypre_CSRMatrixBigJ(S_ext);
HYPRE_Int num_nonzeros = S_ext_i[num_cols_offd];
/*first_col = hypre_ParCSRMatrixFirstColDiag(S);
col_0 = first_col-1;
col_n = col_0+num_variables; */
if (meas_type)
{
for (i=0; i < num_nonzeros; i++)
{
index = (HYPRE_Int)(S_ext_j[i] - first_col);
if (index > -1 && index < num_variables)
measure_array[index]++;
}
}
}
/*---------------------------------------------------
* Loop until all points are either fine or coarse.
*---------------------------------------------------*/
if (debug_flag == 3) wall_time = time_getWallclockSeconds();
/* first coarsening phase */
/*************************************************************
*
* Initialize the lists
*
*************************************************************/
/* Allocate CF_marker if not done before */
if (*CF_marker_ptr == NULL)
{
*CF_marker_ptr = hypre_CTAlloc(HYPRE_Int, num_variables, HYPRE_MEMORY_HOST);
}
CF_marker = *CF_marker_ptr;
num_left = 0;
for (j = 0; j < num_variables; j++)
{
if (CF_marker[j] == 0)
{
nnzrow = (S_i[j+1] - S_i[j]) + (S_offd_i[j+1] - S_offd_i[j]);
if (nnzrow == 0)
{
CF_marker[j] = SF_PT;
if (agg_2)
{
CF_marker[j] = SC_PT;
}
measure_array[j] = 0;
}
else
{
CF_marker[j] = UNDECIDED;
num_left++;
}
}
else
{
measure_array[j] = 0;
}
}
/* Set dense rows as SF_PT */
if ((cut_factor > 0) && (global_num_rows > 0))
{
avg_nnzrow = num_nonzeros/global_num_rows;
cut = cut_factor*avg_nnzrow;
for (j = 0; j < num_variables; j++)
{
nnzrow = (A_i[j+1] - A_i[j]) + (A_offd_i[j+1] - A_offd_i[j]);
if (nnzrow > cut)
{
if (CF_marker[j] == UNDECIDED)
{
num_left--;
}
CF_marker[j] = SF_PT;
}
}
}
for (j = 0; j < num_variables; j++)
{
measure = measure_array[j];
if (CF_marker[j] != SF_PT && CF_marker[j] != SC_PT)
{
if (measure > 0)
{
hypre_enter_on_lists(&LoL_head, &LoL_tail, measure, j, lists, where);
}
else
{
if (measure < 0)
{
hypre_error_w_msg(HYPRE_ERROR_GENERIC,"negative measure!\n");
}
CF_marker[j] = f_pnt;
for (k = S_i[j]; k < S_i[j+1]; k++)
{
nabor = S_j[k];
if (CF_marker[nabor] != SF_PT && CF_marker[nabor] != SC_PT)
{
if (nabor < j)
{
new_meas = measure_array[nabor];
if (new_meas > 0)
{
hypre_remove_point(&LoL_head, &LoL_tail, new_meas,
nabor, lists, where);
}
new_meas = ++(measure_array[nabor]);
hypre_enter_on_lists(&LoL_head, &LoL_tail, new_meas,
nabor, lists, where);
}
else
{
new_meas = ++(measure_array[nabor]);
}
}
}
--num_left;
}
}
}
/****************************************************************
*
* Main loop of Ruge-Stueben first coloring pass.
*
* WHILE there are still points to classify DO:
* 1) find first point, i, on list with max_measure
* make i a C-point, remove it from the lists
* 2) For each point, j, in S_i^T,
* a) Set j to be an F-point
* b) For each point, k, in S_j
* move k to the list in LoL with measure one
* greater than it occupies (creating new LoL
* entry if necessary)
* 3) For each point, j, in S_i,
* move j to the list in LoL with measure one
* smaller than it occupies (creating new LoL
* entry if necessary)
*
****************************************************************/
while (num_left > 0)
{
index = LoL_head -> head;
CF_marker[index] = C_PT;
measure = measure_array[index];
measure_array[index] = 0;
--num_left;
hypre_remove_point(&LoL_head, &LoL_tail, measure, index, lists, where);
for (j = ST_i[index]; j < ST_i[index+1]; j++)
{
nabor = ST_j[j];
if (CF_marker[nabor] == UNDECIDED)
{
CF_marker[nabor] = F_PT;
measure = measure_array[nabor];
hypre_remove_point(&LoL_head, &LoL_tail, measure, nabor, lists, where);
--num_left;
for (k = S_i[nabor]; k < S_i[nabor+1]; k++)
{
nabor_two = S_j[k];
if (CF_marker[nabor_two] == UNDECIDED)
{
measure = measure_array[nabor_two];
hypre_remove_point(&LoL_head, &LoL_tail, measure,
nabor_two, lists, where);
new_meas = ++(measure_array[nabor_two]);
hypre_enter_on_lists(&LoL_head, &LoL_tail, new_meas,
nabor_two, lists, where);
}
}
}
}
for (j = S_i[index]; j < S_i[index+1]; j++)
{
nabor = S_j[j];
if (CF_marker[nabor] == UNDECIDED)
{
measure = measure_array[nabor];
hypre_remove_point(&LoL_head, &LoL_tail, measure, nabor, lists, where);
measure_array[nabor] = --measure;
if (measure > 0)
{
hypre_enter_on_lists(&LoL_head, &LoL_tail, measure, nabor,
lists, where);
}
else
{
CF_marker[nabor] = F_PT;
--num_left;
for (k = S_i[nabor]; k < S_i[nabor+1]; k++)
{
nabor_two = S_j[k];
if (CF_marker[nabor_two] == UNDECIDED)
{
new_meas = measure_array[nabor_two];
hypre_remove_point(&LoL_head, &LoL_tail, new_meas,
nabor_two, lists, where);
new_meas = ++(measure_array[nabor_two]);
hypre_enter_on_lists(&LoL_head, &LoL_tail, new_meas,
nabor_two, lists, where);
}
}
}
}
}
}
hypre_TFree(measure_array, HYPRE_MEMORY_HOST);
hypre_CSRMatrixDestroy(ST);
if (debug_flag == 3)
{
wall_time = time_getWallclockSeconds() - wall_time;
hypre_printf("Proc = %d Coarsen 1st pass = %f\n",
my_id, wall_time);
}
hypre_TFree(lists, HYPRE_MEMORY_HOST);
hypre_TFree(where, HYPRE_MEMORY_HOST);
hypre_TFree(LoL_head, HYPRE_MEMORY_HOST);
hypre_TFree(LoL_tail, HYPRE_MEMORY_HOST);
for (i=0; i < num_variables; i++)
{
if (CF_marker[i] == SC_PT)
{
CF_marker[i] = C_PT;
}
}
if (coarsen_type == 11)
{
if (meas_type && num_procs > 1)
{
hypre_CSRMatrixDestroy(S_ext);
}
return 0;
}
/* second pass, check fine points for coarse neighbors
for coarsen_type = 2, the second pass includes
off-processore boundary points */
/*---------------------------------------------------
* Initialize the graph array
*---------------------------------------------------*/
graph_array = hypre_CTAlloc(HYPRE_Int, num_variables, HYPRE_MEMORY_HOST);
for (i = 0; i < num_variables; i++)
{
graph_array[i] = -1;
}
if (debug_flag == 3) wall_time = time_getWallclockSeconds();
if (coarsen_type == 2)
{
/*------------------------------------------------
* Exchange boundary data for CF_marker
*------------------------------------------------*/
CF_marker_offd = hypre_CTAlloc(HYPRE_Int, num_cols_offd, HYPRE_MEMORY_HOST);
int_buf_data = hypre_CTAlloc(HYPRE_Int, hypre_ParCSRCommPkgSendMapStart(comm_pkg,
num_sends), HYPRE_MEMORY_HOST);
index = 0;
for (i = 0; i < num_sends; i++)
{
start = hypre_ParCSRCommPkgSendMapStart(comm_pkg, i);
for (j = start; j < hypre_ParCSRCommPkgSendMapStart(comm_pkg, i+1); j++)
{
int_buf_data[index++] = CF_marker[hypre_ParCSRCommPkgSendMapElmt(comm_pkg,j)];
}
}
if (num_procs > 1)
{
comm_handle = hypre_ParCSRCommHandleCreate(11, comm_pkg, int_buf_data,
CF_marker_offd);
hypre_ParCSRCommHandleDestroy(comm_handle);
}
ci_array = hypre_CTAlloc(HYPRE_Int, num_cols_offd, HYPRE_MEMORY_HOST);
for (i=0; i < num_cols_offd; i++)
ci_array[i] = -1;
for (i=0; i < num_variables; i++)
{
if (ci_tilde_mark != i) ci_tilde = -1;
if (ci_tilde_offd_mark != i) ci_tilde_offd = -1;
if (CF_marker[i] == -1)
{
break_var = 1;
for (ji = S_i[i]; ji < S_i[i+1]; ji++)
{
j = S_j[ji];
if (CF_marker[j] > 0)
graph_array[j] = i;
}
for (ji = S_offd_i[i]; ji < S_offd_i[i+1]; ji++)
{
j = S_offd_j[ji];
if (CF_marker_offd[j] > 0)
ci_array[j] = i;
}
for (ji = S_i[i]; ji < S_i[i+1]; ji++)
{
j = S_j[ji];
if (CF_marker[j] == -1)
{
set_empty = 1;
for (jj = S_i[j]; jj < S_i[j+1]; jj++)
{
index = S_j[jj];
if (graph_array[index] == i)
{
set_empty = 0;
break;
}
}
if (set_empty)
{
for (jj = S_offd_i[j]; jj < S_offd_i[j+1]; jj++)
{
index = S_offd_j[jj];
if (ci_array[index] == i)
{
set_empty = 0;
break;
}
}
}
if (set_empty)
{
if (C_i_nonempty)
{
CF_marker[i] = 1;
if (ci_tilde > -1)
{
CF_marker[ci_tilde] = -1;
ci_tilde = -1;
}
if (ci_tilde_offd > -1)
{
CF_marker_offd[ci_tilde_offd] = -1;
ci_tilde_offd = -1;
}
C_i_nonempty = 0;
break_var = 0;
break;
}
else
{
ci_tilde = j;
ci_tilde_mark = i;
CF_marker[j] = 1;
C_i_nonempty = 1;
i--;
break_var = 0;
break;
}
}
}
}
if (break_var)
{
for (ji = S_offd_i[i]; ji < S_offd_i[i+1]; ji++)
{
j = S_offd_j[ji];
if (CF_marker_offd[j] == -1)
{
set_empty = 1;
for (jj = S_ext_i[j]; jj < S_ext_i[j+1]; jj++)
{
big_k = S_ext_j[jj];
if (big_k > col_0 && big_k < col_n) /* index interior */
{
if (graph_array[(HYPRE_Int)(big_k-first_col)] == i)
{
set_empty = 0;
break;
}
}
else
{
jk = hypre_BigBinarySearch(col_map_offd,big_k,num_cols_offd);
if (jk != -1)
{
if (ci_array[jk] == i)
{
set_empty = 0;
break;
}
}
}
}
if (set_empty)
{
if (C_i_nonempty)
{
CF_marker[i] = 1;
if (ci_tilde > -1)
{
CF_marker[ci_tilde] = -1;
ci_tilde = -1;
}
if (ci_tilde_offd > -1)
{
CF_marker_offd[ci_tilde_offd] = -1;
ci_tilde_offd = -1;
}
C_i_nonempty = 0;
break;
}
else
{
ci_tilde_offd = j;
ci_tilde_offd_mark = i;
CF_marker_offd[j] = 1;
C_i_nonempty = 1;
i--;
break;
}
}
}
}
}
}
}
}
else
{
for (i=0; i < num_variables; i++)
{
if (ci_tilde_mark != i) ci_tilde = -1;
if (CF_marker[i] == -1)
{
for (ji = S_i[i]; ji < S_i[i+1]; ji++)
{
j = S_j[ji];
if (CF_marker[j] > 0)
graph_array[j] = i;
}
for (ji = S_i[i]; ji < S_i[i+1]; ji++)
{
j = S_j[ji];
if (CF_marker[j] == -1)
{
set_empty = 1;
for (jj = S_i[j]; jj < S_i[j+1]; jj++)
{
index = S_j[jj];
if (graph_array[index] == i)
{
set_empty = 0;
break;
}
}
if (set_empty)
{
if (C_i_nonempty)
{
CF_marker[i] = 1;
if (ci_tilde > -1)
{
CF_marker[ci_tilde] = -1;
ci_tilde = -1;
}
C_i_nonempty = 0;
break;
}
else
{
ci_tilde = j;
ci_tilde_mark = i;
CF_marker[j] = 1;
C_i_nonempty = 1;
i--;
break;
}
}
}
}
}
}
}
if (debug_flag == 3 && coarsen_type != 2)
{
wall_time = time_getWallclockSeconds() - wall_time;
hypre_printf("Proc = %d Coarsen 2nd pass = %f\n",
my_id, wall_time);
}
/* third pass, check boundary fine points for coarse neighbors */
if (coarsen_type == 3 || coarsen_type == 4)
{
if (debug_flag == 3) wall_time = time_getWallclockSeconds();
CF_marker_offd = hypre_CTAlloc(HYPRE_Int, num_cols_offd, HYPRE_MEMORY_HOST);
int_buf_data = hypre_CTAlloc(HYPRE_Int, hypre_ParCSRCommPkgSendMapStart(comm_pkg, num_sends),
HYPRE_MEMORY_HOST);
/*------------------------------------------------
* Exchange boundary data for CF_marker
*------------------------------------------------*/
index = 0;
for (i = 0; i < num_sends; i++)
{
start = hypre_ParCSRCommPkgSendMapStart(comm_pkg, i);
for (j = start; j < hypre_ParCSRCommPkgSendMapStart(comm_pkg, i+1); j++)
int_buf_data[index++]
= CF_marker[hypre_ParCSRCommPkgSendMapElmt(comm_pkg,j)];
}
if (num_procs > 1)
{
comm_handle = hypre_ParCSRCommHandleCreate(11, comm_pkg, int_buf_data,
CF_marker_offd);
hypre_ParCSRCommHandleDestroy(comm_handle);
}
ci_array = hypre_CTAlloc(HYPRE_Int, num_cols_offd, HYPRE_MEMORY_HOST);
for (i=0; i < num_cols_offd; i++)
ci_array[i] = -1;
}
if (coarsen_type > 1 && coarsen_type < 5)
{
for (i=0; i < num_variables; i++)
graph_array[i] = -1;
for (i=0; i < num_cols_offd; i++)
{
if (ci_tilde_mark != i) ci_tilde = -1;
if (ci_tilde_offd_mark != i) ci_tilde_offd = -1;
if (CF_marker_offd[i] == -1)
{
for (ji = S_ext_i[i]; ji < S_ext_i[i+1]; ji++)
{
big_k = S_ext_j[ji];
if (big_k > col_0 && big_k < col_n)
{
j = (HYPRE_Int)(big_k - first_col);
if (CF_marker[j] > 0)
graph_array[j] = i;
}
else
{
jj = hypre_BigBinarySearch(col_map_offd,big_k,num_cols_offd);
if (jj != -1 && CF_marker_offd[jj] > 0)
ci_array[jj] = i;
}
}
for (ji = S_ext_i[i]; ji < S_ext_i[i+1]; ji++)
{
big_k = S_ext_j[ji];
if (big_k > col_0 && big_k < col_n)
{
j = (HYPRE_Int)(big_k - first_col);
if ( CF_marker[j] == -1)
{
set_empty = 1;
for (jj = S_i[j]; jj < S_i[j+1]; jj++)
{
index = S_j[jj];
if (graph_array[index] == i)
{
set_empty = 0;
break;
}
}
for (jj = S_offd_i[j]; jj < S_offd_i[j+1]; jj++)
{
index = S_offd_j[jj];
if (ci_array[index] == i)
{
set_empty = 0;
break;
}
}
if (set_empty)
{
if (C_i_nonempty)
{
CF_marker_offd[i] = 1;
if (ci_tilde > -1)
{
CF_marker[ci_tilde] = -1;
ci_tilde = -1;
}
if (ci_tilde_offd > -1)
{
CF_marker_offd[ci_tilde_offd] = -1;
ci_tilde_offd = -1;
}
C_i_nonempty = 0;
break;
}
else
{
ci_tilde = j;
ci_tilde_mark = i;
CF_marker[j] = 1;
C_i_nonempty = 1;
i--;
break;
}
}
}
}
else
{
jm = hypre_BigBinarySearch(col_map_offd,big_k,num_cols_offd);
if (jm != -1 && CF_marker_offd[jm] == -1)
{
set_empty = 1;
for (jj = S_ext_i[jm]; jj < S_ext_i[jm+1]; jj++)
{
big_k = S_ext_j[jj];
if (big_k > col_0 && big_k < col_n)
{
if (graph_array[(HYPRE_Int)(big_k-first_col)] == i)
{
set_empty = 0;
break;
}
}
else
{
jk = hypre_BigBinarySearch(col_map_offd,big_k,num_cols_offd);
if (jk != -1)
{
if (ci_array[jk] == i)
{
set_empty = 0;
break;
}
}
}
}
if (set_empty)
{
if (C_i_nonempty)
{
CF_marker_offd[i] = 1;
if (ci_tilde > -1)
{
CF_marker[ci_tilde] = -1;
ci_tilde = -1;
}
if (ci_tilde_offd > -1)
{
CF_marker_offd[ci_tilde_offd] = -1;
ci_tilde_offd = -1;
}
C_i_nonempty = 0;
break;
}
else
{
ci_tilde_offd = jm;
ci_tilde_offd_mark = i;
CF_marker_offd[jm] = 1;
C_i_nonempty = 1;
i--;
break;
}
}
}
}
}
}
}
/*------------------------------------------------
* Send boundary data for CF_marker back
*------------------------------------------------*/
if (num_procs > 1)
{
comm_handle = hypre_ParCSRCommHandleCreate(12, comm_pkg, CF_marker_offd,
int_buf_data);
hypre_ParCSRCommHandleDestroy(comm_handle);
}
/* only CF_marker entries from larger procs are accepted
if coarsen_type = 4 coarse points are not overwritten */
index = 0;
if (coarsen_type != 4)
{
for (i = 0; i < num_sends; i++)
{
start = hypre_ParCSRCommPkgSendMapStart(comm_pkg, i);
if (hypre_ParCSRCommPkgSendProc(comm_pkg,i) > my_id)
{
for (j = start; j < hypre_ParCSRCommPkgSendMapStart(comm_pkg, i+1); j++)
CF_marker[hypre_ParCSRCommPkgSendMapElmt(comm_pkg,j)] =
int_buf_data[index++];
}
else
{
index += hypre_ParCSRCommPkgSendMapStart(comm_pkg, i+1) - start;
}
}
}
else
{
for (i = 0; i < num_sends; i++)
{
start = hypre_ParCSRCommPkgSendMapStart(comm_pkg, i);
if (hypre_ParCSRCommPkgSendProc(comm_pkg,i) > my_id)
{
for (j = start; j < hypre_ParCSRCommPkgSendMapStart(comm_pkg, i+1); j++)
{
elmt = hypre_ParCSRCommPkgSendMapElmt(comm_pkg,j);
if (CF_marker[elmt] != 1)
CF_marker[elmt] = int_buf_data[index];
index++;
}
}
else
{
index += hypre_ParCSRCommPkgSendMapStart(comm_pkg, i+1) - start;
}
}
}
if (debug_flag == 3)
{
wall_time = time_getWallclockSeconds() - wall_time;
if (coarsen_type == 4)
hypre_printf("Proc = %d Coarsen 3rd pass = %f\n",
my_id, wall_time);
if (coarsen_type == 3)
hypre_printf("Proc = %d Coarsen 3rd pass = %f\n",
my_id, wall_time);
if (coarsen_type == 2)
hypre_printf("Proc = %d Coarsen 2nd pass = %f\n",
my_id, wall_time);
}
}
if (coarsen_type == 5)
{
/*------------------------------------------------
* Exchange boundary data for CF_marker
*------------------------------------------------*/
if (debug_flag == 3) wall_time = time_getWallclockSeconds();
CF_marker_offd = hypre_CTAlloc(HYPRE_Int, num_cols_offd, HYPRE_MEMORY_HOST);
int_buf_data = hypre_CTAlloc(HYPRE_Int, hypre_ParCSRCommPkgSendMapStart(comm_pkg,
num_sends), HYPRE_MEMORY_HOST);
index = 0;
for (i = 0; i < num_sends; i++)
{
start = hypre_ParCSRCommPkgSendMapStart(comm_pkg, i);
for (j = start; j < hypre_ParCSRCommPkgSendMapStart(comm_pkg, i+1); j++)
int_buf_data[index++]
= CF_marker[hypre_ParCSRCommPkgSendMapElmt(comm_pkg,j)];
}
if (num_procs > 1)
{
comm_handle = hypre_ParCSRCommHandleCreate(11, comm_pkg, int_buf_data,
CF_marker_offd);
hypre_ParCSRCommHandleDestroy(comm_handle);
}
ci_array = hypre_CTAlloc(HYPRE_Int, num_cols_offd, HYPRE_MEMORY_HOST);
for (i=0; i < num_cols_offd; i++)
ci_array[i] = -1;
for (i=0; i < num_variables; i++)
graph_array[i] = -1;
for (i=0; i < num_variables; i++)
{
if (CF_marker[i] == -1 && (S_offd_i[i+1]-S_offd_i[i]) > 0)
{
break_var = 1;
for (ji = S_i[i]; ji < S_i[i+1]; ji++)
{
j = S_j[ji];
if (CF_marker[j] > 0)
graph_array[j] = i;
}
for (ji = S_offd_i[i]; ji < S_offd_i[i+1]; ji++)
{
j = S_offd_j[ji];
if (CF_marker_offd[j] > 0)
ci_array[j] = i;
}
for (ji = S_offd_i[i]; ji < S_offd_i[i+1]; ji++)
{
j = S_offd_j[ji];
if (CF_marker_offd[j] == -1)
{
set_empty = 1;
for (jj = S_ext_i[j]; jj < S_ext_i[j+1]; jj++)
{
big_k = S_ext_j[jj];
if (big_k > col_0 && big_k < col_n) /* index interior */
{
if (graph_array[(HYPRE_Int)(big_k-first_col)] == i)
{
set_empty = 0;
break;
}
}
else
{
jk = hypre_BigBinarySearch(col_map_offd,big_k,num_cols_offd);
if (jk != -1)
{
if (ci_array[jk] == i)
{
set_empty = 0;
break;
}
}
}
}
if (set_empty)
{
if (C_i_nonempty)
{
CF_marker[i] = -2;
C_i_nonempty = 0;
break;
}
else
{
C_i_nonempty = 1;
i--;
break;
}
}
}
}
}
}
if (debug_flag == 3)
{
wall_time = time_getWallclockSeconds() - wall_time;
hypre_printf("Proc = %d Coarsen special points = %f\n",
my_id, wall_time);
}
}
/*---------------------------------------------------
* Clean up and return
*---------------------------------------------------*/
/*if (coarsen_type != 1)
{ */
hypre_TFree(CF_marker_offd, HYPRE_MEMORY_HOST);
hypre_TFree(int_buf_data, HYPRE_MEMORY_HOST);
hypre_TFree(ci_array, HYPRE_MEMORY_HOST);
/*} */
hypre_TFree(graph_array, HYPRE_MEMORY_HOST);
if ((meas_type || (coarsen_type != 1 && coarsen_type != 11)) && num_procs > 1)
{
hypre_CSRMatrixDestroy(S_ext);
}
return hypre_error_flag;
}
HYPRE_Int
hypre_BoomerAMGCoarsenFalgout( hypre_ParCSRMatrix *S,
hypre_ParCSRMatrix *A,
HYPRE_Int measure_type,
HYPRE_Int cut_factor,
HYPRE_Int debug_flag,
HYPRE_Int **CF_marker_ptr)
{
HYPRE_Int ierr = 0;
/*-------------------------------------------------------
* Perform Ruge coarsening followed by CLJP coarsening
*-------------------------------------------------------*/
ierr += hypre_BoomerAMGCoarsenRuge (S, A, measure_type, 6, cut_factor,
debug_flag, CF_marker_ptr);
ierr += hypre_BoomerAMGCoarsen (S, A, 1, debug_flag, CF_marker_ptr);
return (ierr);
}
/*--------------------------------------------------------------------------*/
#define C_PT 1
#define F_PT -1
#define SF_PT -3
#define COMMON_C_PT 2
#define Z_PT -2
/* begin HANS added */
/**************************************************************
*
* Modified Independent Set Coarsening routine
* (don't worry about strong F-F connections
* without a common C point)
*
**************************************************************/
HYPRE_Int
hypre_BoomerAMGCoarsenPMISHost( hypre_ParCSRMatrix *S,
hypre_ParCSRMatrix *A,
HYPRE_Int CF_init,
HYPRE_Int debug_flag,
HYPRE_Int **CF_marker_ptr)
{
#ifdef HYPRE_PROFILE
hypre_profile_times[HYPRE_TIMER_ID_PMIS] -= hypre_MPI_Wtime();
#endif
MPI_Comm comm = hypre_ParCSRMatrixComm(S);
hypre_ParCSRCommPkg *comm_pkg = hypre_ParCSRMatrixCommPkg(S);
hypre_ParCSRCommHandle *comm_handle;
hypre_CSRMatrix *S_diag = hypre_ParCSRMatrixDiag(S);
HYPRE_Int *S_diag_i = hypre_CSRMatrixI(S_diag);
HYPRE_Int *S_diag_j = hypre_CSRMatrixJ(S_diag);
hypre_CSRMatrix *S_offd = hypre_ParCSRMatrixOffd(S);
HYPRE_Int *S_offd_i = hypre_CSRMatrixI(S_offd);
HYPRE_Int *S_offd_j;
HYPRE_Int num_variables = hypre_CSRMatrixNumRows(S_diag);
HYPRE_Int num_cols_offd = 0;
/* hypre_CSRMatrix *S_ext;
HYPRE_Int *S_ext_i;
HYPRE_Int *S_ext_j; */
HYPRE_Int num_sends = 0;
HYPRE_Int *int_buf_data;
HYPRE_Real *buf_data;
HYPRE_Int *CF_marker;
HYPRE_Int *CF_marker_offd;
HYPRE_Real *measure_array;
HYPRE_Int *graph_array;
HYPRE_Int *graph_array_offd;
HYPRE_Int graph_size;
HYPRE_BigInt big_graph_size;
HYPRE_Int graph_offd_size;
HYPRE_BigInt global_graph_size;
HYPRE_Int i, j, jj, jS, ig;
HYPRE_Int index, start, my_id, num_procs, jrow, cnt, elmt;
HYPRE_Int nnzrow;
HYPRE_Int ierr = 0;
HYPRE_Real wall_time;
HYPRE_Int iter = 0;
HYPRE_Int *prefix_sum_workspace;
#if 0 /* debugging */
char filename[256];
FILE *fp;
HYPRE_Int iter = 0;
#endif
/*******************************************************************************
BEFORE THE INDEPENDENT SET COARSENING LOOP:
measure_array: calculate the measures, and communicate them
(this array contains measures for both local and external nodes)
CF_marker, CF_marker_offd: initialize CF_marker
(separate arrays for local and external; 0=unassigned, negative=F point, positive=C point)
******************************************************************************/
/*--------------------------------------------------------------
* Use the ParCSR strength matrix, S.
*
* For now, the "strength" of dependence/influence is defined in
* the following way: i depends on j if
* aij > hypre_max (k != i) aik, aii < 0
* or
* aij < hypre_min (k != i) aik, aii >= 0
* Then S_ij = 1, else S_ij = 0.
*
* NOTE: S_data is not used; in stead, only strong columns are retained
* in S_j, which can then be used like S_data
*----------------------------------------------------------------*/
/*S_ext = NULL; */
if (debug_flag == 3)
{
wall_time = time_getWallclockSeconds();
}
hypre_MPI_Comm_size(comm, &num_procs);
hypre_MPI_Comm_rank(comm, &my_id);
if (!comm_pkg)
{
comm_pkg = hypre_ParCSRMatrixCommPkg(A);
}
if (!comm_pkg)
{
hypre_MatvecCommPkgCreate(A);
comm_pkg = hypre_ParCSRMatrixCommPkg(A);
}
num_sends = hypre_ParCSRCommPkgNumSends(comm_pkg);
int_buf_data = hypre_CTAlloc(HYPRE_Int, hypre_ParCSRCommPkgSendMapStart(comm_pkg, num_sends), HYPRE_MEMORY_HOST);
buf_data = hypre_CTAlloc(HYPRE_Real, hypre_ParCSRCommPkgSendMapStart(comm_pkg, num_sends), HYPRE_MEMORY_HOST);
num_cols_offd = hypre_CSRMatrixNumCols(S_offd);
S_diag_j = hypre_CSRMatrixJ(S_diag);
if (num_cols_offd)
{
S_offd_j = hypre_CSRMatrixJ(S_offd);
}
/*----------------------------------------------------------
* Compute the measures
*
* The measures are currently given by the column sums of S.
* Hence, measure_array[i] is the number of influences
* of variable i.
*
* The measures are augmented by a random number
* between 0 and 1.
*----------------------------------------------------------*/
measure_array = hypre_CTAlloc(HYPRE_Real, num_variables + num_cols_offd, HYPRE_MEMORY_HOST);
/* first calculate the local part of the sums for the external nodes */
#ifdef HYPRE_USING_OPENMP
HYPRE_Int *measure_array_temp = hypre_CTAlloc(HYPRE_Int, num_variables + num_cols_offd, HYPRE_MEMORY_HOST);
#pragma omp parallel for private(i) HYPRE_SMP_SCHEDULE
for (i = 0; i < S_offd_i[num_variables]; i++)
{
#pragma omp atomic
measure_array_temp[num_variables + S_offd_j[i]]++;
}
#pragma omp parallel for private(i) HYPRE_SMP_SCHEDULE
for (i = 0; i < num_cols_offd; i++)
{
measure_array[i + num_variables] = measure_array_temp[i + num_variables];
}
#else
for (i = 0; i < S_offd_i[num_variables]; i++)
{
measure_array[num_variables + S_offd_j[i]] += 1.0;
}
#endif // HYPRE_USING_OPENMP
/* now send those locally calculated values for the external nodes to the neighboring processors */
if (num_procs > 1)
{
comm_handle = hypre_ParCSRCommHandleCreate(2, comm_pkg, &measure_array[num_variables], buf_data);
}
/* calculate the local part for the local nodes */
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(i) HYPRE_SMP_SCHEDULE
for (i = 0; i < S_diag_i[num_variables]; i++)
{
#pragma omp atomic
measure_array_temp[S_diag_j[i]]++;
}
#pragma omp parallel for private(i) HYPRE_SMP_SCHEDULE
for (i = 0; i < num_variables; i++)
{
measure_array[i] = measure_array_temp[i];
}
hypre_TFree(measure_array_temp, HYPRE_MEMORY_HOST);
#else
for (i = 0; i < S_diag_i[num_variables]; i++)
{
measure_array[S_diag_j[i]] += 1.0;
}
#endif // HYPRE_USING_OPENMP
/* finish the communication */
if (num_procs > 1)
{
hypre_ParCSRCommHandleDestroy(comm_handle);
}
/* now add the externally calculated part of the local nodes to the local nodes */
index = 0;
for (i = 0; i < num_sends; i++)
{
start = hypre_ParCSRCommPkgSendMapStart(comm_pkg, i);
for (j = start; j < hypre_ParCSRCommPkgSendMapStart(comm_pkg, i+1); j++)
{
measure_array[hypre_ParCSRCommPkgSendMapElmt(comm_pkg,j)] += buf_data[index++];
}
}
/* set the measures of the external nodes to zero */
for (i = num_variables; i < num_variables + num_cols_offd; i++)
{
measure_array[i] = 0;
}
/* this augments the measures with a random number between 0 and 1 */
/* (only for the local part) */
/* this augments the measures */
if (CF_init == 2 || CF_init == 4)
{
hypre_BoomerAMGIndepSetInit(S, measure_array, 1);
}
else
{
hypre_BoomerAMGIndepSetInit(S, measure_array, 0);
}
/*---------------------------------------------------
* Initialize the graph arrays, and CF_marker arrays
*---------------------------------------------------*/
/* first the off-diagonal part of the graph array */
if (num_cols_offd)
{
graph_array_offd = hypre_CTAlloc(HYPRE_Int, num_cols_offd, HYPRE_MEMORY_HOST);
}
else
{
graph_array_offd = NULL;
}
for (ig = 0; ig < num_cols_offd; ig++)
{
graph_array_offd[ig] = ig;
}
graph_offd_size = num_cols_offd;
/* now the local part of the graph array, and the local CF_marker array */
graph_array = hypre_CTAlloc(HYPRE_Int, num_variables, HYPRE_MEMORY_HOST);
/* Allocate CF_marker if not done before */
if (*CF_marker_ptr == NULL)
{
*CF_marker_ptr = hypre_CTAlloc(HYPRE_Int, num_variables, HYPRE_MEMORY_HOST);
}
CF_marker = *CF_marker_ptr;
if (CF_init == 1)
{
cnt = 0;
for (i = 0; i < num_variables; i++)
{
if ( CF_marker[i] != SF_PT )
{
if ( S_offd_i[i+1] - S_offd_i[i] > 0 || CF_marker[i] == -1 )
{
CF_marker[i] = 0;
}
if ( CF_marker[i] == Z_PT)
{
if ( measure_array[i] >= 1.0 || S_diag_i[i+1] - S_diag_i[i] > 0 )
{
CF_marker[i] = 0;
graph_array[cnt++] = i;
}
else
{
CF_marker[i] = F_PT;
}
}
else
{
graph_array[cnt++] = i;
}
}
else
{
measure_array[i] = 0;
}
}
}
else
{
cnt = 0;
for (i = 0; i < num_variables; i++)
{
CF_marker[i] = 0;
nnzrow = (S_diag_i[i+1] - S_diag_i[i]) + (S_offd_i[i+1] - S_offd_i[i]);
if (nnzrow == 0)
{
CF_marker[i] = SF_PT; /* an isolated fine grid */
if (CF_init == 3 || CF_init == 4)
{
CF_marker[i] = C_PT;
}
measure_array[i] = 0;
}
else
{
graph_array[cnt++] = i;
}
}
}
graph_size = cnt;
/* now the off-diagonal part of CF_marker */
if (num_cols_offd)
{
CF_marker_offd = hypre_CTAlloc(HYPRE_Int, num_cols_offd, HYPRE_MEMORY_HOST);
}
else
{
CF_marker_offd = NULL;
}
for (i = 0; i < num_cols_offd; i++)
{
CF_marker_offd[i] = 0;
}
/*------------------------------------------------
* Communicate the local measures, which are complete,
to the external nodes
*------------------------------------------------*/
index = 0;
for (i = 0; i < num_sends; i++)
{
start = hypre_ParCSRCommPkgSendMapStart(comm_pkg, i);
for (j = start; j < hypre_ParCSRCommPkgSendMapStart(comm_pkg, i+1); j++)
{
jrow = hypre_ParCSRCommPkgSendMapElmt(comm_pkg,j);
buf_data[index++] = measure_array[jrow];
}
}
if (num_procs > 1)
{
comm_handle = hypre_ParCSRCommHandleCreate(1, comm_pkg, buf_data, &measure_array[num_variables]);
hypre_ParCSRCommHandleDestroy(comm_handle);
}
if (debug_flag == 3)
{
wall_time = time_getWallclockSeconds() - wall_time;
hypre_printf("Proc = %d Initialize CLJP phase = %f\n", my_id, wall_time);
}
/* graph_array2 */
HYPRE_Int *graph_array2 = hypre_CTAlloc(HYPRE_Int, num_variables, HYPRE_MEMORY_HOST);
HYPRE_Int *graph_array_offd2 = NULL;
if (num_cols_offd)
{
graph_array_offd2 = hypre_CTAlloc(HYPRE_Int, num_cols_offd, HYPRE_MEMORY_HOST);
}
/*******************************************************************************
THE INDEPENDENT SET COARSENING LOOP:
******************************************************************************/
/*---------------------------------------------------
* Loop until all points are either fine or coarse.
*---------------------------------------------------*/
while (1)
{
big_graph_size = (HYPRE_BigInt) graph_size;
/* stop the coarsening if nothing left to be coarsened */
hypre_MPI_Allreduce(&big_graph_size, &global_graph_size, 1, HYPRE_MPI_BIG_INT, hypre_MPI_SUM,comm);
/* if (my_id == 0) { hypre_printf("graph size %b\n", global_graph_size); } */
if (global_graph_size == 0)
{
break;
}
/*
hypre_printf("\n");
hypre_printf("*** MIS iteration %d\n",iter);
hypre_printf("graph_size remaining %d\n",graph_size);
*/
/*-----------------------------------------------------------------------------------------
* Pick an independent set of points with maximal measure
* At the end, CF_marker is complete, but still needs to be communicated to CF_marker_offd
* for CF_init == 1, as in HMIS, the first IS was fed from prior R-S coarsening
*----------------------------------------------------------------------------------------*/
if (!CF_init || iter)
{
/*
hypre_BoomerAMGIndepSet(S, measure_array, graph_array, graph_size,
graph_array_offd, graph_offd_size, CF_marker, CF_marker_offd);
*/
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(ig, i) HYPRE_SMP_SCHEDULE
#endif
for (ig = 0; ig < graph_size; ig++)
{
i = graph_array[ig];
if (measure_array[i] > 1)
{
CF_marker[i] = 1;
}
}
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(ig, i) HYPRE_SMP_SCHEDULE
#endif
for (ig = 0; ig < graph_offd_size; ig++)
{
i = graph_array_offd[ig];
if (measure_array[i+num_variables] > 1)
{
CF_marker_offd[i] = 1;
}
}
/*-------------------------------------------------------
* Remove nodes from the initial independent set
*-------------------------------------------------------*/
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(ig, i, jS, j, jj) HYPRE_SMP_SCHEDULE
#endif
for (ig = 0; ig < graph_size; ig++)
{
i = graph_array[ig];
if (measure_array[i] > 1)
{
/* for each local neighbor j of i */
for (jS = S_diag_i[i]; jS < S_diag_i[i+1]; jS++)
{
j = S_diag_j[jS];
if (measure_array[j] > 1)
{
if (measure_array[i] > measure_array[j])
{
CF_marker[j] = 0;
}
else if (measure_array[j] > measure_array[i])
{
CF_marker[i] = 0;
}
}
}
/* for each offd neighbor j of i */
for (jS = S_offd_i[i]; jS < S_offd_i[i+1]; jS++)
{
jj = S_offd_j[jS];
j = num_variables + jj;
if (measure_array[j] > 1)
{
if (measure_array[i] > measure_array[j])
{
CF_marker_offd[jj] = 0;
}
else if (measure_array[j] > measure_array[i])
{
CF_marker[i] = 0;
}
}
}
} /* for each node with measure > 1 */
} /* for each node i */
/*------------------------------------------------------------------------------
* Exchange boundary data for CF_marker: send external CF to internal CF
*------------------------------------------------------------------------------*/
if (num_procs > 1)
{
comm_handle = hypre_ParCSRCommHandleCreate(12, comm_pkg, CF_marker_offd, int_buf_data);
hypre_ParCSRCommHandleDestroy(comm_handle);
}
index = 0;
for (i = 0; i < num_sends; i++)
{
start = hypre_ParCSRCommPkgSendMapStart(comm_pkg, i);
for (j = start; j < hypre_ParCSRCommPkgSendMapStart(comm_pkg, i+1); j++)
{
elmt = hypre_ParCSRCommPkgSendMapElmt(comm_pkg,j);
if (!int_buf_data[index] && CF_marker[elmt] > 0)
{
CF_marker[elmt] = 0;
index++;
}
else
{
int_buf_data[index++] = CF_marker[elmt];
}
}
}
if (num_procs > 1)
{
comm_handle = hypre_ParCSRCommHandleCreate(11, comm_pkg, int_buf_data, CF_marker_offd);
hypre_ParCSRCommHandleDestroy(comm_handle);
}
} /* if (!CF_init || iter) */
iter++;
/*------------------------------------------------
* Set C-pts and F-pts.
*------------------------------------------------*/
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(ig, i, jS, j) HYPRE_SMP_SCHEDULE
#endif
for (ig = 0; ig < graph_size; ig++)
{
i = graph_array[ig];
/*---------------------------------------------
* If the measure of i is smaller than 1, then
* make i and F point (because it does not influence
* any other point)
*---------------------------------------------*/
if (measure_array[i] < 1)
{
CF_marker[i]= F_PT;
}
/*---------------------------------------------
* First treat the case where point i is in the
* independent set: make i a C point,
*---------------------------------------------*/
if (CF_marker[i] > 0)
{
CF_marker[i] = C_PT;
}
/*---------------------------------------------
* Now treat the case where point i is not in the
* independent set: loop over
* all the points j that influence equation i; if
* j is a C point, then make i an F point.
*---------------------------------------------*/
else
{
/* first the local part */
for (jS = S_diag_i[i]; jS < S_diag_i[i+1]; jS++)
{
/* j is the column number, or the local number of the point influencing i */
j = S_diag_j[jS];
if (CF_marker[j] > 0) /* j is a C-point */
{
CF_marker[i] = F_PT;
}
}
/* now the external part */
for (jS = S_offd_i[i]; jS < S_offd_i[i+1]; jS++)
{
j = S_offd_j[jS];
if (CF_marker_offd[j] > 0) /* j is a C-point */
{
CF_marker[i] = F_PT;
}
}
} /* end else */
} /* end first loop over graph */
/* now communicate CF_marker to CF_marker_offd, to make
sure that new external F points are known on this processor */
/*------------------------------------------------------------------------------
* Exchange boundary data for CF_marker: send internal points to external points
*------------------------------------------------------------------------------*/
index = 0;
for (i = 0; i < num_sends; i++)
{
start = hypre_ParCSRCommPkgSendMapStart(comm_pkg, i);
for (j = start; j < hypre_ParCSRCommPkgSendMapStart(comm_pkg, i+1); j++)
{
int_buf_data[index++] = CF_marker[hypre_ParCSRCommPkgSendMapElmt(comm_pkg,j)];
}
}
if (num_procs > 1)
{
comm_handle = hypre_ParCSRCommHandleCreate(11, comm_pkg, int_buf_data, CF_marker_offd);
hypre_ParCSRCommHandleDestroy(comm_handle);
}
/*------------------------------------------------
* Update subgraph
*------------------------------------------------*/
/*HYPRE_Int prefix_sum_workspace[2*(hypre_NumThreads() + 1)];*/
prefix_sum_workspace = hypre_TAlloc(HYPRE_Int, 2*(hypre_NumThreads() + 1), HYPRE_MEMORY_HOST);
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel private(ig,i)
#endif
{
HYPRE_Int private_graph_size_cnt = 0;
HYPRE_Int private_graph_offd_size_cnt = 0;
HYPRE_Int ig_begin, ig_end;
hypre_GetSimpleThreadPartition(&ig_begin, &ig_end, graph_size);
HYPRE_Int ig_offd_begin, ig_offd_end;
hypre_GetSimpleThreadPartition(&ig_offd_begin, &ig_offd_end, graph_offd_size);
for (ig = ig_begin; ig < ig_end; ig++)
{
i = graph_array[ig];
if (CF_marker[i] != 0) /* C or F point */
{
/* the independent set subroutine needs measure 0 for removed nodes */
measure_array[i] = 0;
}
else
{
private_graph_size_cnt++;
}
}
for (ig = ig_offd_begin; ig < ig_offd_end; ig++)
{
i = graph_array_offd[ig];
if (CF_marker_offd[i] != 0) /* C of F point */
{
/* the independent set subroutine needs measure 0 for removed nodes */
measure_array[i + num_variables] = 0;
}
else
{
private_graph_offd_size_cnt++;
}
}
hypre_prefix_sum_pair(&private_graph_size_cnt, &graph_size, &private_graph_offd_size_cnt, &graph_offd_size, prefix_sum_workspace);
for (ig = ig_begin; ig < ig_end; ig++)
{
i = graph_array[ig];
if (CF_marker[i] == 0)
{
graph_array2[private_graph_size_cnt++] = i;
}
}
for (ig = ig_offd_begin; ig < ig_offd_end; ig++)
{
i = graph_array_offd[ig];
if (CF_marker_offd[i] == 0)
{
graph_array_offd2[private_graph_offd_size_cnt++] = i;
}
}
} /* omp parallel */
HYPRE_Int *temp = graph_array;
graph_array = graph_array2;
graph_array2 = temp;
temp = graph_array_offd;
graph_array_offd = graph_array_offd2;
graph_array_offd2 = temp;
hypre_TFree(prefix_sum_workspace, HYPRE_MEMORY_HOST);
} /* end while */
/*
hypre_printf("*** MIS iteration %d\n",iter);
hypre_printf("graph_size remaining %d\n",graph_size);
hypre_printf("num_cols_offd %d\n",num_cols_offd);
for (i=0;i<num_variables;i++)
{
if(CF_marker[i] == 1)
{
hypre_printf("node %d CF %d\n",i,CF_marker[i]);
}
}
*/
/*---------------------------------------------------
* Clean up and return
*---------------------------------------------------*/
hypre_TFree(measure_array, HYPRE_MEMORY_HOST);
hypre_TFree(graph_array, HYPRE_MEMORY_HOST);
hypre_TFree(graph_array2, HYPRE_MEMORY_HOST);
hypre_TFree(graph_array_offd2, HYPRE_MEMORY_HOST);
if (num_cols_offd)
{
hypre_TFree(graph_array_offd, HYPRE_MEMORY_HOST);
}
hypre_TFree(buf_data, HYPRE_MEMORY_HOST);
hypre_TFree(int_buf_data, HYPRE_MEMORY_HOST);
hypre_TFree(CF_marker_offd, HYPRE_MEMORY_HOST);
/*if (num_procs > 1) hypre_CSRMatrixDestroy(S_ext);*/
#ifdef HYPRE_PROFILE
hypre_profile_times[HYPRE_TIMER_ID_PMIS] += hypre_MPI_Wtime();
#endif
return (ierr);
}
HYPRE_Int
hypre_BoomerAMGCoarsenPMIS( hypre_ParCSRMatrix *S,
hypre_ParCSRMatrix *A,
HYPRE_Int CF_init,
HYPRE_Int debug_flag,
HYPRE_Int **CF_marker_ptr)
{
#if defined(HYPRE_USING_CUDA) || defined(HYPRE_USING_HIP)
hypre_GpuProfilingPushRange("PMIS");
#endif
HYPRE_Int ierr = 0;
#if defined(HYPRE_USING_CUDA) || defined(HYPRE_USING_HIP)
HYPRE_ExecutionPolicy exec = hypre_GetExecPolicy1( hypre_CSRMatrixMemoryLocation(hypre_ParCSRMatrixDiag(A)) );
if (exec == HYPRE_EXEC_DEVICE)
{
ierr = hypre_BoomerAMGCoarsenPMISDevice( S, A, CF_init, debug_flag, CF_marker_ptr );
}
else
#endif
{
ierr = hypre_BoomerAMGCoarsenPMISHost( S, A, CF_init, debug_flag, CF_marker_ptr );
}
#if defined(HYPRE_USING_CUDA) || defined(HYPRE_USING_HIP)
hypre_GpuProfilingPopRange();
#endif
return ierr;
}
HYPRE_Int
hypre_BoomerAMGCoarsenHMIS( hypre_ParCSRMatrix *S,
hypre_ParCSRMatrix *A,
HYPRE_Int measure_type,
HYPRE_Int cut_factor,
HYPRE_Int debug_flag,
HYPRE_Int **CF_marker_ptr)
{
HYPRE_Int ierr = 0;
/*-------------------------------------------------------
* Perform Ruge coarsening followed by CLJP coarsening
*-------------------------------------------------------*/
ierr += hypre_BoomerAMGCoarsenRuge (S, A, measure_type, 10, cut_factor,
debug_flag, CF_marker_ptr);
ierr += hypre_BoomerAMGCoarsenPMISHost (S, A, 1, debug_flag, CF_marker_ptr);
return (ierr);
}
|
GB_unop__identity_uint64_bool.c | //------------------------------------------------------------------------------
// GB_unop: hard-coded functions for each built-in unary operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2022, All Rights Reserved.
// SPDX-License-Identifier: Apache-2.0
//------------------------------------------------------------------------------
// If this file is in the Generated2/ folder, do not edit it
// (it is auto-generated from Generator/*).
#include "GB.h"
#ifndef GBCOMPACT
#include "GB_control.h"
#include "GB_atomics.h"
#include "GB_unop__include.h"
// C=unop(A) is defined by the following types and operators:
// op(A) function: GB (_unop_apply__identity_uint64_bool)
// op(A') function: GB (_unop_tran__identity_uint64_bool)
// C type: uint64_t
// A type: bool
// cast: uint64_t cij = (uint64_t) aij
// unaryop: cij = aij
#define GB_ATYPE \
bool
#define GB_CTYPE \
uint64_t
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA) \
bool aij = Ax [pA]
#define GB_CX(p) Cx [p]
// unary operator
#define GB_OP(z, x) \
z = x ;
// casting
#define GB_CAST(z, aij) \
uint64_t z = (uint64_t) aij ;
// cij = op (aij)
#define GB_CAST_OP(pC,pA) \
{ \
/* aij = Ax [pA] */ \
bool aij = Ax [pA] ; \
/* Cx [pC] = op (cast (aij)) */ \
uint64_t z = (uint64_t) aij ; \
Cx [pC] = z ; \
}
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_IDENTITY || GxB_NO_UINT64 || GxB_NO_BOOL)
//------------------------------------------------------------------------------
// Cx = op (cast (Ax)): apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB (_unop_apply__identity_uint64_bool)
(
uint64_t *Cx, // Cx and Ax may be aliased
const bool *Ax,
const int8_t *restrict Ab, // A->b if A is bitmap
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t p ;
if (Ab == NULL)
{
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
bool aij = Ax [p] ;
uint64_t z = (uint64_t) aij ;
Cx [p] = z ;
}
}
else
{
// bitmap case, no transpose; A->b already memcpy'd into C->b
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
if (!Ab [p]) continue ;
bool aij = Ax [p] ;
uint64_t z = (uint64_t) aij ;
Cx [p] = z ;
}
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (cast (A')): transpose, typecast, and apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB (_unop_tran__identity_uint64_bool)
(
GrB_Matrix C,
const GrB_Matrix A,
int64_t *restrict *Workspaces,
const int64_t *restrict A_slice,
int nworkspaces,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
5cfe06b37d3f6d74b44e1f86074c47ce092d5c2b.c | #define _POSIX_C_SOURCE 200809L
#include "stdlib.h"
#include "math.h"
#include "sys/time.h"
#include "omp.h"
struct dataobj
{
void *restrict data;
int * size;
int * npsize;
int * dsize;
int * hsize;
int * hofs;
int * oofs;
} ;
struct profiler
{
double section0;
double section1;
double section2;
double section3;
} ;
int ForwardTTI(struct dataobj *restrict damp_vec, struct dataobj *restrict delta_vec, const float dt, struct dataobj *restrict epsilon_vec, const float o_x, const float o_y, const float o_z, struct dataobj *restrict phi_vec, struct dataobj *restrict rec_vec, struct dataobj *restrict rec_coords_vec, struct dataobj *restrict src_vec, struct dataobj *restrict src_coords_vec, struct dataobj *restrict theta_vec, struct dataobj *restrict u_vec, struct dataobj *restrict v_vec, struct dataobj *restrict vp_vec, const int x_M, const int x_m, const int x_size, const int y_M, const int y_m, const int y_size, const int z_M, const int z_m, const int z_size, const int p_rec_M, const int p_rec_m, const int p_src_M, const int p_src_m, const int time_M, const int time_m, struct profiler * timers)
{
float (*restrict damp)[damp_vec->size[1]][damp_vec->size[2]] __attribute__ ((aligned (64))) = (float (*)[damp_vec->size[1]][damp_vec->size[2]]) damp_vec->data;
float (*restrict delta)[delta_vec->size[1]][delta_vec->size[2]] __attribute__ ((aligned (64))) = (float (*)[delta_vec->size[1]][delta_vec->size[2]]) delta_vec->data;
float (*restrict epsilon)[epsilon_vec->size[1]][epsilon_vec->size[2]] __attribute__ ((aligned (64))) = (float (*)[epsilon_vec->size[1]][epsilon_vec->size[2]]) epsilon_vec->data;
float (*restrict phi)[phi_vec->size[1]][phi_vec->size[2]] __attribute__ ((aligned (64))) = (float (*)[phi_vec->size[1]][phi_vec->size[2]]) phi_vec->data;
float (*restrict rec)[rec_vec->size[1]] __attribute__ ((aligned (64))) = (float (*)[rec_vec->size[1]]) rec_vec->data;
float (*restrict rec_coords)[rec_coords_vec->size[1]] __attribute__ ((aligned (64))) = (float (*)[rec_coords_vec->size[1]]) rec_coords_vec->data;
float (*restrict src)[src_vec->size[1]] __attribute__ ((aligned (64))) = (float (*)[src_vec->size[1]]) src_vec->data;
float (*restrict src_coords)[src_coords_vec->size[1]] __attribute__ ((aligned (64))) = (float (*)[src_coords_vec->size[1]]) src_coords_vec->data;
float (*restrict theta)[theta_vec->size[1]][theta_vec->size[2]] __attribute__ ((aligned (64))) = (float (*)[theta_vec->size[1]][theta_vec->size[2]]) theta_vec->data;
float (*restrict u)[u_vec->size[1]][u_vec->size[2]][u_vec->size[3]] __attribute__ ((aligned (64))) = (float (*)[u_vec->size[1]][u_vec->size[2]][u_vec->size[3]]) u_vec->data;
float (*restrict v)[v_vec->size[1]][v_vec->size[2]][v_vec->size[3]] __attribute__ ((aligned (64))) = (float (*)[v_vec->size[1]][v_vec->size[2]][v_vec->size[3]]) v_vec->data;
float (*restrict vp)[vp_vec->size[1]][vp_vec->size[2]] __attribute__ ((aligned (64))) = (float (*)[vp_vec->size[1]][vp_vec->size[2]]) vp_vec->data;
float (*r184)[y_size + 3 + 3][z_size + 3 + 3];
posix_memalign((void**)&r184, 64, sizeof(float[x_size + 3 + 3][y_size + 3 + 3][z_size + 3 + 3]));
#pragma omp target enter data map(alloc: r184[0:x_size + 3 + 3][0:y_size + 3 + 3][0:z_size + 3 + 3])
float (*r185)[y_size + 3 + 3][z_size + 3 + 3];
posix_memalign((void**)&r185, 64, sizeof(float[x_size + 3 + 3][y_size + 3 + 3][z_size + 3 + 3]));
#pragma omp target enter data map(alloc: r185[0:x_size + 3 + 3][0:y_size + 3 + 3][0:z_size + 3 + 3])
float (*r186)[y_size + 3 + 3][z_size + 3 + 3];
posix_memalign((void**)&r186, 64, sizeof(float[x_size + 3 + 3][y_size + 3 + 3][z_size + 3 + 3]));
#pragma omp target enter data map(alloc: r186[0:x_size + 3 + 3][0:y_size + 3 + 3][0:z_size + 3 + 3])
float (*r187)[y_size + 3 + 3][z_size + 3 + 3];
posix_memalign((void**)&r187, 64, sizeof(float[x_size + 3 + 3][y_size + 3 + 3][z_size + 3 + 3]));
#pragma omp target enter data map(alloc: r187[0:x_size + 3 + 3][0:y_size + 3 + 3][0:z_size + 3 + 3])
float (*r188)[y_size + 3 + 3][z_size + 3 + 3];
posix_memalign((void**)&r188, 64, sizeof(float[x_size + 3 + 3][y_size + 3 + 3][z_size + 3 + 3]));
#pragma omp target enter data map(alloc: r188[0:x_size + 3 + 3][0:y_size + 3 + 3][0:z_size + 3 + 3])
float (*r236)[y_size + 3 + 3][z_size + 3 + 3];
posix_memalign((void**)&r236, 64, sizeof(float[x_size + 3 + 3][y_size + 3 + 3][z_size + 3 + 3]));
#pragma omp target enter data map(alloc: r236[0:x_size + 3 + 3][0:y_size + 3 + 3][0:z_size + 3 + 3])
float (*r237)[y_size + 3 + 3][z_size + 3 + 3];
posix_memalign((void**)&r237, 64, sizeof(float[x_size + 3 + 3][y_size + 3 + 3][z_size + 3 + 3]));
#pragma omp target enter data map(alloc: r237[0:x_size + 3 + 3][0:y_size + 3 + 3][0:z_size + 3 + 3])
#pragma omp target enter data map(to: rec[0:rec_vec->size[0]][0:rec_vec->size[1]])
#pragma omp target enter data map(to: u[0:u_vec->size[0]][0:u_vec->size[1]][0:u_vec->size[2]][0:u_vec->size[3]])
#pragma omp target enter data map(to: v[0:v_vec->size[0]][0:v_vec->size[1]][0:v_vec->size[2]][0:v_vec->size[3]])
#pragma omp target enter data map(to: damp[0:damp_vec->size[0]][0:damp_vec->size[1]][0:damp_vec->size[2]])
#pragma omp target enter data map(to: delta[0:delta_vec->size[0]][0:delta_vec->size[1]][0:delta_vec->size[2]])
#pragma omp target enter data map(to: epsilon[0:epsilon_vec->size[0]][0:epsilon_vec->size[1]][0:epsilon_vec->size[2]])
#pragma omp target enter data map(to: phi[0:phi_vec->size[0]][0:phi_vec->size[1]][0:phi_vec->size[2]])
#pragma omp target enter data map(to: rec_coords[0:rec_coords_vec->size[0]][0:rec_coords_vec->size[1]])
#pragma omp target enter data map(to: src[0:src_vec->size[0]][0:src_vec->size[1]])
#pragma omp target enter data map(to: src_coords[0:src_coords_vec->size[0]][0:src_coords_vec->size[1]])
#pragma omp target enter data map(to: theta[0:theta_vec->size[0]][0:theta_vec->size[1]][0:theta_vec->size[2]])
#pragma omp target enter data map(to: vp[0:vp_vec->size[0]][0:vp_vec->size[1]][0:vp_vec->size[2]])
struct timeval start_section0, end_section0;
gettimeofday(&start_section0, NULL);
/* Begin section0 */
#pragma omp target teams distribute parallel for collapse(3)
for (int x = x_m - 3; x <= x_M + 3; x += 1)
{
for (int y = y_m - 3; y <= y_M + 3; y += 1)
{
for (int z = z_m - 3; z <= z_M + 3; z += 1)
{
r184[x + 3][y + 3][z + 3] = sqrt(2*delta[x + 2][y + 2][z + 2] + 1);
r185[x + 3][y + 3][z + 3] = cos(theta[x + 2][y + 2][z + 2]);
r186[x + 3][y + 3][z + 3] = sin(phi[x + 2][y + 2][z + 2]);
r187[x + 3][y + 3][z + 3] = sin(theta[x + 2][y + 2][z + 2]);
r188[x + 3][y + 3][z + 3] = cos(phi[x + 2][y + 2][z + 2]);
}
}
}
/* End section0 */
gettimeofday(&end_section0, NULL);
timers->section0 += (double)(end_section0.tv_sec-start_section0.tv_sec)+(double)(end_section0.tv_usec-start_section0.tv_usec)/1000000;
for (int time = time_m, t0 = (time)%(3), t1 = (time + 1)%(3), t2 = (time + 2)%(3); time <= time_M; time += 1, t0 = (time)%(3), t1 = (time + 1)%(3), t2 = (time + 2)%(3))
{
struct timeval start_section1, end_section1;
gettimeofday(&start_section1, NULL);
/* Begin section1 */
#pragma omp target teams distribute parallel for collapse(3)
for (int x = x_m - 3; x <= x_M + 3; x += 1)
{
for (int y = y_m - 3; y <= y_M + 3; y += 1)
{
for (int z = z_m - 3; z <= z_M + 3; z += 1)
{
float r267 = 8.33333346e-4F*(-v[t0][x + 12][y + 12][z + 9] + v[t0][x + 12][y + 12][z + 15]) + 7.50000011e-3F*(v[t0][x + 12][y + 12][z + 10] - v[t0][x + 12][y + 12][z + 14]) + 3.75000006e-2F*(-v[t0][x + 12][y + 12][z + 11] + v[t0][x + 12][y + 12][z + 13]);
float r268 = 8.33333346e-4F*(-v[t0][x + 12][y + 9][z + 12] + v[t0][x + 12][y + 15][z + 12]) + 7.50000011e-3F*(v[t0][x + 12][y + 10][z + 12] - v[t0][x + 12][y + 14][z + 12]) + 3.75000006e-2F*(-v[t0][x + 12][y + 11][z + 12] + v[t0][x + 12][y + 13][z + 12]);
float r269 = 8.33333346e-4F*(-v[t0][x + 9][y + 12][z + 12] + v[t0][x + 15][y + 12][z + 12]) + 7.50000011e-3F*(v[t0][x + 10][y + 12][z + 12] - v[t0][x + 14][y + 12][z + 12]) + 3.75000006e-2F*(-v[t0][x + 11][y + 12][z + 12] + v[t0][x + 13][y + 12][z + 12]);
float r270 = 8.33333346e-4F*(-u[t0][x + 12][y + 12][z + 9] + u[t0][x + 12][y + 12][z + 15]) + 7.50000011e-3F*(u[t0][x + 12][y + 12][z + 10] - u[t0][x + 12][y + 12][z + 14]) + 3.75000006e-2F*(-u[t0][x + 12][y + 12][z + 11] + u[t0][x + 12][y + 12][z + 13]);
float r271 = 8.33333346e-4F*(-u[t0][x + 12][y + 9][z + 12] + u[t0][x + 12][y + 15][z + 12]) + 7.50000011e-3F*(u[t0][x + 12][y + 10][z + 12] - u[t0][x + 12][y + 14][z + 12]) + 3.75000006e-2F*(-u[t0][x + 12][y + 11][z + 12] + u[t0][x + 12][y + 13][z + 12]);
float r272 = 8.33333346e-4F*(-u[t0][x + 9][y + 12][z + 12] + u[t0][x + 15][y + 12][z + 12]) + 7.50000011e-3F*(u[t0][x + 10][y + 12][z + 12] - u[t0][x + 14][y + 12][z + 12]) + 3.75000006e-2F*(-u[t0][x + 11][y + 12][z + 12] + u[t0][x + 13][y + 12][z + 12]);
r236[x + 3][y + 3][z + 3] = -(r270*r185[x + 3][y + 3][z + 3] + r271*r186[x + 3][y + 3][z + 3]*r187[x + 3][y + 3][z + 3] + r272*r187[x + 3][y + 3][z + 3]*r188[x + 3][y + 3][z + 3]);
r237[x + 3][y + 3][z + 3] = -(r267*r185[x + 3][y + 3][z + 3] + r268*r186[x + 3][y + 3][z + 3]*r187[x + 3][y + 3][z + 3] + r269*r187[x + 3][y + 3][z + 3]*r188[x + 3][y + 3][z + 3]);
}
}
}
#pragma omp target teams distribute parallel for collapse(3)
for (int x = x_m; x <= x_M; x += 1)
{
for (int y = y_m; y <= y_M; y += 1)
{
for (int z = z_m; z <= z_M; z += 1)
{
float r250 = dt*dt;
float r249 = dt*damp[x + 1][y + 1][z + 1];
float r248 = 7.50000011e-3F*(r185[x + 3][y + 3][z + 1]*r236[x + 3][y + 3][z + 1] - r185[x + 3][y + 3][z + 5]*r236[x + 3][y + 3][z + 5] + r186[x + 3][y + 1][z + 3]*r187[x + 3][y + 1][z + 3]*r236[x + 3][y + 1][z + 3] - r186[x + 3][y + 5][z + 3]*r187[x + 3][y + 5][z + 3]*r236[x + 3][y + 5][z + 3] + r187[x + 1][y + 3][z + 3]*r188[x + 1][y + 3][z + 3]*r236[x + 1][y + 3][z + 3] - r187[x + 5][y + 3][z + 3]*r188[x + 5][y + 3][z + 3]*r236[x + 5][y + 3][z + 3]);
float r247 = 8.33333346e-4F*(-r185[x + 3][y + 3][z]*r236[x + 3][y + 3][z] + r185[x + 3][y + 3][z + 6]*r236[x + 3][y + 3][z + 6] - r186[x + 3][y][z + 3]*r187[x + 3][y][z + 3]*r236[x + 3][y][z + 3] + r186[x + 3][y + 6][z + 3]*r187[x + 3][y + 6][z + 3]*r236[x + 3][y + 6][z + 3] - r187[x][y + 3][z + 3]*r188[x][y + 3][z + 3]*r236[x][y + 3][z + 3] + r187[x + 6][y + 3][z + 3]*r188[x + 6][y + 3][z + 3]*r236[x + 6][y + 3][z + 3]);
float r246 = 3.75000006e-2F*(-r185[x + 3][y + 3][z + 2]*r236[x + 3][y + 3][z + 2] + r185[x + 3][y + 3][z + 4]*r236[x + 3][y + 3][z + 4] - r186[x + 3][y + 2][z + 3]*r187[x + 3][y + 2][z + 3]*r236[x + 3][y + 2][z + 3] + r186[x + 3][y + 4][z + 3]*r187[x + 3][y + 4][z + 3]*r236[x + 3][y + 4][z + 3] - r187[x + 2][y + 3][z + 3]*r188[x + 2][y + 3][z + 3]*r236[x + 2][y + 3][z + 3] + r187[x + 4][y + 3][z + 3]*r188[x + 4][y + 3][z + 3]*r236[x + 4][y + 3][z + 3]);
float r245 = 1.0/(vp[x + 2][y + 2][z + 2]*vp[x + 2][y + 2][z + 2]);
float r244 = 1.0/(vp[x + 2][y + 2][z + 2]*vp[x + 2][y + 2][z + 2]);
float r238 = 2.0F*r244 + r249;
float r239 = -2.0F*r244 + r249;
float r240 = -1.50312647e-7F*(u[t0][x + 6][y + 12][z + 12] + u[t0][x + 12][y + 6][z + 12] + u[t0][x + 12][y + 12][z + 6] + u[t0][x + 12][y + 12][z + 18] + u[t0][x + 12][y + 18][z + 12] + u[t0][x + 18][y + 12][z + 12]) + 2.59740254e-6F*(u[t0][x + 7][y + 12][z + 12] + u[t0][x + 12][y + 7][z + 12] + u[t0][x + 12][y + 12][z + 7] + u[t0][x + 12][y + 12][z + 17] + u[t0][x + 12][y + 17][z + 12] + u[t0][x + 17][y + 12][z + 12]) - 2.23214281e-5F*(u[t0][x + 8][y + 12][z + 12] + u[t0][x + 12][y + 8][z + 12] + u[t0][x + 12][y + 12][z + 8] + u[t0][x + 12][y + 12][z + 16] + u[t0][x + 12][y + 16][z + 12] + u[t0][x + 16][y + 12][z + 12]) + 1.32275129e-4F*(u[t0][x + 9][y + 12][z + 12] + u[t0][x + 12][y + 9][z + 12] + u[t0][x + 12][y + 12][z + 9] + u[t0][x + 12][y + 12][z + 15] + u[t0][x + 12][y + 15][z + 12] + u[t0][x + 15][y + 12][z + 12]) - 6.69642842e-4F*(u[t0][x + 10][y + 12][z + 12] + u[t0][x + 12][y + 10][z + 12] + u[t0][x + 12][y + 12][z + 10] + u[t0][x + 12][y + 12][z + 14] + u[t0][x + 12][y + 14][z + 12] + u[t0][x + 14][y + 12][z + 12]) + 4.28571419e-3F*(u[t0][x + 11][y + 12][z + 12] + u[t0][x + 12][y + 11][z + 12] + u[t0][x + 12][y + 12][z + 11] + u[t0][x + 12][y + 12][z + 13] + u[t0][x + 12][y + 13][z + 12] + u[t0][x + 13][y + 12][z + 12]) - 2.23708328e-2F*u[t0][x + 12][y + 12][z + 12];
float r241 = r239*u[t2][x + 12][y + 12][z + 12] + 4.0F*r245*u[t0][x + 12][y + 12][z + 12];
float r242 = r239*v[t2][x + 12][y + 12][z + 12] + 4.0F*r245*v[t0][x + 12][y + 12][z + 12];
float r243 = 8.33333346e-4F*(r185[x + 3][y + 3][z]*r237[x + 3][y + 3][z] - r185[x + 3][y + 3][z + 6]*r237[x + 3][y + 3][z + 6] + r186[x + 3][y][z + 3]*r187[x + 3][y][z + 3]*r237[x + 3][y][z + 3] - r186[x + 3][y + 6][z + 3]*r187[x + 3][y + 6][z + 3]*r237[x + 3][y + 6][z + 3] + r187[x][y + 3][z + 3]*r188[x][y + 3][z + 3]*r237[x][y + 3][z + 3] - r187[x + 6][y + 3][z + 3]*r188[x + 6][y + 3][z + 3]*r237[x + 6][y + 3][z + 3]) + 7.50000011e-3F*(-r185[x + 3][y + 3][z + 1]*r237[x + 3][y + 3][z + 1] + r185[x + 3][y + 3][z + 5]*r237[x + 3][y + 3][z + 5] - r186[x + 3][y + 1][z + 3]*r187[x + 3][y + 1][z + 3]*r237[x + 3][y + 1][z + 3] + r186[x + 3][y + 5][z + 3]*r187[x + 3][y + 5][z + 3]*r237[x + 3][y + 5][z + 3] - r187[x + 1][y + 3][z + 3]*r188[x + 1][y + 3][z + 3]*r237[x + 1][y + 3][z + 3] + r187[x + 5][y + 3][z + 3]*r188[x + 5][y + 3][z + 3]*r237[x + 5][y + 3][z + 3]) + 3.75000006e-2F*(r185[x + 3][y + 3][z + 2]*r237[x + 3][y + 3][z + 2] - r185[x + 3][y + 3][z + 4]*r237[x + 3][y + 3][z + 4] + r186[x + 3][y + 2][z + 3]*r187[x + 3][y + 2][z + 3]*r237[x + 3][y + 2][z + 3] - r186[x + 3][y + 4][z + 3]*r187[x + 3][y + 4][z + 3]*r237[x + 3][y + 4][z + 3] + r187[x + 2][y + 3][z + 3]*r188[x + 2][y + 3][z + 3]*r237[x + 2][y + 3][z + 3] - r187[x + 4][y + 3][z + 3]*r188[x + 4][y + 3][z + 3]*r237[x + 4][y + 3][z + 3]);
u[t1][x + 12][y + 12][z + 12] = 1.0F*(r241 + 2.0F*r250*(r243*r184[x + 3][y + 3][z + 3] + (2*epsilon[x + 2][y + 2][z + 2] + 1)*(r240 + r246 + r247 + r248)))/r238;
v[t1][x + 12][y + 12][z + 12] = 1.0F*(r242 + 2.0F*r250*(r243 + (r240 + r246 + r247 + r248)*r184[x + 3][y + 3][z + 3]))/r238;
}
}
}
/* End section1 */
gettimeofday(&end_section1, NULL);
timers->section1 += (double)(end_section1.tv_sec-start_section1.tv_sec)+(double)(end_section1.tv_usec-start_section1.tv_usec)/1000000;
struct timeval start_section2, end_section2;
gettimeofday(&start_section2, NULL);
/* Begin section2 */
#pragma omp target teams distribute parallel for collapse(1)
for (int p_src = p_src_m; p_src <= p_src_M; p_src += 1)
{
int ii_src_0 = (int)(floor(-5.0e-2*o_x + 5.0e-2*src_coords[p_src][0]));
int ii_src_1 = (int)(floor(-5.0e-2*o_y + 5.0e-2*src_coords[p_src][1]));
int ii_src_2 = (int)(floor(-5.0e-2*o_z + 5.0e-2*src_coords[p_src][2]));
int ii_src_3 = (int)(floor(-5.0e-2*o_z + 5.0e-2*src_coords[p_src][2])) + 1;
int ii_src_4 = (int)(floor(-5.0e-2*o_y + 5.0e-2*src_coords[p_src][1])) + 1;
int ii_src_5 = (int)(floor(-5.0e-2*o_x + 5.0e-2*src_coords[p_src][0])) + 1;
float px = (float)(-o_x - 2.0e+1F*(int)(floor(-5.0e-2F*o_x + 5.0e-2F*src_coords[p_src][0])) + src_coords[p_src][0]);
float py = (float)(-o_y - 2.0e+1F*(int)(floor(-5.0e-2F*o_y + 5.0e-2F*src_coords[p_src][1])) + src_coords[p_src][1]);
float pz = (float)(-o_z - 2.0e+1F*(int)(floor(-5.0e-2F*o_z + 5.0e-2F*src_coords[p_src][2])) + src_coords[p_src][2]);
if (ii_src_0 >= x_m - 1 && ii_src_1 >= y_m - 1 && ii_src_2 >= z_m - 1 && ii_src_0 <= x_M + 1 && ii_src_1 <= y_M + 1 && ii_src_2 <= z_M + 1)
{
float r251 = (dt*dt)*(vp[ii_src_0 + 2][ii_src_1 + 2][ii_src_2 + 2]*vp[ii_src_0 + 2][ii_src_1 + 2][ii_src_2 + 2])*(-1.25e-4F*px*py*pz + 2.5e-3F*px*py + 2.5e-3F*px*pz - 5.0e-2F*px + 2.5e-3F*py*pz - 5.0e-2F*py - 5.0e-2F*pz + 1)*src[time][p_src];
#pragma omp atomic update
u[t1][ii_src_0 + 12][ii_src_1 + 12][ii_src_2 + 12] += r251;
}
if (ii_src_0 >= x_m - 1 && ii_src_1 >= y_m - 1 && ii_src_3 >= z_m - 1 && ii_src_0 <= x_M + 1 && ii_src_1 <= y_M + 1 && ii_src_3 <= z_M + 1)
{
float r252 = (dt*dt)*(vp[ii_src_0 + 2][ii_src_1 + 2][ii_src_3 + 2]*vp[ii_src_0 + 2][ii_src_1 + 2][ii_src_3 + 2])*(1.25e-4F*px*py*pz - 2.5e-3F*px*pz - 2.5e-3F*py*pz + 5.0e-2F*pz)*src[time][p_src];
#pragma omp atomic update
u[t1][ii_src_0 + 12][ii_src_1 + 12][ii_src_3 + 12] += r252;
}
if (ii_src_0 >= x_m - 1 && ii_src_2 >= z_m - 1 && ii_src_4 >= y_m - 1 && ii_src_0 <= x_M + 1 && ii_src_2 <= z_M + 1 && ii_src_4 <= y_M + 1)
{
float r253 = (dt*dt)*(vp[ii_src_0 + 2][ii_src_4 + 2][ii_src_2 + 2]*vp[ii_src_0 + 2][ii_src_4 + 2][ii_src_2 + 2])*(1.25e-4F*px*py*pz - 2.5e-3F*px*py - 2.5e-3F*py*pz + 5.0e-2F*py)*src[time][p_src];
#pragma omp atomic update
u[t1][ii_src_0 + 12][ii_src_4 + 12][ii_src_2 + 12] += r253;
}
if (ii_src_0 >= x_m - 1 && ii_src_3 >= z_m - 1 && ii_src_4 >= y_m - 1 && ii_src_0 <= x_M + 1 && ii_src_3 <= z_M + 1 && ii_src_4 <= y_M + 1)
{
float r254 = (dt*dt)*(vp[ii_src_0 + 2][ii_src_4 + 2][ii_src_3 + 2]*vp[ii_src_0 + 2][ii_src_4 + 2][ii_src_3 + 2])*(-1.25e-4F*px*py*pz + 2.5e-3F*py*pz)*src[time][p_src];
#pragma omp atomic update
u[t1][ii_src_0 + 12][ii_src_4 + 12][ii_src_3 + 12] += r254;
}
if (ii_src_1 >= y_m - 1 && ii_src_2 >= z_m - 1 && ii_src_5 >= x_m - 1 && ii_src_1 <= y_M + 1 && ii_src_2 <= z_M + 1 && ii_src_5 <= x_M + 1)
{
float r255 = (dt*dt)*(vp[ii_src_5 + 2][ii_src_1 + 2][ii_src_2 + 2]*vp[ii_src_5 + 2][ii_src_1 + 2][ii_src_2 + 2])*(1.25e-4F*px*py*pz - 2.5e-3F*px*py - 2.5e-3F*px*pz + 5.0e-2F*px)*src[time][p_src];
#pragma omp atomic update
u[t1][ii_src_5 + 12][ii_src_1 + 12][ii_src_2 + 12] += r255;
}
if (ii_src_1 >= y_m - 1 && ii_src_3 >= z_m - 1 && ii_src_5 >= x_m - 1 && ii_src_1 <= y_M + 1 && ii_src_3 <= z_M + 1 && ii_src_5 <= x_M + 1)
{
float r256 = (dt*dt)*(vp[ii_src_5 + 2][ii_src_1 + 2][ii_src_3 + 2]*vp[ii_src_5 + 2][ii_src_1 + 2][ii_src_3 + 2])*(-1.25e-4F*px*py*pz + 2.5e-3F*px*pz)*src[time][p_src];
#pragma omp atomic update
u[t1][ii_src_5 + 12][ii_src_1 + 12][ii_src_3 + 12] += r256;
}
if (ii_src_2 >= z_m - 1 && ii_src_4 >= y_m - 1 && ii_src_5 >= x_m - 1 && ii_src_2 <= z_M + 1 && ii_src_4 <= y_M + 1 && ii_src_5 <= x_M + 1)
{
float r257 = (dt*dt)*(vp[ii_src_5 + 2][ii_src_4 + 2][ii_src_2 + 2]*vp[ii_src_5 + 2][ii_src_4 + 2][ii_src_2 + 2])*(-1.25e-4F*px*py*pz + 2.5e-3F*px*py)*src[time][p_src];
#pragma omp atomic update
u[t1][ii_src_5 + 12][ii_src_4 + 12][ii_src_2 + 12] += r257;
}
if (ii_src_3 >= z_m - 1 && ii_src_4 >= y_m - 1 && ii_src_5 >= x_m - 1 && ii_src_3 <= z_M + 1 && ii_src_4 <= y_M + 1 && ii_src_5 <= x_M + 1)
{
float r258 = 1.25e-4F*px*py*pz*(dt*dt)*(vp[ii_src_5 + 2][ii_src_4 + 2][ii_src_3 + 2]*vp[ii_src_5 + 2][ii_src_4 + 2][ii_src_3 + 2])*src[time][p_src];
#pragma omp atomic update
u[t1][ii_src_5 + 12][ii_src_4 + 12][ii_src_3 + 12] += r258;
}
ii_src_0 = (int)(floor(-5.0e-2*o_x + 5.0e-2*src_coords[p_src][0]));
ii_src_1 = (int)(floor(-5.0e-2*o_y + 5.0e-2*src_coords[p_src][1]));
ii_src_2 = (int)(floor(-5.0e-2*o_z + 5.0e-2*src_coords[p_src][2]));
ii_src_3 = (int)(floor(-5.0e-2*o_z + 5.0e-2*src_coords[p_src][2])) + 1;
ii_src_4 = (int)(floor(-5.0e-2*o_y + 5.0e-2*src_coords[p_src][1])) + 1;
ii_src_5 = (int)(floor(-5.0e-2*o_x + 5.0e-2*src_coords[p_src][0])) + 1;
px = (float)(-o_x - 2.0e+1F*(int)(floor(-5.0e-2F*o_x + 5.0e-2F*src_coords[p_src][0])) + src_coords[p_src][0]);
py = (float)(-o_y - 2.0e+1F*(int)(floor(-5.0e-2F*o_y + 5.0e-2F*src_coords[p_src][1])) + src_coords[p_src][1]);
pz = (float)(-o_z - 2.0e+1F*(int)(floor(-5.0e-2F*o_z + 5.0e-2F*src_coords[p_src][2])) + src_coords[p_src][2]);
if (ii_src_0 >= x_m - 1 && ii_src_1 >= y_m - 1 && ii_src_2 >= z_m - 1 && ii_src_0 <= x_M + 1 && ii_src_1 <= y_M + 1 && ii_src_2 <= z_M + 1)
{
float r259 = (dt*dt)*(vp[ii_src_0 + 2][ii_src_1 + 2][ii_src_2 + 2]*vp[ii_src_0 + 2][ii_src_1 + 2][ii_src_2 + 2])*(-1.25e-4F*px*py*pz + 2.5e-3F*px*py + 2.5e-3F*px*pz - 5.0e-2F*px + 2.5e-3F*py*pz - 5.0e-2F*py - 5.0e-2F*pz + 1)*src[time][p_src];
#pragma omp atomic update
v[t1][ii_src_0 + 12][ii_src_1 + 12][ii_src_2 + 12] += r259;
}
if (ii_src_0 >= x_m - 1 && ii_src_1 >= y_m - 1 && ii_src_3 >= z_m - 1 && ii_src_0 <= x_M + 1 && ii_src_1 <= y_M + 1 && ii_src_3 <= z_M + 1)
{
float r260 = (dt*dt)*(vp[ii_src_0 + 2][ii_src_1 + 2][ii_src_3 + 2]*vp[ii_src_0 + 2][ii_src_1 + 2][ii_src_3 + 2])*(1.25e-4F*px*py*pz - 2.5e-3F*px*pz - 2.5e-3F*py*pz + 5.0e-2F*pz)*src[time][p_src];
#pragma omp atomic update
v[t1][ii_src_0 + 12][ii_src_1 + 12][ii_src_3 + 12] += r260;
}
if (ii_src_0 >= x_m - 1 && ii_src_2 >= z_m - 1 && ii_src_4 >= y_m - 1 && ii_src_0 <= x_M + 1 && ii_src_2 <= z_M + 1 && ii_src_4 <= y_M + 1)
{
float r261 = (dt*dt)*(vp[ii_src_0 + 2][ii_src_4 + 2][ii_src_2 + 2]*vp[ii_src_0 + 2][ii_src_4 + 2][ii_src_2 + 2])*(1.25e-4F*px*py*pz - 2.5e-3F*px*py - 2.5e-3F*py*pz + 5.0e-2F*py)*src[time][p_src];
#pragma omp atomic update
v[t1][ii_src_0 + 12][ii_src_4 + 12][ii_src_2 + 12] += r261;
}
if (ii_src_0 >= x_m - 1 && ii_src_3 >= z_m - 1 && ii_src_4 >= y_m - 1 && ii_src_0 <= x_M + 1 && ii_src_3 <= z_M + 1 && ii_src_4 <= y_M + 1)
{
float r262 = (dt*dt)*(vp[ii_src_0 + 2][ii_src_4 + 2][ii_src_3 + 2]*vp[ii_src_0 + 2][ii_src_4 + 2][ii_src_3 + 2])*(-1.25e-4F*px*py*pz + 2.5e-3F*py*pz)*src[time][p_src];
#pragma omp atomic update
v[t1][ii_src_0 + 12][ii_src_4 + 12][ii_src_3 + 12] += r262;
}
if (ii_src_1 >= y_m - 1 && ii_src_2 >= z_m - 1 && ii_src_5 >= x_m - 1 && ii_src_1 <= y_M + 1 && ii_src_2 <= z_M + 1 && ii_src_5 <= x_M + 1)
{
float r263 = (dt*dt)*(vp[ii_src_5 + 2][ii_src_1 + 2][ii_src_2 + 2]*vp[ii_src_5 + 2][ii_src_1 + 2][ii_src_2 + 2])*(1.25e-4F*px*py*pz - 2.5e-3F*px*py - 2.5e-3F*px*pz + 5.0e-2F*px)*src[time][p_src];
#pragma omp atomic update
v[t1][ii_src_5 + 12][ii_src_1 + 12][ii_src_2 + 12] += r263;
}
if (ii_src_1 >= y_m - 1 && ii_src_3 >= z_m - 1 && ii_src_5 >= x_m - 1 && ii_src_1 <= y_M + 1 && ii_src_3 <= z_M + 1 && ii_src_5 <= x_M + 1)
{
float r264 = (dt*dt)*(vp[ii_src_5 + 2][ii_src_1 + 2][ii_src_3 + 2]*vp[ii_src_5 + 2][ii_src_1 + 2][ii_src_3 + 2])*(-1.25e-4F*px*py*pz + 2.5e-3F*px*pz)*src[time][p_src];
#pragma omp atomic update
v[t1][ii_src_5 + 12][ii_src_1 + 12][ii_src_3 + 12] += r264;
}
if (ii_src_2 >= z_m - 1 && ii_src_4 >= y_m - 1 && ii_src_5 >= x_m - 1 && ii_src_2 <= z_M + 1 && ii_src_4 <= y_M + 1 && ii_src_5 <= x_M + 1)
{
float r265 = (dt*dt)*(vp[ii_src_5 + 2][ii_src_4 + 2][ii_src_2 + 2]*vp[ii_src_5 + 2][ii_src_4 + 2][ii_src_2 + 2])*(-1.25e-4F*px*py*pz + 2.5e-3F*px*py)*src[time][p_src];
#pragma omp atomic update
v[t1][ii_src_5 + 12][ii_src_4 + 12][ii_src_2 + 12] += r265;
}
if (ii_src_3 >= z_m - 1 && ii_src_4 >= y_m - 1 && ii_src_5 >= x_m - 1 && ii_src_3 <= z_M + 1 && ii_src_4 <= y_M + 1 && ii_src_5 <= x_M + 1)
{
float r266 = 1.25e-4F*px*py*pz*(dt*dt)*(vp[ii_src_5 + 2][ii_src_4 + 2][ii_src_3 + 2]*vp[ii_src_5 + 2][ii_src_4 + 2][ii_src_3 + 2])*src[time][p_src];
#pragma omp atomic update
v[t1][ii_src_5 + 12][ii_src_4 + 12][ii_src_3 + 12] += r266;
}
}
/* End section2 */
gettimeofday(&end_section2, NULL);
timers->section2 += (double)(end_section2.tv_sec-start_section2.tv_sec)+(double)(end_section2.tv_usec-start_section2.tv_usec)/1000000;
struct timeval start_section3, end_section3;
gettimeofday(&start_section3, NULL);
/* Begin section3 */
#pragma omp target teams distribute parallel for collapse(1)
for (int p_rec = p_rec_m; p_rec <= p_rec_M; p_rec += 1)
{
int ii_rec_0 = (int)(floor(-5.0e-2*o_x + 5.0e-2*rec_coords[p_rec][0]));
int ii_rec_1 = (int)(floor(-5.0e-2*o_y + 5.0e-2*rec_coords[p_rec][1]));
int ii_rec_2 = (int)(floor(-5.0e-2*o_z + 5.0e-2*rec_coords[p_rec][2]));
int ii_rec_3 = (int)(floor(-5.0e-2*o_z + 5.0e-2*rec_coords[p_rec][2])) + 1;
int ii_rec_4 = (int)(floor(-5.0e-2*o_y + 5.0e-2*rec_coords[p_rec][1])) + 1;
int ii_rec_5 = (int)(floor(-5.0e-2*o_x + 5.0e-2*rec_coords[p_rec][0])) + 1;
float px = (float)(-o_x - 2.0e+1F*(int)(floor(-5.0e-2F*o_x + 5.0e-2F*rec_coords[p_rec][0])) + rec_coords[p_rec][0]);
float py = (float)(-o_y - 2.0e+1F*(int)(floor(-5.0e-2F*o_y + 5.0e-2F*rec_coords[p_rec][1])) + rec_coords[p_rec][1]);
float pz = (float)(-o_z - 2.0e+1F*(int)(floor(-5.0e-2F*o_z + 5.0e-2F*rec_coords[p_rec][2])) + rec_coords[p_rec][2]);
float sum = 0.0F;
if (ii_rec_0 >= x_m - 1 && ii_rec_1 >= y_m - 1 && ii_rec_2 >= z_m - 1 && ii_rec_0 <= x_M + 1 && ii_rec_1 <= y_M + 1 && ii_rec_2 <= z_M + 1)
{
sum += (u[t0][ii_rec_0 + 12][ii_rec_1 + 12][ii_rec_2 + 12] + v[t0][ii_rec_0 + 12][ii_rec_1 + 12][ii_rec_2 + 12])*(-1.25e-4F*px*py*pz + 2.5e-3F*px*py + 2.5e-3F*px*pz - 5.0e-2F*px + 2.5e-3F*py*pz - 5.0e-2F*py - 5.0e-2F*pz + 1);
}
if (ii_rec_0 >= x_m - 1 && ii_rec_1 >= y_m - 1 && ii_rec_3 >= z_m - 1 && ii_rec_0 <= x_M + 1 && ii_rec_1 <= y_M + 1 && ii_rec_3 <= z_M + 1)
{
sum += (u[t0][ii_rec_0 + 12][ii_rec_1 + 12][ii_rec_3 + 12] + v[t0][ii_rec_0 + 12][ii_rec_1 + 12][ii_rec_3 + 12])*(1.25e-4F*px*py*pz - 2.5e-3F*px*pz - 2.5e-3F*py*pz + 5.0e-2F*pz);
}
if (ii_rec_0 >= x_m - 1 && ii_rec_2 >= z_m - 1 && ii_rec_4 >= y_m - 1 && ii_rec_0 <= x_M + 1 && ii_rec_2 <= z_M + 1 && ii_rec_4 <= y_M + 1)
{
sum += (u[t0][ii_rec_0 + 12][ii_rec_4 + 12][ii_rec_2 + 12] + v[t0][ii_rec_0 + 12][ii_rec_4 + 12][ii_rec_2 + 12])*(1.25e-4F*px*py*pz - 2.5e-3F*px*py - 2.5e-3F*py*pz + 5.0e-2F*py);
}
if (ii_rec_0 >= x_m - 1 && ii_rec_3 >= z_m - 1 && ii_rec_4 >= y_m - 1 && ii_rec_0 <= x_M + 1 && ii_rec_3 <= z_M + 1 && ii_rec_4 <= y_M + 1)
{
sum += (-1.25e-4F*px*py*pz + 2.5e-3F*py*pz)*(u[t0][ii_rec_0 + 12][ii_rec_4 + 12][ii_rec_3 + 12] + v[t0][ii_rec_0 + 12][ii_rec_4 + 12][ii_rec_3 + 12]);
}
if (ii_rec_1 >= y_m - 1 && ii_rec_2 >= z_m - 1 && ii_rec_5 >= x_m - 1 && ii_rec_1 <= y_M + 1 && ii_rec_2 <= z_M + 1 && ii_rec_5 <= x_M + 1)
{
sum += (u[t0][ii_rec_5 + 12][ii_rec_1 + 12][ii_rec_2 + 12] + v[t0][ii_rec_5 + 12][ii_rec_1 + 12][ii_rec_2 + 12])*(1.25e-4F*px*py*pz - 2.5e-3F*px*py - 2.5e-3F*px*pz + 5.0e-2F*px);
}
if (ii_rec_1 >= y_m - 1 && ii_rec_3 >= z_m - 1 && ii_rec_5 >= x_m - 1 && ii_rec_1 <= y_M + 1 && ii_rec_3 <= z_M + 1 && ii_rec_5 <= x_M + 1)
{
sum += (-1.25e-4F*px*py*pz + 2.5e-3F*px*pz)*(u[t0][ii_rec_5 + 12][ii_rec_1 + 12][ii_rec_3 + 12] + v[t0][ii_rec_5 + 12][ii_rec_1 + 12][ii_rec_3 + 12]);
}
if (ii_rec_2 >= z_m - 1 && ii_rec_4 >= y_m - 1 && ii_rec_5 >= x_m - 1 && ii_rec_2 <= z_M + 1 && ii_rec_4 <= y_M + 1 && ii_rec_5 <= x_M + 1)
{
sum += (-1.25e-4F*px*py*pz + 2.5e-3F*px*py)*(u[t0][ii_rec_5 + 12][ii_rec_4 + 12][ii_rec_2 + 12] + v[t0][ii_rec_5 + 12][ii_rec_4 + 12][ii_rec_2 + 12]);
}
if (ii_rec_3 >= z_m - 1 && ii_rec_4 >= y_m - 1 && ii_rec_5 >= x_m - 1 && ii_rec_3 <= z_M + 1 && ii_rec_4 <= y_M + 1 && ii_rec_5 <= x_M + 1)
{
sum += 1.25e-4F*px*py*pz*(u[t0][ii_rec_5 + 12][ii_rec_4 + 12][ii_rec_3 + 12] + v[t0][ii_rec_5 + 12][ii_rec_4 + 12][ii_rec_3 + 12]);
}
rec[time][p_rec] = sum;
}
/* End section3 */
gettimeofday(&end_section3, NULL);
timers->section3 += (double)(end_section3.tv_sec-start_section3.tv_sec)+(double)(end_section3.tv_usec-start_section3.tv_usec)/1000000;
}
#pragma omp target exit data map(delete: r184[0:x_size + 3 + 3][0:y_size + 3 + 3][0:z_size + 3 + 3])
free(r184);
#pragma omp target exit data map(delete: r185[0:x_size + 3 + 3][0:y_size + 3 + 3][0:z_size + 3 + 3])
free(r185);
#pragma omp target exit data map(delete: r186[0:x_size + 3 + 3][0:y_size + 3 + 3][0:z_size + 3 + 3])
free(r186);
#pragma omp target exit data map(delete: r187[0:x_size + 3 + 3][0:y_size + 3 + 3][0:z_size + 3 + 3])
free(r187);
#pragma omp target exit data map(delete: r188[0:x_size + 3 + 3][0:y_size + 3 + 3][0:z_size + 3 + 3])
free(r188);
#pragma omp target exit data map(delete: r236[0:x_size + 3 + 3][0:y_size + 3 + 3][0:z_size + 3 + 3])
free(r236);
#pragma omp target exit data map(delete: r237[0:x_size + 3 + 3][0:y_size + 3 + 3][0:z_size + 3 + 3])
free(r237);
#pragma omp target update from(rec[0:rec_vec->size[0]][0:rec_vec->size[1]])
#pragma omp target exit data map(release: rec[0:rec_vec->size[0]][0:rec_vec->size[1]])
#pragma omp target update from(u[0:u_vec->size[0]][0:u_vec->size[1]][0:u_vec->size[2]][0:u_vec->size[3]])
#pragma omp target exit data map(release: u[0:u_vec->size[0]][0:u_vec->size[1]][0:u_vec->size[2]][0:u_vec->size[3]])
#pragma omp target update from(v[0:v_vec->size[0]][0:v_vec->size[1]][0:v_vec->size[2]][0:v_vec->size[3]])
#pragma omp target exit data map(release: v[0:v_vec->size[0]][0:v_vec->size[1]][0:v_vec->size[2]][0:v_vec->size[3]])
#pragma omp target exit data map(delete: damp[0:damp_vec->size[0]][0:damp_vec->size[1]][0:damp_vec->size[2]])
#pragma omp target exit data map(delete: delta[0:delta_vec->size[0]][0:delta_vec->size[1]][0:delta_vec->size[2]])
#pragma omp target exit data map(delete: epsilon[0:epsilon_vec->size[0]][0:epsilon_vec->size[1]][0:epsilon_vec->size[2]])
#pragma omp target exit data map(delete: phi[0:phi_vec->size[0]][0:phi_vec->size[1]][0:phi_vec->size[2]])
#pragma omp target exit data map(delete: rec_coords[0:rec_coords_vec->size[0]][0:rec_coords_vec->size[1]])
#pragma omp target exit data map(delete: src[0:src_vec->size[0]][0:src_vec->size[1]])
#pragma omp target exit data map(delete: src_coords[0:src_coords_vec->size[0]][0:src_coords_vec->size[1]])
#pragma omp target exit data map(delete: theta[0:theta_vec->size[0]][0:theta_vec->size[1]][0:theta_vec->size[2]])
#pragma omp target exit data map(delete: vp[0:vp_vec->size[0]][0:vp_vec->size[1]][0:vp_vec->size[2]])
return 0;
}
/* Backdoor edit at Mon Mar 2 16:36:30 2020*/
/* Backdoor edit at Mon Mar 2 16:38:22 2020*/
/* Backdoor edit at Mon Mar 2 16:50:54 2020*/
/* Backdoor edit at Mon Mar 2 16:54:28 2020*/
/* Backdoor edit at Mon Mar 2 16:56:22 2020*/
/* Backdoor edit at Mon Mar 2 19:30:39 2020*/
/* Backdoor edit at Mon Mar 2 19:34:09 2020*/
/* Backdoor edit at Mon Mar 2 19:36:00 2020*/
|
chlpca.h | /*
#
# File : chlpca.cpp
# ( C++ source file )
#
# Description : Example of use for the CImg plugin 'plugins/chlpca.h'.
# This file is a part of the CImg Library project.
# ( http://cimg.eu )
#
# Copyright : Jerome Boulanger
# ( http://www.irisa.fr/vista/Equipe/People/Jerome.Boulanger.html )
#
#
# License : CeCILL v2.0
# ( http://www.cecill.info/licences/Licence_CeCILL_V2-en.html )
#
# This software is governed by the CeCILL license under French law and
# abiding by the rules of distribution of free software. You can use,
# modify and/ or redistribute the software under the terms of the CeCILL
# license as circulated by CEA, CNRS and INRIA at the following URL
# "http://www.cecill.info".
#
# As a counterpart to the access to the source code and rights to copy,
# modify and redistribute granted by the license, users are provided only
# with a limited warranty and the software's author, the holder of the
# economic rights, and the successive licensors have only limited
# liability.
#
# In this respect, the user's attention is drawn to the risks associated
# with loading, using, modifying and/or developing or reproducing the
# software by the user in light of its specific status of free software,
# that may mean that it is complicated to manipulate, and that also
# therefore means that it is reserved for developers and experienced
# professionals having in-depth computer knowledge. Users are therefore
# encouraged to load and test the software's suitability as regards their
# requirements in conditions enabling the security of their systems and/or
# data to be ensured and, more generally, to use and operate it in the
# same conditions as regards security.
#
# The fact that you are presently reading this means that you have had
# knowledge of the CeCILL license and that you accept its terms.
#
*/
#ifndef cimg_plugin_chlpca
#define cimg_plugin_chlpca
// Define some useful macros.
//! Some loops
#define cimg_for_step1(bound,i,step) for (int i = 0; i<(int)(bound); i+=step)
#define cimg_for_stepX(img,x,step) cimg_for_step1((img)._width,x,step)
#define cimg_for_stepY(img,y,step) cimg_for_step1((img)._height,y,step)
#define cimg_for_stepZ(img,z,step) cimg_for_step1((img)._depth,z,step)
#define cimg_for_stepXY(img,x,y,step) cimg_for_stepY(img,y,step) cimg_for_stepX(img,x,step)
#define cimg_for_stepXYZ(img,x,y,step) cimg_for_stepZ(img,z,step) cimg_for_stepY(img,y,step) cimg_for_stepX(img,x,step)
//! Loop for point J(xj,yj) in the neighborhood of a point I(xi,yi) of size (2*rx+1,2*ry+1)
/**
Point J is kept inside the boundaries of the image img.
example of summing the pixels values in a neighborhood 11x11
cimg_forXY(img,xi,yi) cimg_for_windowXY(img,xi,yi,xj,yj,5,5) dest(yi,yi) += src(xj,yj);
**/
#define cimg_forXY_window(img,xi,yi,xj,yj,rx,ry) \
for (int yi0 = std::max(0,yi-ry), yi1=std::min(yi + ry,(int)img.height() - 1), yj=yi0;yj<=yi1;++yj) \
for (int xi0 = std::max(0,xi-rx), xi1=std::min(xi + rx,(int)img.width() - 1), xj=xi0;xj<=xi1;++xj)
#define cimg_forXYZ_window(img,xi,yi,zi,xj,yj,zj,rx,ry,rz) \
for (int zi0 = std::max(0,zi-rz), zi1=std::min(zi + rz,(int)img.depth() - 1) , zj=zi0;zj<=zi1;++zj) \
for (int yi0 = std::max(0,yi-ry), yi1=std::min(yi + ry,(int)img.height() - 1), yj=yi0;yj<=yi1;++yj) \
for (int xi0 = std::max(0,xi-rx), xi1=std::min(xi + rx,(int)img.width() - 1) , xj=xi0;xj<=xi1;++xj)
//! Crop a patch in the image around position x,y,z and return a column vector
/**
\param x x-coordinate of the center of the patch
\param y y-coordinate of the center of the patch
\param z z-coordinate of the center of the patch
\param px the patch half width
\param px the patch half height
\param px the patch half depth
\return img.get_crop(x0,y0,z0,x1,y1,z1).unroll('y');
**/
CImg<T> get_patch(int x, int y, int z,
int px, int py, int pz) const {
if (depth() == 1){
const int x0 = x - px, y0 = y - py, x1 = x + px, y1 = y + py;
return get_crop(x0, y0, x1, y1).unroll('y');
} else {
const int
x0 = x - px, y0 = y - py, z0 = z - pz,
x1 = x + px, y1 = y + py, z1 = z + pz;
return get_crop(x0, y0, z0, x1, y1, z1).unroll('y');
}
}
//! Extract a local patch dictionnary around point xi,yi,zi
CImg<T> get_patch_dictionnary(const int xi, const int yi, const int zi,
const int px, const int py, const int pz,
const int wx, const int wy, const int wz,
int & idc) const {
const int
n = (2*wx + 1) * (2*wy + 1) * (2 * (depth()==1?0:wz) + 1),
d = (2*px + 1) * (2*py + 1) * (2 * (depth()==1?0:px) + 1) * spectrum();
CImg<> S(n, d);
int idx = 0;
if (depth() == 1) {
cimg_forXY_window((*this), xi, yi, xj, yj, wx, wy){
CImg<T> patch = get_patch(xj, yj, 0, px, py, 1);
cimg_forY(S,y) S(idx,y) = patch(y);
if (xj==xi && yj==yi) idc = idx;
idx++;
}
} else {
cimg_forXYZ_window((*this), xi,yi,zi,xj,yj,zj,wx,wy,wz){
CImg<T> patch = get_patch(xj, yj, zj, px, py, pz);
cimg_forY(S,y) S(idx,y) = patch(y);
if (xj==xi && yj==yi && zj==zi) idc = idx;
idx++;
}
}
S.columns(0, idx - 1);
return S;
}
//! Add a patch to the image
/**
\param x x-coordinate of the center of the patch
\param y y-coordinate of the center of the patch
\param z z-coordinate of the center of the patch
\param img the patch as a 1D column vector
\param px the patch half width
\param px the patch half height
\param px the patch half depth
**/
CImg<T> & add_patch(const int xi, const int yi, const int zi,
const CImg<T> & patch,
const int px, const int py, const int pz) {
const int
x0 = xi - px, y0 = yi - py, z0 = (depth() == 1 ? 0 : zi - pz),
sx = 2 * px + 1, sy = 2 * py + 1, sz = (depth() == 1 ? 1 : 2 * pz +1);
draw_image(x0, y0, z0, 0, patch.get_resize(sx, sy, sz, spectrum(), -1), -1);
return (*this);
}
//! Add a constant patch to the image
/**
\param x x-coordinate of the center of the patch
\param y y-coordinate of the center of the patch
\param z z-coordinate of the center of the patch
\param value in the patch
\param px the patch half width
\param px the patch half height
\param px the patch half depth
**/
CImg<T> & add_patch(const int xi, const int yi, const int zi, const T value,
const int px, const int py, const int pz) {
const int
x0 = xi - px, y0 = yi - py, z0 = (depth() == 1 ? 0 : zi - pz),
x1 = xi + px, y1 = yi + py, z1 = (depth() == 1 ? 0 : zi + pz);
draw_rectangle(x0, y0, z0, 0, x1, y1, z1, spectrum()-1, value, -1);
return (*this);
}
//! CHLPCA denoising from the PhD thesis of Hu Haijuan
/**
\param px the patch half width
\param py the patch half height
\param pz the patch half depth
\param wx the training region half width
\param wy the training region half height
\param wz the training region half depth
\param nstep the subsampling of the image domain
\param nsim the number of patches used for training as a factor of the patch size
\param lambda_min the threshold on the eigen values of the PCA for dimension reduction
\param threshold the threshold on the value of the coefficients
\param pca_use_svd if true use the svd approach to perform the pca otherwise use the covariance method
\note please cite the PhD thesis of Hu Haijuan http://www.univ-ubs.fr/soutenance-de-these-hu-haijuan-337653.kjsp?RH=1318498222799
**/
CImg<T> get_chlpca(const int px, const int py, const int pz,
const int wx, const int wy, const int wz,
const int nstep, const float nsim,
const float lambda_min, const float threshold,
const float noise_std, const bool pca_use_svd) const {
const int
nd = (2*px + 1) * (2*py + 1) * (depth()==1?1:2*pz + 1) * spectrum(),
K = (int)(nsim * nd);
#ifdef DEBUG
fprintf(stderr,"chlpca: p:%dx%dx%d,w:%dx%dx%d,nd:%d,K:%d\n",
2*px + 1,2*py + 1,2*pz + 1,2*wx + 1,2*wy + 1,2*wz + 1,nd,K);
#endif
float sigma;
if (noise_std<0) sigma = (float)std::sqrt(variance_noise());
else sigma = noise_std;
CImg<T> dest(*this), count(*this);
dest.fill(0);
count.fill(0);
cimg_for_stepZ(*this,zi,(depth()==1||pz==0)?1:nstep){
#ifdef cimg_use_openmp
#pragma omp parallel for
#endif
cimg_for_stepXY((*this),xi,yi,nstep){
// extract the training region X
int idc = 0;
CImg<T> S = get_patch_dictionnary(xi,yi,zi,px,py,pz,wx,wy,wz,idc);
// select the K most similar patches within the training set
CImg<T> Sk(S);
CImg<unsigned int> index(S.width());
if (K < Sk.width() - 1){
CImg<T> mse(S.width());
CImg<unsigned int> perms;
cimg_forX(S,x) { mse(x) = (T)S.get_column(idc).MSE(S.get_column(x)); }
mse.sort(perms,true);
cimg_foroff(perms,i) {
cimg_forY(S,j) Sk(i,j) = S(perms(i),j);
index(perms(i)) = i;
}
Sk.columns(0, K);
perms.threshold(K);
} else {
cimg_foroff(index,i) index(i)=i;
}
// centering the patches
CImg<T> M(1, Sk.height(), 1, 1, 0);
cimg_forXY(Sk,x,y) { M(y) += Sk(x,y); }
M /= (T)Sk.width();
cimg_forXY(Sk,x,y) { Sk(x,y) -= M(y); }
// compute the principal component of the training set S
CImg<T> P, lambda;
if (pca_use_svd) {
CImg<T> V;
Sk.get_transpose().SVD(V,lambda,P,true,100);
} else {
(Sk * Sk.get_transpose()).symmetric_eigen(lambda, P);
lambda.sqrt();
}
// dimension reduction
int s = 0;
const T tx = (T)(std::sqrt((double)Sk.width()-1.0) * lambda_min * sigma);
while((lambda(s) > tx) && (s < ((int)lambda.size() - 1))) { s++; }
P.columns(0,s);
// project all the patches on the basis (compute scalar product)
Sk = P.get_transpose() * Sk;
// threshold the coefficients
if (threshold > 0) { Sk.threshold(threshold, 1); }
// project back to pixel space
Sk = P * Sk;
// recenter the patches
cimg_forXY(Sk,x,y) { Sk(x,y) += M(y); }
int j = 0;
cimg_forXYZ_window((*this),xi,yi,zi,xj,yj,zj,wx,wy,wz){
const int id = index(j);
if (id < Sk.width()) {
dest.add_patch(xj, yj, zj, Sk.get_column(id), px, py, pz);
count.add_patch(xj, yj, zj, (T)1, px, py, pz);
}
j++;
}
}
}
cimg_foroff(dest, i) {
if(count(i) != 0) { dest(i) /= count(i); }
else { dest(i) = (*this)(i); }
}
return dest;
}
//! CHLPCA denoising from the PhD thesis of Hu Haijuan
/**
\param px the patch half width
\param px the patch half height
\param px the patch half depth
\param wx the training region half width
\param wy the training region half height
\param wz the training region half depth
\param nstep the subsampling of the image domain
\param nsim the number of patches used for training as a factor of the patch size
\param lambda_min the threshold on the eigen values of the PCA for dimension reduction
\param threshold the threshold on the value of the coefficients
\param pca_use_svd if true use the svd approach to perform the pca otherwise use the covariance method
\note please cite the PhD thesis of Hu Haijuan http://www.univ-ubs.fr/soutenance-de-these-hu-haijuan-337653.kjsp?RH=1318498222799
**/
CImg<T> & chlpca(const int px, const int py, const int pz,
const int wx, const int wy, const int wz,
const int nstep, const float nsim,
const float lambda_min, const float threshold,
const float noise_std, const bool pca_use_svd) {
(*this) = get_chlpca(px, py, pz, wx, wy, wz, nstep, nsim, lambda_min,
threshold, noise_std, pca_use_svd);
return (*this);
}
//! CHLPCA denoising from the PhD thesis of Hu Haijuan
/**
\param p the patch half size
\param w the training region half size
\param nstep the subsampling of the image domain
\param nsim the number of patches used for training as a factor of the patch size
\param lambda_min the threshold on the eigen values of the PCA for dimension reduction
\param threshold the threshold on the value of the coefficients
\param pca_use_svd if true use the svd approach to perform the pca otherwise use the covariance method
\note please cite the PhD thesis of Hu Haijuan http://www.univ-ubs.fr/soutenance-de-these-hu-haijuan-337653.kjsp?RH=1318498222799
**/
CImg<T> get_chlpca(const int p=3, const int w=10,
const int nstep=5, const float nsim=10,
const float lambda_min=2, const float threshold = -1,
const float noise_std=-1, const bool pca_use_svd=true) const {
if (depth()==1) return get_chlpca(p, p, 0, w, w, 0, nstep, nsim, lambda_min,
threshold, noise_std, pca_use_svd);
else return get_chlpca(p, p, p, w, w, w, nstep, nsim, lambda_min,
threshold, noise_std, pca_use_svd);
}
CImg<T> chlpca(const int p=3, const int w=10,
const int nstep=5, const float nsim=10,
const float lambda_min=2, const float threshold = -1,
const float noise_std=-1, const bool pca_use_svd=true) {
(*this) = get_chlpca(p, w, nstep, nsim, lambda_min,
threshold, noise_std, pca_use_svd);
return (*this);
}
#endif /* cimg_plugin_chlpca */
|
GB_unaryop__lnot_int16_int16.c | //------------------------------------------------------------------------------
// GB_unaryop: hard-coded functions for each built-in unary operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2020, All Rights Reserved.
// http://suitesparse.com See GraphBLAS/Doc/License.txt for license.
//------------------------------------------------------------------------------
// If this file is in the Generated/ folder, do not edit it (auto-generated).
#include "GB.h"
#ifndef GBCOMPACT
#include "GB_control.h"
#include "GB_iterator.h"
#include "GB_unaryop__include.h"
// C=unop(A) is defined by the following types and operators:
// op(A) function: GB_unop__lnot_int16_int16
// op(A') function: GB_tran__lnot_int16_int16
// C type: int16_t
// A type: int16_t
// cast: int16_t cij = (int16_t) aij
// unaryop: cij = !(aij != 0)
#define GB_ATYPE \
int16_t
#define GB_CTYPE \
int16_t
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA) \
int16_t aij = Ax [pA]
#define GB_CX(p) Cx [p]
// unary operator
#define GB_OP(z, x) \
z = !(x != 0) ;
// casting
#define GB_CASTING(z, aij) \
int16_t z = (int16_t) aij ;
// cij = op (cast (aij))
#define GB_CAST_OP(pC,pA) \
{ \
/* aij = Ax [pA] */ \
GB_GETA (aij, Ax, pA) ; \
/* Cx [pC] = op (cast (aij)) */ \
GB_CASTING (z, aij) ; \
GB_OP (GB_CX (pC), z) ; \
}
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_LNOT || GxB_NO_INT16)
//------------------------------------------------------------------------------
// Cx = op (cast (Ax)): apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_unop__lnot_int16_int16
(
int16_t *Cx, // Cx and Ax may be aliased
int16_t *Ax,
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t p ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
GB_CAST_OP (p, p) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (cast (A')): transpose, typecast, and apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_tran__lnot_int16_int16
(
GrB_Matrix C,
const GrB_Matrix A,
int64_t *GB_RESTRICT *Rowcounts,
GBI_single_iterator Iter,
const int64_t *GB_RESTRICT A_slice,
int naslice
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#define GB_PHASE_2_OF_2
#include "GB_unaryop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
gpg_fmt_plug.c | /* GPG cracker patch for JtR. Hacked together during Monsoon of 2012 by
* Dhiru Kholia <dhiru.kholia at gmail.com> .
*
* This software is Copyright (c) 2012, Dhiru Kholia <dhiru.kholia at gmail.com>
* and is based on,
*
* pgpry - PGP private key recovery
* Copyright (C) 2010 Jonas Gehring
*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program. If not, see <http://www.gnu.org/licenses/>
*
* converted to use 'common' code, Feb29-Mar1 2016, JimF.
*/
#if FMT_EXTERNS_H
extern struct fmt_main fmt_gpg;
#elif FMT_REGISTERS_H
john_register_one(&fmt_gpg);
#else
#include <string.h>
#include <assert.h>
#include <stdint.h>
#ifdef _OPENMP
#include <omp.h>
#ifndef OMP_SCALE
#define OMP_SCALE 64
#endif
#endif
#include "arch.h"
#include "params.h"
#include "common.h"
#include "formats.h"
#include "misc.h"
#include "twofish.h"
#include "md5.h"
#include "rc4.h"
#include "pdfcrack_md5.h"
#include "sha.h"
#include "sha2.h"
#include "gpg_common.h"
#include "memdbg.h"
#define FORMAT_LABEL "gpg"
#define FORMAT_NAME "OpenPGP / GnuPG Secret Key"
#define ALGORITHM_NAME "32/" ARCH_BITS_STR
#define SALT_SIZE sizeof(struct gpg_common_custom_salt*)
#define MIN_KEYS_PER_CRYPT 1
#define MAX_KEYS_PER_CRYPT 1
#if defined (_OPENMP)
static int omp_t = 1;
#endif
static char (*saved_key)[PLAINTEXT_LENGTH + 1];
static int *cracked;
static int any_cracked;
static size_t cracked_size;
static void init(struct fmt_main *self)
{
#if defined (_OPENMP)
omp_t = omp_get_max_threads();
self->params.min_keys_per_crypt *= omp_t;
omp_t *= OMP_SCALE;
self->params.max_keys_per_crypt *= omp_t;
#endif
saved_key = mem_calloc_align(sizeof(*saved_key),
self->params.max_keys_per_crypt, MEM_ALIGN_WORD);
any_cracked = 0;
cracked_size = sizeof(*cracked) * self->params.max_keys_per_crypt;
cracked = mem_calloc_align(sizeof(*cracked), self->params.max_keys_per_crypt, MEM_ALIGN_WORD);
Twofish_initialise();
}
static void done(void)
{
MEM_FREE(cracked);
MEM_FREE(saved_key);
}
static int valid(char *ciphertext, struct fmt_main *self)
{
return gpg_common_valid(ciphertext, self, 1);
}
static void set_salt(void *salt)
{
gpg_common_cur_salt = *(struct gpg_common_custom_salt **)salt;
}
static void gpg_set_key(char *key, int index)
{
strnzcpy(saved_key[index], key, sizeof(*saved_key));
}
static char *get_key(int index)
{
return saved_key[index];
}
static int crypt_all(int *pcount, struct db_salt *salt)
{
const int count = *pcount;
int index = 0;
int ks = gpg_common_keySize(gpg_common_cur_salt->cipher_algorithm);
if (any_cracked) {
memset(cracked, 0, cracked_size);
any_cracked = 0;
}
#ifdef _OPENMP
#pragma omp parallel for
for (index = 0; index < count; index++)
#endif
{
int res;
unsigned char keydata[64];
gpg_common_cur_salt->s2kfun(saved_key[index], keydata, ks);
res = gpg_common_check(keydata, ks);
if (res) {
cracked[index] = 1;
#ifdef _OPENMP
#pragma omp atomic
#endif
any_cracked |= 1;
}
}
return count;
}
static int cmp_all(void *binary, int count)
{
return any_cracked;
}
static int cmp_one(void *binary, int index)
{
return cracked[index];
}
static int cmp_exact(char *source, int index)
{
return 1;
}
struct fmt_main fmt_gpg = {
{
FORMAT_LABEL,
FORMAT_NAME,
ALGORITHM_NAME,
BENCHMARK_COMMENT,
BENCHMARK_LENGTH,
0,
PLAINTEXT_LENGTH,
BINARY_SIZE,
BINARY_ALIGN,
SALT_SIZE,
SALT_ALIGN,
MIN_KEYS_PER_CRYPT,
MAX_KEYS_PER_CRYPT,
FMT_CASE | FMT_8_BIT | FMT_OMP | FMT_DYNA_SALT | FMT_HUGE_INPUT,
{
"s2k-count", /* only for gpg --s2k-mode 3, see man gpg, option --s2k-count n */
"hash algorithm [1:MD5 2:SHA1 3:RIPEMD160 8:SHA256 9:SHA384 10:SHA512 11:SHA224]",
"cipher algorithm [1:IDEA 2:3DES 3:CAST5 4:Blowfish 7:AES128 8:AES192 9:AES256 10:Twofish 11:Camellia128 12:Camellia192 13:Camellia256]",
},
{ FORMAT_TAG },
gpg_common_gpg_tests
},
{
init,
done,
fmt_default_reset,
fmt_default_prepare,
valid,
fmt_default_split,
fmt_default_binary,
gpg_common_get_salt,
{
gpg_common_gpg_s2k_count,
gpg_common_gpg_hash_algorithm,
gpg_common_gpg_cipher_algorithm,
},
fmt_default_source,
{
fmt_default_binary_hash
},
fmt_default_salt_hash,
NULL,
set_salt,
gpg_set_key,
get_key,
fmt_default_clear_keys,
crypt_all,
{
fmt_default_get_hash
},
cmp_all,
cmp_one,
cmp_exact
}
};
#endif /* plugin stanza */
|
gemm.c | #include "gemm.h"
float* _tranposed(float *src, unsigned rows, unsigned columns) {
float *out = aalloc(rows*columns*sizeof(float));
#pragma omp parallel for
for (int i = 0; i < rows; i++) {
register float *src_row = src + i * columns;
#pragma omp simd
for (int j = 0; j < columns; j++) {
out[j * rows + i] = src_row[j];
}
}
return out;
}
void gemm (bool transA, bool transB, unsigned m, unsigned n, unsigned k, float *A, float *B, float X, float *C) {
float *in1, *in2;
if (transA) {
in1 = _tranposed(A, k, m);
}
else in1 = A;
if (transB) {
in2 = _tranposed(B, n, k);
}
else in2 = B;
if (X < 1.0f) {
#pragma omp simd
for (int x = 0; x < m*n; x++){
C[x] = X * C[x];
}
}
#pragma omp parallel for
for (int i = 0; i < m; i++) {
for (int l = 0; l < k; l++) {
register float pivot = in1[i*k + l];
#pragma omp simd
for (int j = 0; j < n; j++) {
C[i*n + j] += pivot*in2[l*n + j];
}
}
}
if (transA)
free(in1);
if (transB)
free(in2);
}
|
bmesh_mesh.c | /*
* ***** BEGIN GPL LICENSE BLOCK *****
*
* This program is free software; you can redistribute it and/or
* modify it under the terms of the GNU General Public License
* as published by the Free Software Foundation; either version 2
* of the License, or (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program; if not, write to the Free Software Foundation,
* Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
*
* Contributor(s): Geoffrey Bantle.
*
* ***** END GPL LICENSE BLOCK *****
*/
/** \file blender/bmesh/intern/bmesh_mesh.c
* \ingroup bmesh
*
* BM mesh level functions.
*/
#include "MEM_guardedalloc.h"
#include "DNA_listBase.h"
#include "DNA_object_types.h"
#include "BLI_linklist_stack.h"
#include "BLI_listbase.h"
#include "BLI_math.h"
#include "BLI_stack.h"
#include "BLI_utildefines.h"
#include "BKE_cdderivedmesh.h"
#include "BKE_editmesh.h"
#include "BKE_mesh.h"
#include "BKE_multires.h"
#include "intern/bmesh_private.h"
/* used as an extern, defined in bmesh.h */
const BMAllocTemplate bm_mesh_allocsize_default = {512, 1024, 2048, 512};
const BMAllocTemplate bm_mesh_chunksize_default = {512, 1024, 2048, 512};
static void bm_mempool_init_ex(
const BMAllocTemplate *allocsize, const bool use_toolflags,
BLI_mempool **r_vpool, BLI_mempool **r_epool, BLI_mempool **r_lpool, BLI_mempool **r_fpool)
{
size_t vert_size, edge_size, loop_size, face_size;
if (use_toolflags == true) {
vert_size = sizeof(BMVert_OFlag);
edge_size = sizeof(BMEdge_OFlag);
loop_size = sizeof(BMLoop);
face_size = sizeof(BMFace_OFlag);
}
else {
vert_size = sizeof(BMVert);
edge_size = sizeof(BMEdge);
loop_size = sizeof(BMLoop);
face_size = sizeof(BMFace);
}
if (r_vpool) {
*r_vpool = BLI_mempool_create(
vert_size, allocsize->totvert,
bm_mesh_chunksize_default.totvert, BLI_MEMPOOL_ALLOW_ITER);
}
if (r_epool) {
*r_epool = BLI_mempool_create(
edge_size, allocsize->totedge,
bm_mesh_chunksize_default.totedge, BLI_MEMPOOL_ALLOW_ITER);
}
if (r_lpool) {
*r_lpool = BLI_mempool_create(
loop_size, allocsize->totloop,
bm_mesh_chunksize_default.totloop, BLI_MEMPOOL_NOP);
}
if (r_fpool) {
*r_fpool = BLI_mempool_create(
face_size, allocsize->totface,
bm_mesh_chunksize_default.totface, BLI_MEMPOOL_ALLOW_ITER);
}
}
static void bm_mempool_init(BMesh *bm, const BMAllocTemplate *allocsize, const bool use_toolflags)
{
bm_mempool_init_ex(
allocsize, use_toolflags,
&bm->vpool, &bm->epool, &bm->lpool, &bm->fpool);
#ifdef USE_BMESH_HOLES
bm->looplistpool = BLI_mempool_create(sizeof(BMLoopList), 512, 512, BLI_MEMPOOL_NOP);
#endif
}
void BM_mesh_elem_toolflags_ensure(BMesh *bm)
{
BLI_assert(bm->use_toolflags);
if (bm->vtoolflagpool && bm->etoolflagpool && bm->ftoolflagpool) {
return;
}
bm->vtoolflagpool = BLI_mempool_create(sizeof(BMFlagLayer), bm->totvert, 512, BLI_MEMPOOL_NOP);
bm->etoolflagpool = BLI_mempool_create(sizeof(BMFlagLayer), bm->totedge, 512, BLI_MEMPOOL_NOP);
bm->ftoolflagpool = BLI_mempool_create(sizeof(BMFlagLayer), bm->totface, 512, BLI_MEMPOOL_NOP);
#pragma omp parallel sections if (bm->totvert + bm->totedge + bm->totface >= BM_OMP_LIMIT)
{
#pragma omp section
{
BLI_mempool *toolflagpool = bm->vtoolflagpool;
BMIter iter;
BMVert_OFlag *ele;
BM_ITER_MESH (ele, &iter, bm, BM_VERTS_OF_MESH) {
ele->oflags = BLI_mempool_calloc(toolflagpool);
}
}
#pragma omp section
{
BLI_mempool *toolflagpool = bm->etoolflagpool;
BMIter iter;
BMEdge_OFlag *ele;
BM_ITER_MESH (ele, &iter, bm, BM_EDGES_OF_MESH) {
ele->oflags = BLI_mempool_calloc(toolflagpool);
}
}
#pragma omp section
{
BLI_mempool *toolflagpool = bm->ftoolflagpool;
BMIter iter;
BMFace_OFlag *ele;
BM_ITER_MESH (ele, &iter, bm, BM_FACES_OF_MESH) {
ele->oflags = BLI_mempool_calloc(toolflagpool);
}
}
}
bm->totflags = 1;
}
void BM_mesh_elem_toolflags_clear(BMesh *bm)
{
if (bm->vtoolflagpool) {
BLI_mempool_destroy(bm->vtoolflagpool);
bm->vtoolflagpool = NULL;
}
if (bm->etoolflagpool) {
BLI_mempool_destroy(bm->etoolflagpool);
bm->etoolflagpool = NULL;
}
if (bm->ftoolflagpool) {
BLI_mempool_destroy(bm->ftoolflagpool);
bm->ftoolflagpool = NULL;
}
}
/**
* \brief BMesh Make Mesh
*
* Allocates a new BMesh structure.
*
* \return The New bmesh
*
* \note ob is needed by multires
*/
BMesh *BM_mesh_create(
const BMAllocTemplate *allocsize,
const struct BMeshCreateParams *params)
{
/* allocate the structure */
BMesh *bm = MEM_callocN(sizeof(BMesh), __func__);
/* allocate the memory pools for the mesh elements */
bm_mempool_init(bm, allocsize, params->use_toolflags);
/* allocate one flag pool that we don't get rid of. */
bm->use_toolflags = params->use_toolflags;
bm->toolflag_index = 0;
bm->totflags = 0;
CustomData_reset(&bm->vdata);
CustomData_reset(&bm->edata);
CustomData_reset(&bm->ldata);
CustomData_reset(&bm->pdata);
return bm;
}
/**
* \brief BMesh Free Mesh Data
*
* Frees a BMesh structure.
*
* \note frees mesh, but not actual BMesh struct
*/
void BM_mesh_data_free(BMesh *bm)
{
BMVert *v;
BMEdge *e;
BMLoop *l;
BMFace *f;
BMIter iter;
BMIter itersub;
const bool is_ldata_free = CustomData_bmesh_has_free(&bm->ldata);
const bool is_pdata_free = CustomData_bmesh_has_free(&bm->pdata);
/* Check if we have to call free, if not we can avoid a lot of looping */
if (CustomData_bmesh_has_free(&(bm->vdata))) {
BM_ITER_MESH (v, &iter, bm, BM_VERTS_OF_MESH) {
CustomData_bmesh_free_block(&(bm->vdata), &(v->head.data));
}
}
if (CustomData_bmesh_has_free(&(bm->edata))) {
BM_ITER_MESH (e, &iter, bm, BM_EDGES_OF_MESH) {
CustomData_bmesh_free_block(&(bm->edata), &(e->head.data));
}
}
if (is_ldata_free || is_pdata_free) {
BM_ITER_MESH (f, &iter, bm, BM_FACES_OF_MESH) {
if (is_pdata_free)
CustomData_bmesh_free_block(&(bm->pdata), &(f->head.data));
if (is_ldata_free) {
BM_ITER_ELEM (l, &itersub, f, BM_LOOPS_OF_FACE) {
CustomData_bmesh_free_block(&(bm->ldata), &(l->head.data));
}
}
}
}
/* Free custom data pools, This should probably go in CustomData_free? */
if (bm->vdata.totlayer) BLI_mempool_destroy(bm->vdata.pool);
if (bm->edata.totlayer) BLI_mempool_destroy(bm->edata.pool);
if (bm->ldata.totlayer) BLI_mempool_destroy(bm->ldata.pool);
if (bm->pdata.totlayer) BLI_mempool_destroy(bm->pdata.pool);
/* free custom data */
CustomData_free(&bm->vdata, 0);
CustomData_free(&bm->edata, 0);
CustomData_free(&bm->ldata, 0);
CustomData_free(&bm->pdata, 0);
/* destroy element pools */
BLI_mempool_destroy(bm->vpool);
BLI_mempool_destroy(bm->epool);
BLI_mempool_destroy(bm->lpool);
BLI_mempool_destroy(bm->fpool);
if (bm->vtable) MEM_freeN(bm->vtable);
if (bm->etable) MEM_freeN(bm->etable);
if (bm->ftable) MEM_freeN(bm->ftable);
/* destroy flag pool */
BM_mesh_elem_toolflags_clear(bm);
#ifdef USE_BMESH_HOLES
BLI_mempool_destroy(bm->looplistpool);
#endif
BLI_freelistN(&bm->selected);
BMO_error_clear(bm);
}
/**
* \brief BMesh Clear Mesh
*
* Clear all data in bm
*/
void BM_mesh_clear(BMesh *bm)
{
const bool use_toolflags = bm->use_toolflags;
/* free old mesh */
BM_mesh_data_free(bm);
memset(bm, 0, sizeof(BMesh));
/* allocate the memory pools for the mesh elements */
bm_mempool_init(bm, &bm_mesh_allocsize_default, use_toolflags);
bm->use_toolflags = use_toolflags;
bm->toolflag_index = 0;
bm->totflags = 0;
CustomData_reset(&bm->vdata);
CustomData_reset(&bm->edata);
CustomData_reset(&bm->ldata);
CustomData_reset(&bm->pdata);
}
/**
* \brief BMesh Free Mesh
*
* Frees a BMesh data and its structure.
*/
void BM_mesh_free(BMesh *bm)
{
BM_mesh_data_free(bm);
if (bm->py_handle) {
/* keep this out of 'BM_mesh_data_free' because we want python
* to be able to clear the mesh and maintain access. */
bpy_bm_generic_invalidate(bm->py_handle);
bm->py_handle = NULL;
}
MEM_freeN(bm);
}
/**
* Helpers for #BM_mesh_normals_update and #BM_verts_calc_normal_vcos
*/
static void bm_mesh_edges_calc_vectors(BMesh *bm, float (*edgevec)[3], const float (*vcos)[3])
{
BMIter eiter;
BMEdge *e;
int index;
if (vcos) {
BM_mesh_elem_index_ensure(bm, BM_VERT);
}
BM_ITER_MESH_INDEX (e, &eiter, bm, BM_EDGES_OF_MESH, index) {
BM_elem_index_set(e, index); /* set_inline */
if (e->l) {
const float *v1_co = vcos ? vcos[BM_elem_index_get(e->v1)] : e->v1->co;
const float *v2_co = vcos ? vcos[BM_elem_index_get(e->v2)] : e->v2->co;
sub_v3_v3v3(edgevec[index], v2_co, v1_co);
normalize_v3(edgevec[index]);
}
else {
/* the edge vector will not be needed when the edge has no radial */
}
}
bm->elem_index_dirty &= ~BM_EDGE;
}
static void bm_mesh_verts_calc_normals(
BMesh *bm, const float (*edgevec)[3], const float (*fnos)[3],
const float (*vcos)[3], float (*vnos)[3])
{
BM_mesh_elem_index_ensure(bm, (vnos) ? (BM_EDGE | BM_VERT) : BM_EDGE);
/* add weighted face normals to vertices */
{
BMIter fiter;
BMFace *f;
int i;
BM_ITER_MESH_INDEX (f, &fiter, bm, BM_FACES_OF_MESH, i) {
BMLoop *l_first, *l_iter;
const float *f_no = fnos ? fnos[i] : f->no;
l_iter = l_first = BM_FACE_FIRST_LOOP(f);
do {
const float *e1diff, *e2diff;
float dotprod;
float fac;
float *v_no = vnos ? vnos[BM_elem_index_get(l_iter->v)] : l_iter->v->no;
/* calculate the dot product of the two edges that
* meet at the loop's vertex */
e1diff = edgevec[BM_elem_index_get(l_iter->prev->e)];
e2diff = edgevec[BM_elem_index_get(l_iter->e)];
dotprod = dot_v3v3(e1diff, e2diff);
/* edge vectors are calculated from e->v1 to e->v2, so
* adjust the dot product if one but not both loops
* actually runs from from e->v2 to e->v1 */
if ((l_iter->prev->e->v1 == l_iter->prev->v) ^ (l_iter->e->v1 == l_iter->v)) {
dotprod = -dotprod;
}
fac = saacos(-dotprod);
/* accumulate weighted face normal into the vertex's normal */
madd_v3_v3fl(v_no, f_no, fac);
} while ((l_iter = l_iter->next) != l_first);
}
}
/* normalize the accumulated vertex normals */
{
BMIter viter;
BMVert *v;
int i;
BM_ITER_MESH_INDEX (v, &viter, bm, BM_VERTS_OF_MESH, i) {
float *v_no = vnos ? vnos[i] : v->no;
if (UNLIKELY(normalize_v3(v_no) == 0.0f)) {
const float *v_co = vcos ? vcos[i] : v->co;
normalize_v3_v3(v_no, v_co);
}
}
}
}
/**
* \brief BMesh Compute Normals
*
* Updates the normals of a mesh.
*/
void BM_mesh_normals_update(BMesh *bm)
{
float (*edgevec)[3] = MEM_mallocN(sizeof(*edgevec) * bm->totedge, __func__);
#pragma omp parallel sections if (bm->totvert + bm->totedge + bm->totface >= BM_OMP_LIMIT)
{
#pragma omp section
{
/* calculate all face normals */
BMIter fiter;
BMFace *f;
int i;
BM_ITER_MESH_INDEX (f, &fiter, bm, BM_FACES_OF_MESH, i) {
BM_elem_index_set(f, i); /* set_inline */
BM_face_normal_update(f);
}
bm->elem_index_dirty &= ~BM_FACE;
}
#pragma omp section
{
/* Zero out vertex normals */
BMIter viter;
BMVert *v;
int i;
BM_ITER_MESH_INDEX (v, &viter, bm, BM_VERTS_OF_MESH, i) {
BM_elem_index_set(v, i); /* set_inline */
zero_v3(v->no);
}
bm->elem_index_dirty &= ~BM_VERT;
}
#pragma omp section
{
/* Compute normalized direction vectors for each edge.
* Directions will be used for calculating the weights of the face normals on the vertex normals.
*/
bm_mesh_edges_calc_vectors(bm, edgevec, NULL);
}
}
/* end omp */
/* Add weighted face normals to vertices, and normalize vert normals. */
bm_mesh_verts_calc_normals(bm, (const float(*)[3])edgevec, NULL, NULL, NULL);
MEM_freeN(edgevec);
}
/**
* \brief BMesh Compute Normals from/to external data.
*
* Computes the vertex normals of a mesh into vnos, using given vertex coordinates (vcos) and polygon normals (fnos).
*/
void BM_verts_calc_normal_vcos(BMesh *bm, const float (*fnos)[3], const float (*vcos)[3], float (*vnos)[3])
{
float (*edgevec)[3] = MEM_mallocN(sizeof(*edgevec) * bm->totedge, __func__);
/* Compute normalized direction vectors for each edge.
* Directions will be used for calculating the weights of the face normals on the vertex normals.
*/
bm_mesh_edges_calc_vectors(bm, edgevec, vcos);
/* Add weighted face normals to vertices, and normalize vert normals. */
bm_mesh_verts_calc_normals(bm, (const float(*)[3])edgevec, fnos, vcos, vnos);
MEM_freeN(edgevec);
}
/**
* Helpers for #BM_mesh_loop_normals_update and #BM_loops_calc_normals_vnos
*/
static void bm_mesh_edges_sharp_tag(
BMesh *bm, const float (*vnos)[3], const float (*fnos)[3], float split_angle,
float (*r_lnos)[3])
{
BMIter eiter;
BMEdge *e;
int i;
const bool check_angle = (split_angle < (float)M_PI);
if (check_angle) {
split_angle = cosf(split_angle);
}
{
char htype = BM_VERT | BM_LOOP;
if (fnos) {
htype |= BM_FACE;
}
BM_mesh_elem_index_ensure(bm, htype);
}
/* This first loop checks which edges are actually smooth, and pre-populate lnos with vnos (as if they were
* all smooth).
*/
BM_ITER_MESH_INDEX (e, &eiter, bm, BM_EDGES_OF_MESH, i) {
BMLoop *l_a, *l_b;
BM_elem_index_set(e, i); /* set_inline */
BM_elem_flag_disable(e, BM_ELEM_TAG); /* Clear tag (means edge is sharp). */
/* An edge with only two loops, might be smooth... */
if (BM_edge_loop_pair(e, &l_a, &l_b)) {
bool is_angle_smooth = true;
if (check_angle) {
const float *no_a = fnos ? fnos[BM_elem_index_get(l_a->f)] : l_a->f->no;
const float *no_b = fnos ? fnos[BM_elem_index_get(l_b->f)] : l_b->f->no;
is_angle_smooth = (dot_v3v3(no_a, no_b) >= split_angle);
}
/* We only tag edges that are *really* smooth:
* If the angle between both its polys' normals is below split_angle value,
* and it is tagged as such,
* and both its faces are smooth,
* and both its faces have compatible (non-flipped) normals,
* i.e. both loops on the same edge do not share the same vertex.
*/
if (is_angle_smooth &&
BM_elem_flag_test(e, BM_ELEM_SMOOTH) &&
BM_elem_flag_test(l_a->f, BM_ELEM_SMOOTH) &&
BM_elem_flag_test(l_b->f, BM_ELEM_SMOOTH) &&
l_a->v != l_b->v)
{
const float *no;
BM_elem_flag_enable(e, BM_ELEM_TAG);
/* linked vertices might be fully smooth, copy their normals to loop ones. */
no = vnos ? vnos[BM_elem_index_get(l_a->v)] : l_a->v->no;
copy_v3_v3(r_lnos[BM_elem_index_get(l_a)], no);
no = vnos ? vnos[BM_elem_index_get(l_b->v)] : l_b->v->no;
copy_v3_v3(r_lnos[BM_elem_index_get(l_b)], no);
}
}
}
bm->elem_index_dirty &= ~BM_EDGE;
}
/* Check whether gievn loop is part of an unknown-so-far cyclic smooth fan, or not.
* Needed because cyclic smooth fans have no obvious 'entry point', and yet we need to walk them once, and only once. */
static bool bm_mesh_loop_check_cyclic_smooth_fan(BMLoop *l_curr)
{
BMLoop *lfan_pivot_next = l_curr;
BMEdge *e_next = l_curr->e;
BLI_assert(!BM_elem_flag_test(lfan_pivot_next, BM_ELEM_TAG));
BM_elem_flag_enable(lfan_pivot_next, BM_ELEM_TAG);
while (true) {
/* Much simpler than in sibling code with basic Mesh data! */
lfan_pivot_next = BM_vert_step_fan_loop(lfan_pivot_next, &e_next);
if (!lfan_pivot_next || !BM_elem_flag_test(e_next, BM_ELEM_TAG)) {
/* Sharp loop/edge, so not a cyclic smooth fan... */
return false;
}
/* Smooth loop/edge... */
else if (BM_elem_flag_test(lfan_pivot_next, BM_ELEM_TAG)) {
if (lfan_pivot_next == l_curr) {
/* We walked around a whole cyclic smooth fan without finding any already-processed loop, means we can
* use initial l_curr/l_prev edge as start for this smooth fan. */
return true;
}
/* ... already checked in some previous looping, we can abort. */
return false;
}
else {
/* ... we can skip it in future, and keep checking the smooth fan. */
BM_elem_flag_enable(lfan_pivot_next, BM_ELEM_TAG);
}
}
}
/* BMesh version of BKE_mesh_normals_loop_split() in mesh_evaluate.c
* Will use first clnors_data array, and fallback to cd_loop_clnors_offset (use NULL and -1 to not use clnors). */
static void bm_mesh_loops_calc_normals(
BMesh *bm, const float (*vcos)[3], const float (*fnos)[3], float (*r_lnos)[3],
MLoopNorSpaceArray *r_lnors_spacearr, short (*clnors_data)[2], const int cd_loop_clnors_offset)
{
BMIter fiter;
BMFace *f_curr;
const bool has_clnors = clnors_data || (cd_loop_clnors_offset != -1);
MLoopNorSpaceArray _lnors_spacearr = {NULL};
/* Temp normal stack. */
BLI_SMALLSTACK_DECLARE(normal, float *);
/* Temp clnors stack. */
BLI_SMALLSTACK_DECLARE(clnors, short *);
/* Temp edge vectors stack, only used when computing lnor spacearr. */
BLI_Stack *edge_vectors = NULL;
{
char htype = 0;
if (vcos) {
htype |= BM_VERT;
}
/* Face/Loop indices are set inline below. */
BM_mesh_elem_index_ensure(bm, htype);
}
if (!r_lnors_spacearr && has_clnors) {
/* We need to compute lnor spacearr if some custom lnor data are given to us! */
r_lnors_spacearr = &_lnors_spacearr;
}
if (r_lnors_spacearr) {
BKE_lnor_spacearr_init(r_lnors_spacearr, bm->totloop);
edge_vectors = BLI_stack_new(sizeof(float[3]), __func__);
}
/* Clear all loops' tags (means none are to be skipped for now). */
int index_face, index_loop = 0;
BM_ITER_MESH_INDEX (f_curr, &fiter, bm, BM_FACES_OF_MESH, index_face) {
BMLoop *l_curr, *l_first;
BM_elem_index_set(f_curr, index_face); /* set_inline */
l_curr = l_first = BM_FACE_FIRST_LOOP(f_curr);
do {
BM_elem_index_set(l_curr, index_loop++); /* set_inline */
BM_elem_flag_disable(l_curr, BM_ELEM_TAG);
} while ((l_curr = l_curr->next) != l_first);
}
bm->elem_index_dirty &= ~(BM_FACE | BM_LOOP);
/* We now know edges that can be smoothed (they are tagged), and edges that will be hard (they aren't).
* Now, time to generate the normals.
*/
BM_ITER_MESH (f_curr, &fiter, bm, BM_FACES_OF_MESH) {
BMLoop *l_curr, *l_first;
l_curr = l_first = BM_FACE_FIRST_LOOP(f_curr);
do {
/* A smooth edge, we have to check for cyclic smooth fan case.
* If we find a new, never-processed cyclic smooth fan, we can do it now using that loop/edge as
* 'entry point', otherwise we can skip it. */
/* Note: In theory, we could make bm_mesh_loop_check_cyclic_smooth_fan() store mlfan_pivot's in a stack,
* to avoid having to fan again around the vert during actual computation of clnor & clnorspace.
* However, this would complicate the code, add more memory usage, and BM_vert_step_fan_loop()
* is quite cheap in term of CPU cycles, so really think it's not worth it. */
if (BM_elem_flag_test(l_curr->e, BM_ELEM_TAG) &&
(BM_elem_flag_test(l_curr, BM_ELEM_TAG) || !bm_mesh_loop_check_cyclic_smooth_fan(l_curr)))
{
}
else if (!BM_elem_flag_test(l_curr->e, BM_ELEM_TAG) &&
!BM_elem_flag_test(l_curr->prev->e, BM_ELEM_TAG))
{
/* Simple case (both edges around that vertex are sharp in related polygon),
* this vertex just takes its poly normal.
*/
const int l_curr_index = BM_elem_index_get(l_curr);
const float *no = fnos ? fnos[BM_elem_index_get(f_curr)] : f_curr->no;
copy_v3_v3(r_lnos[l_curr_index], no);
/* If needed, generate this (simple!) lnor space. */
if (r_lnors_spacearr) {
float vec_curr[3], vec_prev[3];
MLoopNorSpace *lnor_space = BKE_lnor_space_create(r_lnors_spacearr);
{
const BMVert *v_pivot = l_curr->v;
const float *co_pivot = vcos ? vcos[BM_elem_index_get(v_pivot)] : v_pivot->co;
const BMVert *v_1 = BM_edge_other_vert(l_curr->e, v_pivot);
const float *co_1 = vcos ? vcos[BM_elem_index_get(v_1)] : v_1->co;
const BMVert *v_2 = BM_edge_other_vert(l_curr->prev->e, v_pivot);
const float *co_2 = vcos ? vcos[BM_elem_index_get(v_2)] : v_2->co;
sub_v3_v3v3(vec_curr, co_1, co_pivot);
normalize_v3(vec_curr);
sub_v3_v3v3(vec_prev, co_2, co_pivot);
normalize_v3(vec_prev);
}
BKE_lnor_space_define(lnor_space, r_lnos[l_curr_index], vec_curr, vec_prev, NULL);
/* We know there is only one loop in this space, no need to create a linklist in this case... */
BKE_lnor_space_add_loop(r_lnors_spacearr, lnor_space, l_curr_index, false);
if (has_clnors) {
short (*clnor)[2] = clnors_data ? &clnors_data[l_curr_index] :
BM_ELEM_CD_GET_VOID_P(l_curr, cd_loop_clnors_offset);
BKE_lnor_space_custom_data_to_normal(lnor_space, *clnor, r_lnos[l_curr_index]);
}
}
}
/* We *do not need* to check/tag loops as already computed!
* Due to the fact a loop only links to one of its two edges, a same fan *will never be walked more than
* once!*
* Since we consider edges having neighbor faces with inverted (flipped) normals as sharp, we are sure that
* no fan will be skipped, even only considering the case (sharp curr_edge, smooth prev_edge), and not the
* alternative (smooth curr_edge, sharp prev_edge).
* All this due/thanks to link between normals and loop ordering.
*/
else {
/* We have to fan around current vertex, until we find the other non-smooth edge,
* and accumulate face normals into the vertex!
* Note in case this vertex has only one sharp edge, this is a waste because the normal is the same as
* the vertex normal, but I do not see any easy way to detect that (would need to count number
* of sharp edges per vertex, I doubt the additional memory usage would be worth it, especially as
* it should not be a common case in real-life meshes anyway).
*/
BMVert *v_pivot = l_curr->v;
BMEdge *e_next;
const BMEdge *e_org = l_curr->e;
BMLoop *lfan_pivot, *lfan_pivot_next;
int lfan_pivot_index;
float lnor[3] = {0.0f, 0.0f, 0.0f};
float vec_curr[3], vec_next[3], vec_org[3];
/* We validate clnors data on the fly - cheapest way to do! */
int clnors_avg[2] = {0, 0};
short (*clnor_ref)[2] = NULL;
int clnors_nbr = 0;
bool clnors_invalid = false;
const float *co_pivot = vcos ? vcos[BM_elem_index_get(v_pivot)] : v_pivot->co;
MLoopNorSpace *lnor_space = r_lnors_spacearr ? BKE_lnor_space_create(r_lnors_spacearr) : NULL;
BLI_assert((edge_vectors == NULL) || BLI_stack_is_empty(edge_vectors));
lfan_pivot = l_curr;
lfan_pivot_index = BM_elem_index_get(lfan_pivot);
e_next = lfan_pivot->e; /* Current edge here, actually! */
/* Only need to compute previous edge's vector once, then we can just reuse old current one! */
{
const BMVert *v_2 = BM_edge_other_vert(e_next, v_pivot);
const float *co_2 = vcos ? vcos[BM_elem_index_get(v_2)] : v_2->co;
sub_v3_v3v3(vec_org, co_2, co_pivot);
normalize_v3(vec_org);
copy_v3_v3(vec_curr, vec_org);
if (r_lnors_spacearr) {
BLI_stack_push(edge_vectors, vec_org);
}
}
while (true) {
/* Much simpler than in sibling code with basic Mesh data! */
lfan_pivot_next = BM_vert_step_fan_loop(lfan_pivot, &e_next);
if (lfan_pivot_next) {
BLI_assert(lfan_pivot_next->v == v_pivot);
}
else {
/* next edge is non-manifold, we have to find it ourselves! */
e_next = (lfan_pivot->e == e_next) ? lfan_pivot->prev->e : lfan_pivot->e;
}
/* Compute edge vector.
* NOTE: We could pre-compute those into an array, in the first iteration, instead of computing them
* twice (or more) here. However, time gained is not worth memory and time lost,
* given the fact that this code should not be called that much in real-life meshes...
*/
{
const BMVert *v_2 = BM_edge_other_vert(e_next, v_pivot);
const float *co_2 = vcos ? vcos[BM_elem_index_get(v_2)] : v_2->co;
sub_v3_v3v3(vec_next, co_2, co_pivot);
normalize_v3(vec_next);
}
{
/* Code similar to accumulate_vertex_normals_poly. */
/* Calculate angle between the two poly edges incident on this vertex. */
const BMFace *f = lfan_pivot->f;
const float fac = saacos(dot_v3v3(vec_next, vec_curr));
const float *no = fnos ? fnos[BM_elem_index_get(f)] : f->no;
/* Accumulate */
madd_v3_v3fl(lnor, no, fac);
if (has_clnors) {
/* Accumulate all clnors, if they are not all equal we have to fix that! */
short (*clnor)[2] = clnors_data ? &clnors_data[lfan_pivot_index] :
BM_ELEM_CD_GET_VOID_P(lfan_pivot, cd_loop_clnors_offset);
if (clnors_nbr) {
clnors_invalid |= ((*clnor_ref)[0] != (*clnor)[0] || (*clnor_ref)[1] != (*clnor)[1]);
}
else {
clnor_ref = clnor;
}
clnors_avg[0] += (*clnor)[0];
clnors_avg[1] += (*clnor)[1];
clnors_nbr++;
/* We store here a pointer to all custom lnors processed. */
BLI_SMALLSTACK_PUSH(clnors, (short *)*clnor);
}
}
/* We store here a pointer to all loop-normals processed. */
BLI_SMALLSTACK_PUSH(normal, (float *)r_lnos[lfan_pivot_index]);
if (r_lnors_spacearr) {
/* Assign current lnor space to current 'vertex' loop. */
BKE_lnor_space_add_loop(r_lnors_spacearr, lnor_space, lfan_pivot_index, true);
if (e_next != e_org) {
/* We store here all edges-normalized vectors processed. */
BLI_stack_push(edge_vectors, vec_next);
}
}
if (!BM_elem_flag_test(e_next, BM_ELEM_TAG) || (e_next == e_org)) {
/* Next edge is sharp, we have finished with this fan of faces around this vert! */
break;
}
/* Copy next edge vector to current one. */
copy_v3_v3(vec_curr, vec_next);
/* Next pivot loop to current one. */
lfan_pivot = lfan_pivot_next;
lfan_pivot_index = BM_elem_index_get(lfan_pivot);
}
{
float lnor_len = normalize_v3(lnor);
/* If we are generating lnor spacearr, we can now define the one for this fan. */
if (r_lnors_spacearr) {
if (UNLIKELY(lnor_len == 0.0f)) {
/* Use vertex normal as fallback! */
copy_v3_v3(lnor, r_lnos[lfan_pivot_index]);
lnor_len = 1.0f;
}
BKE_lnor_space_define(lnor_space, lnor, vec_org, vec_next, edge_vectors);
if (has_clnors) {
if (clnors_invalid) {
short *clnor;
clnors_avg[0] /= clnors_nbr;
clnors_avg[1] /= clnors_nbr;
/* Fix/update all clnors of this fan with computed average value. */
printf("Invalid clnors in this fan!\n");
while ((clnor = BLI_SMALLSTACK_POP(clnors))) {
//print_v2("org clnor", clnor);
clnor[0] = (short)clnors_avg[0];
clnor[1] = (short)clnors_avg[1];
}
//print_v2("new clnors", clnors_avg);
}
else {
/* We still have to consume the stack! */
while (BLI_SMALLSTACK_POP(clnors));
}
BKE_lnor_space_custom_data_to_normal(lnor_space, *clnor_ref, lnor);
}
}
/* In case we get a zero normal here, just use vertex normal already set! */
if (LIKELY(lnor_len != 0.0f)) {
/* Copy back the final computed normal into all related loop-normals. */
float *nor;
while ((nor = BLI_SMALLSTACK_POP(normal))) {
copy_v3_v3(nor, lnor);
}
}
else {
/* We still have to consume the stack! */
while (BLI_SMALLSTACK_POP(normal));
}
}
/* Tag related vertex as sharp, to avoid fanning around it again (in case it was a smooth one). */
if (r_lnors_spacearr) {
BM_elem_flag_enable(l_curr->v, BM_ELEM_TAG);
}
}
} while ((l_curr = l_curr->next) != l_first);
}
if (r_lnors_spacearr) {
BLI_stack_free(edge_vectors);
if (r_lnors_spacearr == &_lnors_spacearr) {
BKE_lnor_spacearr_free(r_lnors_spacearr);
}
}
}
static void bm_mesh_loops_calc_normals_no_autosmooth(
BMesh *bm, const float (*vnos)[3], const float (*fnos)[3], float (*r_lnos)[3])
{
BMIter fiter;
BMFace *f_curr;
{
char htype = BM_LOOP;
if (vnos) {
htype |= BM_VERT;
}
if (fnos) {
htype |= BM_FACE;
}
BM_mesh_elem_index_ensure(bm, htype);
}
BM_ITER_MESH (f_curr, &fiter, bm, BM_FACES_OF_MESH) {
BMLoop *l_curr, *l_first;
const bool is_face_flat = !BM_elem_flag_test(f_curr, BM_ELEM_SMOOTH);
l_curr = l_first = BM_FACE_FIRST_LOOP(f_curr);
do {
const float *no = is_face_flat ? (fnos ? fnos[BM_elem_index_get(f_curr)] : f_curr->no) :
(vnos ? vnos[BM_elem_index_get(l_curr->v)] : l_curr->v->no);
copy_v3_v3(r_lnos[BM_elem_index_get(l_curr)], no);
} while ((l_curr = l_curr->next) != l_first);
}
}
#if 0 /* Unused currently */
/**
* \brief BMesh Compute Loop Normals
*
* Updates the loop normals of a mesh. Assumes vertex and face normals are valid (else call BM_mesh_normals_update()
* first)!
*/
void BM_mesh_loop_normals_update(
BMesh *bm, const bool use_split_normals, const float split_angle, float (*r_lnos)[3],
MLoopNorSpaceArray *r_lnors_spacearr, short (*clnors_data)[2], const int cd_loop_clnors_offset)
{
const bool has_clnors = clnors_data || (cd_loop_clnors_offset != -1);
if (use_split_normals) {
/* Tag smooth edges and set lnos from vnos when they might be completely smooth...
* When using custom loop normals, disable the angle feature! */
bm_mesh_edges_sharp_tag(bm, NULL, NULL, has_clnors ? (float)M_PI : split_angle, r_lnos);
/* Finish computing lnos by accumulating face normals in each fan of faces defined by sharp edges. */
bm_mesh_loops_calc_normals(bm, NULL, NULL, r_lnos, r_lnors_spacearr, clnors_data, cd_loop_clnors_offset);
}
else {
BLI_assert(!r_lnors_spacearr);
bm_mesh_loops_calc_normals_no_autosmooth(bm, NULL, NULL, r_lnos);
}
}
#endif
/**
* \brief BMesh Compute Loop Normals from/to external data.
*
* Compute split normals, i.e. vertex normals associated with each poly (hence 'loop normals').
* Useful to materialize sharp edges (or non-smooth faces) without actually modifying the geometry (splitting edges).
*/
void BM_loops_calc_normal_vcos(
BMesh *bm, const float (*vcos)[3], const float (*vnos)[3], const float (*fnos)[3],
const bool use_split_normals, const float split_angle, float (*r_lnos)[3],
MLoopNorSpaceArray *r_lnors_spacearr, short (*clnors_data)[2], const int cd_loop_clnors_offset)
{
const bool has_clnors = clnors_data || (cd_loop_clnors_offset != -1);
if (use_split_normals) {
/* Tag smooth edges and set lnos from vnos when they might be completely smooth...
* When using custom loop normals, disable the angle feature! */
bm_mesh_edges_sharp_tag(bm, vnos, fnos, has_clnors ? (float)M_PI : split_angle, r_lnos);
/* Finish computing lnos by accumulating face normals in each fan of faces defined by sharp edges. */
bm_mesh_loops_calc_normals(bm, vcos, fnos, r_lnos, r_lnors_spacearr, clnors_data, cd_loop_clnors_offset);
}
else {
BLI_assert(!r_lnors_spacearr);
bm_mesh_loops_calc_normals_no_autosmooth(bm, vnos, fnos, r_lnos);
}
}
static void UNUSED_FUNCTION(bm_mdisps_space_set)(Object *ob, BMesh *bm, int from, int to)
{
/* switch multires data out of tangent space */
if (CustomData_has_layer(&bm->ldata, CD_MDISPS)) {
BMEditMesh *em = BKE_editmesh_create(bm, false);
DerivedMesh *dm = CDDM_from_editbmesh(em, true, false);
MDisps *mdisps;
BMFace *f;
BMIter iter;
// int i = 0; // UNUSED
multires_set_space(dm, ob, from, to);
mdisps = CustomData_get_layer(&dm->loopData, CD_MDISPS);
BM_ITER_MESH (f, &iter, bm, BM_FACES_OF_MESH) {
BMLoop *l;
BMIter liter;
BM_ITER_ELEM (l, &liter, f, BM_LOOPS_OF_FACE) {
MDisps *lmd = CustomData_bmesh_get(&bm->ldata, l->head.data, CD_MDISPS);
if (!lmd->disps) {
printf("%s: warning - 'lmd->disps' == NULL\n", __func__);
}
if (lmd->disps && lmd->totdisp == mdisps->totdisp) {
memcpy(lmd->disps, mdisps->disps, sizeof(float) * 3 * lmd->totdisp);
}
else if (mdisps->disps) {
if (lmd->disps)
MEM_freeN(lmd->disps);
lmd->disps = MEM_dupallocN(mdisps->disps);
lmd->totdisp = mdisps->totdisp;
lmd->level = mdisps->level;
}
mdisps++;
// i += 1;
}
}
dm->needsFree = 1;
dm->release(dm);
/* setting this to NULL prevents BKE_editmesh_free from freeing it */
em->bm = NULL;
BKE_editmesh_free(em);
MEM_freeN(em);
}
}
/**
* \brief BMesh Begin Edit
*
* Functions for setting up a mesh for editing and cleaning up after
* the editing operations are done. These are called by the tools/operator
* API for each time a tool is executed.
*/
void bmesh_edit_begin(BMesh *UNUSED(bm), BMOpTypeFlag UNUSED(type_flag))
{
/* Most operators seem to be using BMO_OPTYPE_FLAG_UNTAN_MULTIRES to change the MDisps to
* absolute space during mesh edits. With this enabled, changes to the topology
* (loop cuts, edge subdivides, etc) are not reflected in the higher levels of
* the mesh at all, which doesn't seem right. Turning off completely for now,
* until this is shown to be better for certain types of mesh edits. */
#ifdef BMOP_UNTAN_MULTIRES_ENABLED
/* switch multires data out of tangent space */
if ((type_flag & BMO_OPTYPE_FLAG_UNTAN_MULTIRES) && CustomData_has_layer(&bm->ldata, CD_MDISPS)) {
bmesh_mdisps_space_set(bm, MULTIRES_SPACE_TANGENT, MULTIRES_SPACE_ABSOLUTE);
/* ensure correct normals, if possible */
bmesh_rationalize_normals(bm, 0);
BM_mesh_normals_update(bm);
}
#endif
}
/**
* \brief BMesh End Edit
*/
void bmesh_edit_end(BMesh *bm, BMOpTypeFlag type_flag)
{
ListBase select_history;
/* BMO_OPTYPE_FLAG_UNTAN_MULTIRES disabled for now, see comment above in bmesh_edit_begin. */
#ifdef BMOP_UNTAN_MULTIRES_ENABLED
/* switch multires data into tangent space */
if ((flag & BMO_OPTYPE_FLAG_UNTAN_MULTIRES) && CustomData_has_layer(&bm->ldata, CD_MDISPS)) {
/* set normals to their previous winding */
bmesh_rationalize_normals(bm, 1);
bmesh_mdisps_space_set(bm, MULTIRES_SPACE_ABSOLUTE, MULTIRES_SPACE_TANGENT);
}
else if (flag & BMO_OP_FLAG_RATIONALIZE_NORMALS) {
bmesh_rationalize_normals(bm, 1);
}
#endif
/* compute normals, clear temp flags and flush selections */
if (type_flag & BMO_OPTYPE_FLAG_NORMALS_CALC) {
BM_mesh_normals_update(bm);
}
if ((type_flag & BMO_OPTYPE_FLAG_SELECT_VALIDATE) == 0) {
select_history = bm->selected;
BLI_listbase_clear(&bm->selected);
}
if (type_flag & BMO_OPTYPE_FLAG_SELECT_FLUSH) {
BM_mesh_select_mode_flush(bm);
}
if ((type_flag & BMO_OPTYPE_FLAG_SELECT_VALIDATE) == 0) {
bm->selected = select_history;
}
}
void BM_mesh_elem_index_ensure(BMesh *bm, const char htype)
{
const char htype_needed = bm->elem_index_dirty & htype;
#ifdef DEBUG
BM_ELEM_INDEX_VALIDATE(bm, "Should Never Fail!", __func__);
#endif
if (htype_needed == 0) {
goto finally;
}
/* skip if we only need to operate on one element */
#pragma omp parallel sections if ((!ELEM(htype_needed, BM_VERT, BM_EDGE, BM_FACE, BM_LOOP, BM_FACE | BM_LOOP)) && \
(bm->totvert + bm->totedge + bm->totface >= BM_OMP_LIMIT))
{
#pragma omp section
{
if (htype & BM_VERT) {
if (bm->elem_index_dirty & BM_VERT) {
BMIter iter;
BMElem *ele;
int index;
BM_ITER_MESH_INDEX (ele, &iter, bm, BM_VERTS_OF_MESH, index) {
BM_elem_index_set(ele, index); /* set_ok */
}
BLI_assert(index == bm->totvert);
}
else {
// printf("%s: skipping vert index calc!\n", __func__);
}
}
}
#pragma omp section
{
if (htype & BM_EDGE) {
if (bm->elem_index_dirty & BM_EDGE) {
BMIter iter;
BMElem *ele;
int index;
BM_ITER_MESH_INDEX (ele, &iter, bm, BM_EDGES_OF_MESH, index) {
BM_elem_index_set(ele, index); /* set_ok */
}
BLI_assert(index == bm->totedge);
}
else {
// printf("%s: skipping edge index calc!\n", __func__);
}
}
}
#pragma omp section
{
if (htype & (BM_FACE | BM_LOOP)) {
if (bm->elem_index_dirty & (BM_FACE | BM_LOOP)) {
BMIter iter;
BMElem *ele;
const bool update_face = (htype & BM_FACE) && (bm->elem_index_dirty & BM_FACE);
const bool update_loop = (htype & BM_LOOP) && (bm->elem_index_dirty & BM_LOOP);
int index;
int index_loop = 0;
BM_ITER_MESH_INDEX (ele, &iter, bm, BM_FACES_OF_MESH, index) {
if (update_face) {
BM_elem_index_set(ele, index); /* set_ok */
}
if (update_loop) {
BMLoop *l_iter, *l_first;
l_iter = l_first = BM_FACE_FIRST_LOOP((BMFace *)ele);
do {
BM_elem_index_set(l_iter, index_loop++); /* set_ok */
} while ((l_iter = l_iter->next) != l_first);
}
}
BLI_assert(index == bm->totface);
if (update_loop) {
BLI_assert(index_loop == bm->totloop);
}
}
else {
// printf("%s: skipping face/loop index calc!\n", __func__);
}
}
}
}
finally:
bm->elem_index_dirty &= ~htype;
}
/**
* Array checking/setting macros
*
* Currently vert/edge/loop/face index data is being abused, in a few areas of the code.
*
* To avoid correcting them afterwards, set 'bm->elem_index_dirty' however its possible
* this flag is set incorrectly which could crash blender.
*
* These functions ensure its correct and are called more often in debug mode.
*/
void BM_mesh_elem_index_validate(
BMesh *bm, const char *location, const char *func,
const char *msg_a, const char *msg_b)
{
const char iter_types[3] = {BM_VERTS_OF_MESH,
BM_EDGES_OF_MESH,
BM_FACES_OF_MESH};
const char flag_types[3] = {BM_VERT, BM_EDGE, BM_FACE};
const char *type_names[3] = {"vert", "edge", "face"};
BMIter iter;
BMElem *ele;
int i;
bool is_any_error = 0;
for (i = 0; i < 3; i++) {
const bool is_dirty = (flag_types[i] & bm->elem_index_dirty) != 0;
int index = 0;
bool is_error = false;
int err_val = 0;
int err_idx = 0;
BM_ITER_MESH (ele, &iter, bm, iter_types[i]) {
if (!is_dirty) {
if (BM_elem_index_get(ele) != index) {
err_val = BM_elem_index_get(ele);
err_idx = index;
is_error = true;
}
}
BM_elem_index_set(ele, index); /* set_ok */
index++;
}
if ((is_error == true) && (is_dirty == false)) {
is_any_error = true;
fprintf(stderr,
"Invalid Index: at %s, %s, %s[%d] invalid index %d, '%s', '%s'\n",
location, func, type_names[i], err_idx, err_val, msg_a, msg_b);
}
else if ((is_error == false) && (is_dirty == true)) {
#if 0 /* mostly annoying */
/* dirty may have been incorrectly set */
fprintf(stderr,
"Invalid Dirty: at %s, %s (%s), dirty flag was set but all index values are correct, '%s', '%s'\n",
location, func, type_names[i], msg_a, msg_b);
#endif
}
}
#if 0 /* mostly annoying, even in debug mode */
#ifdef DEBUG
if (is_any_error == 0) {
fprintf(stderr,
"Valid Index Success: at %s, %s, '%s', '%s'\n",
location, func, msg_a, msg_b);
}
#endif
#endif
(void) is_any_error; /* shut up the compiler */
}
/* debug check only - no need to optimize */
#ifndef NDEBUG
bool BM_mesh_elem_table_check(BMesh *bm)
{
BMIter iter;
BMElem *ele;
int i;
if (bm->vtable && ((bm->elem_table_dirty & BM_VERT) == 0)) {
BM_ITER_MESH_INDEX (ele, &iter, bm, BM_VERTS_OF_MESH, i) {
if (ele != (BMElem *)bm->vtable[i]) {
return false;
}
}
}
if (bm->etable && ((bm->elem_table_dirty & BM_EDGE) == 0)) {
BM_ITER_MESH_INDEX (ele, &iter, bm, BM_EDGES_OF_MESH, i) {
if (ele != (BMElem *)bm->etable[i]) {
return false;
}
}
}
if (bm->ftable && ((bm->elem_table_dirty & BM_FACE) == 0)) {
BM_ITER_MESH_INDEX (ele, &iter, bm, BM_FACES_OF_MESH, i) {
if (ele != (BMElem *)bm->ftable[i]) {
return false;
}
}
}
return true;
}
#endif
void BM_mesh_elem_table_ensure(BMesh *bm, const char htype)
{
/* assume if the array is non-null then its valid and no need to recalc */
const char htype_needed = (((bm->vtable && ((bm->elem_table_dirty & BM_VERT) == 0)) ? 0 : BM_VERT) |
((bm->etable && ((bm->elem_table_dirty & BM_EDGE) == 0)) ? 0 : BM_EDGE) |
((bm->ftable && ((bm->elem_table_dirty & BM_FACE) == 0)) ? 0 : BM_FACE)) & htype;
BLI_assert((htype & ~BM_ALL_NOLOOP) == 0);
/* in debug mode double check we didn't need to recalculate */
BLI_assert(BM_mesh_elem_table_check(bm) == true);
if (htype_needed == 0) {
goto finally;
}
if (htype_needed & BM_VERT) {
if (bm->vtable && bm->totvert <= bm->vtable_tot && bm->totvert * 2 >= bm->vtable_tot) {
/* pass (re-use the array) */
}
else {
if (bm->vtable)
MEM_freeN(bm->vtable);
bm->vtable = MEM_mallocN(sizeof(void **) * bm->totvert, "bm->vtable");
bm->vtable_tot = bm->totvert;
}
}
if (htype_needed & BM_EDGE) {
if (bm->etable && bm->totedge <= bm->etable_tot && bm->totedge * 2 >= bm->etable_tot) {
/* pass (re-use the array) */
}
else {
if (bm->etable)
MEM_freeN(bm->etable);
bm->etable = MEM_mallocN(sizeof(void **) * bm->totedge, "bm->etable");
bm->etable_tot = bm->totedge;
}
}
if (htype_needed & BM_FACE) {
if (bm->ftable && bm->totface <= bm->ftable_tot && bm->totface * 2 >= bm->ftable_tot) {
/* pass (re-use the array) */
}
else {
if (bm->ftable)
MEM_freeN(bm->ftable);
bm->ftable = MEM_mallocN(sizeof(void **) * bm->totface, "bm->ftable");
bm->ftable_tot = bm->totface;
}
}
/* skip if we only need to operate on one element */
#pragma omp parallel sections if ((!ELEM(htype_needed, BM_VERT, BM_EDGE, BM_FACE)) && \
(bm->totvert + bm->totedge + bm->totface >= BM_OMP_LIMIT))
{
#pragma omp section
{
if (htype_needed & BM_VERT) {
BM_iter_as_array(bm, BM_VERTS_OF_MESH, NULL, (void **)bm->vtable, bm->totvert);
}
}
#pragma omp section
{
if (htype_needed & BM_EDGE) {
BM_iter_as_array(bm, BM_EDGES_OF_MESH, NULL, (void **)bm->etable, bm->totedge);
}
}
#pragma omp section
{
if (htype_needed & BM_FACE) {
BM_iter_as_array(bm, BM_FACES_OF_MESH, NULL, (void **)bm->ftable, bm->totface);
}
}
}
finally:
/* Only clear dirty flags when all the pointers and data are actually valid.
* This prevents possible threading issues when dirty flag check failed but
* data wasn't ready still.
*/
bm->elem_table_dirty &= ~htype_needed;
}
/* use BM_mesh_elem_table_ensure where possible to avoid full rebuild */
void BM_mesh_elem_table_init(BMesh *bm, const char htype)
{
BLI_assert((htype & ~BM_ALL_NOLOOP) == 0);
/* force recalc */
BM_mesh_elem_table_free(bm, BM_ALL_NOLOOP);
BM_mesh_elem_table_ensure(bm, htype);
}
void BM_mesh_elem_table_free(BMesh *bm, const char htype)
{
if (htype & BM_VERT) {
MEM_SAFE_FREE(bm->vtable);
}
if (htype & BM_EDGE) {
MEM_SAFE_FREE(bm->etable);
}
if (htype & BM_FACE) {
MEM_SAFE_FREE(bm->ftable);
}
}
BMVert *BM_vert_at_index(BMesh *bm, const int index)
{
BLI_assert((index >= 0) && (index < bm->totvert));
BLI_assert((bm->elem_table_dirty & BM_VERT) == 0);
return bm->vtable[index];
}
BMEdge *BM_edge_at_index(BMesh *bm, const int index)
{
BLI_assert((index >= 0) && (index < bm->totedge));
BLI_assert((bm->elem_table_dirty & BM_EDGE) == 0);
return bm->etable[index];
}
BMFace *BM_face_at_index(BMesh *bm, const int index)
{
BLI_assert((index >= 0) && (index < bm->totface));
BLI_assert((bm->elem_table_dirty & BM_FACE) == 0);
return bm->ftable[index];
}
BMVert *BM_vert_at_index_find(BMesh *bm, const int index)
{
return BLI_mempool_findelem(bm->vpool, index);
}
BMEdge *BM_edge_at_index_find(BMesh *bm, const int index)
{
return BLI_mempool_findelem(bm->epool, index);
}
BMFace *BM_face_at_index_find(BMesh *bm, const int index)
{
return BLI_mempool_findelem(bm->fpool, index);
}
/**
* Use lookup table when available, else use slower find functions.
*
* \note Try to use #BM_mesh_elem_table_ensure instead.
*/
BMVert *BM_vert_at_index_find_or_table(BMesh *bm, const int index)
{
if ((bm->elem_table_dirty & BM_VERT) == 0) {
return (index < bm->totvert) ? bm->vtable[index] : NULL;
}
else {
return BM_vert_at_index_find(bm, index);
}
}
BMEdge *BM_edge_at_index_find_or_table(BMesh *bm, const int index)
{
if ((bm->elem_table_dirty & BM_EDGE) == 0) {
return (index < bm->totedge) ? bm->etable[index] : NULL;
}
else {
return BM_edge_at_index_find(bm, index);
}
}
BMFace *BM_face_at_index_find_or_table(BMesh *bm, const int index)
{
if ((bm->elem_table_dirty & BM_FACE) == 0) {
return (index < bm->totface) ? bm->ftable[index] : NULL;
}
else {
return BM_face_at_index_find(bm, index);
}
}
/**
* Return the amount of element of type 'type' in a given bmesh.
*/
int BM_mesh_elem_count(BMesh *bm, const char htype)
{
BLI_assert((htype & ~BM_ALL_NOLOOP) == 0);
switch (htype) {
case BM_VERT: return bm->totvert;
case BM_EDGE: return bm->totedge;
case BM_FACE: return bm->totface;
default:
{
BLI_assert(0);
return 0;
}
}
}
/**
* Remaps the vertices, edges and/or faces of the bmesh as indicated by vert/edge/face_idx arrays
* (xxx_idx[org_index] = new_index).
*
* A NULL array means no changes.
*
* Note: - Does not mess with indices, just sets elem_index_dirty flag.
* - For verts/edges/faces only (as loops must remain "ordered" and "aligned"
* on a per-face basis...).
*
* WARNING: Be careful if you keep pointers to affected BM elements, or arrays, when using this func!
*/
void BM_mesh_remap(
BMesh *bm,
const uint *vert_idx,
const uint *edge_idx,
const uint *face_idx)
{
/* Mapping old to new pointers. */
GHash *vptr_map = NULL, *eptr_map = NULL, *fptr_map = NULL;
BMIter iter, iterl;
BMVert *ve;
BMEdge *ed;
BMFace *fa;
BMLoop *lo;
if (!(vert_idx || edge_idx || face_idx))
return;
BM_mesh_elem_table_ensure(
bm,
(vert_idx ? BM_VERT : 0) |
(edge_idx ? BM_EDGE : 0) |
(face_idx ? BM_FACE : 0));
/* Remap Verts */
if (vert_idx) {
BMVert **verts_pool, *verts_copy, **vep;
int i, totvert = bm->totvert;
const uint *new_idx;
/* Special case: Python uses custom - data layers to hold PyObject references.
* These have to be kept in - place, else the PyObject's we point to, wont point back to us. */
const int cd_vert_pyptr = CustomData_get_offset(&bm->vdata, CD_BM_ELEM_PYPTR);
/* Init the old-to-new vert pointers mapping */
vptr_map = BLI_ghash_ptr_new_ex("BM_mesh_remap vert pointers mapping", bm->totvert);
/* Make a copy of all vertices. */
verts_pool = bm->vtable;
verts_copy = MEM_mallocN(sizeof(BMVert) * totvert, "BM_mesh_remap verts copy");
void **pyptrs = (cd_vert_pyptr != -1) ? MEM_mallocN(sizeof(void *) * totvert, __func__) : NULL;
for (i = totvert, ve = verts_copy + totvert - 1, vep = verts_pool + totvert - 1; i--; ve--, vep--) {
*ve = **vep;
/* printf("*vep: %p, verts_pool[%d]: %p\n", *vep, i, verts_pool[i]);*/
if (cd_vert_pyptr != -1) {
void **pyptr = BM_ELEM_CD_GET_VOID_P(((BMElem *)ve), cd_vert_pyptr);
pyptrs[i] = *pyptr;
}
}
/* Copy back verts to their new place, and update old2new pointers mapping. */
new_idx = vert_idx + totvert - 1;
ve = verts_copy + totvert - 1;
vep = verts_pool + totvert - 1; /* old, org pointer */
for (i = totvert; i--; new_idx--, ve--, vep--) {
BMVert *new_vep = verts_pool[*new_idx];
*new_vep = *ve;
/* printf("mapping vert from %d to %d (%p/%p to %p)\n", i, *new_idx, *vep, verts_pool[i], new_vep);*/
BLI_ghash_insert(vptr_map, *vep, new_vep);
if (cd_vert_pyptr != -1) {
void **pyptr = BM_ELEM_CD_GET_VOID_P(((BMElem *)new_vep), cd_vert_pyptr);
*pyptr = pyptrs[*new_idx];
}
}
bm->elem_index_dirty |= BM_VERT;
bm->elem_table_dirty |= BM_VERT;
MEM_freeN(verts_copy);
if (pyptrs) {
MEM_freeN(pyptrs);
}
}
/* Remap Edges */
if (edge_idx) {
BMEdge **edges_pool, *edges_copy, **edp;
int i, totedge = bm->totedge;
const uint *new_idx;
/* Special case: Python uses custom - data layers to hold PyObject references.
* These have to be kept in - place, else the PyObject's we point to, wont point back to us. */
const int cd_edge_pyptr = CustomData_get_offset(&bm->edata, CD_BM_ELEM_PYPTR);
/* Init the old-to-new vert pointers mapping */
eptr_map = BLI_ghash_ptr_new_ex("BM_mesh_remap edge pointers mapping", bm->totedge);
/* Make a copy of all vertices. */
edges_pool = bm->etable;
edges_copy = MEM_mallocN(sizeof(BMEdge) * totedge, "BM_mesh_remap edges copy");
void **pyptrs = (cd_edge_pyptr != -1) ? MEM_mallocN(sizeof(void *) * totedge, __func__) : NULL;
for (i = totedge, ed = edges_copy + totedge - 1, edp = edges_pool + totedge - 1; i--; ed--, edp--) {
*ed = **edp;
if (cd_edge_pyptr != -1) {
void **pyptr = BM_ELEM_CD_GET_VOID_P(((BMElem *)ed), cd_edge_pyptr);
pyptrs[i] = *pyptr;
}
}
/* Copy back verts to their new place, and update old2new pointers mapping. */
new_idx = edge_idx + totedge - 1;
ed = edges_copy + totedge - 1;
edp = edges_pool + totedge - 1; /* old, org pointer */
for (i = totedge; i--; new_idx--, ed--, edp--) {
BMEdge *new_edp = edges_pool[*new_idx];
*new_edp = *ed;
BLI_ghash_insert(eptr_map, *edp, new_edp);
/* printf("mapping edge from %d to %d (%p/%p to %p)\n", i, *new_idx, *edp, edges_pool[i], new_edp);*/
if (cd_edge_pyptr != -1) {
void **pyptr = BM_ELEM_CD_GET_VOID_P(((BMElem *)new_edp), cd_edge_pyptr);
*pyptr = pyptrs[*new_idx];
}
}
bm->elem_index_dirty |= BM_EDGE;
bm->elem_table_dirty |= BM_EDGE;
MEM_freeN(edges_copy);
if (pyptrs) {
MEM_freeN(pyptrs);
}
}
/* Remap Faces */
if (face_idx) {
BMFace **faces_pool, *faces_copy, **fap;
int i, totface = bm->totface;
const uint *new_idx;
/* Special case: Python uses custom - data layers to hold PyObject references.
* These have to be kept in - place, else the PyObject's we point to, wont point back to us. */
const int cd_poly_pyptr = CustomData_get_offset(&bm->pdata, CD_BM_ELEM_PYPTR);
/* Init the old-to-new vert pointers mapping */
fptr_map = BLI_ghash_ptr_new_ex("BM_mesh_remap face pointers mapping", bm->totface);
/* Make a copy of all vertices. */
faces_pool = bm->ftable;
faces_copy = MEM_mallocN(sizeof(BMFace) * totface, "BM_mesh_remap faces copy");
void **pyptrs = (cd_poly_pyptr != -1) ? MEM_mallocN(sizeof(void *) * totface, __func__) : NULL;
for (i = totface, fa = faces_copy + totface - 1, fap = faces_pool + totface - 1; i--; fa--, fap--) {
*fa = **fap;
if (cd_poly_pyptr != -1) {
void **pyptr = BM_ELEM_CD_GET_VOID_P(((BMElem *)fa), cd_poly_pyptr);
pyptrs[i] = *pyptr;
}
}
/* Copy back verts to their new place, and update old2new pointers mapping. */
new_idx = face_idx + totface - 1;
fa = faces_copy + totface - 1;
fap = faces_pool + totface - 1; /* old, org pointer */
for (i = totface; i--; new_idx--, fa--, fap--) {
BMFace *new_fap = faces_pool[*new_idx];
*new_fap = *fa;
BLI_ghash_insert(fptr_map, *fap, new_fap);
if (cd_poly_pyptr != -1) {
void **pyptr = BM_ELEM_CD_GET_VOID_P(((BMElem *)new_fap), cd_poly_pyptr);
*pyptr = pyptrs[*new_idx];
}
}
bm->elem_index_dirty |= BM_FACE | BM_LOOP;
bm->elem_table_dirty |= BM_FACE;
MEM_freeN(faces_copy);
if (pyptrs) {
MEM_freeN(pyptrs);
}
}
/* And now, fix all vertices/edges/faces/loops pointers! */
/* Verts' pointers, only edge pointers... */
if (eptr_map) {
BM_ITER_MESH (ve, &iter, bm, BM_VERTS_OF_MESH) {
/* printf("Vert e: %p -> %p\n", ve->e, BLI_ghash_lookup(eptr_map, ve->e));*/
if (ve->e) {
ve->e = BLI_ghash_lookup(eptr_map, ve->e);
BLI_assert(ve->e);
}
}
}
/* Edges' pointers, only vert pointers (as we don't mess with loops!), and - ack! - edge pointers,
* as we have to handle disklinks... */
if (vptr_map || eptr_map) {
BM_ITER_MESH (ed, &iter, bm, BM_EDGES_OF_MESH) {
if (vptr_map) {
/* printf("Edge v1: %p -> %p\n", ed->v1, BLI_ghash_lookup(vptr_map, ed->v1));*/
/* printf("Edge v2: %p -> %p\n", ed->v2, BLI_ghash_lookup(vptr_map, ed->v2));*/
ed->v1 = BLI_ghash_lookup(vptr_map, ed->v1);
ed->v2 = BLI_ghash_lookup(vptr_map, ed->v2);
BLI_assert(ed->v1);
BLI_assert(ed->v2);
}
if (eptr_map) {
/* printf("Edge v1_disk_link prev: %p -> %p\n", ed->v1_disk_link.prev,*/
/* BLI_ghash_lookup(eptr_map, ed->v1_disk_link.prev));*/
/* printf("Edge v1_disk_link next: %p -> %p\n", ed->v1_disk_link.next,*/
/* BLI_ghash_lookup(eptr_map, ed->v1_disk_link.next));*/
/* printf("Edge v2_disk_link prev: %p -> %p\n", ed->v2_disk_link.prev,*/
/* BLI_ghash_lookup(eptr_map, ed->v2_disk_link.prev));*/
/* printf("Edge v2_disk_link next: %p -> %p\n", ed->v2_disk_link.next,*/
/* BLI_ghash_lookup(eptr_map, ed->v2_disk_link.next));*/
ed->v1_disk_link.prev = BLI_ghash_lookup(eptr_map, ed->v1_disk_link.prev);
ed->v1_disk_link.next = BLI_ghash_lookup(eptr_map, ed->v1_disk_link.next);
ed->v2_disk_link.prev = BLI_ghash_lookup(eptr_map, ed->v2_disk_link.prev);
ed->v2_disk_link.next = BLI_ghash_lookup(eptr_map, ed->v2_disk_link.next);
BLI_assert(ed->v1_disk_link.prev);
BLI_assert(ed->v1_disk_link.next);
BLI_assert(ed->v2_disk_link.prev);
BLI_assert(ed->v2_disk_link.next);
}
}
}
/* Faces' pointers (loops, in fact), always needed... */
BM_ITER_MESH (fa, &iter, bm, BM_FACES_OF_MESH) {
BM_ITER_ELEM (lo, &iterl, fa, BM_LOOPS_OF_FACE) {
if (vptr_map) {
/* printf("Loop v: %p -> %p\n", lo->v, BLI_ghash_lookup(vptr_map, lo->v));*/
lo->v = BLI_ghash_lookup(vptr_map, lo->v);
BLI_assert(lo->v);
}
if (eptr_map) {
/* printf("Loop e: %p -> %p\n", lo->e, BLI_ghash_lookup(eptr_map, lo->e));*/
lo->e = BLI_ghash_lookup(eptr_map, lo->e);
BLI_assert(lo->e);
}
if (fptr_map) {
/* printf("Loop f: %p -> %p\n", lo->f, BLI_ghash_lookup(fptr_map, lo->f));*/
lo->f = BLI_ghash_lookup(fptr_map, lo->f);
BLI_assert(lo->f);
}
}
}
/* Selection history */
{
BMEditSelection *ese;
for (ese = bm->selected.first; ese; ese = ese->next) {
switch (ese->htype) {
case BM_VERT:
if (vptr_map) {
ese->ele = BLI_ghash_lookup(vptr_map, ese->ele);
BLI_assert(ese->ele);
}
break;
case BM_EDGE:
if (eptr_map) {
ese->ele = BLI_ghash_lookup(eptr_map, ese->ele);
BLI_assert(ese->ele);
}
break;
case BM_FACE:
if (fptr_map) {
ese->ele = BLI_ghash_lookup(fptr_map, ese->ele);
BLI_assert(ese->ele);
}
break;
}
}
}
if (fptr_map) {
if (bm->act_face) {
bm->act_face = BLI_ghash_lookup(fptr_map, bm->act_face);
BLI_assert(bm->act_face);
}
}
if (vptr_map)
BLI_ghash_free(vptr_map, NULL, NULL);
if (eptr_map)
BLI_ghash_free(eptr_map, NULL, NULL);
if (fptr_map)
BLI_ghash_free(fptr_map, NULL, NULL);
}
/**
* Use new memory pools for this mesh.
*
* \note needed for re-sizing elements (adding/removing tool flags)
* but could also be used for packing fragmented bmeshes.
*/
void BM_mesh_rebuild(
BMesh *bm, const struct BMeshCreateParams *params,
BLI_mempool *vpool_dst, BLI_mempool *epool_dst, BLI_mempool *lpool_dst, BLI_mempool *fpool_dst)
{
const char remap =
(vpool_dst ? BM_VERT : 0) |
(epool_dst ? BM_EDGE : 0) |
(lpool_dst ? BM_LOOP : 0) |
(fpool_dst ? BM_FACE : 0);
BMVert **vtable_dst = (remap & BM_VERT) ? MEM_mallocN(bm->totvert * sizeof(BMVert *), __func__) : NULL;
BMEdge **etable_dst = (remap & BM_EDGE) ? MEM_mallocN(bm->totedge * sizeof(BMEdge *), __func__) : NULL;
BMLoop **ltable_dst = (remap & BM_LOOP) ? MEM_mallocN(bm->totloop * sizeof(BMLoop *), __func__) : NULL;
BMFace **ftable_dst = (remap & BM_FACE) ? MEM_mallocN(bm->totface * sizeof(BMFace *), __func__) : NULL;
const bool use_toolflags = params->use_toolflags;
if (remap & BM_VERT) {
BMIter iter;
int index;
BMVert *v_src;
BM_ITER_MESH_INDEX (v_src, &iter, bm, BM_VERTS_OF_MESH, index) {
BMVert *v_dst = BLI_mempool_alloc(vpool_dst);
memcpy(v_dst, v_src, sizeof(BMVert));
if (use_toolflags) {
((BMVert_OFlag *)v_dst)->oflags = bm->vtoolflagpool ? BLI_mempool_calloc(bm->vtoolflagpool) : NULL;
}
vtable_dst[index] = v_dst;
BM_elem_index_set(v_src, index); /* set_ok */
}
}
if (remap & BM_EDGE) {
BMIter iter;
int index;
BMEdge *e_src;
BM_ITER_MESH_INDEX (e_src, &iter, bm, BM_EDGES_OF_MESH, index) {
BMEdge *e_dst = BLI_mempool_alloc(epool_dst);
memcpy(e_dst, e_src, sizeof(BMEdge));
if (use_toolflags) {
((BMEdge_OFlag *)e_dst)->oflags = bm->etoolflagpool ? BLI_mempool_calloc(bm->etoolflagpool) : NULL;
}
etable_dst[index] = e_dst;
BM_elem_index_set(e_src, index); /* set_ok */
}
}
if (remap & (BM_LOOP | BM_FACE)) {
BMIter iter;
int index, index_loop = 0;
BMFace *f_src;
BM_ITER_MESH_INDEX (f_src, &iter, bm, BM_FACES_OF_MESH, index) {
if (remap & BM_FACE) {
BMFace *f_dst = BLI_mempool_alloc(fpool_dst);
memcpy(f_dst, f_src, sizeof(BMFace));
if (use_toolflags) {
((BMFace_OFlag *)f_dst)->oflags = bm->ftoolflagpool ? BLI_mempool_calloc(bm->ftoolflagpool) : NULL;
}
ftable_dst[index] = f_dst;
BM_elem_index_set(f_src, index); /* set_ok */
}
/* handle loops */
if (remap & BM_LOOP) {
BMLoop *l_iter_src, *l_first_src;
l_iter_src = l_first_src = BM_FACE_FIRST_LOOP((BMFace *)f_src);
do {
BMLoop *l_dst = BLI_mempool_alloc(lpool_dst);
memcpy(l_dst, l_iter_src, sizeof(BMLoop));
ltable_dst[index_loop] = l_dst;
BM_elem_index_set(l_iter_src, index_loop++); /* set_ok */
} while ((l_iter_src = l_iter_src->next) != l_first_src);
}
}
}
#define MAP_VERT(ele) vtable_dst[BM_elem_index_get(ele)]
#define MAP_EDGE(ele) etable_dst[BM_elem_index_get(ele)]
#define MAP_LOOP(ele) ltable_dst[BM_elem_index_get(ele)]
#define MAP_FACE(ele) ftable_dst[BM_elem_index_get(ele)]
#define REMAP_VERT(ele) { if (remap & BM_VERT) { ele = MAP_VERT(ele); }} ((void)0)
#define REMAP_EDGE(ele) { if (remap & BM_EDGE) { ele = MAP_EDGE(ele); }} ((void)0)
#define REMAP_LOOP(ele) { if (remap & BM_LOOP) { ele = MAP_LOOP(ele); }} ((void)0)
#define REMAP_FACE(ele) { if (remap & BM_FACE) { ele = MAP_FACE(ele); }} ((void)0)
/* verts */
{
for (int i = 0; i < bm->totvert; i++) {
BMVert *v = vtable_dst[i];
if (v->e) {
REMAP_EDGE(v->e);
}
}
}
/* edges */
{
for (int i = 0; i < bm->totedge; i++) {
BMEdge *e = etable_dst[i];
REMAP_VERT(e->v1);
REMAP_VERT(e->v2);
REMAP_EDGE(e->v1_disk_link.next);
REMAP_EDGE(e->v1_disk_link.prev);
REMAP_EDGE(e->v2_disk_link.next);
REMAP_EDGE(e->v2_disk_link.prev);
if (e->l) {
REMAP_LOOP(e->l);
}
}
}
/* faces */
{
for (int i = 0; i < bm->totface; i++) {
BMFace *f = ftable_dst[i];
REMAP_LOOP(f->l_first);
{
BMLoop *l_iter, *l_first;
l_iter = l_first = BM_FACE_FIRST_LOOP((BMFace *)f);
do {
REMAP_VERT(l_iter->v);
REMAP_EDGE(l_iter->e);
REMAP_FACE(l_iter->f);
REMAP_LOOP(l_iter->radial_next);
REMAP_LOOP(l_iter->radial_prev);
REMAP_LOOP(l_iter->next);
REMAP_LOOP(l_iter->prev);
} while ((l_iter = l_iter->next) != l_first);
}
}
}
for (BMEditSelection *ese = bm->selected.first; ese; ese = ese->next) {
switch (ese->htype) {
case BM_VERT:
if (remap & BM_VERT) {
ese->ele = (BMElem *)MAP_VERT(ese->ele);
}
break;
case BM_EDGE:
if (remap & BM_EDGE) {
ese->ele = (BMElem *)MAP_EDGE(ese->ele);
}
break;
case BM_FACE:
if (remap & BM_FACE) {
ese->ele = (BMElem *)MAP_FACE(ese->ele);
}
break;
}
}
if (bm->act_face) {
REMAP_FACE(bm->act_face);
}
#undef MAP_VERT
#undef MAP_EDGE
#undef MAP_LOOP
#undef MAP_EDGE
#undef REMAP_VERT
#undef REMAP_EDGE
#undef REMAP_LOOP
#undef REMAP_EDGE
/* Cleanup, re-use local tables if the current mesh had tables allocated.
* could use irrespective but it may use more memory then the caller wants (and not be needed). */
if (remap & BM_VERT) {
if (bm->vtable) {
SWAP(BMVert **, vtable_dst, bm->vtable);
bm->vtable_tot = bm->totvert;
bm->elem_table_dirty &= ~BM_VERT;
}
MEM_freeN(vtable_dst);
BLI_mempool_destroy(bm->vpool);
bm->vpool = vpool_dst;
}
if (remap & BM_EDGE) {
if (bm->etable) {
SWAP(BMEdge **, etable_dst, bm->etable);
bm->etable_tot = bm->totedge;
bm->elem_table_dirty &= ~BM_EDGE;
}
MEM_freeN(etable_dst);
BLI_mempool_destroy(bm->epool);
bm->epool = epool_dst;
}
if (remap & BM_LOOP) {
/* no loop table */
MEM_freeN(ltable_dst);
BLI_mempool_destroy(bm->lpool);
bm->lpool = lpool_dst;
}
if (remap & BM_FACE) {
if (bm->ftable) {
SWAP(BMFace **, ftable_dst, bm->ftable);
bm->ftable_tot = bm->totface;
bm->elem_table_dirty &= ~BM_FACE;
}
MEM_freeN(ftable_dst);
BLI_mempool_destroy(bm->fpool);
bm->fpool = fpool_dst;
}
}
/**
* Re-allocates mesh data with/without toolflags.
*/
void BM_mesh_toolflags_set(BMesh *bm, bool use_toolflags)
{
if (bm->use_toolflags == use_toolflags) {
return;
}
const BMAllocTemplate allocsize = BMALLOC_TEMPLATE_FROM_BM(bm);
BLI_mempool *vpool_dst = NULL;
BLI_mempool *epool_dst = NULL;
BLI_mempool *fpool_dst = NULL;
bm_mempool_init_ex(
&allocsize, use_toolflags,
&vpool_dst, &epool_dst, NULL, &fpool_dst);
if (use_toolflags == false) {
BLI_mempool_destroy(bm->vtoolflagpool);
BLI_mempool_destroy(bm->etoolflagpool);
BLI_mempool_destroy(bm->ftoolflagpool);
bm->vtoolflagpool = NULL;
bm->etoolflagpool = NULL;
bm->ftoolflagpool = NULL;
}
BM_mesh_rebuild(
bm,
&((struct BMeshCreateParams){.use_toolflags = use_toolflags,}),
vpool_dst, epool_dst, NULL, fpool_dst);
bm->use_toolflags = use_toolflags;
}
|
ompmybarrier.c | #include <stdio.h>
#include <stdlib.h>
#include <omp.h>
int main(int argc, char* argv[]) {
int counter;
const int n = 16;
int id;
#pragma omp parallel private(counter, id)
{
id = omp_get_thread_num();
for(counter = 0; counter < n; counter++) {
#pragma omp barrier
printf("%d Performing iteration %d\n", id, counter);
fflush(stdout);
#pragma omp barrier
}
}
}
|
GB_unop__exp2_fc32_fc32.c | //------------------------------------------------------------------------------
// GB_unop: hard-coded functions for each built-in unary operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2021, All Rights Reserved.
// SPDX-License-Identifier: Apache-2.0
//------------------------------------------------------------------------------
// If this file is in the Generated/ folder, do not edit it (auto-generated).
#include "GB.h"
#ifndef GBCOMPACT
#include "GB_control.h"
#include "GB_atomics.h"
#include "GB_unop__include.h"
// C=unop(A) is defined by the following types and operators:
// op(A) function: GB (_unop_apply__exp2_fc32_fc32)
// op(A') function: GB (_unop_tran__exp2_fc32_fc32)
// C type: GxB_FC32_t
// A type: GxB_FC32_t
// cast: GxB_FC32_t cij = aij
// unaryop: cij = GB_cexp2f (aij)
#define GB_ATYPE \
GxB_FC32_t
#define GB_CTYPE \
GxB_FC32_t
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA) \
GxB_FC32_t aij = Ax [pA]
#define GB_CX(p) Cx [p]
// unary operator
#define GB_OP(z, x) \
z = GB_cexp2f (x) ;
// casting
#define GB_CAST(z, aij) \
GxB_FC32_t z = aij ;
// cij = op (aij)
#define GB_CAST_OP(pC,pA) \
{ \
/* aij = Ax [pA] */ \
GxB_FC32_t aij = Ax [pA] ; \
/* Cx [pC] = op (cast (aij)) */ \
GxB_FC32_t z = aij ; \
Cx [pC] = GB_cexp2f (z) ; \
}
// true if operator is the identity op with no typecasting
#define GB_OP_IS_IDENTITY_WITH_NO_TYPECAST \
0
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_EXP2 || GxB_NO_FC32)
//------------------------------------------------------------------------------
// Cx = op (cast (Ax)): apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB (_unop_apply__exp2_fc32_fc32)
(
GxB_FC32_t *Cx, // Cx and Ax may be aliased
const GxB_FC32_t *Ax,
const int8_t *restrict Ab, // A->b if A is bitmap
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t p ;
// TODO: if OP is ONE and uniform-valued matrices are exploited, then
// do this in O(1) time
if (Ab == NULL)
{
#if ( GB_OP_IS_IDENTITY_WITH_NO_TYPECAST )
GB_memcpy (Cx, Ax, anz * sizeof (GxB_FC32_t), nthreads) ;
#else
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
GxB_FC32_t aij = Ax [p] ;
GxB_FC32_t z = aij ;
Cx [p] = GB_cexp2f (z) ;
}
#endif
}
else
{
// bitmap case, no transpose; A->b already memcpy'd into C->b
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
if (!Ab [p]) continue ;
GxB_FC32_t aij = Ax [p] ;
GxB_FC32_t z = aij ;
Cx [p] = GB_cexp2f (z) ;
}
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (cast (A')): transpose, typecast, and apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB (_unop_tran__exp2_fc32_fc32)
(
GrB_Matrix C,
const GrB_Matrix A,
int64_t *restrict *Workspaces,
const int64_t *restrict A_slice,
int nworkspaces,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
omp_reduce.c | /*
* Full CI
*/
#include <stdlib.h>
#include <complex.h>
#include "config.h"
void NPomp_dsum_reduce_inplace(double **vec, size_t count)
{
unsigned int nthreads = omp_get_num_threads();
unsigned int thread_id = omp_get_thread_num();
unsigned int bit, thread_src;
unsigned int mask = 0;
double *dst = vec[thread_id];
double *src;
size_t i;
#pragma omp barrier
for (bit = 0; (1<<bit) < nthreads; bit++) {
mask |= 1 << bit;
if (!(thread_id & mask)) {
thread_src = thread_id | (1<<bit);
if (thread_src < nthreads) {
src = vec[thread_src];
for (i = 0; i < count; i++) {
dst[i] += src[i];
}
}
}
#pragma omp barrier
}
}
void NPomp_dprod_reduce_inplace(double **vec, size_t count)
{
unsigned int nthreads = omp_get_num_threads();
unsigned int thread_id = omp_get_thread_num();
unsigned int bit, thread_src;
unsigned int mask = 0;
double *dst = vec[thread_id];
double *src;
size_t i;
#pragma omp barrier
for (bit = 0; (1<<bit) < nthreads; bit++) {
mask |= 1 << bit;
if (!(thread_id & mask)) {
thread_src = thread_id | (1<<bit);
if (thread_src < nthreads) {
src = vec[thread_src];
for (i = 0; i < count; i++) {
dst[i] *= src[i];
}
}
}
#pragma omp barrier
}
}
void NPomp_zsum_reduce_inplace(double complex **vec, size_t count)
{
unsigned int nthreads = omp_get_num_threads();
unsigned int thread_id = omp_get_thread_num();
unsigned int bit, thread_src;
unsigned int mask = 0;
double complex *dst = vec[thread_id];
double complex *src;
size_t i;
#pragma omp barrier
for (bit = 0; (1<<bit) < nthreads; bit++) {
mask |= 1 << bit;
if (!(thread_id & mask)) {
thread_src = thread_id | (1<<bit);
if (thread_src < nthreads) {
src = vec[thread_src];
for (i = 0; i < count; i++) {
dst[i] += src[i];
}
}
}
#pragma omp barrier
}
}
void NPomp_zprod_reduce_inplace(double complex **vec, size_t count)
{
unsigned int nthreads = omp_get_num_threads();
unsigned int thread_id = omp_get_thread_num();
unsigned int bit, thread_src;
unsigned int mask = 0;
double complex *dst = vec[thread_id];
double complex *src;
size_t i;
#pragma omp barrier
for (bit = 0; (1<<bit) < nthreads; bit++) {
mask |= 1 << bit;
if (!(thread_id & mask)) {
thread_src = thread_id | (1<<bit);
if (thread_src < nthreads) {
src = vec[thread_src];
for (i = 0; i < count; i++) {
dst[i] *= src[i];
}
}
}
#pragma omp barrier
}
}
|
GB_unop__identity_fp32_uint16.c | //------------------------------------------------------------------------------
// GB_unop: hard-coded functions for each built-in unary operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2021, All Rights Reserved.
// SPDX-License-Identifier: Apache-2.0
//------------------------------------------------------------------------------
// If this file is in the Generated2/ folder, do not edit it
// (it is auto-generated from Generator/*).
#include "GB.h"
#ifndef GBCOMPACT
#include "GB_control.h"
#include "GB_atomics.h"
#include "GB_unop__include.h"
// C=unop(A) is defined by the following types and operators:
// op(A) function: GB (_unop_apply__identity_fp32_uint16)
// op(A') function: GB (_unop_tran__identity_fp32_uint16)
// C type: float
// A type: uint16_t
// cast: float cij = (float) aij
// unaryop: cij = aij
#define GB_ATYPE \
uint16_t
#define GB_CTYPE \
float
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA) \
uint16_t aij = Ax [pA]
#define GB_CX(p) Cx [p]
// unary operator
#define GB_OP(z, x) \
z = x ;
// casting
#define GB_CAST(z, aij) \
float z = (float) aij ;
// cij = op (aij)
#define GB_CAST_OP(pC,pA) \
{ \
/* aij = Ax [pA] */ \
uint16_t aij = Ax [pA] ; \
/* Cx [pC] = op (cast (aij)) */ \
float z = (float) aij ; \
Cx [pC] = z ; \
}
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_IDENTITY || GxB_NO_FP32 || GxB_NO_UINT16)
//------------------------------------------------------------------------------
// Cx = op (cast (Ax)): apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB (_unop_apply__identity_fp32_uint16)
(
float *Cx, // Cx and Ax may be aliased
const uint16_t *Ax,
const int8_t *restrict Ab, // A->b if A is bitmap
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t p ;
if (Ab == NULL)
{
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
uint16_t aij = Ax [p] ;
float z = (float) aij ;
Cx [p] = z ;
}
}
else
{
// bitmap case, no transpose; A->b already memcpy'd into C->b
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
if (!Ab [p]) continue ;
uint16_t aij = Ax [p] ;
float z = (float) aij ;
Cx [p] = z ;
}
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (cast (A')): transpose, typecast, and apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB (_unop_tran__identity_fp32_uint16)
(
GrB_Matrix C,
const GrB_Matrix A,
int64_t *restrict *Workspaces,
const int64_t *restrict A_slice,
int nworkspaces,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
GB_binop__first_fc32.c |
//------------------------------------------------------------------------------
// GB_binop: hard-coded functions for each built-in binary operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2022, All Rights Reserved.
// SPDX-License-Identifier: Apache-2.0
//------------------------------------------------------------------------------
// If this file is in the Generated2/ folder, do not edit it
// (it is auto-generated from Generator/*).
#include "GB.h"
#ifndef GBCUDA_DEV
#include "GB_emult.h"
#include "GB_control.h"
#include "GB_ek_slice.h"
#include "GB_dense.h"
#include "GB_atomics.h"
#include "GB_bitmap_assign_methods.h"
#include "GB_binop__include.h"
// C=binop(A,B) is defined by the following types and operators:
// A+B function (eWiseAdd): GB (_AaddB__first_fc32)
// A.*B function (eWiseMult): GB (_AemultB_08__first_fc32)
// A.*B function (eWiseMult): GB (_AemultB_02__first_fc32)
// A.*B function (eWiseMult): GB (_AemultB_04__first_fc32)
// A.*B function (eWiseMult): GB (_AemultB_bitmap__first_fc32)
// A*D function (colscale): GB (_AxD__first_fc32)
// D*A function (rowscale): GB (_DxB__first_fc32)
// C+=B function (dense accum): GB (_Cdense_accumB__first_fc32)
// C+=b function (dense accum): GB (_Cdense_accumb__first_fc32)
// C+=A+B function (dense ewise3): GB ((none))
// C=A+B function (dense ewise3): GB (_Cdense_ewise3_noaccum__first_fc32)
// C=scalar+B GB ((none))
// C=scalar+B' GB ((none))
// C=A+scalar GB ((none))
// C=A'+scalar GB ((none))
// C type: GxB_FC32_t
// A type: GxB_FC32_t
// A pattern? 0
// B type: GxB_FC32_t
// B pattern? 1
// BinaryOp: cij = aij
#define GB_ATYPE \
GxB_FC32_t
#define GB_BTYPE \
GxB_FC32_t
#define GB_CTYPE \
GxB_FC32_t
// true if the types of A and B are identical
#define GB_ATYPE_IS_BTYPE \
1
// true if the types of C and A are identical
#define GB_CTYPE_IS_ATYPE \
1
// true if the types of C and B are identical
#define GB_CTYPE_IS_BTYPE \
1
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA,A_iso) \
GxB_FC32_t aij = GBX (Ax, pA, A_iso)
// true if values of A are not used
#define GB_A_IS_PATTERN \
0 \
// bij = Bx [pB]
#define GB_GETB(bij,Bx,pB,B_iso) \
;
// true if values of B are not used
#define GB_B_IS_PATTERN \
1 \
// declare scalar of the same type as C
#define GB_CTYPE_SCALAR(t) \
GxB_FC32_t t
// cij = Ax [pA]
#define GB_COPY_A_TO_C(cij,Ax,pA,A_iso) \
cij = GBX (Ax, pA, A_iso)
// cij = Bx [pB]
#define GB_COPY_B_TO_C(cij,Bx,pB,B_iso) \
cij = GBX (Bx, pB, B_iso)
#define GB_CX(p) Cx [p]
// binary operator
#define GB_BINOP(z,x,y,i,j) \
z = x ;
// true if the binop must be flipped
#define GB_BINOP_FLIP \
0
// op is second
#define GB_OP_IS_SECOND \
0
// do the numerical phases of GB_add and GB_emult
#define GB_PHASE_2_OF_2
// hard-coded loops can be vectorized
#define GB_PRAGMA_SIMD_VECTORIZE GB_PRAGMA_SIMD
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_FIRST || GxB_NO_FC32 || GxB_NO_FIRST_FC32)
//------------------------------------------------------------------------------
// C += A+B, all 3 matrices dense
//------------------------------------------------------------------------------
#if 0
// The op must be MIN, MAX, PLUS, MINUS, RMINUS, TIMES, DIV, or RDIV.
void GB ((none))
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix B,
const int nthreads
)
{
#include "GB_dense_ewise3_accum_template.c"
}
#endif
//------------------------------------------------------------------------------
// C = A+B, all 3 matrices dense
//------------------------------------------------------------------------------
void GB (_Cdense_ewise3_noaccum__first_fc32)
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix B,
const int nthreads
)
{
#include "GB_dense_ewise3_noaccum_template.c"
}
//------------------------------------------------------------------------------
// C += B, accumulate a sparse matrix into a dense matrix
//------------------------------------------------------------------------------
GrB_Info GB (_Cdense_accumB__first_fc32)
(
GrB_Matrix C,
const GrB_Matrix B,
const int64_t *B_ek_slicing, const int B_ntasks, const int B_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#if 0
{
#include "GB_dense_subassign_23_template.c"
}
#endif
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C += b, accumulate a scalar into a dense matrix
//------------------------------------------------------------------------------
GrB_Info GB (_Cdense_accumb__first_fc32)
(
GrB_Matrix C,
const GB_void *p_bwork,
const int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#if 0
{
// get the scalar b for C += b, of type GxB_FC32_t
GxB_FC32_t bwork = (*((GxB_FC32_t *) p_bwork)) ;
#include "GB_dense_subassign_22_template.c"
return (GrB_SUCCESS) ;
}
#endif
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = A*D, column scale with diagonal D matrix
//------------------------------------------------------------------------------
GrB_Info GB (_AxD__first_fc32)
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix D,
const int64_t *A_ek_slicing, const int A_ntasks, const int A_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
GxB_FC32_t *restrict Cx = (GxB_FC32_t *) C->x ;
#include "GB_AxB_colscale_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = D*B, row scale with diagonal D matrix
//------------------------------------------------------------------------------
GrB_Info GB (_DxB__first_fc32)
(
GrB_Matrix C,
const GrB_Matrix D,
const GrB_Matrix B,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
GxB_FC32_t *restrict Cx = (GxB_FC32_t *) C->x ;
#include "GB_AxB_rowscale_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseAdd: C=A+B, C<M>=A+B, C<!M>=A+B
//------------------------------------------------------------------------------
GrB_Info GB (_AaddB__first_fc32)
(
GrB_Matrix C,
const int C_sparsity,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const bool is_eWiseUnion,
const GB_void *alpha_scalar_in,
const GB_void *beta_scalar_in,
const bool Ch_is_Mh,
const int64_t *restrict C_to_M,
const int64_t *restrict C_to_A,
const int64_t *restrict C_to_B,
const GB_task_struct *restrict TaskList,
const int C_ntasks,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
GB_WERK_DECLARE (M_ek_slicing, int64_t) ;
GB_WERK_DECLARE (A_ek_slicing, int64_t) ;
GB_WERK_DECLARE (B_ek_slicing, int64_t) ;
GxB_FC32_t alpha_scalar ;
GxB_FC32_t beta_scalar ;
if (is_eWiseUnion)
{
alpha_scalar = (*((GxB_FC32_t *) alpha_scalar_in)) ;
beta_scalar = (*((GxB_FC32_t *) beta_scalar_in )) ;
}
#include "GB_add_template.c"
GB_FREE_WORKSPACE ;
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C=A.*B, C<M>=A.*B, or C<M!>=A.*B where C is sparse/hyper
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_08__first_fc32)
(
GrB_Matrix C,
const int C_sparsity,
const int ewise_method,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *restrict C_to_M,
const int64_t *restrict C_to_A,
const int64_t *restrict C_to_B,
const GB_task_struct *restrict TaskList,
const int C_ntasks,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_emult_08_meta.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C<#> = A.*B when A is sparse/hyper and B is bitmap/full
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_02__first_fc32)
(
GrB_Matrix C,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const bool flipxy,
const int64_t *restrict Cp_kfirst,
const int64_t *A_ek_slicing, const int A_ntasks, const int A_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#if GB_BINOP_FLIP
// The operator is not commutative, and does not have a flipped
// variant. For example z=atan2(y,x).
if (flipxy)
{
// use fmult(y,x)
#undef GB_FLIPPED
#define GB_FLIPPED 1
#include "GB_emult_02_template.c"
}
else
{
// use fmult(x,y)
#undef GB_FLIPPED
#define GB_FLIPPED 0
#include "GB_emult_02_template.c"
}
#else
// No need to handle the flip: the operator is either commutative, or
// has been handled by changing z=div(y,x) to z=rdiv(x,y) for example.
#undef GB_FLIPPED
#define GB_FLIPPED 0
#include "GB_emult_02_template.c"
#endif
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C<M> = A.*B, M sparse/hyper, A and B bitmap/full
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_04__first_fc32)
(
GrB_Matrix C,
const GrB_Matrix M,
const bool Mask_struct,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *restrict Cp_kfirst,
const int64_t *M_ek_slicing, const int M_ntasks, const int M_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_emult_04_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C=A.*B, C<M>=A.*B, C<!M>=A.*B where C is bitmap
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_bitmap__first_fc32)
(
GrB_Matrix C,
const int ewise_method,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *M_ek_slicing, const int M_ntasks, const int M_nthreads,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_bitmap_emult_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (x,Bx): apply a binary operator to a matrix with scalar bind1st
//------------------------------------------------------------------------------
#if 0
GrB_Info GB ((none))
(
GB_void *Cx_output, // Cx and Bx may be aliased
const GB_void *x_input,
const GB_void *Bx_input,
const int8_t *restrict Bb,
int64_t bnz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
GxB_FC32_t *Cx = (GxB_FC32_t *) Cx_output ;
GxB_FC32_t x = (*((GxB_FC32_t *) x_input)) ;
GxB_FC32_t *Bx = (GxB_FC32_t *) Bx_input ;
int64_t p ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < bnz ; p++)
{
if (!GBB (Bb, p)) continue ;
; ;
Cx [p] = x ;
}
return (GrB_SUCCESS) ;
#endif
}
#endif
//------------------------------------------------------------------------------
// Cx = op (Ax,y): apply a binary operator to a matrix with scalar bind2nd
//------------------------------------------------------------------------------
#if 0
GrB_Info GB ((none))
(
GB_void *Cx_output, // Cx and Ax may be aliased
const GB_void *Ax_input,
const GB_void *y_input,
const int8_t *restrict Ab,
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t p ;
GxB_FC32_t *Cx = (GxB_FC32_t *) Cx_output ;
GxB_FC32_t *Ax = (GxB_FC32_t *) Ax_input ;
GxB_FC32_t y = (*((GxB_FC32_t *) y_input)) ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
if (!GBB (Ab, p)) continue ;
GxB_FC32_t aij = GBX (Ax, p, false) ;
Cx [p] = aij ;
}
return (GrB_SUCCESS) ;
#endif
}
#endif
//------------------------------------------------------------------------------
// C = op (x, A'): transpose and apply a binary operator
//------------------------------------------------------------------------------
#if 0
// cij = op (x, aij), no typecasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
; ; \
Cx [pC] = x ; \
}
GrB_Info GB ((none))
(
GrB_Matrix C,
const GB_void *x_input,
const GrB_Matrix A,
int64_t *restrict *Workspaces,
const int64_t *restrict A_slice,
int nworkspaces,
int nthreads
)
{
// GB_unop_transpose.c uses GB_ATYPE, but A is
// the 2nd input to binary operator z=f(x,y).
#undef GB_ATYPE
#define GB_ATYPE \
GxB_FC32_t
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
GxB_FC32_t x = (*((const GxB_FC32_t *) x_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
#undef GB_ATYPE
#define GB_ATYPE \
GxB_FC32_t
}
#endif
//------------------------------------------------------------------------------
// C = op (A', y): transpose and apply a binary operator
//------------------------------------------------------------------------------
#if 0
// cij = op (aij, y), no typecasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
GxB_FC32_t aij = GBX (Ax, pA, false) ; \
Cx [pC] = aij ; \
}
GrB_Info GB ((none))
(
GrB_Matrix C,
const GrB_Matrix A,
const GB_void *y_input,
int64_t *restrict *Workspaces,
const int64_t *restrict A_slice,
int nworkspaces,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
GxB_FC32_t y = (*((const GxB_FC32_t *) y_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
#endif
|
mixed_tentusscher_myo_epi_2004_S0.c | // Scenario 0 - Original Mixed-Model TenTusscher 2004 (Myocardium + Epicardium)
#include <stdio.h>
#include "mixed_tentusscher_myo_epi_2004_S0.h"
GET_CELL_MODEL_DATA(init_cell_model_data)
{
if(get_initial_v)
cell_model->initial_v = INITIAL_V;
if(get_neq)
cell_model->number_of_ode_equations = NEQ;
}
SET_ODE_INITIAL_CONDITIONS_CPU(set_model_initial_conditions_cpu)
{
static bool first_call = true;
if(first_call)
{
print_to_stdout_and_file("Using mixed version of TenTusscher 2004 myocardium + epicardium CPU model\n");
first_call = false;
}
// Get the mapping array
uint32_t *mapping = NULL;
if(extra_data)
{
mapping = (uint32_t*)extra_data;
}
else
{
print_to_stderr_and_file_and_exit("You need to specify a mask function when using a mixed model!\n");
}
// Initial conditions for TenTusscher myocardium
if (mapping[sv_id] == 0)
{
// Default initial conditions
/*
sv[0] = INITIAL_V; // V; millivolt
sv[1] = 0.f; //M
sv[2] = 0.75; //H
sv[3] = 0.75f; //J
sv[4] = 0.f; //Xr1
sv[5] = 1.f; //Xr2
sv[6] = 0.f; //Xs
sv[7] = 1.f; //S
sv[8] = 0.f; //R
sv[9] = 0.f; //D
sv[10] = 1.f; //F
sv[11] = 1.f; //FCa
sv[12] = 1.f; //G
sv[13] = 0.0002; //Cai
sv[14] = 0.2f; //CaSR
sv[15] = 11.6f; //Nai
sv[16] = 138.3f; //Ki
*/
// Elnaz's steady-state initial conditions
real sv_sst[]={-86.3965119057144,0.00133824305081220,0.775463576993407,0.775278393595599,0.000179499343643571,0.483303039835057,0.00297647859235379,0.999998290403642,1.98961879737287e-08,1.93486789479597e-05,0.999599147019885,1.00646342475688,0.999975178010127,5.97703651642618e-05,0.418325344820368,10.7429775420171,138.918155900633};
for (uint32_t i = 0; i < NEQ; i++)
sv[i] = sv_sst[i];
}
// Initial conditions for TenTusscher epicardium
else
{
// Default initial conditions
/*
sv[0] = INITIAL_V; // V; millivolt
sv[1] = 0.f; //M
sv[2] = 0.75; //H
sv[3] = 0.75f; //J
sv[4] = 0.f; //Xr1
sv[5] = 1.f; //Xr2
sv[6] = 0.f; //Xs
sv[7] = 1.f; //S
sv[8] = 0.f; //R
sv[9] = 0.f; //D
sv[10] = 1.f; //F
sv[11] = 1.f; //FCa
sv[12] = 1.f; //G
sv[13] = 0.0002; //Cai
sv[14] = 0.2f; //CaSR
sv[15] = 11.6f; //Nai
sv[16] = 138.3f; //Ki
*/
// Elnaz's steady-state initial conditions
real sv_sst[]={-86.4172552153702,0.00133233093318418,0.775980725003160,0.775871451583533,0.000178484465968596,0.483518904573916,0.00297208335439809,0.999998297825169,1.98274727808946e-08,1.92952362196655e-05,0.999768268008847,1.00667048889468,0.999984854519288,5.50424977684767e-05,0.352485262813812,10.8673127043200,138.860197273148};
for (uint32_t i = 0; i < NEQ; i++)
sv[i] = sv_sst[i];
}
}
SOLVE_MODEL_ODES_CPU(solve_model_odes_cpu)
{
// Get the mapping array
uint32_t *mapping = NULL;
if(extra_data)
{
mapping = (uint32_t*)extra_data;
}
else
{
print_to_stderr_and_file_and_exit("You need to specify a mask function when using a mixed model!\n");
}
uint32_t sv_id;
int i;
#pragma omp parallel for private(sv_id)
for (i = 0; i < num_cells_to_solve; i++)
{
if(cells_to_solve)
sv_id = cells_to_solve[i];
else
sv_id = (uint32_t )i;
for (int j = 0; j < num_steps; ++j)
{
if (mapping[i] == 0)
solve_model_ode_cpu_myo(dt, sv + (sv_id * NEQ), stim_currents[i]);
else
solve_model_ode_cpu_epi(dt, sv + (sv_id * NEQ), stim_currents[i]);
}
}
}
void solve_model_ode_cpu_myo (real dt, real *sv, real stim_current)
{
real rY[NEQ], rDY[NEQ];
for(int i = 0; i < NEQ; i++)
rY[i] = sv[i];
RHS_cpu_myo(rY, rDY, stim_current, dt);
for(int i = 0; i < NEQ; i++)
sv[i] = rDY[i];
}
void RHS_cpu_myo(const real *sv, real *rDY_, real stim_current, real dt)
{
// State variables
real svolt = sv[0];
real sm = sv[1];
real sh = sv[2];
real sj = sv[3];
real sxr1 = sv[4];
real sxr2 = sv[5];
real sxs = sv[6];
real ss = sv[7];
real sr = sv[8];
real sd = sv[9];
real sf = sv[10];
real sfca = sv[11];
real sg = sv[12];
real Cai = sv[13];
real CaSR = sv[14];
real Nai = sv[15];
real Ki = sv[16];
//External concentrations
real Ko=5.4;
real Cao=2.0;
real Nao=140.0;
//Intracellular volumes
real Vc=0.016404;
real Vsr=0.001094;
//Calcium dynamics
real Bufc=0.15f;
real Kbufc=0.001f;
real Bufsr=10.f;
real Kbufsr=0.3f;
real taufca=2.f;
real taug=2.f;
real Vmaxup=0.000425f;
real Kup=0.00025f;
//Constants
const real R = 8314.472f;
const real F = 96485.3415f;
const real T =310.0f;
real RTONF =(R*T)/F;
//Cellular capacitance
real CAPACITANCE=0.185;
//Parameters for currents
//Parameters for IKr
real Gkr=0.096;
//Parameters for Iks
real pKNa=0.03;
// [!] Myocardium cell
real Gks=0.062;
//Parameters for Ik1
real GK1=5.405;
//Parameters for Ito
// [!] Myocardium cell
real Gto=0.294;
//Parameters for INa
real GNa=14.838;
//Parameters for IbNa
real GbNa=0.00029;
//Parameters for INaK
real KmK=1.0;
real KmNa=40.0;
real knak=1.362;
//Parameters for ICaL
real GCaL=0.000175;
//Parameters for IbCa
real GbCa=0.000592;
//Parameters for INaCa
real knaca=1000;
real KmNai=87.5;
real KmCa=1.38;
real ksat=0.1;
real n=0.35;
//Parameters for IpCa
real GpCa=0.825;
real KpCa=0.0005;
//Parameters for IpK;
real GpK=0.0146;
real IKr;
real IKs;
real IK1;
real Ito;
real INa;
real IbNa;
real ICaL;
real IbCa;
real INaCa;
real IpCa;
real IpK;
real INaK;
real Irel;
real Ileak;
real dNai;
real dKi;
real dCai;
real dCaSR;
real A;
// real BufferFactorc;
// real BufferFactorsr;
real SERCA;
real Caisquare;
real CaSRsquare;
real CaCurrent;
real CaSRCurrent;
real fcaold;
real gold;
real Ek;
real Ena;
real Eks;
real Eca;
real CaCSQN;
real bjsr;
real cjsr;
real CaBuf;
real bc;
real cc;
real Ak1;
real Bk1;
real rec_iK1;
real rec_ipK;
real rec_iNaK;
real AM;
real BM;
real AH_1;
real BH_1;
real AH_2;
real BH_2;
real AJ_1;
real BJ_1;
real AJ_2;
real BJ_2;
real M_INF;
real H_INF;
real J_INF;
real TAU_M;
real TAU_H;
real TAU_J;
real axr1;
real bxr1;
real axr2;
real bxr2;
real Xr1_INF;
real Xr2_INF;
real TAU_Xr1;
real TAU_Xr2;
real Axs;
real Bxs;
real Xs_INF;
real TAU_Xs;
real R_INF;
real TAU_R;
real S_INF;
real TAU_S;
real Ad;
real Bd;
real Cd;
real TAU_D;
real D_INF;
real TAU_F;
real F_INF;
real FCa_INF;
real G_INF;
real inverseVcF2=1/(2*Vc*F);
real inverseVcF=1./(Vc*F);
real Kupsquare=Kup*Kup;
// real BufcKbufc=Bufc*Kbufc;
// real Kbufcsquare=Kbufc*Kbufc;
// real Kbufc2=2*Kbufc;
// real BufsrKbufsr=Bufsr*Kbufsr;
// const real Kbufsrsquare=Kbufsr*Kbufsr;
// const real Kbufsr2=2*Kbufsr;
const real exptaufca=exp(-dt/taufca);
const real exptaug=exp(-dt/taug);
real sItot;
//Needed to compute currents
Ek=RTONF*(log((Ko/Ki)));
Ena=RTONF*(log((Nao/Nai)));
Eks=RTONF*(log((Ko+pKNa*Nao)/(Ki+pKNa*Nai)));
Eca=0.5*RTONF*(log((Cao/Cai)));
Ak1=0.1/(1.+exp(0.06*(svolt-Ek-200)));
Bk1=(3.*exp(0.0002*(svolt-Ek+100))+
exp(0.1*(svolt-Ek-10)))/(1.+exp(-0.5*(svolt-Ek)));
rec_iK1=Ak1/(Ak1+Bk1);
rec_iNaK=(1./(1.+0.1245*exp(-0.1*svolt*F/(R*T))+0.0353*exp(-svolt*F/(R*T))));
rec_ipK=1./(1.+exp((25-svolt)/5.98));
//Compute currents
INa=GNa*sm*sm*sm*sh*sj*(svolt-Ena);
ICaL=GCaL*sd*sf*sfca*4*svolt*(F*F/(R*T))*
(exp(2*svolt*F/(R*T))*Cai-0.341*Cao)/(exp(2*svolt*F/(R*T))-1.);
Ito=Gto*sr*ss*(svolt-Ek);
IKr=Gkr*sqrt(Ko/5.4)*sxr1*sxr2*(svolt-Ek);
IKs=Gks*sxs*sxs*(svolt-Eks);
IK1=GK1*rec_iK1*(svolt-Ek);
INaCa=knaca*(1./(KmNai*KmNai*KmNai+Nao*Nao*Nao))*(1./(KmCa+Cao))*
(1./(1+ksat*exp((n-1)*svolt*F/(R*T))))*
(exp(n*svolt*F/(R*T))*Nai*Nai*Nai*Cao-
exp((n-1)*svolt*F/(R*T))*Nao*Nao*Nao*Cai*2.5);
INaK=knak*(Ko/(Ko+KmK))*(Nai/(Nai+KmNa))*rec_iNaK;
IpCa=GpCa*Cai/(KpCa+Cai);
IpK=GpK*rec_ipK*(svolt-Ek);
IbNa=GbNa*(svolt-Ena);
IbCa=GbCa*(svolt-Eca);
//Determine total current
(sItot) = IKr +
IKs +
IK1 +
Ito +
INa +
IbNa +
ICaL +
IbCa +
INaK +
INaCa +
IpCa +
IpK +
stim_current;
//update concentrations
Caisquare=Cai*Cai;
CaSRsquare=CaSR*CaSR;
CaCurrent=-(ICaL+IbCa+IpCa-2.0f*INaCa)*inverseVcF2*CAPACITANCE;
A=0.016464f*CaSRsquare/(0.0625f+CaSRsquare)+0.008232f;
Irel=A*sd*sg;
Ileak=0.00008f*(CaSR-Cai);
SERCA=Vmaxup/(1.f+(Kupsquare/Caisquare));
CaSRCurrent=SERCA-Irel-Ileak;
CaCSQN=Bufsr*CaSR/(CaSR+Kbufsr);
dCaSR=dt*(Vc/Vsr)*CaSRCurrent;
bjsr=Bufsr-CaCSQN-dCaSR-CaSR+Kbufsr;
cjsr=Kbufsr*(CaCSQN+dCaSR+CaSR);
CaSR=(sqrt(bjsr*bjsr+4.*cjsr)-bjsr)/2.;
CaBuf=Bufc*Cai/(Cai+Kbufc);
dCai=dt*(CaCurrent-CaSRCurrent);
bc=Bufc-CaBuf-dCai-Cai+Kbufc;
cc=Kbufc*(CaBuf+dCai+Cai);
Cai=(sqrt(bc*bc+4*cc)-bc)/2;
dNai=-(INa+IbNa+3*INaK+3*INaCa)*inverseVcF*CAPACITANCE;
Nai+=dt*dNai;
dKi=-(stim_current+IK1+Ito+IKr+IKs-2*INaK+IpK)*inverseVcF*CAPACITANCE;
Ki+=dt*dKi;
//compute steady state values and time constants
AM=1./(1.+exp((-60.-svolt)/5.));
BM=0.1/(1.+exp((svolt+35.)/5.))+0.10/(1.+exp((svolt-50.)/200.));
TAU_M=AM*BM;
M_INF=1./((1.+exp((-56.86-svolt)/9.03))*(1.+exp((-56.86-svolt)/9.03)));
if (svolt>=-40.)
{
AH_1=0.;
BH_1=(0.77/(0.13*(1.+exp(-(svolt+10.66)/11.1))));
TAU_H= 1.0/(AH_1+BH_1);
}
else
{
AH_2=(0.057*exp(-(svolt+80.)/6.8));
BH_2=(2.7*exp(0.079*svolt)+(3.1e5)*exp(0.3485*svolt));
TAU_H=1.0/(AH_2+BH_2);
}
H_INF=1./((1.+exp((svolt+71.55)/7.43))*(1.+exp((svolt+71.55)/7.43)));
if(svolt>=-40.)
{
AJ_1=0.;
BJ_1=(0.6*exp((0.057)*svolt)/(1.+exp(-0.1*(svolt+32.))));
TAU_J= 1.0/(AJ_1+BJ_1);
}
else
{
AJ_2=(((-2.5428e4)*exp(0.2444*svolt)-(6.948e-6)*
exp(-0.04391*svolt))*(svolt+37.78)/
(1.+exp(0.311*(svolt+79.23))));
BJ_2=(0.02424*exp(-0.01052*svolt)/(1.+exp(-0.1378*(svolt+40.14))));
TAU_J= 1.0/(AJ_2+BJ_2);
}
J_INF=H_INF;
Xr1_INF=1./(1.+exp((-26.-svolt)/7.));
axr1=450./(1.+exp((-45.-svolt)/10.));
bxr1=6./(1.+exp((svolt-(-30.))/11.5));
TAU_Xr1=axr1*bxr1;
Xr2_INF=1./(1.+exp((svolt-(-88.))/24.));
axr2=3./(1.+exp((-60.-svolt)/20.));
bxr2=1.12/(1.+exp((svolt-60.)/20.));
TAU_Xr2=axr2*bxr2;
Xs_INF=1./(1.+exp((-5.-svolt)/14.));
Axs=1100./(sqrt(1.+exp((-10.-svolt)/6)));
Bxs=1./(1.+exp((svolt-60.)/20.));
TAU_Xs=Axs*Bxs;
// [!] Myocardium cell
R_INF=1./(1.+exp((20-svolt)/6.));
S_INF=1./(1.+exp((svolt+20)/5.));
TAU_R=9.5*exp(-(svolt+40.)*(svolt+40.)/1800.)+0.8;
TAU_S=85.*exp(-(svolt+45.)*(svolt+45.)/320.)+5./(1.+exp((svolt-20.)/5.))+3.;
D_INF=1./(1.+exp((-5-svolt)/7.5));
Ad=1.4/(1.+exp((-35-svolt)/13))+0.25;
Bd=1.4/(1.+exp((svolt+5)/5));
Cd=1./(1.+exp((50-svolt)/20));
TAU_D=Ad*Bd+Cd;
F_INF=1./(1.+exp((svolt+20)/7));
//TAU_F=1125*exp(-(svolt+27)*(svolt+27)/300)+80+165/(1.+exp((25-svolt)/10));
TAU_F=1125*exp(-(svolt+27)*(svolt+27)/240)+80+165/(1.+exp((25-svolt)/10));
FCa_INF=(1./(1.+pow((Cai/0.000325),8))+
0.1/(1.+exp((Cai-0.0005)/0.0001))+
0.20/(1.+exp((Cai-0.00075)/0.0008))+
0.23 )/1.46;
if(Cai<0.00035)
G_INF=1./(1.+pow((Cai/0.00035),6));
else
G_INF=1./(1.+pow((Cai/0.00035),16));
//Update gates
rDY_[1] = M_INF-(M_INF-sm)*exp(-dt/TAU_M);
rDY_[2] = H_INF-(H_INF-sh)*exp(-dt/TAU_H);
rDY_[3] = J_INF-(J_INF-sj)*exp(-dt/TAU_J);
rDY_[4] = Xr1_INF-(Xr1_INF-sxr1)*exp(-dt/TAU_Xr1);
rDY_[5] = Xr2_INF-(Xr2_INF-sxr2)*exp(-dt/TAU_Xr2);
rDY_[6] = Xs_INF-(Xs_INF-sxs)*exp(-dt/TAU_Xs);
rDY_[7] = S_INF-(S_INF-ss)*exp(-dt/TAU_S);
rDY_[8] = R_INF-(R_INF-sr)*exp(-dt/TAU_R);
rDY_[9] = D_INF-(D_INF-sd)*exp(-dt/TAU_D);
rDY_[10] = F_INF-(F_INF-sf)*exp(-dt/TAU_F);
fcaold= sfca;
sfca = FCa_INF-(FCa_INF-sfca)*exptaufca;
if(sfca>fcaold && (svolt)>-37.0)
sfca = fcaold;
gold = sg;
sg = G_INF-(G_INF-sg)*exptaug;
if(sg>gold && (svolt)>-37.0)
sg=gold;
//update voltage
rDY_[0] = svolt + dt*(-sItot);
rDY_[11] = sfca;
rDY_[12] = sg;
rDY_[13] = Cai;
rDY_[14] = CaSR;
rDY_[15] = Nai;
rDY_[16] = Ki;
}
void solve_model_ode_cpu_epi (real dt, real *sv, real stim_current)
{
real rY[NEQ], rDY[NEQ];
for(int i = 0; i < NEQ; i++)
rY[i] = sv[i];
RHS_cpu_epi(rY, rDY, stim_current, dt);
for(int i = 0; i < NEQ; i++)
sv[i] = rDY[i];
}
void RHS_cpu_epi(const real *sv, real *rDY_, real stim_current, real dt)
{
// State variables
real svolt = sv[0];
real sm = sv[1];
real sh = sv[2];
real sj = sv[3];
real sxr1 = sv[4];
real sxr2 = sv[5];
real sxs = sv[6];
real ss = sv[7];
real sr = sv[8];
real sd = sv[9];
real sf = sv[10];
real sfca = sv[11];
real sg = sv[12];
real Cai = sv[13];
real CaSR = sv[14];
real Nai = sv[15];
real Ki = sv[16];
//External concentrations
real Ko=5.4;
real Cao=2.0;
real Nao=140.0;
//Intracellular volumes
real Vc=0.016404;
real Vsr=0.001094;
//Calcium dynamics
real Bufc=0.15f;
real Kbufc=0.001f;
real Bufsr=10.f;
real Kbufsr=0.3f;
real taufca=2.f;
real taug=2.f;
real Vmaxup=0.000425f;
real Kup=0.00025f;
//Constants
const real R = 8314.472f;
const real F = 96485.3415f;
const real T =310.0f;
real RTONF =(R*T)/F;
//Cellular capacitance
real CAPACITANCE=0.185;
//Parameters for currents
//Parameters for IKr
real Gkr=0.096;
//Parameters for Iks
real pKNa=0.03;
// [!] Epicardium cell
real Gks=0.245;
//Parameters for Ik1
real GK1=5.405;
//Parameters for Ito
// [!] Epicardium cell
real Gto=0.294;
//Parameters for INa
real GNa=14.838;
//Parameters for IbNa
real GbNa=0.00029;
//Parameters for INaK
real KmK=1.0;
real KmNa=40.0;
real knak=1.362;
//Parameters for ICaL
real GCaL=0.000175;
//Parameters for IbCa
real GbCa=0.000592;
//Parameters for INaCa
real knaca=1000;
real KmNai=87.5;
real KmCa=1.38;
real ksat=0.1;
real n=0.35;
//Parameters for IpCa
real GpCa=0.825;
real KpCa=0.0005;
//Parameters for IpK;
real GpK=0.0146;
real IKr;
real IKs;
real IK1;
real Ito;
real INa;
real IbNa;
real ICaL;
real IbCa;
real INaCa;
real IpCa;
real IpK;
real INaK;
real Irel;
real Ileak;
real dNai;
real dKi;
real dCai;
real dCaSR;
real A;
// real BufferFactorc;
// real BufferFactorsr;
real SERCA;
real Caisquare;
real CaSRsquare;
real CaCurrent;
real CaSRCurrent;
real fcaold;
real gold;
real Ek;
real Ena;
real Eks;
real Eca;
real CaCSQN;
real bjsr;
real cjsr;
real CaBuf;
real bc;
real cc;
real Ak1;
real Bk1;
real rec_iK1;
real rec_ipK;
real rec_iNaK;
real AM;
real BM;
real AH_1;
real BH_1;
real AH_2;
real BH_2;
real AJ_1;
real BJ_1;
real AJ_2;
real BJ_2;
real M_INF;
real H_INF;
real J_INF;
real TAU_M;
real TAU_H;
real TAU_J;
real axr1;
real bxr1;
real axr2;
real bxr2;
real Xr1_INF;
real Xr2_INF;
real TAU_Xr1;
real TAU_Xr2;
real Axs;
real Bxs;
real Xs_INF;
real TAU_Xs;
real R_INF;
real TAU_R;
real S_INF;
real TAU_S;
real Ad;
real Bd;
real Cd;
real TAU_D;
real D_INF;
real TAU_F;
real F_INF;
real FCa_INF;
real G_INF;
real inverseVcF2=1/(2*Vc*F);
real inverseVcF=1./(Vc*F);
real Kupsquare=Kup*Kup;
// real BufcKbufc=Bufc*Kbufc;
// real Kbufcsquare=Kbufc*Kbufc;
// real Kbufc2=2*Kbufc;
// real BufsrKbufsr=Bufsr*Kbufsr;
// const real Kbufsrsquare=Kbufsr*Kbufsr;
// const real Kbufsr2=2*Kbufsr;
const real exptaufca=exp(-dt/taufca);
const real exptaug=exp(-dt/taug);
real sItot;
//Needed to compute currents
Ek=RTONF*(log((Ko/Ki)));
Ena=RTONF*(log((Nao/Nai)));
Eks=RTONF*(log((Ko+pKNa*Nao)/(Ki+pKNa*Nai)));
Eca=0.5*RTONF*(log((Cao/Cai)));
Ak1=0.1/(1.+exp(0.06*(svolt-Ek-200)));
Bk1=(3.*exp(0.0002*(svolt-Ek+100))+
exp(0.1*(svolt-Ek-10)))/(1.+exp(-0.5*(svolt-Ek)));
rec_iK1=Ak1/(Ak1+Bk1);
rec_iNaK=(1./(1.+0.1245*exp(-0.1*svolt*F/(R*T))+0.0353*exp(-svolt*F/(R*T))));
rec_ipK=1./(1.+exp((25-svolt)/5.98));
//Compute currents
INa=GNa*sm*sm*sm*sh*sj*(svolt-Ena);
ICaL=GCaL*sd*sf*sfca*4*svolt*(F*F/(R*T))*
(exp(2*svolt*F/(R*T))*Cai-0.341*Cao)/(exp(2*svolt*F/(R*T))-1.);
Ito=Gto*sr*ss*(svolt-Ek);
IKr=Gkr*sqrt(Ko/5.4)*sxr1*sxr2*(svolt-Ek);
IKs=Gks*sxs*sxs*(svolt-Eks);
IK1=GK1*rec_iK1*(svolt-Ek);
INaCa=knaca*(1./(KmNai*KmNai*KmNai+Nao*Nao*Nao))*(1./(KmCa+Cao))*
(1./(1+ksat*exp((n-1)*svolt*F/(R*T))))*
(exp(n*svolt*F/(R*T))*Nai*Nai*Nai*Cao-
exp((n-1)*svolt*F/(R*T))*Nao*Nao*Nao*Cai*2.5);
INaK=knak*(Ko/(Ko+KmK))*(Nai/(Nai+KmNa))*rec_iNaK;
IpCa=GpCa*Cai/(KpCa+Cai);
IpK=GpK*rec_ipK*(svolt-Ek);
IbNa=GbNa*(svolt-Ena);
IbCa=GbCa*(svolt-Eca);
//Determine total current
(sItot) = IKr +
IKs +
IK1 +
Ito +
INa +
IbNa +
ICaL +
IbCa +
INaK +
INaCa +
IpCa +
IpK +
stim_current;
//update concentrations
Caisquare=Cai*Cai;
CaSRsquare=CaSR*CaSR;
CaCurrent=-(ICaL+IbCa+IpCa-2.0f*INaCa)*inverseVcF2*CAPACITANCE;
A=0.016464f*CaSRsquare/(0.0625f+CaSRsquare)+0.008232f;
Irel=A*sd*sg;
Ileak=0.00008f*(CaSR-Cai);
SERCA=Vmaxup/(1.f+(Kupsquare/Caisquare));
CaSRCurrent=SERCA-Irel-Ileak;
CaCSQN=Bufsr*CaSR/(CaSR+Kbufsr);
dCaSR=dt*(Vc/Vsr)*CaSRCurrent;
bjsr=Bufsr-CaCSQN-dCaSR-CaSR+Kbufsr;
cjsr=Kbufsr*(CaCSQN+dCaSR+CaSR);
CaSR=(sqrt(bjsr*bjsr+4.*cjsr)-bjsr)/2.;
CaBuf=Bufc*Cai/(Cai+Kbufc);
dCai=dt*(CaCurrent-CaSRCurrent);
bc=Bufc-CaBuf-dCai-Cai+Kbufc;
cc=Kbufc*(CaBuf+dCai+Cai);
Cai=(sqrt(bc*bc+4*cc)-bc)/2;
dNai=-(INa+IbNa+3*INaK+3*INaCa)*inverseVcF*CAPACITANCE;
Nai+=dt*dNai;
dKi=-(stim_current+IK1+Ito+IKr+IKs-2*INaK+IpK)*inverseVcF*CAPACITANCE;
Ki+=dt*dKi;
//compute steady state values and time constants
AM=1./(1.+exp((-60.-svolt)/5.));
BM=0.1/(1.+exp((svolt+35.)/5.))+0.10/(1.+exp((svolt-50.)/200.));
TAU_M=AM*BM;
M_INF=1./((1.+exp((-56.86-svolt)/9.03))*(1.+exp((-56.86-svolt)/9.03)));
if (svolt>=-40.)
{
AH_1=0.;
BH_1=(0.77/(0.13*(1.+exp(-(svolt+10.66)/11.1))));
TAU_H= 1.0/(AH_1+BH_1);
}
else
{
AH_2=(0.057*exp(-(svolt+80.)/6.8));
BH_2=(2.7*exp(0.079*svolt)+(3.1e5)*exp(0.3485*svolt));
TAU_H=1.0/(AH_2+BH_2);
}
H_INF=1./((1.+exp((svolt+71.55)/7.43))*(1.+exp((svolt+71.55)/7.43)));
if(svolt>=-40.)
{
AJ_1=0.;
BJ_1=(0.6*exp((0.057)*svolt)/(1.+exp(-0.1*(svolt+32.))));
TAU_J= 1.0/(AJ_1+BJ_1);
}
else
{
AJ_2=(((-2.5428e4)*exp(0.2444*svolt)-(6.948e-6)*
exp(-0.04391*svolt))*(svolt+37.78)/
(1.+exp(0.311*(svolt+79.23))));
BJ_2=(0.02424*exp(-0.01052*svolt)/(1.+exp(-0.1378*(svolt+40.14))));
TAU_J= 1.0/(AJ_2+BJ_2);
}
J_INF=H_INF;
Xr1_INF=1./(1.+exp((-26.-svolt)/7.));
axr1=450./(1.+exp((-45.-svolt)/10.));
bxr1=6./(1.+exp((svolt-(-30.))/11.5));
TAU_Xr1=axr1*bxr1;
Xr2_INF=1./(1.+exp((svolt-(-88.))/24.));
axr2=3./(1.+exp((-60.-svolt)/20.));
bxr2=1.12/(1.+exp((svolt-60.)/20.));
TAU_Xr2=axr2*bxr2;
Xs_INF=1./(1.+exp((-5.-svolt)/14.));
Axs=1100./(sqrt(1.+exp((-10.-svolt)/6)));
Bxs=1./(1.+exp((svolt-60.)/20.));
TAU_Xs=Axs*Bxs;
R_INF=1./(1.+exp((20-svolt)/6.));
S_INF=1./(1.+exp((svolt+20)/5.));
TAU_R=9.5*exp(-(svolt+40.)*(svolt+40.)/1800.)+0.8;
TAU_S=85.*exp(-(svolt+45.)*(svolt+45.)/320.)+5./(1.+exp((svolt-20.)/5.))+3.;
D_INF=1./(1.+exp((-5-svolt)/7.5));
Ad=1.4/(1.+exp((-35-svolt)/13))+0.25;
Bd=1.4/(1.+exp((svolt+5)/5));
Cd=1./(1.+exp((50-svolt)/20));
TAU_D=Ad*Bd+Cd;
F_INF=1./(1.+exp((svolt+20)/7));
//TAU_F=1125*exp(-(svolt+27)*(svolt+27)/300)+80+165/(1.+exp((25-svolt)/10));
TAU_F=1125*exp(-(svolt+27)*(svolt+27)/240)+80+165/(1.+exp((25-svolt)/10)); // Updated version from CellML !!!
FCa_INF=(1./(1.+pow((Cai/0.000325),8))+
0.1/(1.+exp((Cai-0.0005)/0.0001))+
0.20/(1.+exp((Cai-0.00075)/0.0008))+
0.23 )/1.46;
if(Cai<0.00035)
G_INF=1./(1.+pow((Cai/0.00035),6));
else
G_INF=1./(1.+pow((Cai/0.00035),16));
//Update gates
rDY_[1] = M_INF-(M_INF-sm)*exp(-dt/TAU_M);
rDY_[2] = H_INF-(H_INF-sh)*exp(-dt/TAU_H);
rDY_[3] = J_INF-(J_INF-sj)*exp(-dt/TAU_J);
rDY_[4] = Xr1_INF-(Xr1_INF-sxr1)*exp(-dt/TAU_Xr1);
rDY_[5] = Xr2_INF-(Xr2_INF-sxr2)*exp(-dt/TAU_Xr2);
rDY_[6] = Xs_INF-(Xs_INF-sxs)*exp(-dt/TAU_Xs);
rDY_[7] = S_INF-(S_INF-ss)*exp(-dt/TAU_S);
rDY_[8] = R_INF-(R_INF-sr)*exp(-dt/TAU_R);
rDY_[9] = D_INF-(D_INF-sd)*exp(-dt/TAU_D);
rDY_[10] = F_INF-(F_INF-sf)*exp(-dt/TAU_F);
fcaold= sfca;
sfca = FCa_INF-(FCa_INF-sfca)*exptaufca;
if(sfca>fcaold && (svolt)>-37.0)
sfca = fcaold;
gold = sg;
sg = G_INF-(G_INF-sg)*exptaug;
if(sg>gold && (svolt)>-37.0)
sg=gold;
//update voltage
rDY_[0] = svolt + dt*(-sItot);
rDY_[11] = sfca;
rDY_[12] = sg;
rDY_[13] = Cai;
rDY_[14] = CaSR;
rDY_[15] = Nai;
rDY_[16] = Ki;
}
|
simd_misc_messages.c | // RUN: %clang_cc1 -fsyntax-only -fopenmp -verify %s -Wuninitialized
// RUN: %clang_cc1 -fsyntax-only -fopenmp-simd -verify %s -Wuninitialized
void xxx(int argc) {
int x; // expected-note {{initialize the variable 'x' to silence this warning}}
#pragma omp simd
for (int i = 0; i < 10; ++i)
argc = x; // expected-warning {{variable 'x' is uninitialized when used here}}
}
// expected-error@+1 {{unexpected OpenMP directive '#pragma omp simd'}}
#pragma omp simd
// expected-error@+1 {{unexpected OpenMP directive '#pragma omp simd'}}
#pragma omp simd foo
// expected-error@+1 {{unexpected OpenMP directive '#pragma omp simd'}}
#pragma omp simd safelen(4)
void test_no_clause() {
int i;
#pragma omp simd
for (i = 0; i < 16; ++i)
;
// expected-error@+2 {{statement after '#pragma omp simd' must be a for loop}}
#pragma omp simd
++i;
}
void test_branch_protected_scope() {
int i = 0;
L1:
++i;
int x[24];
#pragma omp simd
for (i = 0; i < 16; ++i) {
if (i == 5)
goto L1; // expected-error {{use of undeclared label 'L1'}}
else if (i == 6)
return; // expected-error {{cannot return from OpenMP region}}
else if (i == 7)
goto L2;
else if (i == 8) {
L2:
x[i]++;
}
}
if (x[0] == 0)
goto L2; // expected-error {{use of undeclared label 'L2'}}
else if (x[1] == 1)
goto L1;
}
void test_invalid_clause() {
int i;
// expected-warning@+1 {{extra tokens at the end of '#pragma omp simd' are ignored}}
#pragma omp simd foo bar
for (i = 0; i < 16; ++i)
;
}
void test_non_identifiers() {
int i, x;
// expected-warning@+1 {{extra tokens at the end of '#pragma omp simd' are ignored}}
#pragma omp simd;
for (i = 0; i < 16; ++i)
;
// expected-error@+2 {{unexpected OpenMP clause 'firstprivate' in directive '#pragma omp simd'}}
// expected-warning@+1 {{extra tokens at the end of '#pragma omp simd' are ignored}}
#pragma omp simd firstprivate(x);
for (i = 0; i < 16; ++i)
;
// expected-warning@+1 {{extra tokens at the end of '#pragma omp simd' are ignored}}
#pragma omp simd private(x);
for (i = 0; i < 16; ++i)
;
// expected-warning@+1 {{extra tokens at the end of '#pragma omp simd' are ignored}}
#pragma omp simd, private(x);
for (i = 0; i < 16; ++i)
;
}
extern int foo();
void test_safelen() {
int i;
// expected-error@+1 {{expected '('}}
#pragma omp simd safelen
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{expected expression}} expected-error@+1 {{expected ')'}} expected-note@+1 {{to match this '('}}
#pragma omp simd safelen(
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{expected expression}}
#pragma omp simd safelen()
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{expected expression}} expected-error@+1 {{expected ')'}} expected-note@+1 {{to match this '('}}
#pragma omp simd safelen(,
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{expected expression}} expected-error@+1 {{expected ')'}} expected-note@+1 {{to match this '('}}
#pragma omp simd safelen(, )
for (i = 0; i < 16; ++i)
;
// expected-warning@+2 {{extra tokens at the end of '#pragma omp simd' are ignored}}
// expected-error@+1 {{expected '('}}
#pragma omp simd safelen 4)
for (i = 0; i < 16; ++i)
;
// expected-error@+2 {{expected ')'}}
// expected-note@+1 {{to match this '('}}
#pragma omp simd safelen(4
for (i = 0; i < 16; ++i)
;
// expected-error@+2 {{expected ')'}}
// expected-note@+1 {{to match this '('}}
#pragma omp simd safelen(4,
for (i = 0; i < 16; ++i)
;
// expected-error@+2 {{expected ')'}}
// expected-note@+1 {{to match this '('}}
#pragma omp simd safelen(4, )
for (i = 0; i < 16; ++i)
;
// xxpected-error@+1 {{expected expression}}
#pragma omp simd safelen(4)
for (i = 0; i < 16; ++i)
;
// expected-error@+2 {{expected ')'}}
// expected-note@+1 {{to match this '('}}
#pragma omp simd safelen(4 4)
for (i = 0; i < 16; ++i)
;
// expected-error@+2 {{expected ')'}}
// expected-note@+1 {{to match this '('}}
#pragma omp simd safelen(4, , 4)
for (i = 0; i < 16; ++i)
;
#pragma omp simd safelen(4)
for (i = 0; i < 16; ++i)
;
// expected-error@+2 {{expected ')'}}
// expected-note@+1 {{to match this '('}}
#pragma omp simd safelen(4, 8)
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{expression is not an integer constant expression}}
#pragma omp simd safelen(2.5)
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{expression is not an integer constant expression}}
#pragma omp simd safelen(foo())
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{argument to 'safelen' clause must be a strictly positive integer value}}
#pragma omp simd safelen(-5)
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{argument to 'safelen' clause must be a strictly positive integer value}}
#pragma omp simd safelen(0)
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{argument to 'safelen' clause must be a strictly positive integer value}}
#pragma omp simd safelen(5 - 5)
for (i = 0; i < 16; ++i)
;
}
void test_simdlen() {
int i;
// expected-error@+1 {{expected '('}}
#pragma omp simd simdlen
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{expected expression}} expected-error@+1 {{expected ')'}} expected-note@+1 {{to match this '('}}
#pragma omp simd simdlen(
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{expected expression}}
#pragma omp simd simdlen()
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{expected expression}} expected-error@+1 {{expected ')'}} expected-note@+1 {{to match this '('}}
#pragma omp simd simdlen(,
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{expected expression}} expected-error@+1 {{expected ')'}} expected-note@+1 {{to match this '('}}
#pragma omp simd simdlen(, )
for (i = 0; i < 16; ++i)
;
// expected-warning@+2 {{extra tokens at the end of '#pragma omp simd' are ignored}}
// expected-error@+1 {{expected '('}}
#pragma omp simd simdlen 4)
for (i = 0; i < 16; ++i)
;
// expected-error@+2 {{expected ')'}}
// expected-note@+1 {{to match this '('}}
#pragma omp simd simdlen(4
for (i = 0; i < 16; ++i)
;
// expected-error@+2 {{expected ')'}}
// expected-note@+1 {{to match this '('}}
#pragma omp simd simdlen(4,
for (i = 0; i < 16; ++i)
;
// expected-error@+2 {{expected ')'}}
// expected-note@+1 {{to match this '('}}
#pragma omp simd simdlen(4, )
for (i = 0; i < 16; ++i)
;
#pragma omp simd simdlen(4)
for (i = 0; i < 16; ++i)
;
// expected-error@+2 {{expected ')'}}
// expected-note@+1 {{to match this '('}}
#pragma omp simd simdlen(4 4)
for (i = 0; i < 16; ++i)
;
// expected-error@+2 {{expected ')'}}
// expected-note@+1 {{to match this '('}}
#pragma omp simd simdlen(4, , 4)
for (i = 0; i < 16; ++i)
;
#pragma omp simd simdlen(4)
for (i = 0; i < 16; ++i)
;
// expected-error@+2 {{expected ')'}}
// expected-note@+1 {{to match this '('}}
#pragma omp simd simdlen(4, 8)
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{expression is not an integer constant expression}}
#pragma omp simd simdlen(2.5)
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{expression is not an integer constant expression}}
#pragma omp simd simdlen(foo())
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{argument to 'simdlen' clause must be a strictly positive integer value}}
#pragma omp simd simdlen(-5)
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{argument to 'simdlen' clause must be a strictly positive integer value}}
#pragma omp simd simdlen(0)
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{argument to 'simdlen' clause must be a strictly positive integer value}}
#pragma omp simd simdlen(5 - 5)
for (i = 0; i < 16; ++i)
;
}
void test_safelen_simdlen() {
int i;
// expected-error@+1 {{the value of 'simdlen' parameter must be less than or equal to the value of the 'safelen' parameter}}
#pragma omp simd simdlen(6) safelen(5)
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{the value of 'simdlen' parameter must be less than or equal to the value of the 'safelen' parameter}}
#pragma omp simd safelen(5) simdlen(6)
for (i = 0; i < 16; ++i)
;
}
void test_collapse() {
int i;
// expected-error@+1 {{expected '('}}
#pragma omp simd collapse
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{expected expression}} expected-error@+1 {{expected ')'}} expected-note@+1 {{to match this '('}}
#pragma omp simd collapse(
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{expected expression}}
#pragma omp simd collapse()
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{expected expression}} expected-error@+1 {{expected ')'}} expected-note@+1 {{to match this '('}}
#pragma omp simd collapse(,
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{expected expression}} expected-error@+1 {{expected ')'}} expected-note@+1 {{to match this '('}}
#pragma omp simd collapse(, )
for (i = 0; i < 16; ++i)
;
// expected-warning@+2 {{extra tokens at the end of '#pragma omp simd' are ignored}}
// expected-error@+1 {{expected '('}}
#pragma omp simd collapse 4)
for (i = 0; i < 16; ++i)
;
// expected-error@+2 {{expected ')'}}
// expected-note@+1 {{to match this '('}} expected-note@+1 {{as specified in 'collapse' clause}}
#pragma omp simd collapse(4
for (i = 0; i < 16; ++i)
; // expected-error {{expected 4 for loops after '#pragma omp simd', but found only 1}}
// expected-error@+2 {{expected ')'}}
// expected-note@+1 {{to match this '('}} expected-note@+1 {{as specified in 'collapse' clause}}
#pragma omp simd collapse(4,
for (i = 0; i < 16; ++i)
; // expected-error {{expected 4 for loops after '#pragma omp simd', but found only 1}}
// expected-error@+2 {{expected ')'}}
// expected-note@+1 {{to match this '('}} expected-note@+1 {{as specified in 'collapse' clause}}
#pragma omp simd collapse(4, )
for (i = 0; i < 16; ++i)
; // expected-error {{expected 4 for loops after '#pragma omp simd', but found only 1}}
// xxpected-error@+1 {{expected expression}} expected-note@+1 {{as specified in 'collapse' clause}}
#pragma omp simd collapse(4)
for (i = 0; i < 16; ++i)
; // expected-error {{expected 4 for loops after '#pragma omp simd', but found only 1}}
// expected-error@+2 {{expected ')'}}
// expected-note@+1 {{to match this '('}} expected-note@+1 {{as specified in 'collapse' clause}}
#pragma omp simd collapse(4 4)
for (i = 0; i < 16; ++i)
; // expected-error {{expected 4 for loops after '#pragma omp simd', but found only 1}}
// expected-error@+2 {{expected ')'}}
// expected-note@+1 {{to match this '('}} expected-note@+1 {{as specified in 'collapse' clause}}
#pragma omp simd collapse(4, , 4)
for (i = 0; i < 16; ++i)
; // expected-error {{expected 4 for loops after '#pragma omp simd', but found only 1}}
#pragma omp simd collapse(4)
for (int i1 = 0; i1 < 16; ++i1)
for (int i2 = 0; i2 < 16; ++i2)
for (int i3 = 0; i3 < 16; ++i3)
for (int i4 = 0; i4 < 16; ++i4)
foo();
// expected-error@+2 {{expected ')'}}
// expected-note@+1 {{to match this '('}} expected-note@+1 {{as specified in 'collapse' clause}}
#pragma omp simd collapse(4, 8)
for (i = 0; i < 16; ++i)
; // expected-error {{expected 4 for loops after '#pragma omp simd', but found only 1}}
// expected-error@+1 {{expression is not an integer constant expression}}
#pragma omp simd collapse(2.5)
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{expression is not an integer constant expression}}
#pragma omp simd collapse(foo())
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{argument to 'collapse' clause must be a strictly positive integer value}}
#pragma omp simd collapse(-5)
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{argument to 'collapse' clause must be a strictly positive integer value}}
#pragma omp simd collapse(0)
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{argument to 'collapse' clause must be a strictly positive integer value}}
#pragma omp simd collapse(5 - 5)
for (i = 0; i < 16; ++i)
;
// expected-note@+2 2 {{defined as reduction}}
#pragma omp parallel
#pragma omp simd collapse(2) reduction(+ : i)
for (i = 0; i < 16; ++i) // expected-error {{loop iteration variable in the associated loop of 'omp simd' directive may not be reduction, predetermined as lastprivate}}
// expected-note@+1 {{variable with automatic storage duration is predetermined as private; perhaps you forget to enclose 'omp for' directive into a parallel or another task region?}}
for (int j = 0; j < 16; ++j)
// expected-error@+2 2 {{reduction variable must be shared}}
// expected-error@+1 {{OpenMP constructs may not be nested inside a simd region}}
#pragma omp for reduction(+ : i, j)
for (int k = 0; k < 16; ++k)
i += j;
#pragma omp parallel
#pragma omp for
for (i = 0; i < 16; ++i)
for (int j = 0; j < 16; ++j)
#pragma omp simd reduction(+ : i, j)
for (int k = 0; k < 16; ++k)
i += j;
}
void test_linear() {
int i;
// expected-error@+1 {{expected expression}} expected-error@+1 {{expected ')'}} expected-note@+1 {{to match this '('}}
#pragma omp simd linear(
for (i = 0; i < 16; ++i)
;
// expected-error@+2 {{expected expression}}
// expected-error@+1 {{expected expression}} expected-error@+1 {{expected ')'}} expected-note@+1 {{to match this '('}}
#pragma omp simd linear(,
for (i = 0; i < 16; ++i)
;
// expected-error@+2 {{expected expression}}
// expected-error@+1 {{expected expression}}
#pragma omp simd linear(, )
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{expected expression}}
#pragma omp simd linear()
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{expected expression}}
#pragma omp simd linear(int)
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{expected variable name}}
#pragma omp simd linear(0)
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{use of undeclared identifier 'x'}}
#pragma omp simd linear(x)
for (i = 0; i < 16; ++i)
;
// expected-error@+2 {{use of undeclared identifier 'x'}}
// expected-error@+1 {{use of undeclared identifier 'y'}}
#pragma omp simd linear(x, y)
for (i = 0; i < 16; ++i)
;
// expected-error@+3 {{use of undeclared identifier 'x'}}
// expected-error@+2 {{use of undeclared identifier 'y'}}
// expected-error@+1 {{use of undeclared identifier 'z'}}
#pragma omp simd linear(x, y, z)
for (i = 0; i < 16; ++i)
;
int x, y;
// expected-error@+1 {{expected expression}}
#pragma omp simd linear(x :)
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{expected expression}} expected-error@+1 {{expected ')'}} expected-note@+1 {{to match this '('}}
#pragma omp simd linear(x :, )
for (i = 0; i < 16; ++i)
;
#pragma omp simd linear(x : 1)
for (i = 0; i < 16; ++i)
;
#pragma omp simd linear(x : 2 * 2)
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{expected ')'}} expected-note@+1 {{to match this '('}}
#pragma omp simd linear(x : 1, y)
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{expected ')'}} expected-note@+1 {{to match this '('}}
#pragma omp simd linear(x : 1, y, z : 1)
for (i = 0; i < 16; ++i)
;
// expected-note@+2 {{defined as linear}}
// expected-error@+1 {{linear variable cannot be linear}}
#pragma omp simd linear(x) linear(x)
for (i = 0; i < 16; ++i)
;
// expected-note@+2 {{defined as private}}
// expected-error@+1 {{private variable cannot be linear}}
#pragma omp simd private(x) linear(x)
for (i = 0; i < 16; ++i)
;
// expected-note@+2 {{defined as linear}}
// expected-error@+1 {{linear variable cannot be private}}
#pragma omp simd linear(x) private(x)
for (i = 0; i < 16; ++i)
;
// expected-warning@+1 {{zero linear step (x and other variables in clause should probably be const)}}
#pragma omp simd linear(x, y : 0)
for (i = 0; i < 16; ++i)
;
// expected-note@+2 {{defined as linear}}
// expected-error@+1 {{linear variable cannot be lastprivate}}
#pragma omp simd linear(x) lastprivate(x)
for (i = 0; i < 16; ++i)
;
// expected-note@+2 {{defined as lastprivate}}
// expected-error@+1 {{lastprivate variable cannot be linear}}
#pragma omp simd lastprivate(x) linear(x)
for (i = 0; i < 16; ++i)
;
}
void test_aligned() {
int i;
// expected-error@+1 {{expected expression}} expected-error@+1 {{expected ')'}} expected-note@+1 {{to match this '('}}
#pragma omp simd aligned(
for (i = 0; i < 16; ++i)
;
// expected-error@+2 {{expected expression}}
// expected-error@+1 {{expected expression}} expected-error@+1 {{expected ')'}} expected-note@+1 {{to match this '('}}
#pragma omp simd aligned(,
for (i = 0; i < 16; ++i)
;
// expected-error@+2 {{expected expression}}
// expected-error@+1 {{expected expression}}
#pragma omp simd aligned(, )
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{expected expression}}
#pragma omp simd aligned()
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{expected expression}}
#pragma omp simd aligned(int)
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{expected variable name}}
#pragma omp simd aligned(0)
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{use of undeclared identifier 'x'}}
#pragma omp simd aligned(x)
for (i = 0; i < 16; ++i)
;
// expected-error@+2 {{use of undeclared identifier 'x'}}
// expected-error@+1 {{use of undeclared identifier 'y'}}
#pragma omp simd aligned(x, y)
for (i = 0; i < 16; ++i)
;
// expected-error@+3 {{use of undeclared identifier 'x'}}
// expected-error@+2 {{use of undeclared identifier 'y'}}
// expected-error@+1 {{use of undeclared identifier 'z'}}
#pragma omp simd aligned(x, y, z)
for (i = 0; i < 16; ++i)
;
int *x, y, z[25]; // expected-note 4 {{'y' defined here}}
#pragma omp simd aligned(x)
for (i = 0; i < 16; ++i)
;
#pragma omp simd aligned(z)
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{expected expression}}
#pragma omp simd aligned(x :)
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{expected expression}} expected-error@+1 {{expected ')'}} expected-note@+1 {{to match this '('}}
#pragma omp simd aligned(x :, )
for (i = 0; i < 16; ++i)
;
#pragma omp simd aligned(x : 1)
for (i = 0; i < 16; ++i)
;
#pragma omp simd aligned(x : 2 * 2)
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{expected ')'}} expected-note@+1 {{to match this '('}}
#pragma omp simd aligned(x : 1, y)
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{expected ')'}} expected-note@+1 {{to match this '('}}
#pragma omp simd aligned(x : 1, y, z : 1)
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{argument of aligned clause should be array or pointer, not 'int'}}
#pragma omp simd aligned(x, y)
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{argument of aligned clause should be array or pointer, not 'int'}}
#pragma omp simd aligned(x, y, z)
for (i = 0; i < 16; ++i)
;
// expected-note@+2 {{defined as aligned}}
// expected-error@+1 {{a variable cannot appear in more than one aligned clause}}
#pragma omp simd aligned(x) aligned(z, x)
for (i = 0; i < 16; ++i)
;
// expected-note@+3 {{defined as aligned}}
// expected-error@+2 {{a variable cannot appear in more than one aligned clause}}
// expected-error@+1 2 {{argument of aligned clause should be array or pointer, not 'int'}}
#pragma omp simd aligned(x, y, z) aligned(y, z)
for (i = 0; i < 16; ++i)
;
}
void test_private() {
int i;
// expected-error@+2 {{expected expression}}
// expected-error@+1 {{expected ')'}} expected-note@+1 {{to match this '('}}
#pragma omp simd private(
for (i = 0; i < 16; ++i)
;
// expected-error@+2 {{expected ')'}} expected-note@+2 {{to match this '('}}
// expected-error@+1 2 {{expected expression}}
#pragma omp simd private(,
for (i = 0; i < 16; ++i)
;
// expected-error@+1 2 {{expected expression}}
#pragma omp simd private(, )
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{expected expression}}
#pragma omp simd private()
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{expected expression}}
#pragma omp simd private(int)
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{expected variable name}}
#pragma omp simd private(0)
for (i = 0; i < 16; ++i)
;
int x, y, z;
#pragma omp simd private(x)
for (i = 0; i < 16; ++i)
;
#pragma omp simd private(x, y)
for (i = 0; i < 16; ++i)
;
#pragma omp simd private(x, y, z)
for (i = 0; i < 16; ++i) {
x = y * i + z;
}
}
void test_firstprivate() {
int i;
// expected-error@+3 {{expected ')'}} expected-note@+3 {{to match this '('}}
// expected-error@+2 {{unexpected OpenMP clause 'firstprivate' in directive '#pragma omp simd'}}
// expected-error@+1 {{expected expression}}
#pragma omp simd firstprivate(
for (i = 0; i < 16; ++i)
;
}
void test_lastprivate() {
int i;
// expected-error@+2 {{expected ')'}} expected-note@+2 {{to match this '('}}
// expected-error@+1 {{expected expression}}
#pragma omp simd lastprivate(
for (i = 0; i < 16; ++i)
;
// expected-error@+2 {{expected ')'}} expected-note@+2 {{to match this '('}}
// expected-error@+1 2 {{expected expression}}
#pragma omp simd lastprivate(,
for (i = 0; i < 16; ++i)
;
// expected-error@+1 2 {{expected expression}}
#pragma omp simd lastprivate(, )
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{expected expression}}
#pragma omp simd lastprivate()
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{expected expression}}
#pragma omp simd lastprivate(int)
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{expected variable name}}
#pragma omp simd lastprivate(0)
for (i = 0; i < 16; ++i)
;
int x, y, z;
#pragma omp simd lastprivate(x)
for (i = 0; i < 16; ++i)
;
#pragma omp simd lastprivate(x, y)
for (i = 0; i < 16; ++i)
;
#pragma omp simd lastprivate(x, y, z)
for (i = 0; i < 16; ++i)
;
}
void test_reduction() {
int i, x, y;
// expected-error@+3 {{expected ')'}} expected-note@+3 {{to match this '('}}
// expected-error@+2 {{expected identifier}}
// expected-warning@+1 {{missing ':' after reduction identifier - ignoring}}
#pragma omp simd reduction(
for (i = 0; i < 16; ++i)
;
// expected-error@+2 {{expected identifier}}
// expected-warning@+1 {{missing ':' after reduction identifier - ignoring}}
#pragma omp simd reduction()
for (i = 0; i < 16; ++i)
;
// expected-error@+2 {{expected expression}}
// expected-warning@+1 {{missing ':' after reduction identifier - ignoring}}
#pragma omp simd reduction(x)
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{expected identifier}}
#pragma omp simd reduction( : x)
for (i = 0; i < 16; ++i)
;
// expected-error@+3 {{expected ')'}} expected-note@+3 {{to match this '('}}
// expected-error@+2 {{expected identifier}}
// expected-warning@+1 {{missing ':' after reduction identifier - ignoring}}
#pragma omp simd reduction(,
for (i = 0; i < 16; ++i)
;
// expected-error@+3 {{expected ')'}} expected-note@+3 {{to match this '('}}
// expected-error@+2 {{expected expression}}
// expected-warning@+1 {{missing ':' after reduction identifier - ignoring}}
#pragma omp simd reduction(+
for (i = 0; i < 16; ++i)
;
// expected-error@+3 {{expected ')'}} expected-note@+3 {{to match this '('}}
//
// expected-error@+1 {{expected expression}}
#pragma omp simd reduction(+:
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{expected expression}}
#pragma omp simd reduction(+ :)
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{expected expression}}
#pragma omp simd reduction(+ :, y)
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{expected expression}}
#pragma omp simd reduction(+ : x, + : y)
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{expected identifier}}
#pragma omp simd reduction(% : x)
for (i = 0; i < 16; ++i)
;
#pragma omp simd reduction(+ : x)
for (i = 0; i < 16; ++i)
;
#pragma omp simd reduction(* : x)
for (i = 0; i < 16; ++i)
;
#pragma omp simd reduction(- : x)
for (i = 0; i < 16; ++i)
;
#pragma omp simd reduction(& : x)
for (i = 0; i < 16; ++i)
;
#pragma omp simd reduction(| : x)
for (i = 0; i < 16; ++i)
;
#pragma omp simd reduction(^ : x)
for (i = 0; i < 16; ++i)
;
#pragma omp simd reduction(&& : x)
for (i = 0; i < 16; ++i)
;
#pragma omp simd reduction(|| : x)
for (i = 0; i < 16; ++i)
;
#pragma omp simd reduction(max : x)
for (i = 0; i < 16; ++i)
;
#pragma omp simd reduction(min : x)
for (i = 0; i < 16; ++i)
;
struct X {
int x;
};
struct X X;
// expected-error@+1 {{expected variable name}}
#pragma omp simd reduction(+ : X.x)
for (i = 0; i < 16; ++i)
;
// expected-error@+1 {{expected variable name}}
#pragma omp simd reduction(+ : x + x)
for (i = 0; i < 16; ++i)
;
}
void test_loop_messages() {
float a[100], b[100], c[100];
// expected-error@+2 {{variable must be of integer or pointer type}}
#pragma omp simd
for (float fi = 0; fi < 10.0; fi++) {
c[(int)fi] = a[(int)fi] + b[(int)fi];
}
// expected-error@+2 {{variable must be of integer or pointer type}}
#pragma omp simd
for (double fi = 0; fi < 10.0; fi++) {
c[(int)fi] = a[(int)fi] + b[(int)fi];
}
}
void linear_modifiers(int argc) {
int f;
#pragma omp simd linear(f)
for (int k = 0; k < argc; ++k) ++k;
#pragma omp simd linear(val(f))
for (int k = 0; k < argc; ++k) ++k;
#pragma omp simd linear(uval(f)) // expected-error {{expected 'val' modifier}}
for (int k = 0; k < argc; ++k) ++k;
#pragma omp simd linear(ref(f)) // expected-error {{expected 'val' modifier}}
for (int k = 0; k < argc; ++k) ++k;
#pragma omp simd linear(foo(f)) // expected-error {{expected 'val' modifier}}
for (int k = 0; k < argc; ++k) ++k;
}
|
sum_v2.c | /*
* Assignment 2 (CSE436)
* Kazumi Malhan
* 06/08/2016
*
* Sum of A[N]
*/
#include <stdio.h>
#include <stdlib.h>
#include <math.h>
#include <string.h>
#include <sys/timeb.h>
/* read timer in second */
double read_timer() {
struct timeb tm;
ftime(&tm);
return (double) tm.time + (double) tm.millitm / 1000.0;
}
/* read timer in ms */
double read_timer_ms() {
struct timeb tm;
ftime(&tm);
return (double) tm.time * 1000.0 + (double) tm.millitm;
}
#define REAL float
#define VECTOR_LENGTH 102400
/* initialize a vector with random floating point numbers */
void init(REAL *A, int N) {
int i;
for (i = 0; i < N; i++) {
A[i] = (double) drand48();
}
}
/* Function Prototypes */
REAL sum (int N, REAL *A);
REAL sum_omp_parallel (int N, REAL *A, int num_tasks);
REAL sum_omp_parallel_for (int N, REAL *A, int num_tasks);
/*
* To compile: gcc sum.c -fopenmp -o sum
* To run: ./sum N num_tasks
*/
int main(int argc, char *argv[]) {
int N = VECTOR_LENGTH;
int num_tasks = 4;
double elapsed_serial, elapsed_para, elapsed_para_for; /* for timing */
if (argc < 3) {
fprintf(stderr, "Usage: sum [<N(%d)>] [<#tasks(%d)>]\n", N,num_tasks);
fprintf(stderr, "\t Example: ./sum %d %d\n", N,num_tasks);
} else {
N = atoi(argv[1]);
num_tasks = atoi(argv[2]);
}
REAL *A = (REAL*)malloc(sizeof(REAL)*N);
srand48((1 << 12));
init(A, N);
/* Serial Run */
elapsed_serial = read_timer();
REAL result = sum(N, A);
elapsed_serial = (read_timer() - elapsed_serial);
/* Parallel Run */
elapsed_para = read_timer();
result = sum_omp_parallel(N, A, num_tasks);
elapsed_para = (read_timer() - elapsed_para);
/* Parallel For Run */
elapsed_para_for = read_timer();
result = sum_omp_parallel_for(N, A, num_tasks);
elapsed_para_for = (read_timer() - elapsed_para_for);
/* you should add the call to each function and time the execution */
printf("======================================================================================================\n");
printf("\tSum %d numbers with %d tasks\n", N, num_tasks);
printf("------------------------------------------------------------------------------------------------------\n");
printf("Performance:\t\tRuntime (ms)\t MFLOPS \n");
printf("------------------------------------------------------------------------------------------------------\n");
printf("Sum Serial:\t\t\t%4f\t%4f\n", elapsed_serial * 1.0e3, 2*N / (1.0e6 * elapsed_serial));
printf("Sum Parallel:\t\t\t%4f\t%4f\n", elapsed_para * 1.0e3, 2*N / (1.0e6 * elapsed_para));
printf("Sum Parallel For:\t\t%4f\t%4f\n", elapsed_para_for * 1.0e3, 2*N / (1.0e6 * elapsed_para_for));
free(A);
return 0;
}
/* Serial Implemenration */
REAL sum(int N, REAL *A) {
int i;
REAL result = 0.0;
for (i = 0; i < N; ++i)
result += A[i];
return result;
}
/* Parallel Implemenration */
REAL sum_omp_parallel (int N, REAL *A, int num_tasks) {
REAL result = 0.0;
int partial_result[num_tasks];
int t;
/* Determine if task can be evenly distrubutable */
int each_task = N / num_tasks;
int leftover = N - (each_task * num_tasks);
#pragma omp parallel shared (N, A, num_tasks, leftover) num_threads(num_tasks)
{
int i, tid, istart, iend;
REAL temp;
tid = omp_get_thread_num();
istart = tid * (N / num_tasks);
iend = (tid + 1) * (N / num_tasks);
for (i = istart; i < iend; ++i) {
temp += A[i];
}
/* Take care left over */
if (tid < leftover) {
temp += A[N - tid - 1];
}
partial_result[tid] = temp;
} // end of parallel
/* Add result together */
for(t=0; t<num_tasks; t++)
result += partial_result[t];
return result;
}
/* Parallel For Implemenration */
REAL sum_omp_parallel_for (int N, REAL *A, int num_tasks) {
int i;
REAL result = 0.0;
# pragma omp parallel shared (N, A, result) private (i) num_threads(num_tasks)
{
# pragma omp for schedule(runtime) reduction (+:result) nowait
for (i = 0; i < N; ++i) {
result += A[i];
}
} // end of parallel
return result;
}
|
computeQ.c | /***************************************************************************
*cr
*cr (C) Copyright 2007 The Board of Trustees of the
*cr University of Illinois
*cr All Rights Reserved
*cr
***************************************************************************/
#ifdef SPEC_NO_INLINE
#define INLINE
#else
#ifdef SPEC_NO_STATIC_INLINE
#define INLINE inline
#else
#define INLINE static inline
#endif
#endif
#define PI 3.1415926535897932384626433832795029f
#define PIx2 6.2831853071795864769252867665590058f
#define MIN(X,Y) ((X) < (Y) ? (X) : (Y))
#define K_ELEMS_PER_GRID 2048
struct kValues {
float Kx;
float Ky;
float Kz;
float PhiMag;
};
INLINE
void
ComputePhiMagCPU(int numK,
float* phiR, float* phiI, float* phiMag) {
int indexK = 0;
#pragma omp target map(from:phiMag[0:numK]) map(to:phiR[0:numK],phiI[0:numK])
#pragma omp teams distribute parallel for simd
for (indexK = 0; indexK < numK; indexK++) {
float real = phiR[indexK];
float imag = phiI[indexK];
phiMag[indexK] = real*real + imag*imag;
}
}
INLINE
void
ComputeQCPU(int numK, int numX,
struct kValues *kVals,
float* x, float* y, float* z,
float *Qr, float *Qi) {
float expArg;
float cosArg;
float sinArg;
int indexK, indexX;
#pragma omp target map(to:kVals[0:numK], x[0:numX], y[0:numX], z[0:numX]), \
map(tofrom:Qr[0:numX], Qi[0:numX])
{
#pragma omp teams distribute parallel for private(expArg, cosArg, sinArg)
for (indexX = 0; indexX < numX; indexX++) {
float QrSum = 0.0;
float QiSum = 0.0;
#pragma omp simd private(expArg, cosArg, sinArg) reduction(+:QrSum, QiSum)
for (indexK = 0; indexK < numK; indexK++) {
expArg = PIx2 * (kVals[indexK].Kx * x[indexX] +
kVals[indexK].Ky * y[indexX] +
kVals[indexK].Kz * z[indexX]);
cosArg = cosf(expArg);
sinArg = sinf(expArg);
float phi = kVals[indexK].PhiMag;
QrSum += phi * cosArg;
QiSum += phi * sinArg;
}
Qr[indexX] += QrSum;
Qi[indexX] += QiSum;
}
}
}
void createDataStructsCPU(int numK, int numX, float** phiMag,
float** Qr, float** Qi)
{
size_t alignment = SPEC_ALIGNMENT_SIZE;
*phiMag = (float* ) memalign(alignment, numK * sizeof(float));
*Qr = (float*) memalign(alignment, numX * sizeof (float));
memset((void *)*Qr, 0, numX * sizeof(float));
*Qi = (float*) memalign(alignment, numX * sizeof (float));
memset((void *)*Qi, 0, numX * sizeof(float));
}
|
symm_x_dia_n_hi_col_conj.c | #include "alphasparse/kernel.h"
#include "alphasparse/util.h"
#include "alphasparse/opt.h"
#ifdef _OPENMP
#include <omp.h>
#endif
alphasparse_status_t ONAME(const ALPHA_Number alpha, const ALPHA_SPMAT_DIA *mat, const ALPHA_Number *x, const ALPHA_INT columns, const ALPHA_INT ldx, const ALPHA_Number beta, ALPHA_Number *y, const ALPHA_INT ldy)
{
#ifdef COMPLEX
ALPHA_INT num_threads = alpha_get_thread_num();
#ifdef _OPENMP
#pragma omp parallel for num_threads(num_threads)
#endif
for (ALPHA_INT cc = 0; cc < columns; ++cc)
{
ALPHA_Number* Y = &y[index2(cc,0,ldy)];
for (ALPHA_INT i = 0; i < mat->rows; i++)
alpha_mul(Y[i],Y[i],beta);
const ALPHA_Number* X = &x[index2(cc,0,ldx)];
for(ALPHA_INT di = 0; di < mat->ndiag;++di){
ALPHA_INT d = mat->distance[di];
if(d > 0){
ALPHA_INT ars = alpha_max(0,-d);
ALPHA_INT acs = alpha_max(0,d);
ALPHA_INT an = alpha_min(mat->rows - ars,mat->cols - acs);
for(ALPHA_INT i = 0; i < an; ++i){
ALPHA_INT ar = ars + i;
ALPHA_INT ac = acs + i;
ALPHA_Number val;
alpha_mul_2c(val,mat->values[index2(di,ar,mat->lval)],alpha);
alpha_madde(Y[ar],val,X[ac]);
alpha_madde(Y[ac],val,X[ar]);
}
}
if(d == 0){
for(ALPHA_INT r = 0; r < mat->rows; ++r){
ALPHA_Number val;
alpha_mul_2c(val,mat->values[index2(di,r,mat->lval)],alpha);
alpha_madde(Y[r],val,X[r]);
}
}
}
}
return ALPHA_SPARSE_STATUS_SUCCESS;
#else
return ALPHA_SPARSE_STATUS_INVALID_VALUE;
#endif
}
|
updater_basemaker-inl.h | /*!
* Copyright 2014 by Contributors
* \file updater_basemaker-inl.h
* \brief implement a common tree constructor
* \author Tianqi Chen
*/
#ifndef XGBOOST_TREE_UPDATER_BASEMAKER_INL_H_
#define XGBOOST_TREE_UPDATER_BASEMAKER_INL_H_
#include <xgboost/base.h>
#include <xgboost/tree_updater.h>
#include <vector>
#include <algorithm>
#include <string>
#include <limits>
#include <utility>
#include "./param.h"
#include "../common/sync.h"
#include "../common/io.h"
#include "../common/random.h"
#include "../common/quantile.h"
namespace xgboost {
namespace tree {
/*!
* \brief base tree maker class that defines common operation
* needed in tree making
*/
class BaseMaker: public TreeUpdater {
public:
void Init(const std::vector<std::pair<std::string, std::string> >& args) override {
param.InitAllowUnknown(args);
}
protected:
// helper to collect and query feature meta information
struct FMetaHelper {
public:
/*! \brief find type of each feature, use column format */
inline void InitByCol(DMatrix* p_fmat,
const RegTree& tree) {
fminmax.resize(tree.param.num_feature * 2);
std::fill(fminmax.begin(), fminmax.end(),
-std::numeric_limits<bst_float>::max());
// start accumulating statistics
dmlc::DataIter<ColBatch>* iter = p_fmat->ColIterator();
iter->BeforeFirst();
while (iter->Next()) {
const ColBatch& batch = iter->Value();
for (bst_uint i = 0; i < batch.size; ++i) {
const bst_uint fid = batch.col_index[i];
const ColBatch::Inst& c = batch[i];
if (c.length != 0) {
fminmax[fid * 2 + 0] = std::max(-c[0].fvalue, fminmax[fid * 2 + 0]);
fminmax[fid * 2 + 1] = std::max(c[c.length - 1].fvalue, fminmax[fid * 2 + 1]);
}
}
}
rabit::Allreduce<rabit::op::Max>(dmlc::BeginPtr(fminmax), fminmax.size());
}
// get feature type, 0:empty 1:binary 2:real
inline int Type(bst_uint fid) const {
CHECK_LT(fid * 2 + 1, fminmax.size())
<< "FeatHelper fid exceed query bound ";
bst_float a = fminmax[fid * 2];
bst_float b = fminmax[fid * 2 + 1];
if (a == -std::numeric_limits<bst_float>::max()) return 0;
if (-a == b) {
return 1;
} else {
return 2;
}
}
inline bst_float MaxValue(bst_uint fid) const {
return fminmax[fid *2 + 1];
}
inline void SampleCol(float p, std::vector<bst_uint> *p_findex) const {
std::vector<bst_uint> &findex = *p_findex;
findex.clear();
for (size_t i = 0; i < fminmax.size(); i += 2) {
const bst_uint fid = static_cast<bst_uint>(i / 2);
if (this->Type(fid) != 0) findex.push_back(fid);
}
unsigned n = static_cast<unsigned>(p * findex.size());
std::shuffle(findex.begin(), findex.end(), common::GlobalRandom());
findex.resize(n);
// sync the findex if it is subsample
std::string s_cache;
common::MemoryBufferStream fc(&s_cache);
dmlc::Stream& fs = fc;
if (rabit::GetRank() == 0) {
fs.Write(findex);
}
rabit::Broadcast(&s_cache, 0);
fs.Read(&findex);
}
private:
std::vector<bst_float> fminmax;
};
// ------static helper functions ------
// helper function to get to next level of the tree
/*! \brief this is helper function for row based data*/
inline static int NextLevel(const RowBatch::Inst &inst, const RegTree &tree, int nid) {
const RegTree::Node &n = tree[nid];
bst_uint findex = n.split_index();
for (unsigned i = 0; i < inst.length; ++i) {
if (findex == inst[i].index) {
if (inst[i].fvalue < n.split_cond()) {
return n.cleft();
} else {
return n.cright();
}
}
}
return n.cdefault();
}
/*! \brief get number of omp thread in current context */
inline static int get_nthread() {
int nthread;
#pragma omp parallel
{
nthread = omp_get_num_threads();
}
return nthread;
}
// ------class member helpers---------
/*! \brief initialize temp data structure */
inline void InitData(const std::vector<bst_gpair> &gpair,
const DMatrix &fmat,
const RegTree &tree) {
CHECK_EQ(tree.param.num_nodes, tree.param.num_roots)
<< "TreeMaker: can only grow new tree";
const std::vector<unsigned> &root_index = fmat.info().root_index;
{
// setup position
position.resize(gpair.size());
if (root_index.size() == 0) {
std::fill(position.begin(), position.end(), 0);
} else {
for (size_t i = 0; i < position.size(); ++i) {
position[i] = root_index[i];
CHECK_LT(root_index[i], (unsigned)tree.param.num_roots)
<< "root index exceed setting";
}
}
// mark delete for the deleted datas
for (size_t i = 0; i < position.size(); ++i) {
if (gpair[i].hess < 0.0f) position[i] = ~position[i];
}
// mark subsample
if (param.subsample < 1.0f) {
std::bernoulli_distribution coin_flip(param.subsample);
auto& rnd = common::GlobalRandom();
for (size_t i = 0; i < position.size(); ++i) {
if (gpair[i].hess < 0.0f) continue;
if (!coin_flip(rnd)) position[i] = ~position[i];
}
}
}
{
// expand query
qexpand.reserve(256); qexpand.clear();
for (int i = 0; i < tree.param.num_roots; ++i) {
qexpand.push_back(i);
}
this->UpdateNode2WorkIndex(tree);
}
}
/*! \brief update queue expand add in new leaves */
inline void UpdateQueueExpand(const RegTree &tree) {
std::vector<int> newnodes;
for (size_t i = 0; i < qexpand.size(); ++i) {
const int nid = qexpand[i];
if (!tree[nid].is_leaf()) {
newnodes.push_back(tree[nid].cleft());
newnodes.push_back(tree[nid].cright());
}
}
// use new nodes for qexpand
qexpand = newnodes;
this->UpdateNode2WorkIndex(tree);
}
// return decoded position
inline int DecodePosition(bst_uint ridx) const {
const int pid = position[ridx];
return pid < 0 ? ~pid : pid;
}
// encode the encoded position value for ridx
inline void SetEncodePosition(bst_uint ridx, int nid) {
if (position[ridx] < 0) {
position[ridx] = ~nid;
} else {
position[ridx] = nid;
}
}
/*!
* \brief this is helper function uses column based data structure,
* reset the positions to the lastest one
* \param nodes the set of nodes that contains the split to be used
* \param p_fmat feature matrix needed for tree construction
* \param tree the regression tree structure
*/
inline void ResetPositionCol(const std::vector<int> &nodes,
DMatrix *p_fmat,
const RegTree &tree) {
// set the positions in the nondefault
this->SetNonDefaultPositionCol(nodes, p_fmat, tree);
this->SetDefaultPostion(p_fmat, tree);
}
/*!
* \brief helper function to set the non-leaf positions to default direction.
* This function can be applied multiple times and will get the same result.
* \param p_fmat feature matrix needed for tree construction
* \param tree the regression tree structure
*/
inline void SetDefaultPostion(DMatrix *p_fmat,
const RegTree &tree) {
// set rest of instances to default position
const RowSet &rowset = p_fmat->buffered_rowset();
// set default direct nodes to default
// for leaf nodes that are not fresh, mark then to ~nid,
// so that they are ignored in future statistics collection
const bst_omp_uint ndata = static_cast<bst_omp_uint>(rowset.size());
#pragma omp parallel for schedule(static)
for (bst_omp_uint i = 0; i < ndata; ++i) {
const bst_uint ridx = rowset[i];
const int nid = this->DecodePosition(ridx);
if (tree[nid].is_leaf()) {
// mark finish when it is not a fresh leaf
if (tree[nid].cright() == -1) {
position[ridx] = ~nid;
}
} else {
// push to default branch
if (tree[nid].default_left()) {
this->SetEncodePosition(ridx, tree[nid].cleft());
} else {
this->SetEncodePosition(ridx, tree[nid].cright());
}
}
}
}
/*!
* \brief this is helper function uses column based data structure,
* to CORRECT the positions of non-default directions that WAS set to default
* before calling this function.
* \param batch The column batch
* \param sorted_split_set The set of index that contains split solutions.
* \param tree the regression tree structure
*/
inline void CorrectNonDefaultPositionByBatch(
const ColBatch& batch,
const std::vector<bst_uint> &sorted_split_set,
const RegTree &tree) {
for (size_t i = 0; i < batch.size; ++i) {
ColBatch::Inst col = batch[i];
const bst_uint fid = batch.col_index[i];
auto it = std::lower_bound(sorted_split_set.begin(), sorted_split_set.end(), fid);
if (it != sorted_split_set.end() && *it == fid) {
const bst_omp_uint ndata = static_cast<bst_omp_uint>(col.length);
#pragma omp parallel for schedule(static)
for (bst_omp_uint j = 0; j < ndata; ++j) {
const bst_uint ridx = col[j].index;
const float fvalue = col[j].fvalue;
const int nid = this->DecodePosition(ridx);
CHECK(tree[nid].is_leaf());
int pid = tree[nid].parent();
// go back to parent, correct those who are not default
if (!tree[nid].is_root() && tree[pid].split_index() == fid) {
if (fvalue < tree[pid].split_cond()) {
this->SetEncodePosition(ridx, tree[pid].cleft());
} else {
this->SetEncodePosition(ridx, tree[pid].cright());
}
}
}
}
}
}
/*!
* \brief this is helper function uses column based data structure,
* \param nodes the set of nodes that contains the split to be used
* \param tree the regression tree structure
* \param out_split_set The split index set
*/
inline void GetSplitSet(const std::vector<int> &nodes,
const RegTree &tree,
std::vector<unsigned>* out_split_set) {
std::vector<unsigned>& fsplits = *out_split_set;
fsplits.clear();
// step 1, classify the non-default data into right places
for (size_t i = 0; i < nodes.size(); ++i) {
const int nid = nodes[i];
if (!tree[nid].is_leaf()) {
fsplits.push_back(tree[nid].split_index());
}
}
std::sort(fsplits.begin(), fsplits.end());
fsplits.resize(std::unique(fsplits.begin(), fsplits.end()) - fsplits.begin());
}
/*!
* \brief this is helper function uses column based data structure,
* update all positions into nondefault branch, if any, ignore the default branch
* \param nodes the set of nodes that contains the split to be used
* \param p_fmat feature matrix needed for tree construction
* \param tree the regression tree structure
*/
virtual void SetNonDefaultPositionCol(const std::vector<int> &nodes,
DMatrix *p_fmat,
const RegTree &tree) {
std::vector<unsigned> fsplits;
this->GetSplitSet(nodes, tree, &fsplits);
dmlc::DataIter<ColBatch> *iter = p_fmat->ColIterator(fsplits);
while (iter->Next()) {
const ColBatch &batch = iter->Value();
for (size_t i = 0; i < batch.size; ++i) {
ColBatch::Inst col = batch[i];
const bst_uint fid = batch.col_index[i];
const bst_omp_uint ndata = static_cast<bst_omp_uint>(col.length);
#pragma omp parallel for schedule(static)
for (bst_omp_uint j = 0; j < ndata; ++j) {
const bst_uint ridx = col[j].index;
const float fvalue = col[j].fvalue;
const int nid = this->DecodePosition(ridx);
// go back to parent, correct those who are not default
if (!tree[nid].is_leaf() && tree[nid].split_index() == fid) {
if (fvalue < tree[nid].split_cond()) {
this->SetEncodePosition(ridx, tree[nid].cleft());
} else {
this->SetEncodePosition(ridx, tree[nid].cright());
}
}
}
}
}
}
/*! \brief helper function to get statistics from a tree */
template<typename TStats>
inline void GetNodeStats(const std::vector<bst_gpair> &gpair,
const DMatrix &fmat,
const RegTree &tree,
std::vector< std::vector<TStats> > *p_thread_temp,
std::vector<TStats> *p_node_stats) {
std::vector< std::vector<TStats> > &thread_temp = *p_thread_temp;
const MetaInfo &info = fmat.info();
thread_temp.resize(this->get_nthread());
p_node_stats->resize(tree.param.num_nodes);
#pragma omp parallel
{
const int tid = omp_get_thread_num();
thread_temp[tid].resize(tree.param.num_nodes, TStats(param));
for (size_t i = 0; i < qexpand.size(); ++i) {
const unsigned nid = qexpand[i];
thread_temp[tid][nid].Clear();
}
}
const RowSet &rowset = fmat.buffered_rowset();
// setup position
const bst_omp_uint ndata = static_cast<bst_omp_uint>(rowset.size());
#pragma omp parallel for schedule(static)
for (bst_omp_uint i = 0; i < ndata; ++i) {
const bst_uint ridx = rowset[i];
const int nid = position[ridx];
const int tid = omp_get_thread_num();
if (nid >= 0) {
thread_temp[tid][nid].Add(gpair, info, ridx);
}
}
// sum the per thread statistics together
for (size_t j = 0; j < qexpand.size(); ++j) {
const int nid = qexpand[j];
TStats &s = (*p_node_stats)[nid];
s.Clear();
for (size_t tid = 0; tid < thread_temp.size(); ++tid) {
s.Add(thread_temp[tid][nid]);
}
}
}
/*! \brief common helper data structure to build sketch */
struct SketchEntry {
/*! \brief total sum of amount to be met */
double sum_total;
/*! \brief statistics used in the sketch */
double rmin, wmin;
/*! \brief last seen feature value */
bst_float last_fvalue;
/*! \brief current size of sketch */
double next_goal;
// pointer to the sketch to put things in
common::WXQuantileSketch<bst_float, bst_float> *sketch;
// initialize the space
inline void Init(unsigned max_size) {
next_goal = -1.0f;
rmin = wmin = 0.0f;
sketch->temp.Reserve(max_size + 1);
sketch->temp.size = 0;
}
/*!
* \brief push a new element to sketch
* \param fvalue feature value, comes in sorted ascending order
* \param w weight
* \param max_size
*/
inline void Push(bst_float fvalue, bst_float w, unsigned max_size) {
if (next_goal == -1.0f) {
next_goal = 0.0f;
last_fvalue = fvalue;
wmin = w;
return;
}
if (last_fvalue != fvalue) {
double rmax = rmin + wmin;
if (rmax >= next_goal && sketch->temp.size != max_size) {
if (sketch->temp.size == 0 ||
last_fvalue > sketch->temp.data[sketch->temp.size-1].value) {
// push to sketch
sketch->temp.data[sketch->temp.size] =
common::WXQuantileSketch<bst_float, bst_float>::
Entry(static_cast<bst_float>(rmin),
static_cast<bst_float>(rmax),
static_cast<bst_float>(wmin), last_fvalue);
CHECK_LT(sketch->temp.size, max_size)
<< "invalid maximum size max_size=" << max_size
<< ", stemp.size" << sketch->temp.size;
++sketch->temp.size;
}
if (sketch->temp.size == max_size) {
next_goal = sum_total * 2.0f + 1e-5f;
} else {
next_goal = static_cast<bst_float>(sketch->temp.size * sum_total / max_size);
}
} else {
if (rmax >= next_goal) {
LOG(TRACKER) << "INFO: rmax=" << rmax
<< ", sum_total=" << sum_total
<< ", naxt_goal=" << next_goal
<< ", size=" << sketch->temp.size;
}
}
rmin = rmax;
wmin = w;
last_fvalue = fvalue;
} else {
wmin += w;
}
}
/*! \brief push final unfinished value to the sketch */
inline void Finalize(unsigned max_size) {
double rmax = rmin + wmin;
if (sketch->temp.size == 0 || last_fvalue > sketch->temp.data[sketch->temp.size-1].value) {
CHECK_LE(sketch->temp.size, max_size)
<< "Finalize: invalid maximum size, max_size=" << max_size
<< ", stemp.size=" << sketch->temp.size;
// push to sketch
sketch->temp.data[sketch->temp.size] =
common::WXQuantileSketch<bst_float, bst_float>::
Entry(static_cast<bst_float>(rmin),
static_cast<bst_float>(rmax),
static_cast<bst_float>(wmin), last_fvalue);
++sketch->temp.size;
}
sketch->PushTemp();
}
};
/*! \brief training parameter of tree grower */
TrainParam param;
/*! \brief queue of nodes to be expanded */
std::vector<int> qexpand;
/*!
* \brief map active node to is working index offset in qexpand,
* can be -1, which means the node is node actively expanding
*/
std::vector<int> node2workindex;
/*!
* \brief position of each instance in the tree
* can be negative, which means this position is no longer expanding
* see also Decode/EncodePosition
*/
std::vector<int> position;
private:
inline void UpdateNode2WorkIndex(const RegTree &tree) {
// update the node2workindex
std::fill(node2workindex.begin(), node2workindex.end(), -1);
node2workindex.resize(tree.param.num_nodes);
for (size_t i = 0; i < qexpand.size(); ++i) {
node2workindex[qexpand[i]] = static_cast<int>(i);
}
}
};
} // namespace tree
} // namespace xgboost
#endif // XGBOOST_TREE_UPDATER_BASEMAKER_INL_H_
|
3d7pt.c | /*
* Order-1, 3D 7 point stencil
* Adapted from PLUTO and Pochoir test bench
*
* Tareq Malas
*/
#include <stdio.h>
#include <stdlib.h>
#include <sys/time.h>
#ifdef LIKWID_PERFMON
#include <likwid.h>
#endif
#include "print_utils.h"
#define TESTS 2
#define MAX(a,b) ((a) > (b) ? a : b)
#define MIN(a,b) ((a) < (b) ? a : b)
/* Subtract the `struct timeval' values X and Y,
* storing the result in RESULT.
*
* Return 1 if the difference is negative, otherwise 0.
*/
int timeval_subtract(struct timeval *result, struct timeval *x, struct timeval *y)
{
/* Perform the carry for the later subtraction by updating y. */
if (x->tv_usec < y->tv_usec)
{
int nsec = (y->tv_usec - x->tv_usec) / 1000000 + 1;
y->tv_usec -= 1000000 * nsec;
y->tv_sec += nsec;
}
if (x->tv_usec - y->tv_usec > 1000000)
{
int nsec = (x->tv_usec - y->tv_usec) / 1000000;
y->tv_usec += 1000000 * nsec;
y->tv_sec -= nsec;
}
/* Compute the time remaining to wait.
* tv_usec is certainly positive.
*/
result->tv_sec = x->tv_sec - y->tv_sec;
result->tv_usec = x->tv_usec - y->tv_usec;
/* Return 1 if result is negative. */
return x->tv_sec < y->tv_sec;
}
int main(int argc, char *argv[])
{
int t, i, j, k, test;
int Nx, Ny, Nz, Nt;
if (argc > 3) {
Nx = atoi(argv[1])+2;
Ny = atoi(argv[2])+2;
Nz = atoi(argv[3])+2;
}
if (argc > 4)
Nt = atoi(argv[4]);
double ****A = (double ****) malloc(sizeof(double***)*2);
A[0] = (double ***) malloc(sizeof(double**)*Nz);
A[1] = (double ***) malloc(sizeof(double**)*Nz);
for(i=0; i<Nz; i++){
A[0][i] = (double**) malloc(sizeof(double*)*Ny);
A[1][i] = (double**) malloc(sizeof(double*)*Ny);
for(j=0;j<Ny;j++){
A[0][i][j] = (double*) malloc(sizeof(double)*Nx);
A[1][i][j] = (double*) malloc(sizeof(double)*Nx);
}
}
// tile size information, including extra element to decide the list length
int *tile_size = (int*) malloc(sizeof(int));
tile_size[0] = -1;
// The list is modified here before source-to-source transformations
tile_size = (int*) realloc((void *)tile_size, sizeof(int)*5);
tile_size[0] = 24;
tile_size[1] = 24;
tile_size[2] = 8;
tile_size[3] = 512;
tile_size[4] = -1;
// for timekeeping
int ts_return = -1;
struct timeval start, end, result;
double tdiff = 0.0, min_tdiff=1.e100;
const int BASE = 1024;
const double alpha = 0.0876;
const double beta = 0.0765;
// initialize variables
//
srand(42);
for (i = 1; i < Nz; i++) {
for (j = 1; j < Ny; j++) {
for (k = 1; k < Nx; k++) {
A[0][i][j][k] = 1.0 * (rand() % BASE);
}
}
}
#ifdef LIKWID_PERFMON
LIKWID_MARKER_INIT;
#pragma omp parallel
{
LIKWID_MARKER_THREADINIT;
#pragma omp barrier
LIKWID_MARKER_START("calc");
}
#endif
int num_threads = 1;
#if defined(_OPENMP)
num_threads = omp_get_max_threads();
#endif
for(test=0; test<TESTS; test++){
gettimeofday(&start, 0);
// serial execution - Addition: 6 && Multiplication: 2
#pragma scop
for (t = 0; t < Nt-1; t++) {
for (i = 1; i < Nz-1; i++) {
for (j = 1; j < Ny-1; j++) {
for (k = 1; k < Nx-1; k++) {
A[(t+1)%2][i][j][k] = alpha * (A[t%2][i][j][k])
+ beta * (A[t%2][i - 1][j][k] + A[t%2][i][j - 1][k] + A[t%2][i][j][k - 1] +
A[t%2][i + 1][j][k] + A[t%2][i][j + 1][k] + A[t%2][i][j][k + 1]);
}
}
}
}
#pragma endscop
gettimeofday(&end, 0);
ts_return = timeval_subtract(&result, &end, &start);
tdiff = (double) (result.tv_sec + result.tv_usec * 1.0e-6);
min_tdiff = min(min_tdiff, tdiff);
printf("Rank 0 TEST# %d time: %f\n", test, tdiff);
}
PRINT_RESULTS(1, "constant")
#ifdef LIKWID_PERFMON
#pragma omp parallel
{
LIKWID_MARKER_STOP("calc");
}
LIKWID_MARKER_CLOSE;
#endif
// Free allocated arrays (Causing performance degradation
/* for(i=0; i<Nz; i++){
for(j=0;j<Ny;j++){
free(A[0][i][j]);
free(A[1][i][j]);
}
free(A[0][i]);
free(A[1][i]);
}
free(A[0]);
free(A[1]);
*/
return 0;
}
|
elemwise_binary_scalar_op.h | /*
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you under the Apache License, Version 2.0 (the
* "License"); you may not use this file except in compliance
* with the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing,
* software distributed under the License is distributed on an
* "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
* KIND, either express or implied. See the License for the
* specific language governing permissions and limitations
* under the License.
*/
/*!
* Copyright (c) 2016 by Contributors
* \file elemwise_binary_scalar_op.h
* \brief Function definition of elementwise binary scalar operators
*/
#ifndef MXNET_OPERATOR_TENSOR_ELEMWISE_BINARY_SCALAR_OP_H_
#define MXNET_OPERATOR_TENSOR_ELEMWISE_BINARY_SCALAR_OP_H_
#include <mxnet/operator_util.h>
#include <vector>
#include <utility>
#include "../mshadow_op.h"
#include "../elemwise_op_common.h"
#include "elemwise_unary_op.h"
namespace mxnet {
namespace op {
class BinaryScalarOp : public UnaryOp {
/*! \brief Tensor operation against a scalar with a dense result */
template<typename OP, typename DType, typename IType>
static void ComputeExDenseResultRsp(mshadow::Stream<cpu> *stream,
const nnvm::NodeAttrs &attrs,
const OpContext &ctx,
const NDArray &input,
const OpReqType req,
const NDArray &output) {
const double alpha = nnvm::get<double>(attrs.parsed);
CHECK_EQ(output.shape(), input.shape());
const int64_t row_count = output.shape()[0];
const int64_t items_per_row = output.shape().Size() / row_count;
const DType result_for_zero = OP::Map(DType(0), DType(alpha));
mshadow::Tensor<cpu, 1, DType> input_data = input.data().FlatTo1D<cpu, DType>(stream);
mshadow::Tensor<cpu, 1, DType> output_data = output.data().FlatTo1D<cpu, DType>(stream);
const int64_t sparse_row_count = input.aux_shape(rowsparse::kIdx).Size();
if (sparse_row_count != row_count) {
mshadow::Tensor<cpu, 1, IType> row_indexes = input.aux_data(
rowsparse::kIdx).FlatTo1D<cpu, IType>(stream);
int64_t input_iter = 0;
int64_t output_row = 0;
IType next_input_row = 0;
while (output_row < row_count) {
next_input_row = input_iter < sparse_row_count ? int64_t(row_indexes[input_iter])
: row_count;
// Split up into blocks of contiguous data and do those together
// Do contiguous dense blocks
const int64_t dense_block_count = next_input_row - output_row;
if (dense_block_count > 0) {
MXNET_ASSIGN_REQ_SWITCH(req, Req, {
mxnet_op::Kernel<mxnet_op::op_with_req<mshadow_op::identity, Req>, cpu>::Launch(
stream,
items_per_row * dense_block_count,
output_data.dptr_ + items_per_row * output_row,
result_for_zero);
});
output_row += dense_block_count;
continue;
}
// Do contiguous sparse blocks
int64_t next_non_contiguous_sparse = input_iter;
while (next_non_contiguous_sparse < sparse_row_count - 1) {
if (row_indexes[next_non_contiguous_sparse + 1]
!= row_indexes[next_non_contiguous_sparse] + 1) {
break;
}
++next_non_contiguous_sparse;
}
const int64_t sparse_block_count = next_non_contiguous_sparse - input_iter + 1;
if (sparse_block_count > 0) {
MXNET_ASSIGN_REQ_SWITCH(req, Req, {
mxnet_op::Kernel<mxnet_op::op_with_req<OP, Req>, cpu>::Launch(
stream,
items_per_row * sparse_block_count,
&output_data.dptr_[items_per_row * output_row],
&input_data.dptr_[items_per_row * input_iter],
DType(alpha));
});
output_row += sparse_block_count;
input_iter += sparse_block_count;
continue;
}
}
} else {
// All rows exist (eventually we don't have to do complex
// things to call GPU kernels because we don't need to access row indices)
MXNET_ASSIGN_REQ_SWITCH(req, Req, {
mxnet_op::Kernel<mxnet_op::op_with_req<OP, Req>, cpu>::Launch(
stream,
items_per_row * row_count,
output_data.dptr_,
input_data.dptr_,
DType(alpha));
});
}
}
/*! \brief Tensor operation against a scalar with a dense result */
template<typename OP, typename DType, typename IType>
static void ComputeExDenseResultRsp(mshadow::Stream<gpu> *stream,
const nnvm::NodeAttrs &attrs,
const OpContext &ctx,
const NDArray &input,
const OpReqType req,
const NDArray &output) {
LOG(FATAL) << "NOT IMPLEMENTED";
}
/*! \brief Tensor operation against a scalar with a dense result */
template<typename OP, typename DType, typename IType, typename CType>
static void ComputeExDenseResultCsr(mshadow::Stream<cpu> *stream,
const nnvm::NodeAttrs &attrs,
const OpContext &ctx,
const NDArray &input,
const OpReqType req,
const NDArray &output) {
CHECK_EQ(output.shape(), input.shape());
const double alpha = nnvm::get<double>(attrs.parsed);
const DType dense_fill_val = OP::Map(DType(0), DType(alpha));
const TBlob column_indexes = input.aux_data(csr::kIdx);
const size_t item_count = column_indexes.Size();
// Pre-fill dense with 0-input/output value
FillDense<DType>(stream, output.shape().Size(), dense_fill_val,
req, output.data().dptr<DType>());
mshadow::Tensor<cpu, 2, DType> out = AsRowise2D<DType>(stream, output.data());
if (item_count) {
const DType *in = input.data().dptr<DType>();
const IType *column_indexes_ptr = column_indexes.dptr<IType>();
const auto row_count = static_cast<size_t>(input.shape()[0]);
const TBlob row_starts = input.aux_data(csr::kIndPtr);
const CType *row_starts_ptr = row_starts.dptr<CType>();
#pragma omp parallel for
for (int i = 0; i < static_cast<int>(row_count); ++i) {
const bool last_row = i == static_cast<int>(row_count) - 1;
// Split up into blocks of contiguous data and do those together
const size_t row_item_start_iter = row_starts_ptr[i];
const size_t input_items_this_row = !last_row
? static_cast<size_t>(row_starts_ptr[i + 1])
- row_item_start_iter
: item_count - row_item_start_iter;
if (input_items_this_row) {
const IType *this_row_column_indexes = column_indexes_ptr + row_item_start_iter;
const DType *row_data_start = in + row_item_start_iter;
DType *output_this_row = out[i].dptr_;
// More overhead to use OMP for small loops, so don't
if (input_items_this_row > 1000) {
#pragma omp parallel for
for (CType j = 0; j < static_cast<CType>(input_items_this_row); ++j) {
const IType col = this_row_column_indexes[j];
const DType val = row_data_start[j];
output_this_row[col] = OP::Map(val, DType(alpha));
}
} else {
for (CType j = 0; j < static_cast<CType>(input_items_this_row); ++j) {
const IType col = this_row_column_indexes[j];
const DType val = row_data_start[j];
output_this_row[col] = OP::Map(val, DType(alpha));
}
}
}
}
}
}
/*! \brief Tensor operation against a scalar with a dense result */
template<typename OP, typename DType, typename IType, typename CType>
static void ComputeExDenseResultCsr(mshadow::Stream<gpu> *stream,
const nnvm::NodeAttrs &attrs,
const OpContext &ctx,
const NDArray &input,
const OpReqType req,
const NDArray &output) {
LOG(FATAL) << "NOT IMPLEMENTED";
}
template<typename xpu, typename OP, typename DType, typename IType>
static void ComputeExDenseResult(const nnvm::NodeAttrs &attrs,
const OpContext &ctx,
const NDArray &input,
const OpReqType req,
const NDArray output) {
mshadow::Stream<xpu> *stream = ctx.get_stream<xpu>();
CHECK_EQ(output.storage_type(), kDefaultStorage);
switch (input.storage_type()) {
case kRowSparseStorage: {
ComputeExDenseResultRsp<OP, DType, IType>(stream, attrs, ctx, input, req, output);
break;
}
case kCSRStorage: {
MSHADOW_IDX_TYPE_SWITCH(input.aux_data(csr::kIndPtr).type_flag_, CType, {
ComputeExDenseResultCsr<OP, DType, IType, CType>(stream, attrs, ctx, input, req, output);
});
break;
}
default:
CHECK(false) << "Unsupported sparse storage type";
break;
}
}
public:
template<typename xpu, typename OP>
static void Compute(const nnvm::NodeAttrs &attrs,
const OpContext &ctx,
const std::vector<TBlob> &inputs,
const std::vector<OpReqType> &req,
const std::vector<TBlob> &outputs) {
DCHECK_EQ(inputs.size(), 1);
DCHECK_EQ(outputs.size(), 1);
using namespace mshadow;
using namespace mshadow::expr;
Stream<xpu> *s = ctx.get_stream<xpu>();
const double alpha = nnvm::get<double>(attrs.parsed);
MSHADOW_TYPE_SWITCH(outputs[0].type_flag_, DType, {
MXNET_ASSIGN_REQ_SWITCH(req[0], Req, {
mxnet_op::Kernel<mxnet_op::op_with_req<OP, Req>, xpu>::Launch(
s, inputs[0].Size(), outputs[0].dptr<DType>(), inputs[0].dptr<DType>(), DType(alpha));
});
});
}
template<typename xpu, typename OP>
static void ComputeLogic(const nnvm::NodeAttrs &attrs,
const OpContext &ctx,
const std::vector<TBlob> &inputs,
const std::vector<OpReqType> &req,
const std::vector<TBlob> &outputs) {
DCHECK_EQ(inputs.size(), 1);
DCHECK_EQ(outputs.size(), 1);
using namespace mshadow;
using namespace mshadow::expr;
Stream<xpu> *s = ctx.get_stream<xpu>();
const double alpha = nnvm::get<double>(attrs.parsed);
MSHADOW_TYPE_SWITCH_WITH_BOOL(inputs[0].type_flag_, DType, {
MXNET_ASSIGN_REQ_SWITCH(req[0], Req, {
mxnet_op::Kernel<mxnet_op::op_with_req<OP, Req>, xpu>::Launch(
s, inputs[0].Size(), outputs[0].dptr<bool>(), inputs[0].dptr<DType>(), DType(alpha));
});
});
}
template<typename xpu, typename OP>
static void ComputeEx(const nnvm::NodeAttrs &attrs,
const OpContext &ctx,
const std::vector<NDArray> &inputs,
const std::vector<OpReqType> &req,
const std::vector<NDArray> &outputs) {
DCHECK_EQ(inputs.size(), 1);
DCHECK_EQ(outputs.size(), 1);
const auto in_stype = inputs[0].storage_type();
const auto out_stype = outputs[0].storage_type();
if (req[0] == kNullOp) {
return;
}
if ((in_stype == kRowSparseStorage && out_stype == kRowSparseStorage) ||
(in_stype == kCSRStorage && out_stype == kCSRStorage)) {
// csr -> csr, or rsp -> rsp
UnaryOp::MapToFCompute<xpu>(attrs, ctx, inputs, req, outputs, Compute<xpu, OP>);
} else if (out_stype == kDefaultStorage &&
(in_stype == kRowSparseStorage || in_stype == kCSRStorage)) {
MSHADOW_TYPE_SWITCH(outputs[0].data().type_flag_, DType, {
MSHADOW_IDX_TYPE_SWITCH(inputs[0].aux_type(rowsparse::kIdx), IType, {
ComputeExDenseResult<xpu, OP, DType, IType>(attrs, ctx, inputs[0], req[0], outputs[0]);
});
});
} else {
LogUnimplementedOp(attrs, ctx, inputs, req, outputs);
}
}
template<typename xpu, typename OP>
static void LogicComputeEx(const nnvm::NodeAttrs &attrs,
const OpContext &ctx,
const std::vector<NDArray> &inputs,
const std::vector<OpReqType> &req,
const std::vector<NDArray> &outputs) {
DCHECK_EQ(inputs.size(), 1);
DCHECK_EQ(outputs.size(), 1);
const auto in_stype = inputs[0].storage_type();
const auto out_stype = outputs[0].storage_type();
if (req[0] == kNullOp) {
return;
}
if ((in_stype == kRowSparseStorage && out_stype == kRowSparseStorage) ||
(in_stype == kCSRStorage && out_stype == kCSRStorage)) {
// csr -> csr, or rsp -> rsp
UnaryOp::MapToFCompute<xpu>(attrs, ctx, inputs, req, outputs, Compute<xpu, OP>);
} else {
LogUnimplementedOp(attrs, ctx, inputs, req, outputs);
}
}
template<typename xpu, typename OP>
static void Backward(const nnvm::NodeAttrs &attrs,
const OpContext &ctx,
const std::vector<TBlob> &inputs,
const std::vector<OpReqType> &req,
const std::vector<TBlob> &outputs) {
using namespace mshadow;
using namespace mshadow::expr;
Stream<xpu> *s = ctx.get_stream<xpu>();
const double alpha = nnvm::get<double>(attrs.parsed);
MSHADOW_TYPE_SWITCH(outputs[0].type_flag_, DType, {
MXNET_ASSIGN_REQ_SWITCH(req[0], Req, {
mxnet::op::mxnet_op::Kernel<mxnet::op::mxnet_op::op_with_req<
mxnet::op::mxnet_op::backward_grad_tuned<OP>, Req>, xpu>::
Launch(s, inputs[0].Size(), outputs[0].dptr<DType>(),
inputs[0].dptr<DType>(), inputs[1].dptr<DType>(),
DType(alpha));
});
});
}
};
#define MXNET_OPERATOR_REGISTER_BINARY_SCALAR(name) \
NNVM_REGISTER_OP(name) \
.set_num_inputs(1) \
.set_num_outputs(1) \
.set_attr_parser([](NodeAttrs* attrs) { \
attrs->parsed = std::stod(attrs->dict["scalar"]); \
}) \
.set_attr<mxnet::FInferShape>("FInferShape", ElemwiseShape<1, 1>) \
.set_attr<nnvm::FInferType>("FInferType", ElemwiseType<1, 1>) \
.set_attr<nnvm::FInplaceOption>("FInplaceOption", \
[](const NodeAttrs& attrs){ \
return std::vector<std::pair<int, int> >{{0, 0}}; \
}) \
.add_argument("data", "NDArray-or-Symbol", "source input") \
.add_argument("scalar", "float", "scalar input")
} // namespace op
} // namespace mxnet
#endif // MXNET_OPERATOR_TENSOR_ELEMWISE_BINARY_SCALAR_OP_H_
|
gVbHmm_Common.c | /*
* gVbHmm_Common.c
* Common VB-HMM engine for global analysis.
* Reference:
* Christopher M. Bishop, "Pattern Recognition and Machine Learning", Springer, 2006
*
* Created by OKAMOTO Kenji, SAKO Yasushi and RIKEN
* Copyright 2011-2015
* Cellular Informatics Laboratory, Advance Science Institute, RIKEN, Japan.
* All rights reserved.
*
* Ver. 1.1.0
* Last modified on 2016.11.04
*/
#include "gVbHmm_Common.h"
#include <string.h>
#include <float.h>
// Pointers of functions to call model-specific functions.
extern new_model_parameters_func newModelParameters;
extern free_model_parameters_func freeModelParameters;
extern new_model_stats_func newModelStats;
extern free_model_stats_func freeModelStats;
new_model_statsG_func newModelStatsG = NULL;
free_model_statsG_func freeModelStatsG = NULL;
initialize_vbHmmG_func initializeVbHmmG = NULL;
extern pTilde_z1_func pTilde_z1;
extern pTilde_zn_zn1_func pTilde_zn_zn1;
extern pTilde_xn_zn_func pTilde_xn_zn;
calcStatsVarsG_func calcStatsVarsG = NULL;
maximizationG_func maximizationG = NULL;
varLowerBoundG_func varLowerBoundG = NULL;
reorderParametersG_func reorderParametersG = NULL;
outputResultsG_func outputResultsG = NULL;
// This function must be called to connect with the model before executing analysis.
void setGFunctions( funcs )
gCommonFunctions funcs;
{
newModelParameters = funcs.newModelParameters;
freeModelParameters = funcs.freeModelParameters;
newModelStats = funcs.newModelStats;
freeModelStats = funcs.freeModelStats;
newModelStatsG = funcs.newModelStatsG;
freeModelStatsG = funcs.freeModelStatsG;
initializeVbHmmG = funcs.initializeVbHmmG;
pTilde_z1 = funcs.pTilde_z1;
pTilde_zn_zn1 = funcs.pTilde_zn_zn1;
pTilde_xn_zn = funcs.pTilde_xn_zn;
calcStatsVarsG = funcs.calcStatsVarsG;
maximizationG = funcs.maximizationG;
varLowerBoundG = funcs.varLowerBoundG;
reorderParametersG = funcs.reorderParametersG;
outputResultsG = funcs.outputResultsG;
}
////////////////////////////////////////////////////////////////// VB-HMM Execution Functions
int gModelComparison( xns, sFrom, sTo, trials, maxIteration, threshold, logFP )
xnDataBundle *xns;
int sFrom, sTo, trials;
int maxIteration;
double threshold;
FILE *logFP;
{
int s, t;
if( logFP != NULL ){
fprintf( logFP, " No. of states from %d to %d, trials = %d, ", sFrom, sTo, trials);
fprintf( logFP, " analyze: maxIteration = %d, threshold = %g \n\n", maxIteration, threshold);
}
double *LqVsK = malloc( trials * (sTo - sFrom + 1) * sizeof(double) );
int maxS = 0, rNo = xns->R;
double maxLq = -DBL_MAX;
globalVars **gvArray = (globalVars**)malloc( trials * sizeof(globalVars*) );
indVarBundle **ivsArray = (indVarBundle**)malloc( trials * sizeof(indVarBundle*) );
for( s = sFrom ; s <= sTo ; s++ ){
#ifdef _OPENMP
#pragma omp parallel for private(t)
#endif
for( t = 0 ; t < trials ; t++ ){
int r, st = (s - sFrom) * trials + t;
gvArray[t] = newGlobalVarsG( xns, s );
ivsArray[t] = (indVarBundle*)malloc( sizeof(indVarBundle) );
ivsArray[t]->indVars = (indVars**)malloc( rNo * sizeof(indVars*) );
for( r = 0 ; r < rNo ; r++ ){
ivsArray[t]->indVars[r] = newIndVars( xns->xn[r], gvArray[t] );
}
ivsArray[t]->stats = (*newModelStatsG)( xns, gvArray[t], ivsArray[t] );
LqVsK[st] = gVbHmm_Main( xns, gvArray[t], ivsArray[t], maxIteration, threshold, logFP );
if( LqVsK[st] > maxLq ){
maxLq = LqVsK[st];
maxS = s;
}
}
double maxLqForS = 0.0;
int maxT = 0;
for( t = 0 ; t < trials ; t++ ){
int st = (s - sFrom) * trials + t;
if( LqVsK[st] > maxLqForS ){
maxLqForS = LqVsK[st];
maxT = t;
}
}
(*outputResultsG)( xns, gvArray[maxT], ivsArray[maxT], logFP );
for( t = 0 ; t < trials ; t++ ){
int r;
for( r = 0 ; r < rNo ; r++ ){
freeIndVars( xns->xn[r], gvArray[t], &ivsArray[t]->indVars[r] );
}
free( ivsArray[t]->indVars );
free( ivsArray[t]->stats );
free( ivsArray[t] );
ivsArray[t] = NULL;
freeGlobalVarsG( xns, &gvArray[t] );
}
if( s >= (maxS+3) ){
s++;
break;
}
}
sTo = s - 1;
free( gvArray );
free( ivsArray );
char fn[256];
FILE *fp = NULL;
strncpy( fn, xns->xn[0]->name, sizeof(fn) );
strncat( fn, ".g.LqVsK", sizeof(fn) - strlen(fn) - 1 );
if( (fp = fopen( fn, "w" )) != NULL ){
for( s = 0 ; s < trials * (sTo - sFrom + 1) ; s++ ){
fprintf( fp, "%2d, %.20g\n", (s/trials) + sFrom, LqVsK[s] );
}
fclose(fp);
}
free( LqVsK );
return maxS;
}
// Initializes parameters commonly used in VB-HMM analysis
globalVars *newGlobalVarsG( xns, sNo )
xnDataBundle *xns;
int sNo;
{
globalVars *gv = (globalVars*)malloc( sizeof(globalVars) );
gv->sNo = sNo;
gv->iteration = 0;
gv->maxLq = 0.0;
gv->LqArr = NULL;
gv->params = (*newModelParameters)( NULL, sNo );
return gv;
}
// Frees memory for common parameters
void freeGlobalVarsG( xns, gv )
xnDataBundle *xns;
globalVars **gv;
{
free( (*gv)->LqArr );
(*freeModelParameters)( &(*gv)->params, NULL, (*gv)->sNo );
free( *gv );
*gv = NULL;
}
////////////////////////////////////////////////////////////////// VB-HMM Common Engine
double gVbHmm_Main( xns, gv, ivs, maxIteration, threshold, logFP )
xnDataBundle *xns;
globalVars *gv;
indVarBundle *ivs;
int maxIteration;
double threshold;
FILE *logFP;
{
double **LqArr = &gv->LqArr;
*LqArr = realloc( *LqArr, maxIteration * sizeof(double) );
(*initializeVbHmmG)( xns, gv, ivs );
int i, r, rNo = xns->R;
for( i = 0 ; i < maxIteration ; i++ ){
// E-step
for( r = 0 ; r < rNo ; r++ ){
forwardBackward( xns->xn[r], gv, ivs->indVars[r] );
}
(*calcStatsVarsG)( xns, gv, ivs );
(*LqArr)[i] = (*varLowerBoundG)( xns, gv, ivs );
// End loop if derivative of variational lower bound reaches threshold.
if( (i>0) && ( fabs( ((*LqArr)[i] - (*LqArr)[i-1]) / (*LqArr)[i] ) < threshold ) ){
break;
}
// M-step
(*maximizationG)( xns, gv, ivs );
}
if( i == maxIteration ){
if( logFP != NULL ){
fprintf(logFP, "MAX iteration (%d) reached.\n", maxIteration);
}
i--;
}
(*reorderParametersG)( xns, gv, ivs );
for( r = 0 ; r < rNo ; r++ ){
#ifdef OUTPUT_MAX_GAMMA
maxGamma( xns->xn[r], gv, ivs->indVars[r] );
#endif
maxSum( xns->xn[r], gv, ivs->indVars[r] );
}
gv->iteration = i+1;
*LqArr = realloc( *LqArr, (i+1) * sizeof(double) );
gv->maxLq = (*LqArr)[i];
if( logFP != NULL ){
fprintf( logFP, " iteration: %d evidence p(x|K=%d) = %.20g \n", i+1, gv->sNo, gv->maxLq );
}
return gv->maxLq;
}
//
|
declare_variant_messages.c | // RUN: %clang_cc1 -triple=x86_64-pc-win32 -verify -fopenmp -x c -std=c99 -fms-extensions -Wno-pragma-pack %s
// RUN: %clang_cc1 -triple=x86_64-pc-win32 -verify -fopenmp-simd -x c -std=c99 -fms-extensions -Wno-pragma-pack %s
#pragma omp declare // expected-error {{expected an OpenMP directive}}
int foo(void);
#pragma omp declare variant // expected-error {{expected '(' after 'declare variant'}}
#pragma omp declare variant( // expected-error {{expected expression}} expected-error {{expected ')'}} expected-note {{to match this '('}}
#pragma omp declare variant(foo // expected-error {{expected ')'}} expected-error {{expected 'match' clause on 'omp declare variant' directive}} expected-note {{to match this '('}}
#pragma omp declare variant(x) // expected-error {{use of undeclared identifier 'x'}} expected-error {{expected 'match' clause on}}
#pragma omp declare variant(foo) // expected-error {{expected 'match' clause on 'omp declare variant' directive}}
#pragma omp declare variant(foo) // expected-error {{expected 'match' clause on 'omp declare variant' directive}}
#pragma omp declare variant(foo) xxx // expected-error {{expected 'match' clause on 'omp declare variant' directive}}
#pragma omp declare variant(foo) match // expected-error {{expected '(' after 'match'}}
#pragma omp declare variant(foo) match( // expected-error {{expected ')'}} expected-warning {{expected identifier or string literal describing a context set; set skipped}} expected-note {{context set options are: 'construct' 'device' 'implementation' 'user'}} expected-note {{the ignored set spans until here}} expected-note {{to match this '('}}
#pragma omp declare variant(foo) match() // expected-warning {{expected identifier or string literal describing a context set; set skipped}} expected-note {{context set options are: 'construct' 'device' 'implementation' 'user'}} expected-note {{the ignored set spans until here}}
#pragma omp declare variant(foo) match(xxx) // expected-warning {{'xxx' is not a valid context set in a `declare variant`; set ignored}} expected-note {{context set options are: 'construct' 'device' 'implementation' 'user'}} expected-note {{the ignored set spans until here}}
#pragma omp declare variant(foo) match(xxx=) // expected-warning {{'xxx' is not a valid context set in a `declare variant`; set ignored}} expected-note {{context set options are: 'construct' 'device' 'implementation' 'user'}} expected-note {{the ignored set spans until here}}
#pragma omp declare variant(foo) match(xxx=yyy) // expected-warning {{'xxx' is not a valid context set in a `declare variant`; set ignored}} expected-note {{context set options are: 'construct' 'device' 'implementation' 'user'}} expected-note {{the ignored set spans until here}}
#pragma omp declare variant(foo) match(xxx=yyy}) // expected-error {{expected ')'}} expected-warning {{'xxx' is not a valid context set in a `declare variant`; set ignored}} expected-note {{context set options are: 'construct' 'device' 'implementation' 'user'}} expected-note {{the ignored set spans until here}} expected-note {{to match this '('}} expected-error {{expected 'match' clause on 'omp declare variant' directive}}
#pragma omp declare variant(foo) match(xxx={) // expected-error {{expected ')'}} expected-warning {{'xxx' is not a valid context set in a `declare variant`; set ignored}} expected-note {{context set options are: 'construct' 'device' 'implementation' 'user'}} expected-note {{the ignored set spans until here}} expected-note {{to match this '('}}
#pragma omp declare variant(foo) match(xxx={}) // expected-warning {{'xxx' is not a valid context set in a `declare variant`; set ignored}} expected-note {{context set options are: 'construct' 'device' 'implementation' 'user'}} expected-note {{the ignored set spans until here}}
#pragma omp declare variant(foo) match(xxx={vvv, vvv}) // expected-warning {{'xxx' is not a valid context set in a `declare variant`; set ignored}} expected-note {{context set options are: 'construct' 'device' 'implementation' 'user'}} expected-note {{the ignored set spans until here}}
#pragma omp declare variant(foo) match(xxx={vvv} xxx) // expected-warning {{'xxx' is not a valid context set in a `declare variant`; set ignored}} expected-note {{context set options are: 'construct' 'device' 'implementation' 'user'}} expected-note {{the ignored set spans until here}}
#pragma omp declare variant(foo) match(xxx={vvv}) xxx // expected-warning {{'xxx' is not a valid context set in a `declare variant`; set ignored}} expected-note {{context set options are: 'construct' 'device' 'implementation' 'user'}} expected-note {{the ignored set spans until here}} expected-error {{expected 'match' clause on 'omp declare variant' directive}}
#pragma omp declare variant(foo) match(implementation={xxx}) // expected-warning {{'xxx' is not a valid context selector for the context set 'implementation'; selector ignored}} expected-note {{context selector options are: 'vendor' 'extension' 'unified_address' 'unified_shared_memory' 'reverse_offload' 'dynamic_allocators' 'atomic_default_mem_order'}} expected-note {{the ignored selector spans until here}}
#pragma omp declare variant(foo) match(implementation={vendor}) // expected-warning {{the context selector 'vendor' in context set 'implementation' requires a context property defined in parentheses; selector ignored}} expected-note {{the ignored selector spans until here}}
#pragma omp declare variant(foo) match(implementation={vendor(}) // expected-error {{expected ')'}} expected-warning {{expected identifier or string literal describing a context property; property skipped}} expected-note {{context property options are: 'amd' 'arm' 'bsc' 'cray' 'fujitsu' 'gnu' 'ibm' 'intel' 'llvm' 'pgi' 'ti' 'unknown'}} expected-note {{to match this '('}}
#pragma omp declare variant(foo) match(implementation={vendor()}) // expected-warning {{expected identifier or string literal describing a context property; property skipped}} expected-note {{context property options are: 'amd' 'arm' 'bsc' 'cray' 'fujitsu' 'gnu' 'ibm' 'intel' 'llvm' 'pgi' 'ti' 'unknown'}}
#pragma omp declare variant(foo) match(implementation={vendor(score ibm)}) // expected-error {{expected '(' after 'score'}} expected-warning {{expected '':'' after the score expression; '':'' assumed}}
#pragma omp declare variant(foo) match(implementation={vendor(score( ibm)}) // expected-error {{use of undeclared identifier 'ibm'}} expected-error {{expected ')'}} expected-warning {{expected '':'' after the score expression; '':'' assumed}} expected-warning {{expected identifier or string literal describing a context property; property skipped}} expected-note {{context property options are: 'amd' 'arm' 'bsc' 'cray' 'fujitsu' 'gnu' 'ibm' 'intel' 'llvm' 'pgi' 'ti' 'unknown'}} expected-note {{to match this '('}}
#pragma omp declare variant(foo) match(implementation={vendor(score(2 ibm)}) // expected-error {{expected ')'}} expected-error {{expected ')'}} expected-warning {{expected '':'' after the score expression; '':'' assumed}} expected-warning {{expected identifier or string literal describing a context property; property skipped}} expected-note {{to match this '('}} expected-note {{context property options are: 'amd' 'arm' 'bsc' 'cray' 'fujitsu' 'gnu' 'ibm' 'intel' 'llvm' 'pgi' 'ti' 'unknown'}} expected-note {{to match this '('}}
#pragma omp declare variant(foo) match(implementation={vendor(score(foo()) ibm)}) // expected-warning {{expected '':'' after the score expression; '':'' assumed}} expected-warning {{score expressions in the OpenMP context selector need to be constant; foo() is not and will be ignored}}
#pragma omp declare variant(foo) match(implementation={vendor(score(5): ibm), vendor(llvm)}) // expected-warning {{the context selector 'vendor' was used already in the same 'omp declare variant' directive; selector ignored}} expected-note {{the previous context selector 'vendor' used here}} expected-note {{the ignored selector spans until here}}
#pragma omp declare variant(foo) match(implementation={vendor(score(5): ibm), kind(cpu)}) // expected-warning {{the context selector 'kind' is not valid for the context set 'implementation'; selector ignored}} expected-note {{the context selector 'kind' can be nested in the context set 'device'; try 'match(device={kind(property)})'}} expected-note {{the ignored selector spans until here}}
#pragma omp declare variant(foo) match(device={xxx}) // expected-warning {{'xxx' is not a valid context selector for the context set 'device'; selector ignored}} expected-note {{context selector options are: 'kind' 'arch' 'isa'}} expected-note {{the ignored selector spans until here}}
#pragma omp declare variant(foo) match(device={kind}) // expected-warning {{the context selector 'kind' in context set 'device' requires a context property defined in parentheses; selector ignored}} expected-note {{the ignored selector spans until here}}
#pragma omp declare variant(foo) match(device={kind(}) // expected-error {{expected ')'}} expected-warning {{expected identifier or string literal describing a context property; property skipped}} expected-note {{context property options are: 'host' 'nohost' 'cpu' 'gpu' 'fpga' 'any'}} expected-note {{to match this '('}}
#pragma omp declare variant(foo) match(device={kind()}) // expected-warning {{expected identifier or string literal describing a context property; property skipped}} expected-note {{context property options are: 'host' 'nohost' 'cpu' 'gpu' 'fpga' 'any'}}
#pragma omp declare variant(foo) match(device={kind(score cpu)}) // expected-error {{expected '(' after 'score'}} expected-warning {{expected '':'' after the score expression; '':'' assumed}} expected-warning {{the context selector 'kind' in the context set 'device' cannot have a score ('<invalid>'); score ignored}}
#pragma omp declare variant(foo) match(device = {kind(score(ibm) }) // expected-error {{use of undeclared identifier 'ibm'}} expected-error {{expected ')'}} expected-warning {{expected '':'' after the score expression; '':'' assumed}} expected-warning {{the context selector 'kind' in the context set 'device' cannot have a score ('<recovery-expr>()'); score ignored}} expected-warning {{expected identifier or string literal describing a context property; property skipped}} expected-note {{context property options are: 'host' 'nohost' 'cpu' 'gpu' 'fpga' 'any'}} expected-note {{to match this '('}}
#pragma omp declare variant(foo) match(device={kind(score(2 gpu)}) // expected-error {{expected ')'}} expected-error {{expected ')'}} expected-warning {{expected '':'' after the score expression; '':'' assumed}} expected-warning {{the context selector 'kind' in the context set 'device' cannot have a score ('2'); score ignored}} expected-warning {{expected identifier or string literal describing a context property; property skipped}} expected-note {{to match this '('}} expected-note {{context property options are: 'host' 'nohost' 'cpu' 'gpu' 'fpga' 'any'}} expected-note {{to match this '('}}
#pragma omp declare variant(foo) match(device={kind(score(foo()) ibm)}) // expected-warning {{expected '':'' after the score expression; '':'' assumed}} expected-warning {{the context selector 'kind' in the context set 'device' cannot have a score ('foo()'); score ignored}} expected-warning {{'ibm' is not a valid context property for the context selector 'kind' and the context set 'device'; property ignored}} expected-note {{try 'match(implementation={vendor(ibm)})'}} expected-note {{the ignored property spans until here}}
#pragma omp declare variant(foo) match(device={kind(score(5): host), kind(llvm)}) // expected-warning {{the context selector 'kind' in the context set 'device' cannot have a score ('5'); score ignored}} expected-warning {{the context selector 'kind' was used already in the same 'omp declare variant' directive; selector ignored}} expected-note {{the previous context selector 'kind' used here}} expected-note {{the ignored selector spans until here}}
#pragma omp declare variant(foo) match(device={kind(score(5): nohost), vendor(llvm)}) // expected-warning {{the context selector 'kind' in the context set 'device' cannot have a score ('5'); score ignored}} expected-warning {{the context selector 'vendor' is not valid for the context set 'device'; selector ignored}} expected-note {{the context selector 'vendor' can be nested in the context set 'implementation'; try 'match(implementation={vendor(property)})'}} expected-note {{the ignored selector spans until here}}
#pragma omp declare variant(foo) match(implementation={extension("aaa")}) // expected-warning {{'aaa' is not a valid context property for the context selector 'extension' and the context set 'implementation'; property ignored}} expected-note {{context property options are: 'match_all' 'match_any' 'match_none'}} expected-note {{the ignored property spans until here}}
int bar(void);
#pragma omp declare variant(foo) match(implementation = {vendor(score(foo) :llvm)}) // expected-warning {{score expressions in the OpenMP context selector need to be constant; foo is not and will be ignored}}
#pragma omp declare variant(foo) match(implementation = {vendor(score(foo()) :llvm)}) // expected-warning {{score expressions in the OpenMP context selector need to be constant; foo() is not and will be ignored}}
#pragma omp declare variant(foo) match(implementation = {vendor(score(<expr>) :llvm)}) // expected-error {{expected expression}} expected-error {{use of undeclared identifier 'expr'}} expected-error {{expected expression}}
#pragma omp declare variant(foo) match(user = {condition(foo)}) // expected-error {{the user condition in the OpenMP context selector needs to be constant; foo is not}}
#pragma omp declare variant(foo) match(user = {condition(foo())}) // expected-error {{the user condition in the OpenMP context selector needs to be constant; foo() is not}}
#pragma omp declare variant(foo) match(user = {condition(<expr>)}) // expected-error {{expected expression}} expected-error {{use of undeclared identifier 'expr'}} expected-error {{expected expression}} expected-note {{the ignored selector spans until here}}
int score_and_cond_non_const();
#pragma omp declare variant(foo) match(construct={teams,parallel,for,simd})
#pragma omp declare variant(foo) match(construct={target teams}) // expected-error {{expected ')'}} expected-warning {{expected '}' after the context selectors for the context set "construct"; '}' assumed}} expected-note {{to match this '('}} expected-error {{expected 'match' clause on 'omp declare variant' directive}}
#pragma omp declare variant(foo) match(construct={parallel for}) // expected-error {{expected ')'}} expected-warning {{expected '}' after the context selectors for the context set "construct"; '}' assumed}} expected-note {{to match this '('}} expected-error {{expected 'match' clause on 'omp declare variant' directive}}
#pragma omp declare variant(foo) match(construct={for simd}) // expected-error {{expected ')'}} expected-warning {{expected '}' after the context selectors for the context set "construct"; '}' assumed}} expected-note {{to match this '('}} expected-error {{expected 'match' clause on 'omp declare variant' directive}}
int construct(void);
#pragma omp declare variant(foo) match(xxx={}) // expected-warning {{'xxx' is not a valid context set in a `declare variant`; set ignored}} expected-note {{context set options are: 'construct' 'device' 'implementation' 'user'}} expected-note {{the ignored set spans until here}}
int a; // expected-error {{'#pragma omp declare variant' can only be applied to functions}}
#pragma omp declare variant(foo) match(xxx={}) // expected-warning {{'xxx' is not a valid context set in a `declare variant`; set ignored}} expected-note {{context set options are: 'construct' 'device' 'implementation' 'user'}} expected-note {{the ignored set spans until here}}
#pragma omp threadprivate(a) // expected-error {{'#pragma omp declare variant' can only be applied to functions}}
int var;
#pragma omp threadprivate(var)
#pragma omp declare variant(foo) match(xxx={}) // expected-error {{function declaration is expected after 'declare variant' directive}}
#pragma omp declare // expected-error {{expected an OpenMP directive}}
#pragma omp declare variant(foo) match(xxx={}) // expected-error {{function declaration is expected after 'declare variant' directive}}
#pragma omp declare variant(foo) match(xxx={}) // expected-error {{function declaration is expected after 'declare variant' directive}}
#pragma options align=packed
int main();
#pragma omp declare variant(foo) match(implementation={vendor(llvm)}) // expected-error {{function declaration is expected after 'declare variant' directive}}
#pragma omp declare variant(foo) match(implementation={vendor(llvm)}) // expected-error {{function declaration is expected after 'declare variant' directive}}
#pragma init_seg(compiler)
int main();
#pragma omp declare variant(foo) match(xxx={}) // expected-error {{single declaration is expected after 'declare variant' directive}} expected-warning {{'xxx' is not a valid context set in a `declare variant`; set ignored}} expected-note {{context set options are: 'construct' 'device' 'implementation' 'user'}} expected-note {{the ignored set spans until here}}
int b, c;
int no_proto();
#pragma omp declare variant(no_proto) match(xxx={}) // expected-warning {{'xxx' is not a valid context set in a `declare variant`; set ignored}} expected-note {{context set options are: 'construct' 'device' 'implementation' 'user'}} expected-note {{the ignored set spans until here}}
int no_proto_too();
int proto1(int);
#pragma omp declare variant(proto1) match(xxx={}) // expected-warning {{'xxx' is not a valid context set in a `declare variant`; set ignored}} expected-note {{context set options are: 'construct' 'device' 'implementation' 'user'}} expected-note {{the ignored set spans until here}}
int diff_proto(); // expected-note {{previous declaration is here}}
int diff_proto(double); // expected-error {{conflicting types for 'diff_proto'}}
#pragma omp declare variant(no_proto) match(xxx={}) // expected-warning {{'xxx' is not a valid context set in a `declare variant`; set ignored}} expected-note {{context set options are: 'construct' 'device' 'implementation' 'user'}} expected-note {{the ignored set spans until here}}
int diff_proto1(double);
int after_use_variant(void);
int after_use();
int bar() {
return after_use();
}
#pragma omp declare variant(after_use_variant) match(xxx={}) // expected-warning {{'xxx' is not a valid context set in a `declare variant`; set ignored}} expected-warning {{'#pragma omp declare variant' cannot be applied for function after first usage; the original function might be used}} expected-note {{context set options are: 'construct' 'device' 'implementation' 'user'}} expected-note {{the ignored set spans until here}}
int after_use(void);
#pragma omp declare variant(after_use_variant) match(xxx={}) // expected-warning {{'xxx' is not a valid context set in a `declare variant`; set ignored}} expected-note {{context set options are: 'construct' 'device' 'implementation' 'user'}} expected-note {{the ignored set spans until here}}
int defined(void) { return 0; }
int defined1(void) { return 0; }
#pragma omp declare variant(after_use_variant) match(xxx={}) // expected-warning {{'xxx' is not a valid context set in a `declare variant`; set ignored}} expected-warning {{'#pragma omp declare variant' cannot be applied to the function that was defined already; the original function might be used}} expected-note {{context set options are: 'construct' 'device' 'implementation' 'user'}} expected-note {{the ignored set spans until here}}
int defined1(void);
int diff_cc_variant(void);
#pragma omp declare variant(diff_cc_variant) match(xxx={}) // expected-error {{variant in '#pragma omp declare variant' with type 'int (void)' is incompatible with type 'int (void) __attribute__((vectorcall))'}} expected-warning {{'xxx' is not a valid context set in a `declare variant`; set ignored}} expected-note {{context set options are: 'construct' 'device' 'implementation' 'user'}} expected-note {{the ignored set spans until here}}
__vectorcall int diff_cc(void);
int diff_ret_variant(void);
#pragma omp declare variant(diff_ret_variant) match(xxx={}) // expected-error {{variant in '#pragma omp declare variant' with type 'int (void)' is incompatible with type 'void (void)'}} expected-warning {{'xxx' is not a valid context set in a `declare variant`; set ignored}} expected-note {{context set options are: 'construct' 'device' 'implementation' 'user'}} expected-note {{the ignored set spans until here}}
void diff_ret(void);
void marked(void);
void not_marked(void);
#pragma omp declare variant(not_marked) match(implementation={vendor(unknown)}, device={kind(cpu)}) // expected-note {{marked as 'declare variant' here}}
void marked_variant(void);
#pragma omp declare variant(marked_variant) match(xxx={}) // expected-warning {{'xxx' is not a valid context set in a `declare variant`; set ignored}} expected-warning {{variant function in '#pragma omp declare variant' is itself marked as '#pragma omp declare variant'}} expected-note {{context set options are: 'construct' 'device' 'implementation' 'user'}} expected-note {{the ignored set spans until here}}
void marked(void);
#pragma omp declare variant(foo) match(device = {isa("foo")})
int unknown_isa_trait(void);
#pragma omp declare variant(foo) match(device = {isa(foo)})
int unknown_isa_trait2(void);
#pragma omp declare variant(foo) match(device = {kind(fpga), isa(bar)})
int ignored_isa_trait(void);
void caller() {
unknown_isa_trait(); // expected-warning {{isa trait 'foo' is not known to the current target; verify the spelling or consider restricting the context selector with the 'arch' selector further}}
unknown_isa_trait2(); // expected-warning {{isa trait 'foo' is not known to the current target; verify the spelling or consider restricting the context selector with the 'arch' selector further}}
ignored_isa_trait();
}
// Unknown arch
#pragma omp begin declare variant match(device={isa(sse2020)}) // expected-warning {{isa trait 'sse2020' is not known to the current target; verify the spelling or consider restricting the context selector with the 'arch' selector further}}
#pragma omp end declare variant
// Unknown arch guarded by arch.
#pragma omp begin declare variant match(device={isa(sse2020), arch(ppc)})
#pragma omp end declare variant
#pragma omp declare variant // expected-error {{function declaration is expected after 'declare variant' directive}}
#pragma omp declare variant // expected-error {{function declaration is expected after 'declare variant' directive}}
// FIXME: If the scores are equivalent we should detect that and allow it.
#pragma omp begin declare variant match(implementation = {vendor(score(2) \
: llvm)})
#pragma omp declare variant(foo) match(implementation = {vendor(score(2) \
: llvm)}) // expected-error@-1 {{nested OpenMP context selector contains duplicated trait 'llvm' in selector 'vendor' and set 'implementation' with different score}}
int conflicting_nested_score(void);
#pragma omp end declare variant
// FIXME: We should build the conjuction of different conditions, see also the score fixme above.
#pragma omp begin declare variant match(user = {condition(1)})
#pragma omp declare variant(foo) match(user = {condition(1)}) // expected-error {{nested user conditions in OpenMP context selector not supported (yet)}}
int conflicting_nested_condition(void);
#pragma omp end declare variant
|
hpgmg-fv.c | //------------------------------------------------------------------------------------------------------------------------------
// Copyright Notice
//------------------------------------------------------------------------------------------------------------------------------
// HPGMG, Copyright (c) 2014, The Regents of the University of
// California, through Lawrence Berkeley National Laboratory (subject to
// receipt of any required approvals from the U.S. Dept. of Energy). All
// rights reserved.
//
// If you have questions about your rights to use or distribute this
// software, please contact Berkeley Lab's Technology Transfer Department
// at TTD@lbl.gov.
//
// NOTICE. This software is owned by the U.S. Department of Energy. As
// such, the U.S. Government has been granted for itself and others
// acting on its behalf a paid-up, nonexclusive, irrevocable, worldwide
// license in the Software to reproduce, prepare derivative works, and
// perform publicly and display publicly. Beginning five (5) years after
// the date permission to assert copyright is obtained from the U.S.
// Department of Energy, and subject to any subsequent five (5) year
// renewals, the U.S. Government is granted for itself and others acting
// on its behalf a paid-up, nonexclusive, irrevocable, worldwide license
// in the Software to reproduce, prepare derivative works, distribute
// copies to the public, perform publicly and display publicly, and to
// permit others to do so.
//------------------------------------------------------------------------------------------------------------------------------
// Samuel Williams
// SWWilliams@lbl.gov
// Lawrence Berkeley National Lab
//------------------------------------------------------------------------------------------------------------------------------
#include <stdio.h>
#include <stdlib.h>
#include <stdint.h>
#include <string.h>
#include <math.h>
//------------------------------------------------------------------------------------------------------------------------------
#ifdef USE_MPI
#include <mpi.h>
#endif
#ifdef _OPENMP
#include <omp.h>
#endif
//------------------------------------------------------------------------------------------------------------------------------
#include "timers.h"
#include "defines.h"
#include "level.h"
#include "mg.h"
#include "operators.h"
#include "solvers.h"
//------------------------------------------------------------------------------------------------------------------------------
void bench_hpgmg(mg_type *all_grids, int onLevel, double a, double b, double dtol, double rtol){
int doTiming;
int minSolves = 10; // do at least minSolves MGSolves
double timePerSolve = 0;
for(doTiming=0;doTiming<=1;doTiming++){ // first pass warms up, second pass times
#ifdef USE_HPM // IBM performance counters for BGQ...
if( (doTiming==1) && (onLevel==0) )HPM_Start("FMGSolve()");
#endif
#ifdef USE_MPI
double minTime = 60.0; // minimum time in seconds that the benchmark should run
double startTime = MPI_Wtime();
if(doTiming==1){
if((minTime/timePerSolve)>minSolves)minSolves=(minTime/timePerSolve); // if one needs to do more than minSolves to run for minTime, change minSolves
}
#endif
if(all_grids->levels[onLevel]->my_rank==0){
if(doTiming==0){fprintf(stdout,"\n\n===== Warming up by running %d solves ==========================================\n",minSolves);}
else{fprintf(stdout,"\n\n===== Running %d solves ========================================================\n",minSolves);}
fflush(stdout);
}
int numSolves = 0; // solves completed
MGResetTimers(all_grids);
while( (numSolves<minSolves) ){
zero_vector(all_grids->levels[onLevel],VECTOR_U);
#ifdef USE_FCYCLES
FMGSolve(all_grids,onLevel,VECTOR_U,VECTOR_F,a,b,dtol,rtol);
#else
MGSolve(all_grids,onLevel,VECTOR_U,VECTOR_F,a,b,dtol,rtol);
#endif
numSolves++;
}
#ifdef USE_MPI
if(doTiming==0){
double endTime = MPI_Wtime();
timePerSolve = (endTime-startTime)/numSolves;
MPI_Bcast(&timePerSolve,1,MPI_DOUBLE,0,MPI_COMM_WORLD); // after warmup, process 0 broadcasts the average time per solve (consensus)
}
#endif
#ifdef USE_HPM // IBM performance counters for BGQ...
if( (doTiming==1) && (onLevel==0) )HPM_Stop("FMGSolve()");
#endif
}
}
//------------------------------------------------------------------------------------------------------------------------------
int main(int argc, char **argv){
int my_rank=0;
int num_tasks=1;
int OMP_Threads = 1;
//- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
#ifdef _OPENMP
#pragma omp parallel
{
#pragma omp master
{
OMP_Threads = omp_get_num_threads();
}
}
#endif
//- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
// initialize MPI and HPM
#ifdef USE_MPI
int actual_threading_model = -1;
int requested_threading_model = -1;
requested_threading_model = MPI_THREAD_SINGLE;
//requested_threading_model = MPI_THREAD_FUNNELED;
//requested_threading_model = MPI_THREAD_SERIALIZED;
//requested_threading_model = MPI_THREAD_MULTIPLE;
#ifdef _OPENMP
requested_threading_model = MPI_THREAD_FUNNELED;
//requested_threading_model = MPI_THREAD_SERIALIZED;
//requested_threading_model = MPI_THREAD_MULTIPLE;
#endif
MPI_Init_thread(&argc, &argv, requested_threading_model, &actual_threading_model);
MPI_Comm_size(MPI_COMM_WORLD, &num_tasks);
MPI_Comm_rank(MPI_COMM_WORLD, &my_rank);
#ifdef USE_HPM // IBM HPM counters for BGQ...
HPM_Init();
#endif
#endif // USE_MPI
//- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
// parse the arguments...
int log2_box_dim = 6; // 64^3
int target_boxes_per_rank = 1;
//int64_t target_memory_per_rank = -1; // not specified
int64_t box_dim = -1;
int64_t boxes_in_i = -1;
int64_t target_boxes = -1;
if(argc==3){
log2_box_dim=atoi(argv[1]);
target_boxes_per_rank=atoi(argv[2]);
if(log2_box_dim>9){
// NOTE, in order to use 32b int's for array indexing, box volumes must be less than 2^31 doubles
if(my_rank==0){fprintf(stderr,"log2_box_dim must be less than 10\n");}
#ifdef USE_MPI
MPI_Finalize();
#endif
exit(0);
}
if(log2_box_dim<4){
if(my_rank==0){fprintf(stderr,"log2_box_dim must be at least 4\n");}
#ifdef USE_MPI
MPI_Finalize();
#endif
exit(0);
}
if(target_boxes_per_rank<1){
if(my_rank==0){fprintf(stderr,"target_boxes_per_rank must be at least 1\n");}
#ifdef USE_MPI
MPI_Finalize();
#endif
exit(0);
}
#ifndef MAX_COARSE_DIM
#define MAX_COARSE_DIM 11
#endif
box_dim=1<<log2_box_dim;
target_boxes = (int64_t)target_boxes_per_rank*(int64_t)num_tasks;
boxes_in_i = -1;
int64_t bi;
for(bi=1;bi<1000;bi++){ // search all possible problem sizes to find acceptable boxes_in_i
int64_t total_boxes = bi*bi*bi;
if(total_boxes<=target_boxes){
int64_t coarse_grid_dim = box_dim*bi;
while( (coarse_grid_dim%2) == 0){coarse_grid_dim=coarse_grid_dim/2;}
if(coarse_grid_dim<=MAX_COARSE_DIM){
boxes_in_i = bi;
}
}
}
if(boxes_in_i<1){
if(my_rank==0){fprintf(stderr,"failed to find an acceptable problem size\n");}
#ifdef USE_MPI
MPI_Finalize();
#endif
exit(0);
}
} // argc==3
#if 0
else if(argc==2){ // interpret argv[1] as target_memory_per_rank
char *ptr = argv[1];
char *tmp;
target_memory_per_rank = strtol(ptr,&ptr,10);
if(target_memory_per_rank<1){
if(my_rank==0){fprintf(stderr,"unrecognized target_memory_per_rank... '%s'\n",argv[1]);}
#ifdef USE_MPI
MPI_Finalize();
#endif
exit(0);
}
tmp=strstr(ptr,"TB");if(tmp){ptr=tmp+2;target_memory_per_rank *= (uint64_t)(1<<30)*(1<<10);}
tmp=strstr(ptr,"GB");if(tmp){ptr=tmp+2;target_memory_per_rank *= (uint64_t)(1<<30);}
tmp=strstr(ptr,"MB");if(tmp){ptr=tmp+2;target_memory_per_rank *= (uint64_t)(1<<20);}
tmp=strstr(ptr,"tb");if(tmp){ptr=tmp+2;target_memory_per_rank *= (uint64_t)(1<<30)*(1<<10);}
tmp=strstr(ptr,"gb");if(tmp){ptr=tmp+2;target_memory_per_rank *= (uint64_t)(1<<30);}
tmp=strstr(ptr,"mb");if(tmp){ptr=tmp+2;target_memory_per_rank *= (uint64_t)(1<<20);}
if( (ptr) && (*ptr != '\0') ){
if(my_rank==0){fprintf(stderr,"unrecognized units... '%s'\n",ptr);}
#ifdef USE_MPI
MPI_Finalize();
#endif
exit(0);
}
// FIX, now search for an 'acceptable' box_dim and boxes_in_i constrained by target_memory_per_rank, num_tasks, and MAX_COARSE_DIM
} // argc==2
#endif
else{
if(my_rank==0){fprintf(stderr,"usage: ./hpgmg-fv [log2_box_dim] [target_boxes_per_rank]\n");}
//fprintf(stderr," ./hpgmg-fv [target_memory_per_rank[MB,GB,TB]]\n");}
#ifdef USE_MPI
MPI_Finalize();
#endif
exit(0);
}
//- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
if(my_rank==0){
fprintf(stdout,"\n\n");
fprintf(stdout,"********************************************************************************\n");
fprintf(stdout,"*** HPGMG-FV Benchmark ***\n");
fprintf(stdout,"********************************************************************************\n");
#ifdef USE_MPI
if(requested_threading_model == MPI_THREAD_MULTIPLE )fprintf(stdout,"Requested MPI_THREAD_MULTIPLE, ");
else if(requested_threading_model == MPI_THREAD_SINGLE )fprintf(stdout,"Requested MPI_THREAD_SINGLE, ");
else if(requested_threading_model == MPI_THREAD_FUNNELED )fprintf(stdout,"Requested MPI_THREAD_FUNNELED, ");
else if(requested_threading_model == MPI_THREAD_SERIALIZED)fprintf(stdout,"Requested MPI_THREAD_SERIALIZED, ");
else if(requested_threading_model == MPI_THREAD_MULTIPLE )fprintf(stdout,"Requested MPI_THREAD_MULTIPLE, ");
else fprintf(stdout,"Requested Unknown MPI Threading Model (%d), ",requested_threading_model);
if(actual_threading_model == MPI_THREAD_MULTIPLE )fprintf(stdout,"got MPI_THREAD_MULTIPLE\n");
else if(actual_threading_model == MPI_THREAD_SINGLE )fprintf(stdout,"got MPI_THREAD_SINGLE\n");
else if(actual_threading_model == MPI_THREAD_FUNNELED )fprintf(stdout,"got MPI_THREAD_FUNNELED\n");
else if(actual_threading_model == MPI_THREAD_SERIALIZED)fprintf(stdout,"got MPI_THREAD_SERIALIZED\n");
else if(actual_threading_model == MPI_THREAD_MULTIPLE )fprintf(stdout,"got MPI_THREAD_MULTIPLE\n");
else fprintf(stdout,"got Unknown MPI Threading Model (%d)\n",actual_threading_model);
#endif
fprintf(stdout,"%d MPI Tasks of %d threads\n",num_tasks,OMP_Threads);
fprintf(stdout,"\n\n===== Benchmark setup ==========================================================\n");
}
//- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
// create the fine level...
#ifdef USE_PERIODIC_BC
int bc = BC_PERIODIC;
int minCoarseDim = 2; // avoid problems with black box calculation of D^{-1} for poisson with periodic BC's on a 1^3 grid
#else
int bc = BC_DIRICHLET;
int minCoarseDim = 1; // assumes you can drop order on the boundaries
#endif
level_type level_h;
int ghosts=stencil_get_radius();
create_level(&level_h,boxes_in_i,box_dim,ghosts,VECTORS_RESERVED,bc,my_rank,num_tasks);
#ifdef USE_HELMHOLTZ
double a=1.0;double b=1.0; // Helmholtz
if(my_rank==0)fprintf(stdout," Creating Helmholtz (a=%f, b=%f) test problem\n",a,b);
#else
double a=0.0;double b=1.0; // Poisson
if(my_rank==0)fprintf(stdout," Creating Poisson (a=%f, b=%f) test problem\n",a,b);
#endif
double h=1.0/( (double)boxes_in_i*(double)box_dim ); // [0,1]^3 problem
initialize_problem(&level_h,h,a,b); // initialize VECTOR_ALPHA, VECTOR_BETA*, and VECTOR_F
rebuild_operator(&level_h,NULL,a,b); // calculate Dinv and lambda_max
if(level_h.boundary_condition.type == BC_PERIODIC){ // remove any constants from the RHS for periodic problems
double average_value_of_f = mean(&level_h,VECTOR_F);
if(average_value_of_f!=0.0){
if(my_rank==0){fprintf(stderr," WARNING... Periodic boundary conditions, but f does not sum to zero... mean(f)=%e\n",average_value_of_f);}
shift_vector(&level_h,VECTOR_F,VECTOR_F,-average_value_of_f);
}
}
//- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
// create the MG hierarchy...
mg_type MG_h;
MGBuild(&MG_h,&level_h,a,b,minCoarseDim); // build the Multigrid Hierarchy
//- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
// HPGMG-500 benchmark proper
// evaluate performance on problem sizes of h, 2h, and 4h
// (i.e. examine dynamic range for problem sizes N, N/8, and N/64)
//double dtol=1e-15;double rtol= 0.0; // converged if ||D^{-1}(b-Ax)|| < dtol
double dtol= 0.0;double rtol=1e-10; // converged if ||b-Ax|| / ||b|| < rtol
int l;
#ifndef TEST_ERROR
double AverageSolveTime[3];
for(l=0;l<3;l++){
if(l>0)restriction(MG_h.levels[l],VECTOR_F,MG_h.levels[l-1],VECTOR_F,RESTRICT_CELL);
bench_hpgmg(&MG_h,l,a,b,dtol,rtol);
AverageSolveTime[l] = (double)MG_h.timers.MGSolve / (double)MG_h.MGSolves_performed;
if(my_rank==0){fprintf(stdout,"\n\n===== Timing Breakdown =========================================================\n");}
MGPrintTiming(&MG_h,l);
}
if(my_rank==0){
#ifdef CALIBRATE_TIMER
double _timeStart=getTime();sleep(1);double _timeEnd=getTime();
double SecondsPerCycle = (double)1.0/(double)(_timeEnd-_timeStart);
#else
double SecondsPerCycle = 1.0;
#endif
fprintf(stdout,"\n\n===== Performance Summary ======================================================\n");
for(l=0;l<3;l++){
double DOF = (double)MG_h.levels[l]->dim.i*(double)MG_h.levels[l]->dim.j*(double)MG_h.levels[l]->dim.k;
double seconds = SecondsPerCycle*(double)AverageSolveTime[l];
double DOFs = DOF / seconds;
fprintf(stdout," h=%0.15e DOF=%0.15e time=%0.6f DOF/s=%0.3e MPI=%d OMP=%d\n",MG_h.levels[l]->h,DOF,seconds,DOFs,num_tasks,OMP_Threads);
}
}
#endif
//- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
if(my_rank==0){fprintf(stdout,"\n\n===== Richardson error analysis ================================================\n");}
// solve A^h u^h = f^h
// solve A^2h u^2h = f^2h
// solve A^4h u^4h = f^4h
// error analysis...
MGResetTimers(&MG_h);
for(l=0;l<3;l++){
if(l>0)restriction(MG_h.levels[l],VECTOR_F,MG_h.levels[l-1],VECTOR_F,RESTRICT_CELL);
zero_vector(MG_h.levels[l],VECTOR_U);
#ifdef USE_FCYCLES
FMGSolve(&MG_h,l,VECTOR_U,VECTOR_F,a,b,dtol,rtol);
#else
MGSolve(&MG_h,l,VECTOR_U,VECTOR_F,a,b,dtol,rtol);
#endif
}
richardson_error(&MG_h,0,VECTOR_U);
//- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
if(my_rank==0){fprintf(stdout,"\n\n===== Deallocating memory ======================================================\n");}
MGDestroy(&MG_h);
destroy_level(&level_h);
//- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
if(my_rank==0){fprintf(stdout,"\n\n===== Done =====================================================================\n");}
#ifdef USE_MPI
#ifdef USE_HPM // IBM performance counters for BGQ...
HPM_Print();
#endif
MPI_Finalize();
#endif
return(0);
//- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
}
|
3d7pt_var.c | /*
* Order-1, 3D 7 point stencil with variable coefficients
* Adapted from PLUTO and Pochoir test bench
*
* Tareq Malas
*/
#include <stdio.h>
#include <stdlib.h>
#include <sys/time.h>
#ifdef LIKWID_PERFMON
#include <likwid.h>
#endif
#include "print_utils.h"
#define TESTS 2
#define MAX(a,b) ((a) > (b) ? a : b)
#define MIN(a,b) ((a) < (b) ? a : b)
/* Subtract the `struct timeval' values X and Y,
* storing the result in RESULT.
*
* Return 1 if the difference is negative, otherwise 0.
*/
int timeval_subtract(struct timeval *result, struct timeval *x, struct timeval *y)
{
/* Perform the carry for the later subtraction by updating y. */
if (x->tv_usec < y->tv_usec)
{
int nsec = (y->tv_usec - x->tv_usec) / 1000000 + 1;
y->tv_usec -= 1000000 * nsec;
y->tv_sec += nsec;
}
if (x->tv_usec - y->tv_usec > 1000000)
{
int nsec = (x->tv_usec - y->tv_usec) / 1000000;
y->tv_usec += 1000000 * nsec;
y->tv_sec -= nsec;
}
/* Compute the time remaining to wait.
* tv_usec is certainly positive.
*/
result->tv_sec = x->tv_sec - y->tv_sec;
result->tv_usec = x->tv_usec - y->tv_usec;
/* Return 1 if result is negative. */
return x->tv_sec < y->tv_sec;
}
int main(int argc, char *argv[])
{
int t, i, j, k, m, test;
int Nx, Ny, Nz, Nt;
if (argc > 3) {
Nx = atoi(argv[1])+2;
Ny = atoi(argv[2])+2;
Nz = atoi(argv[3])+2;
}
if (argc > 4)
Nt = atoi(argv[4]);
// allocate the arrays
double ****A = (double ****) malloc(sizeof(double***)*2);
for(m=0; m<2;m++){
A[m] = (double ***) malloc(sizeof(double**)*Nz);
for(i=0; i<Nz; i++){
A[m][i] = (double**) malloc(sizeof(double*)*Ny);
for(j=0;j<Ny;j++){
A[m][i][j] = (double*) malloc(sizeof(double)*Nx);
}
}
}
double ****coef = (double ****) malloc(sizeof(double***)*7);
for(m=0; m<7;m++){
coef[m] = (double ***) malloc(sizeof(double**)*Nz);
for(i=0; i<Nz; i++){
coef[m][i] = (double**) malloc(sizeof(double*)*Ny);
for(j=0;j<Ny;j++){
coef[m][i][j] = (double*) malloc(sizeof(double)*Nx);
}
}
}
// tile size information, including extra element to decide the list length
int *tile_size = (int*) malloc(sizeof(int));
tile_size[0] = -1;
// The list is modified here before source-to-source transformations
tile_size = (int*) realloc((void *)tile_size, sizeof(int)*5);
tile_size[0] = 16;
tile_size[1] = 16;
tile_size[2] = 24;
tile_size[3] = 512;
tile_size[4] = -1;
// for timekeeping
int ts_return = -1;
struct timeval start, end, result;
double tdiff = 0.0, min_tdiff=1.e100;
const int BASE = 1024;
// initialize variables
//
srand(42);
for (i = 1; i < Nz; i++) {
for (j = 1; j < Ny; j++) {
for (k = 1; k < Nx; k++) {
A[0][i][j][k] = 1.0 * (rand() % BASE);
}
}
}
for (m=0; m<7; m++) {
for (i=1; i<Nz; i++) {
for (j=1; j<Ny; j++) {
for (k=1; k<Nx; k++) {
coef[m][i][j][k] = 1.0 * (rand() % BASE);
}
}
}
}
#ifdef LIKWID_PERFMON
LIKWID_MARKER_INIT;
#pragma omp parallel
{
LIKWID_MARKER_THREADINIT;
#pragma omp barrier
LIKWID_MARKER_START("calc");
}
#endif
int num_threads = 1;
#if defined(_OPENMP)
num_threads = omp_get_max_threads();
#endif
for(test=0; test<TESTS; test++){
gettimeofday(&start, 0);
// serial execution - Addition: 6 && Multiplication: 2
#pragma scop
for (t = 0; t < Nt-1; t++) {
for (i = 1; i < Nz-1; i++) {
for (j = 1; j < Ny-1; j++) {
for (k = 1; k < Nx-1; k++) {
A[(t+1)%2][i][j][k] = coef[0][i][j][k] * A[t%2][i ][j ][k ] +
coef[1][i][j][k] * A[t%2][i-1][j ][k ] +
coef[2][i][j][k] * A[t%2][i ][j-1][k ] +
coef[3][i][j][k] * A[t%2][i ][j ][k-1] +
coef[4][i][j][k] * A[t%2][i+1][j ][k ] +
coef[5][i][j][k] * A[t%2][i ][j+1][k ] +
coef[6][i][j][k] * A[t%2][i ][j ][k+1];
}
}
}
}
#pragma endscop
gettimeofday(&end, 0);
ts_return = timeval_subtract(&result, &end, &start);
tdiff = (double) (result.tv_sec + result.tv_usec * 1.0e-6);
min_tdiff = min(min_tdiff, tdiff);
printf("Rank 0 TEST# %d time: %f\n", test, tdiff);
}
PRINT_RESULTS(1, "variable no-symmetry")
#ifdef LIKWID_PERFMON
#pragma omp parallel
{
LIKWID_MARKER_STOP("calc");
}
LIKWID_MARKER_CLOSE;
#endif
// Free allocated arrays
for(i=0; i<Nz; i++){
for(j=0;j<Ny;j++){
free(A[0][i][j]);
free(A[1][i][j]);
}
free(A[0][i]);
free(A[1][i]);
}
free(A[0]);
free(A[1]);
for(m=0; m<7;m++){
for(i=0; i<Nz; i++){
for(j=0;j<Ny;j++){
free(coef[m][i][j]);
}
free(coef[m][i]);
}
free(coef[m]);
}
return 0;
}
|
meshsim.c | #include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <omp.h>
int grid_x_length, grid_y_length;
float *average_latency_map;
void bf(int*, int, int);
void print_grid(int*);
void print_float_grid(float*);
void reset_grid(int*);
float average_grid(int*);
int main(int argc, char *argv[]) {
if (argc < 3) {
grid_x_length = 32;
grid_y_length = 32;
} else {
grid_x_length = atoi(argv[1]);
grid_y_length = atoi(argv[2]);
}
printf("Using %dx%d grid\n", grid_x_length, grid_y_length);
average_latency_map = (float *)malloc(sizeof(float) * grid_x_length * grid_y_length);
memset(average_latency_map, 0, sizeof(float) * grid_x_length * grid_y_length);
for (int start_y = 0; start_y < grid_y_length; start_y++) {
printf("Working on row %d\n", start_y);
#pragma omp parallel for
for (int start_x = 0; start_x < grid_x_length; start_x++) {
int *grid = (int *)malloc(sizeof(int) * grid_x_length * grid_y_length);
reset_grid(grid);
for (int v = 0; v < grid_y_length * grid_x_length; v++) bf(grid, start_x, start_y);
//printf("Centered on %d,%d:\n", start_x, start_y);
//print_grid(grid);
float avg = average_grid(grid);
//printf("average for %d, %d: %f\n", start_x, start_y, avg);
average_latency_map[start_y * grid_x_length + start_x] = avg;
free(grid);
}
}
print_float_grid(average_latency_map);
return 0;
}
void reset_grid(int *target_grid) {
for (int y = 0; y < grid_y_length; y++)
for (int x = 0; x < grid_x_length; x++) target_grid[y * grid_x_length + x] = -1;
}
float average_grid(int *target_grid) {
float sum = 0;
for (int y = 0; y < grid_y_length; y++)
for (int x = 0; x < grid_x_length; x++) sum += target_grid[y * grid_x_length + x];
return sum / (grid_x_length * grid_y_length);
}
// one iteration of bellman-ford
void bf(int *grid, int start_x, int start_y) {
grid[start_y * grid_x_length + start_x] = 0;
for (int y = 0; y < grid_y_length; y++) {
for (int x = 0; x < grid_x_length; x++) {
if (grid[y * grid_x_length + x] > -1) {
int current = grid[y * grid_x_length + x];
if (x > 0) {
int *left = grid + (y * grid_x_length + (x - 1));
if (*left == -1 || *left > current + 1) *left = current + 1;
}
if (y > 0) {
int *up = grid + ((y - 1) * grid_x_length + x);
if (*up == -1 || *up > current + 1) *up = current + 1;
}
if (x < grid_x_length - 1) {
int *right = grid + (y * grid_x_length + (x + 1));
if (*right == -1 || *right > current + 1) *right = current + 1;
}
if (y < grid_y_length - 1) {
int *down = grid + ((y + 1) * grid_x_length + x);
if (*down == -1 || *down > current + 1) *down = current + 1;
}
}
}
}
}
void print_grid(int *target_grid) {
for (int x = 0; x < grid_x_length; x++) {
printf(",%d", x);
}
printf("\n");
for (int y = 0; y < grid_y_length; y++) {
printf("%d", y);
for (int x = 0; x < grid_y_length; x++) {
printf(",%d", target_grid[y * grid_x_length + x]);
}
printf("\n");
}
}
void print_float_grid(float *target_grid) {
for (int x = 0; x < grid_x_length; x++) {
printf(",%d", x);
}
printf("\n");
for (int y = 0; y < grid_y_length; y++) {
printf("%d", y);
for (int x = 0; x < grid_x_length; x++) {
printf(",%f", target_grid[y * grid_x_length + x]);
}
printf("\n");
}
}
|
atomic-20.c | /* { dg-do compile } */
/* { dg-additional-options "-fdump-tree-original" } */
/* { dg-final { scan-tree-dump-times "omp atomic release" 1 "original" } } */
/* { dg-final { scan-tree-dump-times "omp atomic seq_cst" 3 "original" } } */
/* { dg-final { scan-tree-dump-times "omp atomic read seq_cst" 1 "original" } } */
/* { dg-final { scan-tree-dump-times "omp atomic capture seq_cst" 1 "original" } } */
int i, j, k, l, m, n;
void
foo ()
{
#pragma omp atomic release
i = i + 1;
}
#pragma omp requires atomic_default_mem_order (seq_cst)
void
bar ()
{
int v;
#pragma omp atomic
j = j + 1;
#pragma omp atomic update
k = k + 1;
#pragma omp atomic read
v = l;
#pragma omp atomic write
m = v;
#pragma omp atomic capture
v = n = n + 1;
}
|
3d25pt.lbpar.c | #include <omp.h>
#include <math.h>
#define ceild(n,d) ceil(((double)(n))/((double)(d)))
#define floord(n,d) floor(((double)(n))/((double)(d)))
#define max(x,y) ((x) > (y)? (x) : (y))
#define min(x,y) ((x) < (y)? (x) : (y))
/*
* Order-2, 3D 25 point stencil
* Adapted from PLUTO and Pochoir test bench
*
* Tareq Malas
*/
#include <stdio.h>
#include <stdlib.h>
#include <sys/time.h>
#ifdef LIKWID_PERFMON
#include <likwid.h>
#endif
#include "print_utils.h"
#define TESTS 2
#define MAX(a,b) ((a) > (b) ? a : b)
#define MIN(a,b) ((a) < (b) ? a : b)
#ifndef min
#define min(x,y) ((x) < (y)? (x) : (y))
#endif
/* Subtract the `struct timeval' values X and Y,
* storing the result in RESULT.
*
* Return 1 if the difference is negative, otherwise 0.
*/
int timeval_subtract(struct timeval *result, struct timeval *x, struct timeval *y)
{
/* Perform the carry for the later subtraction by updating y. */
if (x->tv_usec < y->tv_usec)
{
int nsec = (y->tv_usec - x->tv_usec) / 1000000 + 1;
y->tv_usec -= 1000000 * nsec;
y->tv_sec += nsec;
}
if (x->tv_usec - y->tv_usec > 1000000)
{
int nsec = (x->tv_usec - y->tv_usec) / 1000000;
y->tv_usec += 1000000 * nsec;
y->tv_sec -= nsec;
}
/* Compute the time remaining to wait.
* tv_usec is certainly positive.
*/
result->tv_sec = x->tv_sec - y->tv_sec;
result->tv_usec = x->tv_usec - y->tv_usec;
/* Return 1 if result is negative. */
return x->tv_sec < y->tv_sec;
}
int main(int argc, char *argv[])
{
int t, i, j, k, test;
int Nx, Ny, Nz, Nt;
if (argc > 3) {
Nx = atoi(argv[1])+8;
Ny = atoi(argv[2])+8;
Nz = atoi(argv[3])+8;
}
if (argc > 4)
Nt = atoi(argv[4]);
double ****A = (double ****) malloc(sizeof(double***)*2);
double ***roc2 = (double ***) malloc(sizeof(double**));
A[0] = (double ***) malloc(sizeof(double**)*Nz);
A[1] = (double ***) malloc(sizeof(double**)*Nz);
roc2 = (double ***) malloc(sizeof(double**)*Nz);
for(i=0; i<Nz; i++){
A[0][i] = (double**) malloc(sizeof(double*)*Ny);
A[1][i] = (double**) malloc(sizeof(double*)*Ny);
roc2[i] = (double**) malloc(sizeof(double*)*Ny);
for(j=0;j<Ny;j++){
A[0][i][j] = (double*) malloc(sizeof(double)*Nx);
A[1][i][j] = (double*) malloc(sizeof(double)*Nx);
roc2[i][j] = (double*) malloc(sizeof(double)*Nx);
}
}
// tile size information, including extra element to decide the list length
int *tile_size = (int*) malloc(sizeof(int));
tile_size[0] = -1;
// The list is modified here before source-to-source transformations
tile_size = (int*) realloc((void *)tile_size, sizeof(int)*5);
tile_size[0] = 4;
tile_size[1] = 4;
tile_size[2] = 8;
tile_size[3] = 1024;
tile_size[4] = -1;
// for timekeeping
int ts_return = -1;
struct timeval start, end, result;
double tdiff = 0.0, min_tdiff=1.e100;
const int BASE = 1024;
// initialize variables
//
srand(42);
for (i = 1; i < Nz; i++) {
for (j = 1; j < Ny; j++) {
for (k = 1; k < Nx; k++) {
A[0][i][j][k] = 1.0 * (rand() % BASE);
roc2[i][j][k] = 2.0 * (rand() % BASE);
}
}
}
#ifdef LIKWID_PERFMON
LIKWID_MARKER_INIT;
#pragma omp parallel
{
LIKWID_MARKER_THREADINIT;
#pragma omp barrier
LIKWID_MARKER_START("calc");
}
#endif
int num_threads = 1;
#if defined(_OPENMP)
num_threads = omp_get_max_threads();
#endif
const double coef0 = -0.28472;
const double coef1 = 0.16000;
const double coef2 = -0.02000;
const double coef3 = 0.00254;
const double coef4 = -0.00018;
for(test=0; test<TESTS; test++){
gettimeofday(&start, 0);
// serial execution - Addition: 6 && Multiplication: 2
/* Copyright (C) 1991-2014 Free Software Foundation, Inc.
This file is part of the GNU C Library.
The GNU C Library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
The GNU C Library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with the GNU C Library; if not, see
<http://www.gnu.org/licenses/>. */
/* This header is separate from features.h so that the compiler can
include it implicitly at the start of every compilation. It must
not itself include <features.h> or any other header that includes
<features.h> because the implicit include comes before any feature
test macros that may be defined in a source file before it first
explicitly includes a system header. GCC knows the name of this
header in order to preinclude it. */
/* glibc's intent is to support the IEC 559 math functionality, real
and complex. If the GCC (4.9 and later) predefined macros
specifying compiler intent are available, use them to determine
whether the overall intent is to support these features; otherwise,
presume an older compiler has intent to support these features and
define these macros by default. */
/* wchar_t uses ISO/IEC 10646 (2nd ed., published 2011-03-15) /
Unicode 6.0. */
/* We do not support C11 <threads.h>. */
int t1, t2, t3, t4, t5, t6, t7, t8;
int lb, ub, lbp, ubp, lb2, ub2;
register int lbv, ubv;
/* Start of CLooG code */
if ((Nt >= 1) && (Nx >= 9) && (Ny >= 9) && (Nz >= 9)) {
for (t1=-1;t1<=2*Nt-2;t1++) {
lbp=ceild(t1+2,2);
ubp=min(floord(4*Nt+Nz-9,4),floord(2*t1+Nz-4,4));
#pragma omp parallel for private(lbv,ubv,t3,t4,t5,t6,t7,t8)
for (t2=lbp;t2<=ubp;t2++) {
for (t3=max(ceild(t1,4),ceild(4*t2-Nz+5,8));t3<=min(min(floord(4*Nt+Ny-9,8),floord(2*t1+Ny-3,8)),floord(4*t2+Ny-9,8));t3++) {
for (t4=max(max(ceild(t1-508,512),ceild(4*t2-Nz-1011,1024)),ceild(8*t3-Ny-1011,1024));t4<=min(min(min(floord(4*Nt+Nx-9,1024),floord(2*t1+Nx-3,1024)),floord(4*t2+Nx-9,1024)),floord(8*t3+Nx-5,1024));t4++) {
for (t5=max(max(max(ceild(t1,2),ceild(4*t2-Nz+5,4)),ceild(8*t3-Ny+5,4)),ceild(1024*t4-Nx+5,4));t5<=floord(t1+1,2);t5++) {
for (t6=max(4*t2,-4*t1+4*t2+8*t5-3);t6<=min(min(4*t2+3,-4*t1+4*t2+8*t5),4*t5+Nz-5);t6++) {
for (t7=max(8*t3,4*t5+4);t7<=min(8*t3+7,4*t5+Ny-5);t7++) {
lbv=max(1024*t4,4*t5+4);
ubv=min(1024*t4+1023,4*t5+Nx-5);
#pragma ivdep
#pragma vector always
for (t8=lbv;t8<=ubv;t8++) {
A[( t5 + 1) % 2][ (-4*t5+t6)][ (-4*t5+t7)][ (-4*t5+t8)] = (((2.0 * A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7)][ (-4*t5+t8)]) - A[( t5 + 1) % 2][ (-4*t5+t6)][ (-4*t5+t7)][ (-4*t5+t8)]) + (roc2[ (-4*t5+t6)][ (-4*t5+t7)][ (-4*t5+t8)] * (((((coef0 * A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7)][ (-4*t5+t8)]) + (coef1 * (((((A[ t5 % 2][ (-4*t5+t6) - 1][ (-4*t5+t7)][ (-4*t5+t8)] + A[ t5 % 2][ (-4*t5+t6) + 1][ (-4*t5+t7)][ (-4*t5+t8)]) + A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7) - 1][ (-4*t5+t8)]) + A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7) + 1][ (-4*t5+t8)]) + A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7)][ (-4*t5+t8) - 1]) + A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7)][ (-4*t5+t8) + 1]))) + (coef2 * (((((A[ t5 % 2][ (-4*t5+t6) - 2][ (-4*t5+t7)][ (-4*t5+t8)] + A[ t5 % 2][ (-4*t5+t6) + 2][ (-4*t5+t7)][ (-4*t5+t8)]) + A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7) - 2][ (-4*t5+t8)]) + A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7) + 2][ (-4*t5+t8)]) + A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7)][ (-4*t5+t8) - 2]) + A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7)][ (-4*t5+t8) + 2]))) + (coef3 * (((((A[ t5 % 2][ (-4*t5+t6) - 3][ (-4*t5+t7)][ (-4*t5+t8)] + A[ t5 % 2][ (-4*t5+t6) + 3][ (-4*t5+t7)][ (-4*t5+t8)]) + A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7) - 3][ (-4*t5+t8)]) + A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7) + 3][ (-4*t5+t8)]) + A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7)][ (-4*t5+t8) - 3]) + A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7)][ (-4*t5+t8) + 3]))) + (coef4 * (((((A[ t5 % 2][ (-4*t5+t6) - 4][ (-4*t5+t7)][ (-4*t5+t8)] + A[ t5 % 2][ (-4*t5+t6) + 4][ (-4*t5+t7)][ (-4*t5+t8)]) + A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7) - 4][ (-4*t5+t8)]) + A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7) + 4][ (-4*t5+t8)]) + A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7)][ (-4*t5+t8) - 4]) + A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7)][ (-4*t5+t8) + 4])))));;
}
}
}
}
}
}
}
}
}
/* End of CLooG code */
gettimeofday(&end, 0);
ts_return = timeval_subtract(&result, &end, &start);
tdiff = (double) (result.tv_sec + result.tv_usec * 1.0e-6);
min_tdiff = MIN(min_tdiff, tdiff);
printf("Rank 0 TEST# %d time: %f\n", test, tdiff);
}
PRINT_RESULTS(4, "constant")
#ifdef LIKWID_PERFMON
#pragma omp parallel
{
LIKWID_MARKER_STOP("calc");
}
LIKWID_MARKER_CLOSE;
#endif
// Free allocated arrays
for(i=0; i<Nz; i++){
for(j=0;j<Ny;j++){
free(A[0][i][j]);
free(A[1][i][j]);
free(roc2[i][j]);
}
free(A[0][i]);
free(A[1][i]);
free(roc2[i]);
}
free(A[0]);
free(A[1]);
free(roc2);
return 0;
}
|
rom_builder_and_solver.h | // | / |
// ' / __| _` | __| _ \ __|
// . \ | ( | | ( |\__ `
// _|\_\_| \__,_|\__|\___/ ____/
// Multi-Physics
//
// License: BSD License
// Kratos default license: kratos/license.txt
//
// Main authors: Riccardo Rossi
// Raul Bravo
//
#if !defined(KRATOS_ROM_BUILDER_AND_SOLVER)
#define KRATOS_ROM_BUILDER_AND_SOLVER
/* System includes */
/* External includes */
/* Project includes */
#include "includes/define.h"
#include "includes/model_part.h"
#include "solving_strategies/schemes/scheme.h"
#include "solving_strategies/builder_and_solvers/builder_and_solver.h"
#include "utilities/builtin_timer.h"
/* Application includes */
#include "rom_application_variables.h"
namespace Kratos
{
///@name Kratos Globals
///@{
///@}
///@name Type Definitions
///@{
///@}
///@name Enum's
///@{
///@}
///@name Functions
///@{
///@}
///@name Kratos Classes
///@{
template <class TSparseSpace, class TDenseSpace, class TLinearSolver>
class ROMBuilderAndSolver : public BuilderAndSolver<TSparseSpace, TDenseSpace, TLinearSolver>
{
public:
//TODO: UPDATE THIS
/**
* This struct is used in the component wise calculation only
* is defined here and is used to declare a member variable in the component wise builder and solver
* private pointers can only be accessed by means of set and get functions
* this allows to set and not copy the Element_Variables and Condition_Variables
* which will be asked and set by another strategy object
*/
///@name Type Definitions
///@{
// Class pointer definition
KRATOS_CLASS_POINTER_DEFINITION(ROMBuilderAndSolver);
// The size_t types
typedef std::size_t SizeType;
typedef std::size_t IndexType;
/// The definition of the current class
typedef ROMBuilderAndSolver<TSparseSpace, TDenseSpace, TLinearSolver> ClassType;
/// Definition of the classes from the base class
typedef BuilderAndSolver<TSparseSpace, TDenseSpace, TLinearSolver> BaseType;
typedef typename BaseType::TSchemeType TSchemeType;
typedef typename BaseType::DofsArrayType DofsArrayType;
typedef typename BaseType::TSystemMatrixType TSystemMatrixType;
typedef typename BaseType::TSystemVectorType TSystemVectorType;
typedef typename BaseType::LocalSystemVectorType LocalSystemVectorType;
typedef typename BaseType::LocalSystemMatrixType LocalSystemMatrixType;
typedef typename BaseType::TSystemMatrixPointerType TSystemMatrixPointerType;
typedef typename BaseType::TSystemVectorPointerType TSystemVectorPointerType;
typedef typename BaseType::ElementsArrayType ElementsArrayType;
typedef typename BaseType::ConditionsArrayType ConditionsArrayType;
/// Additional definitions
typedef Element::EquationIdVectorType EquationIdVectorType;
typedef Element::DofsVectorType DofsVectorType;
typedef boost::numeric::ublas::compressed_matrix<double> CompressedMatrixType;
/// DoF types definition
typedef Node<3> NodeType;
typedef typename NodeType::DofType DofType;
typedef typename DofType::Pointer DofPointerType;
typedef typename std::unordered_set<DofPointerType, DofPointerHasher> DofSetType;
///@}
///@name Life cycle
///@{
explicit ROMBuilderAndSolver(
typename TLinearSolver::Pointer pNewLinearSystemSolver,
Parameters ThisParameters)
: BuilderAndSolver<TSparseSpace, TDenseSpace, TLinearSolver>(pNewLinearSystemSolver)
{
// Validate and assign defaults
Parameters this_parameters_copy = ThisParameters.Clone();
this_parameters_copy = this->ValidateAndAssignParameters(this_parameters_copy, this->GetDefaultParameters());
this->AssignSettings(this_parameters_copy);
}
~ROMBuilderAndSolver() = default;
///@}
///@name Operators
///@{
///@}
///@name Operations
///@{
typename BaseType::Pointer Create(
typename TLinearSolver::Pointer pNewLinearSystemSolver,
Parameters ThisParameters) const override
{
return Kratos::make_shared<ClassType>(pNewLinearSystemSolver,ThisParameters);
}
void SetUpDofSet(
typename TSchemeType::Pointer pScheme,
ModelPart &rModelPart) override
{
KRATOS_TRY;
KRATOS_INFO_IF("ROMBuilderAndSolver", (this->GetEchoLevel() > 1 && rModelPart.GetCommunicator().MyPID() == 0)) << "Setting up the dofs" << std::endl;
KRATOS_INFO_IF("ROMBuilderAndSolver", (this->GetEchoLevel() > 2)) << "Number of threads" << ParallelUtilities::GetNumThreads() << "\n" << std::endl;
KRATOS_INFO_IF("ROMBuilderAndSolver", (this->GetEchoLevel() > 2)) << "Initializing element loop" << std::endl;
// Get model part data
const auto& r_elements_array = rModelPart.Elements();
const auto& r_conditions_array = rModelPart.Conditions();
const auto& r_constraints_array = rModelPart.MasterSlaveConstraints();
const int number_of_elements = static_cast<int>(r_elements_array.size());
const int number_of_conditions = static_cast<int>(r_conditions_array.size());
const int number_of_constraints = static_cast<int>(r_constraints_array.size());
const auto& r_current_process_info = rModelPart.GetProcessInfo();
DofsVectorType dof_list;
DofsVectorType second_dof_list; // NOTE: The second dof list is only used on constraints to include master/slave relations
DofSetType dof_global_set;
dof_global_set.reserve(number_of_elements * 20);
if (mHromWeightsInitialized == false){
int number_of_hrom_entities = 0;
#pragma omp parallel firstprivate(dof_list, second_dof_list) reduction(+:number_of_hrom_entities)
{
// We create the temporal set and we reserve some space on them
DofSetType dofs_tmp_set;
dofs_tmp_set.reserve(20000);
// Loop the array of elements
ElementsArrayType selected_elements_private;
#pragma omp for schedule(guided, 512) nowait
for (int i = 0; i < number_of_elements; ++i) {
auto it_elem = r_elements_array.begin() + i;
// Detect whether the element has an hyperreduced weight (H-ROM simulation) or not (ROM simulation)
if ((it_elem)->Has(HROM_WEIGHT)){
selected_elements_private.push_back(*it_elem.base());
number_of_hrom_entities++;
} else {
it_elem->SetValue(HROM_WEIGHT, 1.0);
}
// Gets list of DOF involved on every element
pScheme->GetDofList(*it_elem, dof_list, r_current_process_info);
dofs_tmp_set.insert(dof_list.begin(), dof_list.end());
}
// Loop the array of conditions
ConditionsArrayType selected_conditions_private;
#pragma omp for schedule(guided, 512) nowait
for (int i = 0; i < number_of_conditions; ++i) {
auto it_cond = r_conditions_array.begin() + i;
// Detect whether the condition has an hyperreduced weight (H-ROM simulation) or not (ROM simulation)
// Note that those conditions used for displaying results are to be ignored as they will not be assembled
if (it_cond->Has(HROM_WEIGHT)){
selected_conditions_private.push_back(*it_cond.base());
number_of_hrom_entities++;
} else {
it_cond->SetValue(HROM_WEIGHT, 1.0);
}
// Gets list of DOF involved on every condition
pScheme->GetDofList(*it_cond, dof_list, r_current_process_info);
dofs_tmp_set.insert(dof_list.begin(), dof_list.end());
}
// Loop the array of constraints
#pragma omp for schedule(guided, 512) nowait
for (int i = 0; i < number_of_constraints; ++i) {
auto it_const = r_constraints_array.begin() + i;
// Gets list of Dof involved on every constraint
it_const->GetDofList(dof_list, second_dof_list, r_current_process_info);
dofs_tmp_set.insert(dof_list.begin(), dof_list.end());
dofs_tmp_set.insert(second_dof_list.begin(), second_dof_list.end());
}
#pragma omp critical
{
// Collect the elements and conditions belonging to the H-ROM mesh
// These are those that feature a weight and are to be assembled
for (auto &r_cond : selected_conditions_private){
mSelectedConditions.push_back(&r_cond);
}
for (auto &r_elem : selected_elements_private){
mSelectedElements.push_back(&r_elem);
}
// We merge all the sets in one thread
dof_global_set.insert(dofs_tmp_set.begin(), dofs_tmp_set.end());
}
}
// Update H-ROM flags
if (number_of_hrom_entities) {
mHromSimulation = true;
}
mHromWeightsInitialized = true;
} else {
#pragma omp parallel firstprivate(dof_list, second_dof_list)
{
// We create the temporal set and we reserve some space on them
DofSetType dofs_tmp_set;
dofs_tmp_set.reserve(20000);
// Loop the array of elements
ElementsArrayType selected_elements_private;
#pragma omp for schedule(guided, 512) nowait
for (int i = 0; i < number_of_elements; ++i) {
auto it_elem = r_elements_array.begin() + i;
// Gets list of DOF involved on every element
pScheme->GetDofList(*it_elem, dof_list, r_current_process_info);
dofs_tmp_set.insert(dof_list.begin(), dof_list.end());
}
// Loop the array of conditions
ConditionsArrayType selected_conditions_private;
#pragma omp for schedule(guided, 512) nowait
for (int i = 0; i < number_of_conditions; ++i) {
auto it_cond = r_conditions_array.begin() + i;
// Gets list of DOF involved on every condition
pScheme->GetDofList(*it_cond, dof_list, r_current_process_info);
dofs_tmp_set.insert(dof_list.begin(), dof_list.end());
}
// Loop the array of constraints
#pragma omp for schedule(guided, 512) nowait
for (int i = 0; i < number_of_constraints; ++i) {
auto it_const = r_constraints_array.begin() + i;
// Gets list of Dof involved on every constraint
it_const->GetDofList(dof_list, second_dof_list, r_current_process_info);
dofs_tmp_set.insert(dof_list.begin(), dof_list.end());
dofs_tmp_set.insert(second_dof_list.begin(), second_dof_list.end());
}
#pragma omp critical
{
// We merge all the sets in one thread
dof_global_set.insert(dofs_tmp_set.begin(), dofs_tmp_set.end());
}
}
}
// Fill a sorted auxiliary array of with the DOFs set
KRATOS_INFO_IF("ROMBuilderAndSolver", (this->GetEchoLevel() > 2)) << "Initializing ordered array filling\n" << std::endl;
DofsArrayType Doftemp;
Doftemp.reserve(dof_global_set.size());
for (auto it = dof_global_set.begin(); it != dof_global_set.end(); it++) {
Doftemp.push_back(*it);
}
Doftemp.Sort();
// Update base builder and solver DOFs array and set corresponding flag
BaseType::GetDofSet() = Doftemp;
BaseType::SetDofSetIsInitializedFlag(true);
// Throw an exception if there are no DOFs involved in the analysis
KRATOS_ERROR_IF(BaseType::GetDofSet().size() == 0) << "No degrees of freedom!" << std::endl;
KRATOS_INFO_IF("ROMBuilderAndSolver", (this->GetEchoLevel() > 2)) << "Number of degrees of freedom:" << BaseType::mDofSet.size() << std::endl;
KRATOS_INFO_IF("ROMBuilderAndSolver", (this->GetEchoLevel() > 2 && rModelPart.GetCommunicator().MyPID() == 0)) << "Finished setting up the dofs" << std::endl;
#ifdef KRATOS_DEBUG
// If reactions are to be calculated, we check if all the dofs have reactions defined
if (BaseType::GetCalculateReactionsFlag()) {
for (auto dof_iterator = BaseType::mDofSet.begin(); dof_iterator != BaseType::mDofSet.end(); ++dof_iterator) {
KRATOS_ERROR_IF_NOT(dof_iterator->HasReaction())
<< "Reaction variable not set for the following : " << std::endl
<< "Node : " << dof_iterator->Id() << std::endl
<< "Dof : " << (*dof_iterator) << std::endl
<< "Not possible to calculate reactions." << std::endl;
}
}
#endif
KRATOS_CATCH("");
}
void SetUpSystem(ModelPart &rModelPart) override
{
auto& r_dof_set = BaseType::GetDofSet();
BaseType::mEquationSystemSize = r_dof_set.size();
int ndofs = static_cast<int>(r_dof_set.size());
#pragma omp parallel for firstprivate(ndofs)
for (int i = 0; i < ndofs; i++){
auto dof_iterator = r_dof_set.begin() + i;
dof_iterator->SetEquationId(i);
}
}
// Vector ProjectToReducedBasis(
// const TSystemVectorType& rX,
// ModelPart::NodesContainerType& rNodes
// )
// {
// Vector rom_unknowns = ZeroVector(mNumberOfRomModes);
// for(const auto& node : rNodes)
// {
// unsigned int node_aux_id = node.GetValue(AUX_ID);
// const auto& nodal_rom_basis = node.GetValue(ROM_BASIS);
// for (int i = 0; i < mNumberOfRomModes; ++i) {
// for (int j = 0; j < mNodalDofs; ++j) {
// rom_unknowns[i] += nodal_rom_basis(j, i)*rX(node_aux_id*mNodalDofs + j);
// }
// }
// }
// return rom_unknowns;
// }
void ProjectToFineBasis(
const TSystemVectorType& rRomUnkowns,
ModelPart& rModelPart,
TSystemVectorType& rDx)
{
auto& r_dof_set = BaseType::GetDofSet();
const int dofs_number = r_dof_set.size();
const auto dofs_begin = r_dof_set.begin();
#pragma omp parallel firstprivate(dofs_begin, dofs_number)
{
const Matrix *pcurrent_rom_nodal_basis = nullptr;
unsigned int old_dof_id;
#pragma omp for nowait
for (int k = 0; k < dofs_number; k++) {
auto dof = dofs_begin + k;
if (pcurrent_rom_nodal_basis == nullptr) {
pcurrent_rom_nodal_basis = &(rModelPart.pGetNode(dof->Id())->GetValue(ROM_BASIS));
old_dof_id = dof->Id();
} else if (dof->Id() != old_dof_id ) {
pcurrent_rom_nodal_basis = &(rModelPart.pGetNode(dof->Id())->GetValue(ROM_BASIS));
old_dof_id = dof->Id();
}
rDx[dof->EquationId()] = inner_prod(row(*pcurrent_rom_nodal_basis, mMapPhi[dof->GetVariable().Key()]), rRomUnkowns);
}
}
}
void GetPhiElemental(
Matrix &PhiElemental,
const Element::DofsVectorType& rDofs,
const Element::GeometryType& rGeom)
{
const Matrix *pcurrent_rom_nodal_basis = nullptr;
int counter = 0;
for(int k = 0; k < static_cast<int>(rDofs.size()); ++k){
auto variable_key = rDofs[k]->GetVariable().Key();
if(k==0) {
pcurrent_rom_nodal_basis = &(rGeom[counter].GetValue(ROM_BASIS));
} else if(rDofs[k]->Id() != rDofs[k-1]->Id()) {
counter++;
pcurrent_rom_nodal_basis = &(rGeom[counter].GetValue(ROM_BASIS));
}
if (rDofs[k]->IsFixed()) {
noalias(row(PhiElemental, k)) = ZeroVector(PhiElemental.size2());
} else {
noalias(row(PhiElemental, k)) = row(*pcurrent_rom_nodal_basis, mMapPhi[variable_key]);
}
}
}
void BuildAndSolve(
typename TSchemeType::Pointer pScheme,
ModelPart &rModelPart,
TSystemMatrixType &A,
TSystemVectorType &Dx,
TSystemVectorType &b) override
{
// Define a dense matrix to hold the reduced problem
Matrix Arom = ZeroMatrix(mNumberOfRomModes, mNumberOfRomModes);
Vector brom = ZeroVector(mNumberOfRomModes);
TSystemVectorType x(Dx.size());
const auto forward_projection_timer = BuiltinTimer();
Vector xrom = ZeroVector(mNumberOfRomModes);
//this->ProjectToReducedBasis(x, rModelPart.Nodes(),xrom);
KRATOS_INFO_IF("ROMBuilderAndSolver", (this->GetEchoLevel() > 0 && rModelPart.GetCommunicator().MyPID() == 0)) << "Project to reduced basis time: " << forward_projection_timer.ElapsedSeconds() << std::endl;
// Build the system matrix by looping over elements and conditions and assembling to A
KRATOS_ERROR_IF(!pScheme) << "No scheme provided!" << std::endl;
// Getting the elements from the model
// Only selected conditions and elements are used for the calculation in an H-ROM simulation
const auto el_begin = mHromSimulation ? mSelectedElements.begin() : rModelPart.ElementsBegin();
const int nelements = mHromSimulation ? mSelectedElements.size() : rModelPart.NumberOfElements();
const auto cond_begin = mHromSimulation ? mSelectedConditions.begin() : rModelPart.ConditionsBegin();
const int nconditions = mHromSimulation ? mSelectedConditions.size() : rModelPart.NumberOfConditions();
// Get ProcessInfo from main model part
const ProcessInfo& r_current_process_info = rModelPart.GetProcessInfo();
// Contributions to the system
LocalSystemMatrixType LHS_Contribution = LocalSystemMatrixType(0, 0);
LocalSystemVectorType RHS_Contribution = LocalSystemVectorType(0);
// Vector containing the localization in the system of the different terms
Element::EquationIdVectorType EquationId;
// Assemble all entities
const auto assembling_timer = BuiltinTimer();
#pragma omp parallel firstprivate(nelements, nconditions, LHS_Contribution, RHS_Contribution, EquationId, el_begin, cond_begin)
{
Matrix PhiElemental;
Matrix tempA = ZeroMatrix(mNumberOfRomModes,mNumberOfRomModes);
Vector tempb = ZeroVector(mNumberOfRomModes);
Matrix aux;
#pragma omp for nowait
for (int k = 0; k < static_cast<int>(nelements); k++) {
auto it_el = el_begin + k;
// Detect if the element is active or not. If the user did not make any choice the element is active by default
bool element_is_active = true;
if ((it_el)->IsDefined(ACTIVE)) {
element_is_active = (it_el)->Is(ACTIVE);
}
// Calculate elemental contribution
if (element_is_active){
pScheme->CalculateSystemContributions(*it_el, LHS_Contribution, RHS_Contribution, EquationId, r_current_process_info);
Element::DofsVectorType dofs;
it_el->GetDofList(dofs, r_current_process_info);
const auto &geom = it_el->GetGeometry();
if(PhiElemental.size1() != dofs.size() || PhiElemental.size2() != mNumberOfRomModes) {
PhiElemental.resize(dofs.size(), mNumberOfRomModes,false);
}
if(aux.size1() != dofs.size() || aux.size2() != mNumberOfRomModes) {
aux.resize(dofs.size(), mNumberOfRomModes,false);
}
GetPhiElemental(PhiElemental, dofs, geom);
noalias(aux) = prod(LHS_Contribution, PhiElemental);
double h_rom_weight = it_el->GetValue(HROM_WEIGHT);
noalias(tempA) += prod(trans(PhiElemental), aux) * h_rom_weight;
noalias(tempb) += prod(trans(PhiElemental), RHS_Contribution) * h_rom_weight;
}
}
#pragma omp for nowait
for (int k = 0; k < static_cast<int>(nconditions); k++){
auto it = cond_begin + k;
// Detect if the element is active or not. If the user did not make any choice the condition is active by default
bool condition_is_active = true;
if ((it)->IsDefined(ACTIVE)) {
condition_is_active = (it)->Is(ACTIVE);
}
// Calculate condition contribution
if (condition_is_active) {
Condition::DofsVectorType dofs;
it->GetDofList(dofs, r_current_process_info);
pScheme->CalculateSystemContributions(*it, LHS_Contribution, RHS_Contribution, EquationId, r_current_process_info);
const auto &geom = it->GetGeometry();
if(PhiElemental.size1() != dofs.size() || PhiElemental.size2() != mNumberOfRomModes) {
PhiElemental.resize(dofs.size(), mNumberOfRomModes,false);
}
if(aux.size1() != dofs.size() || aux.size2() != mNumberOfRomModes) {
aux.resize(dofs.size(), mNumberOfRomModes,false);
}
GetPhiElemental(PhiElemental, dofs, geom);
noalias(aux) = prod(LHS_Contribution, PhiElemental);
double h_rom_weight = it->GetValue(HROM_WEIGHT);
noalias(tempA) += prod(trans(PhiElemental), aux) * h_rom_weight;
noalias(tempb) += prod(trans(PhiElemental), RHS_Contribution) * h_rom_weight;
}
}
#pragma omp critical
{
noalias(Arom) += tempA;
noalias(brom) += tempb;
}
}
KRATOS_INFO_IF("ROMBuilderAndSolver", (this->GetEchoLevel() > 0 && rModelPart.GetCommunicator().MyPID() == 0)) << "Build time: " << assembling_timer.ElapsedSeconds() << std::endl;
KRATOS_INFO_IF("ROMBuilderAndSolver", (this->GetEchoLevel() > 2 && rModelPart.GetCommunicator().MyPID() == 0)) << "Finished parallel building" << std::endl;
//solve for the rom unkowns dunk = Arom^-1 * brom
Vector dxrom(xrom.size());
const auto solving_timer = BuiltinTimer();
MathUtils<double>::Solve(Arom, dxrom, brom);
KRATOS_INFO_IF("ROMBuilderAndSolver", (this->GetEchoLevel() > 0 && rModelPart.GetCommunicator().MyPID() == 0)) << "Solve reduced system time: " << solving_timer.ElapsedSeconds() << std::endl;
// //update database
// noalias(xrom) += dxrom;
// project reduced solution back to full order model
const auto backward_projection_timer = BuiltinTimer();
ProjectToFineBasis(dxrom, rModelPart, Dx);
KRATOS_INFO_IF("ROMBuilderAndSolver", (this->GetEchoLevel() > 0 && rModelPart.GetCommunicator().MyPID() == 0)) << "Project to fine basis time: " << backward_projection_timer.ElapsedSeconds() << std::endl;
}
void ResizeAndInitializeVectors(
typename TSchemeType::Pointer pScheme,
TSystemMatrixPointerType &pA,
TSystemVectorPointerType &pDx,
TSystemVectorPointerType &pb,
ModelPart &rModelPart) override
{
KRATOS_TRY
// If not initialized, initalize the system arrays to an empty vector/matrix
if (!pA) {
TSystemMatrixPointerType p_new_A = Kratos::make_shared<TSystemMatrixType>(0, 0);
pA.swap(p_new_A);
}
if (!pDx) {
TSystemVectorPointerType p_new_Dx = Kratos::make_shared<TSystemVectorType>(0);
pDx.swap(p_new_Dx);
}
if (!pb) {
TSystemVectorPointerType p_new_b = Kratos::make_shared<TSystemVectorType>(0);
pb.swap(p_new_b);
}
TSystemVectorType& r_Dx = *pDx;
if (r_Dx.size() != BaseType::GetEquationSystemSize()) {
r_Dx.resize(BaseType::GetEquationSystemSize(), false);
}
TSystemVectorType& r_b = *pb;
if (r_b.size() != BaseType::GetEquationSystemSize()) {
r_b.resize(BaseType::GetEquationSystemSize(), false);
}
KRATOS_CATCH("")
}
Parameters GetDefaultParameters() const override
{
Parameters default_parameters = Parameters(R"(
{
"name" : "rom_builder_and_solver",
"nodal_unknowns" : [],
"number_of_rom_dofs" : 10
})");
default_parameters.AddMissingParameters(BaseType::GetDefaultParameters());
return default_parameters;
}
static std::string Name()
{
return "rom_builder_and_solver";
}
///@}
///@name Access
///@{
///@}
///@name Inquiry
///@{
///@}
///@name Input and output
///@{
/// Turn back information as a string.
virtual std::string Info() const override
{
return "ROMBuilderAndSolver";
}
/// Print information about this object.
virtual void PrintInfo(std::ostream &rOStream) const override
{
rOStream << Info();
}
/// Print object's data.
virtual void PrintData(std::ostream &rOStream) const override
{
rOStream << Info();
}
///@}
///@name Friends
///@{
///@}
protected:
///@}
///@name Protected static member variables
///@{
///@}
///@name Protected member variables
///@{
SizeType mNodalDofs;
SizeType mNumberOfRomModes;
std::unordered_map<Kratos::VariableData::KeyType,int> mMapPhi;
ElementsArrayType mSelectedElements;
ConditionsArrayType mSelectedConditions;
bool mHromSimulation = false;
bool mHromWeightsInitialized = false;
///@}
///@name Protected operators
///@{
///@}
///@name Protected operations
///@{
void AssignSettings(const Parameters ThisParameters) override
{
BaseType::AssignSettings(ThisParameters);
// Set member variables
mNodalDofs = ThisParameters["nodal_unknowns"].size();
mNumberOfRomModes = ThisParameters["number_of_rom_dofs"].GetInt();
// Set up a map with key the variable key and value the correct row in ROM basis
IndexType k = 0;
for (const auto& r_var_name : ThisParameters["nodal_unknowns"].GetStringArray()) {
if(KratosComponents<Variable<double>>::Has(r_var_name)) {
const auto& var = KratosComponents<Variable<double>>::Get(r_var_name);
mMapPhi[var.Key()] = k++;
} else {
KRATOS_ERROR << "Variable \""<< r_var_name << "\" not valid" << std::endl;
}
}
}
///@}
///@name Protected access
///@{
///@}
///@name Protected inquiry
///@{
///@}
///@name Protected life cycle
///@{
///@}
}; /* Class ROMBuilderAndSolver */
///@}
///@name Type Definitions
///@{
///@}
} /* namespace Kratos.*/
#endif /* KRATOS_ROM_BUILDER_AND_SOLVER defined */
|
convolution_1x1_pack8to1_fp16s.h | // Tencent is pleased to support the open source community by making ncnn available.
//
// Copyright (C) 2020 THL A29 Limited, a Tencent company. All rights reserved.
//
// Licensed under the BSD 3-Clause License (the "License"); you may not use this file except
// in compliance with the License. You may obtain a copy of the License at
//
// https://opensource.org/licenses/BSD-3-Clause
//
// Unless required by applicable law or agreed to in writing, software distributed
// under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
// CONDITIONS OF ANY KIND, either express or implied. See the License for the
// specific language governing permissions and limitations under the License.
static void conv1x1s1_sgemm_transform_kernel_pack8to1_fp16sa_neon(const Mat& kernel, Mat& kernel_tm_pack8to1, int inch, int outch)
{
// interleave
// src = inch-outch
// dst = 8a-inch/8a-outch
kernel_tm_pack8to1.create(8, inch / 8, outch / 8 + outch % 8, (size_t)2u * 8, 8);
int p = 0;
for (; p + 7 < outch; p += 8)
{
const float* k0 = (const float*)kernel + (p + 0) * inch;
const float* k1 = (const float*)kernel + (p + 1) * inch;
const float* k2 = (const float*)kernel + (p + 2) * inch;
const float* k3 = (const float*)kernel + (p + 3) * inch;
const float* k4 = (const float*)kernel + (p + 4) * inch;
const float* k5 = (const float*)kernel + (p + 5) * inch;
const float* k6 = (const float*)kernel + (p + 6) * inch;
const float* k7 = (const float*)kernel + (p + 7) * inch;
__fp16* g0 = kernel_tm_pack8to1.channel(p / 8);
for (int q = 0; q + 7 < inch; q += 8)
{
for (int i = 0; i < 8; i++)
{
g0[0] = (__fp16)k0[i];
g0[1] = (__fp16)k1[i];
g0[2] = (__fp16)k2[i];
g0[3] = (__fp16)k3[i];
g0[4] = (__fp16)k4[i];
g0[5] = (__fp16)k5[i];
g0[6] = (__fp16)k6[i];
g0[7] = (__fp16)k7[i];
g0 += 8;
}
k0 += 8;
k1 += 8;
k2 += 8;
k3 += 8;
k4 += 8;
k5 += 8;
k6 += 8;
k7 += 8;
}
}
for (; p < outch; p++)
{
const float* k0 = (const float*)kernel + p * inch;
__fp16* g0 = kernel_tm_pack8to1.channel(p / 8 + p % 8);
for (int q = 0; q + 7 < inch; q += 8)
{
for (int i = 0; i < 8; i++)
{
g0[0] = (__fp16)k0[i];
g0 += 1;
}
k0 += 8;
}
}
}
static void conv1x1s1_sgemm_pack8to1_fp16sa_neon(const Mat& bottom_blob, Mat& top_blob, const Mat& kernel, const Mat& _bias, const Option& opt)
{
int w = bottom_blob.w;
int h = bottom_blob.h;
int inch = bottom_blob.c;
int outch = top_blob.c;
size_t elemsize = bottom_blob.elemsize;
int elempack = bottom_blob.elempack;
const int size = w * h;
const __fp16* bias = _bias;
// interleave
Mat tmp;
if (size >= 8)
tmp.create(8, inch, size / 8 + (size % 8) / 4 + size % 4, elemsize, elempack, opt.workspace_allocator);
else if (size >= 4)
tmp.create(4, inch, size / 4 + size % 4, elemsize, elempack, opt.workspace_allocator);
else // if (size >= 1)
tmp.create(1, inch, size, elemsize, elempack, opt.workspace_allocator);
{
int nn_size;
int remain_size_start = 0;
nn_size = (size - remain_size_start) >> 3;
#pragma omp parallel for num_threads(opt.num_threads)
for (int ii = 0; ii < nn_size; ii++)
{
int i = remain_size_start + ii * 8;
const __fp16* img0 = bottom_blob.channel(0);
img0 += i * 8;
__fp16* tmpptr = tmp.channel(i / 8);
for (int q = 0; q < inch; q++)
{
// transpose 8x8
asm volatile(
"prfm pldl1keep, [%0, #512] \n"
"ld4 {v0.8h, v1.8h, v2.8h, v3.8h}, [%0], #64 \n"
"ld4 {v4.8h, v5.8h, v6.8h, v7.8h}, [%0] \n"
"sub %0, %0, #64 \n"
"uzp1 v16.8h, v0.8h, v4.8h \n"
"uzp2 v20.8h, v0.8h, v4.8h \n"
"uzp1 v17.8h, v1.8h, v5.8h \n"
"uzp2 v21.8h, v1.8h, v5.8h \n"
"uzp1 v18.8h, v2.8h, v6.8h \n"
"uzp2 v22.8h, v2.8h, v6.8h \n"
"uzp1 v19.8h, v3.8h, v7.8h \n"
"uzp2 v23.8h, v3.8h, v7.8h \n"
"st1 {v16.8h, v17.8h, v18.8h, v19.8h}, [%1], #64 \n"
"st1 {v20.8h, v21.8h, v22.8h, v23.8h}, [%1], #64 \n"
: "=r"(img0), // %0
"=r"(tmpptr) // %1
: "0"(img0),
"1"(tmpptr)
: "memory", "v0", "v1", "v2", "v3", "v4", "v5", "v6", "v7", "v16", "v17", "v18", "v19", "v20", "v21", "v22", "v23");
img0 += bottom_blob.cstep * 8;
}
}
remain_size_start += nn_size << 3;
nn_size = (size - remain_size_start) >> 2;
#pragma omp parallel for num_threads(opt.num_threads)
for (int ii = 0; ii < nn_size; ii++)
{
int i = remain_size_start + ii * 4;
const __fp16* img0 = bottom_blob.channel(0);
img0 += i * 8;
__fp16* tmpptr = tmp.channel(i / 8 + (i % 8) / 4);
for (int q = 0; q < inch; q++)
{
// transpose 8x4
asm volatile(
"prfm pldl1keep, [%0, #256] \n"
"ld1 {v0.8h, v1.8h, v2.8h, v3.8h}, [%0] \n"
"st4 {v0.8h, v1.8h, v2.8h, v3.8h}, [%1], #64 \n"
: "=r"(img0), // %0
"=r"(tmpptr) // %1
: "0"(img0),
"1"(tmpptr)
: "memory", "v0", "v1", "v2", "v3");
img0 += bottom_blob.cstep * 8;
}
}
remain_size_start += nn_size << 2;
#pragma omp parallel for num_threads(opt.num_threads)
for (int i = remain_size_start; i < size; i++)
{
const __fp16* img0 = bottom_blob.channel(0);
img0 += i * 8;
__fp16* tmpptr = tmp.channel(i / 8 + (i % 8) / 4 + i % 4);
for (int q = 0; q < inch; q++)
{
asm volatile(
"prfm pldl1keep, [%0, #128] \n"
"ld1 {v0.8h}, [%0] \n"
"st1 {v0.8h}, [%1], #16 \n"
: "=r"(img0), // %0
"=r"(tmpptr) // %1
: "0"(img0),
"1"(tmpptr)
: "memory", "v0");
img0 += bottom_blob.cstep * 8;
}
}
}
int nn_outch = 0;
int remain_outch_start = 0;
nn_outch = outch >> 3;
#pragma omp parallel for num_threads(opt.num_threads)
for (int pp = 0; pp < nn_outch; pp++)
{
int p = pp * 8;
__fp16* outptr0 = top_blob.channel(p);
__fp16* outptr1 = top_blob.channel(p + 1);
__fp16* outptr2 = top_blob.channel(p + 2);
__fp16* outptr3 = top_blob.channel(p + 3);
__fp16* outptr4 = top_blob.channel(p + 4);
__fp16* outptr5 = top_blob.channel(p + 5);
__fp16* outptr6 = top_blob.channel(p + 6);
__fp16* outptr7 = top_blob.channel(p + 7);
const __fp16 zeros[8] = {0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f};
const __fp16* biasptr = bias ? bias + p : zeros;
float16x8_t _bias0 = vld1q_f16(biasptr);
int i = 0;
for (; i + 7 < size; i += 8)
{
__fp16* tmpptr = tmp.channel(i / 8);
const __fp16* kptr = kernel.channel(p / 8);
int nn = inch; // inch always > 0
asm volatile(
"dup v24.8h, %22.h[0] \n"
"dup v25.8h, %22.h[1] \n"
"dup v26.8h, %22.h[2] \n"
"dup v27.8h, %22.h[3] \n"
"dup v28.8h, %22.h[4] \n"
"dup v29.8h, %22.h[5] \n"
"dup v30.8h, %22.h[6] \n"
"dup v31.8h, %22.h[7] \n"
"0: \n"
"prfm pldl1keep, [%9, #512] \n"
"ld1 {v16.8h, v17.8h, v18.8h, v19.8h}, [%9], #64 \n"
"prfm pldl1keep, [%10, #512] \n"
"ld1 {v0.8h, v1.8h, v2.8h, v3.8h}, [%10], #64 \n"
"fmla v24.8h, v16.8h, v0.h[0] \n"
"fmla v25.8h, v16.8h, v0.h[1] \n"
"fmla v26.8h, v16.8h, v0.h[2] \n"
"fmla v27.8h, v16.8h, v0.h[3] \n"
"fmla v28.8h, v16.8h, v0.h[4] \n"
"fmla v29.8h, v16.8h, v0.h[5] \n"
"fmla v30.8h, v16.8h, v0.h[6] \n"
"fmla v31.8h, v16.8h, v0.h[7] \n"
"fmla v24.8h, v17.8h, v1.h[0] \n"
"fmla v25.8h, v17.8h, v1.h[1] \n"
"fmla v26.8h, v17.8h, v1.h[2] \n"
"fmla v27.8h, v17.8h, v1.h[3] \n"
"fmla v28.8h, v17.8h, v1.h[4] \n"
"fmla v29.8h, v17.8h, v1.h[5] \n"
"fmla v30.8h, v17.8h, v1.h[6] \n"
"fmla v31.8h, v17.8h, v1.h[7] \n"
"prfm pldl1keep, [%9, #512] \n"
"ld1 {v20.8h, v21.8h, v22.8h, v23.8h}, [%9], #64 \n"
"fmla v24.8h, v18.8h, v2.h[0] \n"
"fmla v25.8h, v18.8h, v2.h[1] \n"
"fmla v26.8h, v18.8h, v2.h[2] \n"
"fmla v27.8h, v18.8h, v2.h[3] \n"
"fmla v28.8h, v18.8h, v2.h[4] \n"
"fmla v29.8h, v18.8h, v2.h[5] \n"
"fmla v30.8h, v18.8h, v2.h[6] \n"
"fmla v31.8h, v18.8h, v2.h[7] \n"
"prfm pldl1keep, [%10, #512] \n"
"ld1 {v4.8h, v5.8h, v6.8h, v7.8h}, [%10], #64 \n"
"fmla v24.8h, v19.8h, v3.h[0] \n"
"fmla v25.8h, v19.8h, v3.h[1] \n"
"fmla v26.8h, v19.8h, v3.h[2] \n"
"fmla v27.8h, v19.8h, v3.h[3] \n"
"fmla v28.8h, v19.8h, v3.h[4] \n"
"fmla v29.8h, v19.8h, v3.h[5] \n"
"fmla v30.8h, v19.8h, v3.h[6] \n"
"fmla v31.8h, v19.8h, v3.h[7] \n"
"fmla v24.8h, v20.8h, v4.h[0] \n"
"fmla v25.8h, v20.8h, v4.h[1] \n"
"fmla v26.8h, v20.8h, v4.h[2] \n"
"fmla v27.8h, v20.8h, v4.h[3] \n"
"fmla v28.8h, v20.8h, v4.h[4] \n"
"fmla v29.8h, v20.8h, v4.h[5] \n"
"fmla v30.8h, v20.8h, v4.h[6] \n"
"fmla v31.8h, v20.8h, v4.h[7] \n"
"fmla v24.8h, v21.8h, v5.h[0] \n"
"fmla v25.8h, v21.8h, v5.h[1] \n"
"fmla v26.8h, v21.8h, v5.h[2] \n"
"fmla v27.8h, v21.8h, v5.h[3] \n"
"fmla v28.8h, v21.8h, v5.h[4] \n"
"fmla v29.8h, v21.8h, v5.h[5] \n"
"fmla v30.8h, v21.8h, v5.h[6] \n"
"fmla v31.8h, v21.8h, v5.h[7] \n"
"fmla v24.8h, v22.8h, v6.h[0] \n"
"fmla v25.8h, v22.8h, v6.h[1] \n"
"fmla v26.8h, v22.8h, v6.h[2] \n"
"fmla v27.8h, v22.8h, v6.h[3] \n"
"fmla v28.8h, v22.8h, v6.h[4] \n"
"fmla v29.8h, v22.8h, v6.h[5] \n"
"fmla v30.8h, v22.8h, v6.h[6] \n"
"fmla v31.8h, v22.8h, v6.h[7] \n"
"subs %w0, %w0, #1 \n"
"fmla v24.8h, v23.8h, v7.h[0] \n"
"fmla v25.8h, v23.8h, v7.h[1] \n"
"fmla v26.8h, v23.8h, v7.h[2] \n"
"fmla v27.8h, v23.8h, v7.h[3] \n"
"fmla v28.8h, v23.8h, v7.h[4] \n"
"fmla v29.8h, v23.8h, v7.h[5] \n"
"fmla v30.8h, v23.8h, v7.h[6] \n"
"fmla v31.8h, v23.8h, v7.h[7] \n"
"bne 0b \n"
"st1 {v24.8h}, [%1], #16 \n"
"st1 {v25.8h}, [%2], #16 \n"
"st1 {v26.8h}, [%3], #16 \n"
"st1 {v27.8h}, [%4], #16 \n"
"st1 {v28.8h}, [%5], #16 \n"
"st1 {v29.8h}, [%6], #16 \n"
"st1 {v30.8h}, [%7], #16 \n"
"st1 {v31.8h}, [%8], #16 \n"
: "=r"(nn), // %0
"=r"(outptr0), // %1
"=r"(outptr1), // %2
"=r"(outptr2), // %3
"=r"(outptr3), // %4
"=r"(outptr4), // %5
"=r"(outptr5), // %6
"=r"(outptr6), // %7
"=r"(outptr7), // %8
"=r"(tmpptr), // %9
"=r"(kptr) // %10
: "0"(nn),
"1"(outptr0),
"2"(outptr1),
"3"(outptr2),
"4"(outptr3),
"5"(outptr4),
"6"(outptr5),
"7"(outptr6),
"8"(outptr7),
"9"(tmpptr),
"10"(kptr),
"w"(_bias0) // %22
: "cc", "memory", "v0", "v1", "v2", "v3", "v4", "v5", "v6", "v7", "v16", "v17", "v18", "v19", "v20", "v21", "v22", "v23", "v24", "v25", "v26", "v27", "v28", "v29", "v30", "v31");
}
for (; i + 3 < size; i += 4)
{
__fp16* tmpptr = tmp.channel(i / 8 + (i % 8) / 4);
const __fp16* kptr = kernel.channel(p / 8);
int nn = inch; // inch always > 0
asm volatile(
"dup v24.4h, %22.h[0] \n"
"dup v25.4h, %22.h[1] \n"
"dup v26.4h, %22.h[2] \n"
"dup v27.4h, %22.h[3] \n"
"dup v28.4h, %22.h[4] \n"
"dup v29.4h, %22.h[5] \n"
"dup v30.4h, %22.h[6] \n"
"dup v31.4h, %22.h[7] \n"
"0: \n"
"prfm pldl1keep, [%9, #256] \n"
"ld1 {v16.4h, v17.4h, v18.4h, v19.4h}, [%9], #32 \n"
"prfm pldl1keep, [%10, #512] \n"
"ld1 {v0.8h, v1.8h, v2.8h, v3.8h}, [%10], #64 \n"
"fmla v24.4h, v16.4h, v0.h[0] \n"
"fmla v25.4h, v16.4h, v0.h[1] \n"
"fmla v26.4h, v16.4h, v0.h[2] \n"
"fmla v27.4h, v16.4h, v0.h[3] \n"
"fmla v28.4h, v16.4h, v0.h[4] \n"
"fmla v29.4h, v16.4h, v0.h[5] \n"
"fmla v30.4h, v16.4h, v0.h[6] \n"
"fmla v31.4h, v16.4h, v0.h[7] \n"
"fmla v24.4h, v17.4h, v1.h[0] \n"
"fmla v25.4h, v17.4h, v1.h[1] \n"
"fmla v26.4h, v17.4h, v1.h[2] \n"
"fmla v27.4h, v17.4h, v1.h[3] \n"
"fmla v28.4h, v17.4h, v1.h[4] \n"
"fmla v29.4h, v17.4h, v1.h[5] \n"
"fmla v30.4h, v17.4h, v1.h[6] \n"
"fmla v31.4h, v17.4h, v1.h[7] \n"
"prfm pldl1keep, [%9, #256] \n"
"ld1 {v20.4h, v21.4h, v22.4h, v23.4h}, [%9], #32 \n"
"fmla v24.4h, v18.4h, v2.h[0] \n"
"fmla v25.4h, v18.4h, v2.h[1] \n"
"fmla v26.4h, v18.4h, v2.h[2] \n"
"fmla v27.4h, v18.4h, v2.h[3] \n"
"fmla v28.4h, v18.4h, v2.h[4] \n"
"fmla v29.4h, v18.4h, v2.h[5] \n"
"fmla v30.4h, v18.4h, v2.h[6] \n"
"fmla v31.4h, v18.4h, v2.h[7] \n"
"prfm pldl1keep, [%10, #512] \n"
"ld1 {v4.8h, v5.8h, v6.8h, v7.8h}, [%10], #64 \n"
"fmla v24.4h, v19.4h, v3.h[0] \n"
"fmla v25.4h, v19.4h, v3.h[1] \n"
"fmla v26.4h, v19.4h, v3.h[2] \n"
"fmla v27.4h, v19.4h, v3.h[3] \n"
"fmla v28.4h, v19.4h, v3.h[4] \n"
"fmla v29.4h, v19.4h, v3.h[5] \n"
"fmla v30.4h, v19.4h, v3.h[6] \n"
"fmla v31.4h, v19.4h, v3.h[7] \n"
"fmla v24.4h, v20.4h, v4.h[0] \n"
"fmla v25.4h, v20.4h, v4.h[1] \n"
"fmla v26.4h, v20.4h, v4.h[2] \n"
"fmla v27.4h, v20.4h, v4.h[3] \n"
"fmla v28.4h, v20.4h, v4.h[4] \n"
"fmla v29.4h, v20.4h, v4.h[5] \n"
"fmla v30.4h, v20.4h, v4.h[6] \n"
"fmla v31.4h, v20.4h, v4.h[7] \n"
"fmla v24.4h, v21.4h, v5.h[0] \n"
"fmla v25.4h, v21.4h, v5.h[1] \n"
"fmla v26.4h, v21.4h, v5.h[2] \n"
"fmla v27.4h, v21.4h, v5.h[3] \n"
"fmla v28.4h, v21.4h, v5.h[4] \n"
"fmla v29.4h, v21.4h, v5.h[5] \n"
"fmla v30.4h, v21.4h, v5.h[6] \n"
"fmla v31.4h, v21.4h, v5.h[7] \n"
"fmla v24.4h, v22.4h, v6.h[0] \n"
"fmla v25.4h, v22.4h, v6.h[1] \n"
"fmla v26.4h, v22.4h, v6.h[2] \n"
"fmla v27.4h, v22.4h, v6.h[3] \n"
"fmla v28.4h, v22.4h, v6.h[4] \n"
"fmla v29.4h, v22.4h, v6.h[5] \n"
"fmla v30.4h, v22.4h, v6.h[6] \n"
"fmla v31.4h, v22.4h, v6.h[7] \n"
"subs %w0, %w0, #1 \n"
"fmla v24.4h, v23.4h, v7.h[0] \n"
"fmla v25.4h, v23.4h, v7.h[1] \n"
"fmla v26.4h, v23.4h, v7.h[2] \n"
"fmla v27.4h, v23.4h, v7.h[3] \n"
"fmla v28.4h, v23.4h, v7.h[4] \n"
"fmla v29.4h, v23.4h, v7.h[5] \n"
"fmla v30.4h, v23.4h, v7.h[6] \n"
"fmla v31.4h, v23.4h, v7.h[7] \n"
"bne 0b \n"
"st1 {v24.4h}, [%1], #8 \n"
"st1 {v25.4h}, [%2], #8 \n"
"st1 {v26.4h}, [%3], #8 \n"
"st1 {v27.4h}, [%4], #8 \n"
"st1 {v28.4h}, [%5], #8 \n"
"st1 {v29.4h}, [%6], #8 \n"
"st1 {v30.4h}, [%7], #8 \n"
"st1 {v31.4h}, [%8], #8 \n"
: "=r"(nn), // %0
"=r"(outptr0), // %1
"=r"(outptr1), // %2
"=r"(outptr2), // %3
"=r"(outptr3), // %4
"=r"(outptr4), // %5
"=r"(outptr5), // %6
"=r"(outptr6), // %7
"=r"(outptr7), // %8
"=r"(tmpptr), // %9
"=r"(kptr) // %10
: "0"(nn),
"1"(outptr0),
"2"(outptr1),
"3"(outptr2),
"4"(outptr3),
"5"(outptr4),
"6"(outptr5),
"7"(outptr6),
"8"(outptr7),
"9"(tmpptr),
"10"(kptr),
"w"(_bias0) // %22
: "cc", "memory", "v0", "v1", "v2", "v3", "v4", "v5", "v6", "v7", "v16", "v17", "v18", "v19", "v20", "v21", "v22", "v23", "v24", "v25", "v26", "v27", "v28", "v29", "v30", "v31");
}
for (; i < size; i++)
{
__fp16* tmpptr = tmp.channel(i / 8 + (i % 8) / 4 + i % 4);
const __fp16* kptr = kernel.channel(p / 8);
int nn = inch; // inch always > 0
asm volatile(
"mov v30.16b, %22.16b \n"
"0: \n"
"prfm pldl1keep, [%9, #128] \n"
"ld1 {v0.8h}, [%9], #16 \n"
"prfm pldl1keep, [%10, #512] \n"
"ld1 {v16.8h, v17.8h, v18.8h, v19.8h}, [%10], #64 \n"
"fmla v30.8h, v16.8h, v0.h[0] \n"
"fmla v30.8h, v17.8h, v0.h[1] \n"
"prfm pldl1keep, [%10, #512] \n"
"ld1 {v20.8h, v21.8h, v22.8h, v23.8h}, [%10], #64 \n"
"fmla v30.8h, v18.8h, v0.h[2] \n"
"fmla v30.8h, v19.8h, v0.h[3] \n"
"subs %w0, %w0, #1 \n"
"fmla v30.8h, v20.8h, v0.h[4] \n"
"fmla v30.8h, v21.8h, v0.h[5] \n"
"fmla v30.8h, v22.8h, v0.h[6] \n"
"fmla v30.8h, v23.8h, v0.h[7] \n"
"bne 0b \n"
"st1 {v30.h}[0], [%1], #2 \n"
"st1 {v30.h}[1], [%2], #2 \n"
"st1 {v30.h}[2], [%3], #2 \n"
"st1 {v30.h}[3], [%4], #2 \n"
"st1 {v30.h}[4], [%5], #2 \n"
"st1 {v30.h}[5], [%6], #2 \n"
"st1 {v30.h}[6], [%7], #2 \n"
"st1 {v30.h}[7], [%8], #2 \n"
: "=r"(nn), // %0
"=r"(outptr0), // %1
"=r"(outptr1), // %2
"=r"(outptr2), // %3
"=r"(outptr3), // %4
"=r"(outptr4), // %5
"=r"(outptr5), // %6
"=r"(outptr6), // %7
"=r"(outptr7), // %8
"=r"(tmpptr), // %9
"=r"(kptr) // %10
: "0"(nn),
"1"(outptr0),
"2"(outptr1),
"3"(outptr2),
"4"(outptr3),
"5"(outptr4),
"6"(outptr5),
"7"(outptr6),
"8"(outptr7),
"9"(tmpptr),
"10"(kptr),
"w"(_bias0) // %22
: "cc", "memory", "v0", "v16", "v17", "v18", "v19", "v20", "v21", "v22", "v23", "v30");
}
}
remain_outch_start += nn_outch << 3;
#pragma omp parallel for num_threads(opt.num_threads)
for (int p = remain_outch_start; p < outch; p++)
{
__fp16* outptr0 = top_blob.channel(p);
const __fp16 bias0 = bias ? bias[p] : 0.f;
float16x8_t _bias0 = vdupq_n_f16(bias0);
int i = 0;
for (; i + 7 < size; i += 8)
{
__fp16* tmpptr = tmp.channel(i / 8);
const __fp16* kptr = kernel.channel(p / 8 + p % 8);
int nn = inch; // inch always > 0
asm volatile(
"mov v30.16b, %8.16b \n"
"0: \n"
"prfm pldl1keep, [%2, #512] \n"
"ld1 {v16.8h, v17.8h, v18.8h, v19.8h}, [%2], #64 \n"
"prfm pldl1keep, [%3, #128] \n"
"ld1 {v0.8h}, [%3], #16 \n"
"fmla v30.8h, v16.8h, v0.h[0] \n"
"fmla v30.8h, v17.8h, v0.h[1] \n"
"prfm pldl1keep, [%2, #512] \n"
"ld1 {v20.8h, v21.8h, v22.8h, v23.8h}, [%2], #64 \n"
"fmla v30.8h, v18.8h, v0.h[2] \n"
"fmla v30.8h, v19.8h, v0.h[3] \n"
"subs %w0, %w0, #1 \n"
"fmla v30.8h, v20.8h, v0.h[4] \n"
"fmla v30.8h, v21.8h, v0.h[5] \n"
"fmla v30.8h, v22.8h, v0.h[6] \n"
"fmla v30.8h, v23.8h, v0.h[7] \n"
"bne 0b \n"
"st1 {v30.8h}, [%1], #16 \n"
: "=r"(nn), // %0
"=r"(outptr0), // %1
"=r"(tmpptr), // %2
"=r"(kptr) // %3
: "0"(nn),
"1"(outptr0),
"2"(tmpptr),
"3"(kptr),
"w"(_bias0) // %8
: "cc", "memory", "v0", "v16", "v17", "v18", "v19", "v20", "v21", "v22", "v23", "v30");
}
for (; i + 3 < size; i += 4)
{
__fp16* tmpptr = tmp.channel(i / 8 + (i % 8) / 4);
const __fp16* kptr = kernel.channel(p / 8 + p % 8);
int nn = inch; // inch always > 0
asm volatile(
"mov v30.16b, %8.16b \n"
"0: \n"
"prfm pldl1keep, [%2, #256] \n"
"ld1 {v16.4h, v17.4h, v18.4h, v19.4h}, [%2], #32 \n"
"prfm pldl1keep, [%3, #128] \n"
"ld1 {v0.8h}, [%3], #16 \n"
"fmla v30.4h, v16.4h, v0.h[0] \n"
"fmla v30.4h, v17.4h, v0.h[1] \n"
"prfm pldl1keep, [%2, #256] \n"
"ld1 {v20.4h, v21.4h, v22.4h, v23.4h}, [%2], #32 \n"
"fmla v30.4h, v18.4h, v0.h[2] \n"
"fmla v30.4h, v19.4h, v0.h[3] \n"
"subs %w0, %w0, #1 \n"
"fmla v30.4h, v20.4h, v0.h[4] \n"
"fmla v30.4h, v21.4h, v0.h[5] \n"
"fmla v30.4h, v22.4h, v0.h[6] \n"
"fmla v30.4h, v23.4h, v0.h[7] \n"
"bne 0b \n"
"st1 {v30.4h}, [%1], #8 \n"
: "=r"(nn), // %0
"=r"(outptr0), // %1
"=r"(tmpptr), // %2
"=r"(kptr) // %3
: "0"(nn),
"1"(outptr0),
"2"(tmpptr),
"3"(kptr),
"w"(_bias0) // %8
: "cc", "memory", "v0", "v16", "v17", "v18", "v19", "v20", "v21", "v22", "v23", "v30");
}
for (; i < size; i++)
{
__fp16* tmpptr = tmp.channel(i / 8 + (i % 8) / 4 + i % 4);
const __fp16* kptr = kernel.channel(p / 8 + p % 8);
float16x8_t _sum0 = vdupq_n_f16((__fp16)0.f);
for (int q = 0; q < inch; q++)
{
float16x8_t _r0 = vld1q_f16(tmpptr);
float16x8_t _k0 = vld1q_f16(kptr);
_sum0 = vfmaq_f16(_sum0, _r0, _k0);
kptr += 8;
tmpptr += 8;
}
__fp16 sum0 = bias0 + vaddvq_f32(vcvt_f32_f16(vadd_f16(vget_low_f16(_sum0), vget_high_f16(_sum0))));
outptr0[0] = sum0;
outptr0++;
}
}
// // NOTE sgemm
// for (; p<outch; p++)
// {
// Mat out0 = top_blob.channel(p);
//
// const float bias0 = bias ? bias[p] : 0.f;
//
// __fp16* outptr0 = out0;
//
// for (int i=0; i<size; i++)
// {
// float sum = bias0;
//
// const __fp16* kptr = _kernel.channel(p);
//
// for (int q=0; q<inch; q++)
// {
// const __fp16* img0 = bottom_blob.channel(q);
//
// sum += img0[i] * kptr[0];
// kptr ++;
// }
//
// outptr0[i] = sum;
// }
// }
}
static void conv1x1s2_pack8to1_fp16sa_neon(const Mat& bottom_blob, Mat& top_blob, const Mat& kernel, const Mat& _bias, const Option& opt)
{
int w = bottom_blob.w;
int channels = bottom_blob.c;
size_t elemsize = bottom_blob.elemsize;
int elempack = bottom_blob.elempack;
int outw = top_blob.w;
int outh = top_blob.h;
const int tailstep = (w - 2 * outw + w) * 8;
Mat bottom_blob_shrinked;
bottom_blob_shrinked.create(outw, outh, channels, elemsize, elempack, opt.workspace_allocator);
#pragma omp parallel for num_threads(opt.num_threads)
for (int p = 0; p < channels; p++)
{
const __fp16* r0 = bottom_blob.channel(p);
__fp16* outptr = bottom_blob_shrinked.channel(p);
for (int i = 0; i < outh; i++)
{
int j = 0;
for (; j + 3 < outw; j += 4)
{
float16x8_t _v0 = vld1q_f16(r0);
float16x8_t _v1 = vld1q_f16(r0 + 16);
float16x8_t _v2 = vld1q_f16(r0 + 32);
float16x8_t _v3 = vld1q_f16(r0 + 48);
vst1q_f16(outptr, _v0);
vst1q_f16(outptr + 8, _v1);
vst1q_f16(outptr + 16, _v2);
vst1q_f16(outptr + 24, _v3);
r0 += 64;
outptr += 32;
}
for (; j + 1 < outw; j += 2)
{
float16x8_t _v0 = vld1q_f16(r0);
float16x8_t _v1 = vld1q_f16(r0 + 16);
vst1q_f16(outptr, _v0);
vst1q_f16(outptr + 8, _v1);
r0 += 32;
outptr += 16;
}
for (; j < outw; j++)
{
float16x8_t _v = vld1q_f16(r0);
vst1q_f16(outptr, _v);
r0 += 16;
outptr += 8;
}
r0 += tailstep;
}
}
conv1x1s1_sgemm_pack8to1_fp16sa_neon(bottom_blob_shrinked, top_blob, kernel, _bias, opt);
}
|
md2_fmt_plug.c | /* MD2 cracker patch for JtR. Hacked together during May of 2013 by Dhiru
* Kholia <dhiru at openwall.com>.
*
* This software is Copyright (c) 2013 Dhiru Kholia <dhiru at openwall.com> and
* it is hereby released to the general public under the following terms:
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted.
*/
#if FMT_EXTERNS_H
extern struct fmt_main fmt_md2_;
#elif FMT_REGISTERS_H
john_register_one(&fmt_md2_);
#else
#include <string.h>
#include "arch.h"
#include "sph_md2.h"
#include "misc.h"
#include "common.h"
#include "formats.h"
#include "params.h"
#include "options.h"
#ifdef _OPENMP
static int omp_t = 1;
#include <omp.h>
// OMP_SCALE tuned on core i7 quad core HT
// 1 - 153k
// 64 - 433k
// 128 - 572k
// 256 - 612k
// 512 - 543k
// 1k - 680k ** chosen
// 2k - 660k
// 4k - 670k
// 8k - 680k
// 16k - 650k
#ifndef OMP_SCALE
#ifdef __MIC__
#define OMP_SCALE 32
#else
#define OMP_SCALE (1024)
#endif // __MIC__
#endif // OMP_SCALE
#endif // _OPENMP
#include "memdbg.h"
#define FORMAT_LABEL "MD2"
#define FORMAT_NAME ""
#define FORMAT_TAG "$md2$"
#define TAG_LENGTH 5
#define ALGORITHM_NAME "MD2 32/" ARCH_BITS_STR
#define BENCHMARK_COMMENT ""
#define BENCHMARK_LENGTH -1
#define PLAINTEXT_LENGTH 125
#define BINARY_SIZE 16
#define SALT_SIZE 0
#define BINARY_ALIGN 4
#define SALT_ALIGN 1
#define MIN_KEYS_PER_CRYPT 1
#define MAX_KEYS_PER_CRYPT 1
static struct fmt_tests md2__tests[] = {
{"$md2$ab4f496bfb2a530b219ff33031fe06b0", "message digest"},
{"ab4f496bfb2a530b219ff33031fe06b0", "message digest"},
{"921adc047dad311394d2b8553002042d","len=125_____________________________________________________________________________________________________________________x"},
{NULL}
};
static char (*saved_key)[PLAINTEXT_LENGTH + 1];
static ARCH_WORD_32 (*crypt_out)[BINARY_SIZE / sizeof(ARCH_WORD_32)];
static void init(struct fmt_main *self)
{
#ifdef _OPENMP
omp_t = omp_get_max_threads();
self->params.min_keys_per_crypt *= omp_t;
omp_t *= OMP_SCALE;
self->params.max_keys_per_crypt *= omp_t;
#endif
saved_key = mem_calloc(self->params.max_keys_per_crypt,
sizeof(*saved_key));
crypt_out = mem_calloc(self->params.max_keys_per_crypt,
sizeof(*crypt_out));
}
static void done(void)
{
MEM_FREE(crypt_out);
MEM_FREE(saved_key);
}
static int valid(char *ciphertext, struct fmt_main *self)
{
char *p;
int extra;
p = ciphertext;
if (!strncmp(p, FORMAT_TAG, TAG_LENGTH))
p += TAG_LENGTH;
if (hexlenl(p, &extra) != 32 || extra)
return 0;
return 1;
}
static char *split(char *ciphertext, int index, struct fmt_main *self)
{
static char out[TAG_LENGTH + BINARY_SIZE * 2 + 1];
if (!strncmp(ciphertext, FORMAT_TAG, TAG_LENGTH))
ciphertext += TAG_LENGTH;
memcpy(out, FORMAT_TAG, TAG_LENGTH);
strnzcpy(out + TAG_LENGTH, ciphertext, BINARY_SIZE*2 + 1);
return out;
}
static void *get_binary(char *ciphertext)
{
static union {
unsigned char c[32];
ARCH_WORD dummy;
} buf;
unsigned char *out = buf.c;
char *p;
int i;
if (!strncmp(ciphertext, FORMAT_TAG, TAG_LENGTH))
p = strrchr(ciphertext, '$') + 1;
else
p = ciphertext;
for (i = 0; i < BINARY_SIZE; i++) {
out[i] =
(atoi16[ARCH_INDEX(*p)] << 4) |
atoi16[ARCH_INDEX(p[1])];
p += 2;
}
return out;
}
static int get_hash_0(int index) { return crypt_out[index][0] & PH_MASK_0; }
static int get_hash_1(int index) { return crypt_out[index][0] & PH_MASK_1; }
static int get_hash_2(int index) { return crypt_out[index][0] & PH_MASK_2; }
static int get_hash_3(int index) { return crypt_out[index][0] & PH_MASK_3; }
static int get_hash_4(int index) { return crypt_out[index][0] & PH_MASK_4; }
static int get_hash_5(int index) { return crypt_out[index][0] & PH_MASK_5; }
static int get_hash_6(int index) { return crypt_out[index][0] & PH_MASK_6; }
static int crypt_all(int *pcount, struct db_salt *salt)
{
const int count = *pcount;
int index = 0;
#ifdef _OPENMP
#pragma omp parallel for
for (index = 0; index < count; index++)
#endif
{
sph_md2_context ctx;
sph_md2_init(&ctx);
sph_md2(&ctx, saved_key[index], strlen(saved_key[index]));
sph_md2_close(&ctx, (unsigned char*)crypt_out[index]);
}
return count;
}
static int cmp_all(void *binary, int count)
{
int index = 0;
#ifdef _OPENMP
for (; index < count; index++)
#endif
if (!memcmp(binary, crypt_out[index], ARCH_SIZE))
return 1;
return 0;
}
static int cmp_one(void *binary, int index)
{
return !memcmp(binary, crypt_out[index], BINARY_SIZE);
}
static int cmp_exact(char *source, int index)
{
return 1;
}
static void md2_set_key(char *key, int index)
{
int saved_len = strlen(key);
if (saved_len > PLAINTEXT_LENGTH)
saved_len = PLAINTEXT_LENGTH;
memcpy(saved_key[index], key, saved_len);
saved_key[index][saved_len] = 0;
}
static char *get_key(int index)
{
return saved_key[index];
}
struct fmt_main fmt_md2_ = {
{
FORMAT_LABEL,
FORMAT_NAME,
ALGORITHM_NAME,
BENCHMARK_COMMENT,
BENCHMARK_LENGTH,
0,
PLAINTEXT_LENGTH,
BINARY_SIZE,
BINARY_ALIGN,
SALT_SIZE,
SALT_ALIGN,
MIN_KEYS_PER_CRYPT,
MAX_KEYS_PER_CRYPT,
FMT_CASE | FMT_8_BIT | FMT_OMP,
{ NULL },
{ FORMAT_TAG },
md2__tests
}, {
init,
done,
fmt_default_reset,
fmt_default_prepare,
valid,
split,
get_binary,
fmt_default_salt,
{ NULL },
fmt_default_source,
{
fmt_default_binary_hash_0,
fmt_default_binary_hash_1,
fmt_default_binary_hash_2,
fmt_default_binary_hash_3,
fmt_default_binary_hash_4,
fmt_default_binary_hash_5,
fmt_default_binary_hash_6
},
fmt_default_salt_hash,
NULL,
fmt_default_set_salt,
md2_set_key,
get_key,
fmt_default_clear_keys,
crypt_all,
{
get_hash_0,
get_hash_1,
get_hash_2,
get_hash_3,
get_hash_4,
get_hash_5,
get_hash_6
},
cmp_all,
cmp_one,
cmp_exact
}
};
#endif /* plugin stanza */
|
attribute.c | /*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% AAA TTTTT TTTTT RRRR IIIII BBBB U U TTTTT EEEEE %
% A A T T R R I B B U U T E %
% AAAAA T T RRRR I BBBB U U T EEE %
% A A T T R R I B B U U T E %
% A A T T R R IIIII BBBB UUU T EEEEE %
% %
% %
% MagickCore Get / Set Image Attributes %
% %
% Software Design %
% Cristy %
% October 2002 %
% %
% %
% Copyright 1999-2018 ImageMagick Studio LLC, a non-profit organization %
% dedicated to making software imaging solutions freely available. %
% %
% You may not use this file except in compliance with the License. You may %
% obtain a copy of the License at %
% %
% https://www.imagemagick.org/script/license.php %
% %
% Unless required by applicable law or agreed to in writing, software %
% distributed under the License is distributed on an "AS IS" BASIS, %
% WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. %
% See the License for the specific language governing permissions and %
% limitations under the License. %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
%
%
*/
/*
Include declarations.
*/
#include "magick/studio.h"
#include "magick/artifact.h"
#include "magick/attribute.h"
#include "magick/blob.h"
#include "magick/blob-private.h"
#include "magick/cache.h"
#include "magick/cache-private.h"
#include "magick/cache-view.h"
#include "magick/client.h"
#include "magick/channel.h"
#include "magick/color.h"
#include "magick/color-private.h"
#include "magick/colormap.h"
#include "magick/colormap-private.h"
#include "magick/colorspace.h"
#include "magick/colorspace-private.h"
#include "magick/composite.h"
#include "magick/composite-private.h"
#include "magick/constitute.h"
#include "magick/deprecate.h"
#include "magick/draw.h"
#include "magick/draw-private.h"
#include "magick/effect.h"
#include "magick/enhance.h"
#include "magick/exception.h"
#include "magick/exception-private.h"
#include "magick/geometry.h"
#include "magick/histogram.h"
#include "magick/identify.h"
#include "magick/image.h"
#include "magick/image-private.h"
#include "magick/list.h"
#include "magick/log.h"
#include "magick/memory_.h"
#include "magick/magick.h"
#include "magick/monitor.h"
#include "magick/monitor-private.h"
#include "magick/option.h"
#include "magick/paint.h"
#include "magick/pixel.h"
#include "magick/pixel-private.h"
#include "magick/property.h"
#include "magick/quantize.h"
#include "magick/random_.h"
#include "magick/resource_.h"
#include "magick/semaphore.h"
#include "magick/segment.h"
#include "magick/splay-tree.h"
#include "magick/string_.h"
#include "magick/thread-private.h"
#include "magick/threshold.h"
#include "magick/transform.h"
#include "magick/utility.h"
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
+ G e t I m a g e B o u n d i n g B o x %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% GetImageBoundingBox() returns the bounding box of an image canvas.
%
% The format of the GetImageBoundingBox method is:
%
% RectangleInfo GetImageBoundingBox(const Image *image,
% ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o bounds: Method GetImageBoundingBox returns the bounding box of an
% image canvas.
%
% o image: the image.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport RectangleInfo GetImageBoundingBox(const Image *image,
ExceptionInfo *exception)
{
CacheView
*image_view;
MagickBooleanType
status;
MagickPixelPacket
target[3],
zero;
RectangleInfo
bounds;
register const PixelPacket
*p;
ssize_t
y;
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
bounds.width=0;
bounds.height=0;
bounds.x=(ssize_t) image->columns;
bounds.y=(ssize_t) image->rows;
GetMagickPixelPacket(image,&target[0]);
image_view=AcquireVirtualCacheView(image,exception);
p=GetCacheViewVirtualPixels(image_view,0,0,1,1,exception);
if (p == (const PixelPacket *) NULL)
{
image_view=DestroyCacheView(image_view);
return(bounds);
}
SetMagickPixelPacket(image,p,GetCacheViewVirtualIndexQueue(image_view),
&target[0]);
GetMagickPixelPacket(image,&target[1]);
p=GetCacheViewVirtualPixels(image_view,(ssize_t) image->columns-1,0,1,1,
exception);
if (p != (const PixelPacket *) NULL)
SetMagickPixelPacket(image,p,GetCacheViewVirtualIndexQueue(image_view),
&target[1]);
GetMagickPixelPacket(image,&target[2]);
p=GetCacheViewVirtualPixels(image_view,0,(ssize_t) image->rows-1,1,1,
exception);
if (p != (const PixelPacket *) NULL)
SetMagickPixelPacket(image,p,GetCacheViewVirtualIndexQueue(image_view),
&target[2]);
status=MagickTrue;
GetMagickPixelPacket(image,&zero);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static) shared(status) \
magick_number_threads(image,image,image->rows,1)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
MagickPixelPacket
pixel;
RectangleInfo
bounding_box;
register const IndexPacket
*magick_restrict indexes;
register const PixelPacket
*magick_restrict p;
register ssize_t
x;
if (status == MagickFalse)
continue;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
# pragma omp critical (MagickCore_GetImageBoundingBox)
#endif
bounding_box=bounds;
p=GetCacheViewVirtualPixels(image_view,0,y,image->columns,1,exception);
if (p == (const PixelPacket *) NULL)
{
status=MagickFalse;
continue;
}
indexes=GetCacheViewVirtualIndexQueue(image_view);
pixel=zero;
for (x=0; x < (ssize_t) image->columns; x++)
{
SetMagickPixelPacket(image,p,indexes+x,&pixel);
if ((x < bounding_box.x) &&
(IsMagickColorSimilar(&pixel,&target[0]) == MagickFalse))
bounding_box.x=x;
if ((x > (ssize_t) bounding_box.width) &&
(IsMagickColorSimilar(&pixel,&target[1]) == MagickFalse))
bounding_box.width=(size_t) x;
if ((y < bounding_box.y) &&
(IsMagickColorSimilar(&pixel,&target[0]) == MagickFalse))
bounding_box.y=y;
if ((y > (ssize_t) bounding_box.height) &&
(IsMagickColorSimilar(&pixel,&target[2]) == MagickFalse))
bounding_box.height=(size_t) y;
p++;
}
#if defined(MAGICKCORE_OPENMP_SUPPORT)
# pragma omp critical (MagickCore_GetImageBoundingBox)
#endif
{
if (bounding_box.x < bounds.x)
bounds.x=bounding_box.x;
if (bounding_box.y < bounds.y)
bounds.y=bounding_box.y;
if (bounding_box.width > bounds.width)
bounds.width=bounding_box.width;
if (bounding_box.height > bounds.height)
bounds.height=bounding_box.height;
}
}
image_view=DestroyCacheView(image_view);
if ((bounds.width == 0) && (bounds.height == 0))
(void) ThrowMagickException(exception,GetMagickModule(),OptionWarning,
"GeometryDoesNotContainImage","`%s'",image->filename);
else
{
bounds.width-=(bounds.x-1);
bounds.height-=(bounds.y-1);
}
return(bounds);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% G e t I m a g e C h a n n e l D e p t h %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% GetImageChannelDepth() returns the depth of a particular image channel.
%
% The format of the GetImageChannelDepth method is:
%
% size_t GetImageDepth(const Image *image,ExceptionInfo *exception)
% size_t GetImageChannelDepth(const Image *image,
% const ChannelType channel,ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o channel: the channel.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport size_t GetImageDepth(const Image *image,ExceptionInfo *exception)
{
return(GetImageChannelDepth(image,CompositeChannels,exception));
}
MagickExport size_t GetImageChannelDepth(const Image *image,
const ChannelType channel,ExceptionInfo *exception)
{
CacheView
*image_view;
MagickBooleanType
status;
register ssize_t
i;
size_t
*current_depth,
depth,
number_threads;
ssize_t
y;
/*
Compute image depth.
*/
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
number_threads=(size_t) GetMagickResourceLimit(ThreadResource);
current_depth=(size_t *) AcquireQuantumMemory(number_threads,
sizeof(*current_depth));
if (current_depth == (size_t *) NULL)
ThrowFatalException(ResourceLimitFatalError,"MemoryAllocationFailed");
status=MagickTrue;
for (i=0; i < (ssize_t) number_threads; i++)
current_depth[i]=1;
if ((image->storage_class == PseudoClass) && (image->matte == MagickFalse))
{
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static) shared(status) \
magick_number_threads(image,image,image->colors,1)
#endif
for (i=0; i < (ssize_t) image->colors; i++)
{
const int
id = GetOpenMPThreadId();
while (current_depth[id] < MAGICKCORE_QUANTUM_DEPTH)
{
MagickBooleanType
atDepth;
QuantumAny
range;
atDepth=MagickTrue;
range=GetQuantumRange(current_depth[id]);
if ((atDepth != MagickFalse) && ((channel & RedChannel) != 0))
if (IsPixelAtDepth(image->colormap[i].red,range) == MagickFalse)
atDepth=MagickFalse;
if ((atDepth != MagickFalse) && ((channel & GreenChannel) != 0))
if (IsPixelAtDepth(image->colormap[i].green,range) == MagickFalse)
atDepth=MagickFalse;
if ((atDepth != MagickFalse) && ((channel & BlueChannel) != 0))
if (IsPixelAtDepth(image->colormap[i].blue,range) == MagickFalse)
atDepth=MagickFalse;
if ((atDepth != MagickFalse))
break;
current_depth[id]++;
}
}
depth=current_depth[0];
for (i=1; i < (ssize_t) number_threads; i++)
if (depth < current_depth[i])
depth=current_depth[i];
current_depth=(size_t *) RelinquishMagickMemory(current_depth);
return(depth);
}
image_view=AcquireVirtualCacheView(image,exception);
#if !defined(MAGICKCORE_HDRI_SUPPORT)
DisableMSCWarning(4127)
if (1UL*QuantumRange <= MaxMap)
RestoreMSCWarning
{
size_t
*depth_map;
/*
Scale pixels to desired (optimized with depth map).
*/
depth_map=(size_t *) AcquireQuantumMemory(MaxMap+1,sizeof(*depth_map));
if (depth_map == (size_t *) NULL)
ThrowFatalException(ResourceLimitFatalError,"MemoryAllocationFailed");
for (i=0; i <= (ssize_t) MaxMap; i++)
{
unsigned int
depth;
for (depth=1; depth < MAGICKCORE_QUANTUM_DEPTH; depth++)
{
Quantum
pixel;
QuantumAny
range;
range=GetQuantumRange(depth);
pixel=(Quantum) i;
if (pixel == ScaleAnyToQuantum(ScaleQuantumToAny(pixel,range),range))
break;
}
depth_map[i]=depth;
}
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static) shared(status) \
magick_number_threads(image,image,image->rows,1)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
const int
id = GetOpenMPThreadId();
register const IndexPacket
*magick_restrict indexes;
register const PixelPacket
*magick_restrict p;
register ssize_t
x;
if (status == MagickFalse)
continue;
p=GetCacheViewVirtualPixels(image_view,0,y,image->columns,1,exception);
if (p == (const PixelPacket *) NULL)
continue;
indexes=GetCacheViewVirtualIndexQueue(image_view);
for (x=0; x < (ssize_t) image->columns; x++)
{
Quantum
pixel;
if ((channel & RedChannel) != 0)
{
pixel=GetPixelRed(p);
if (depth_map[ScaleQuantumToMap(pixel)] > current_depth[id])
current_depth[id]=depth_map[ScaleQuantumToMap(pixel)];
}
if ((channel & GreenChannel) != 0)
{
pixel=GetPixelGreen(p);
if (depth_map[ScaleQuantumToMap(pixel)] > current_depth[id])
current_depth[id]=depth_map[ScaleQuantumToMap(pixel)];
}
if ((channel & BlueChannel) != 0)
{
pixel=GetPixelBlue(p);
if (depth_map[ScaleQuantumToMap(pixel)] > current_depth[id])
current_depth[id]=depth_map[ScaleQuantumToMap(pixel)];
}
if (((channel & OpacityChannel) != 0) &&
(image->matte != MagickFalse))
{
pixel=GetPixelOpacity(p);
if (depth_map[ScaleQuantumToMap(pixel)] > current_depth[id])
current_depth[id]=depth_map[ScaleQuantumToMap(pixel)];
}
if (((channel & IndexChannel) != 0) &&
(image->colorspace == CMYKColorspace))
{
pixel=GetPixelIndex(indexes+x);
if (depth_map[ScaleQuantumToMap(pixel)] > current_depth[id])
current_depth[id]=depth_map[ScaleQuantumToMap(pixel)];
}
p++;
}
if (current_depth[id] == MAGICKCORE_QUANTUM_DEPTH)
status=MagickFalse;
}
image_view=DestroyCacheView(image_view);
depth=current_depth[0];
for (i=1; i < (ssize_t) number_threads; i++)
if (depth < current_depth[i])
depth=current_depth[i];
depth_map=(size_t *) RelinquishMagickMemory(depth_map);
current_depth=(size_t *) RelinquishMagickMemory(current_depth);
return(depth);
}
#endif
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static) shared(status) \
magick_number_threads(image,image,image->rows,1)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
const int
id = GetOpenMPThreadId();
register const IndexPacket
*magick_restrict indexes;
register const PixelPacket
*magick_restrict p;
register ssize_t
x;
if (status == MagickFalse)
continue;
p=GetCacheViewVirtualPixels(image_view,0,y,image->columns,1,exception);
if (p == (const PixelPacket *) NULL)
continue;
indexes=GetCacheViewVirtualIndexQueue(image_view);
for (x=0; x < (ssize_t) image->columns; x++)
{
while (current_depth[id] < MAGICKCORE_QUANTUM_DEPTH)
{
MagickBooleanType
atDepth;
QuantumAny
range;
atDepth=MagickTrue;
range=GetQuantumRange(current_depth[id]);
if ((atDepth != MagickFalse) && ((channel & RedChannel) != 0))
if (IsPixelAtDepth(GetPixelRed(p),range) == MagickFalse)
atDepth=MagickFalse;
if ((atDepth != MagickFalse) && ((channel & GreenChannel) != 0))
if (IsPixelAtDepth(GetPixelGreen(p),range) == MagickFalse)
atDepth=MagickFalse;
if ((atDepth != MagickFalse) && ((channel & BlueChannel) != 0))
if (IsPixelAtDepth(GetPixelBlue(p),range) == MagickFalse)
atDepth=MagickFalse;
if ((atDepth != MagickFalse) && ((channel & OpacityChannel) != 0) &&
(image->matte != MagickFalse))
if (IsPixelAtDepth(GetPixelOpacity(p),range) == MagickFalse)
atDepth=MagickTrue;
if ((atDepth != MagickFalse) && ((channel & IndexChannel) != 0) &&
(image->colorspace == CMYKColorspace))
if (IsPixelAtDepth(GetPixelIndex(indexes+x),range) == MagickFalse)
atDepth=MagickFalse;
if ((atDepth != MagickFalse))
break;
current_depth[id]++;
}
p++;
}
if (current_depth[id] == MAGICKCORE_QUANTUM_DEPTH)
status=MagickFalse;
}
image_view=DestroyCacheView(image_view);
depth=current_depth[0];
for (i=1; i < (ssize_t) number_threads; i++)
if (depth < current_depth[i])
depth=current_depth[i];
current_depth=(size_t *) RelinquishMagickMemory(current_depth);
return(depth);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% G e t I m a g e Q u a n t u m D e p t h %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% GetImageQuantumDepth() returns the depth of the image rounded to a legal
% quantum depth: 8, 16, or 32.
%
% The format of the GetImageQuantumDepth method is:
%
% size_t GetImageQuantumDepth(const Image *image,
% const MagickBooleanType constrain)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o constrain: A value other than MagickFalse, constrains the depth to
% a maximum of MAGICKCORE_QUANTUM_DEPTH.
%
*/
MagickExport size_t GetImageQuantumDepth(const Image *image,
const MagickBooleanType constrain)
{
size_t
depth;
depth=image->depth;
if (depth <= 8)
depth=8;
else
if (depth <= 16)
depth=16;
else
if (depth <= 32)
depth=32;
else
if (depth <= 64)
depth=64;
if (constrain != MagickFalse)
depth=(size_t) MagickMin((double) depth,(double) MAGICKCORE_QUANTUM_DEPTH);
return(depth);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% G e t I m a g e T y p e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% GetImageType() returns the potential type of image:
%
% Bilevel Grayscale GrayscaleMatte
% Palette PaletteMatte TrueColor
% TrueColorMatte ColorSeparation ColorSeparationMatte
%
% To ensure the image type matches its potential, use SetImageType():
%
% (void) SetImageType(image,GetImageType(image));
%
% The format of the GetImageType method is:
%
% ImageType GetImageType(const Image *image,ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport ImageType GetImageType(const Image *image,ExceptionInfo *exception)
{
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
if (image->colorspace == CMYKColorspace)
{
if (image->matte == MagickFalse)
return(ColorSeparationType);
return(ColorSeparationMatteType);
}
if (IsMonochromeImage(image,exception) != MagickFalse)
return(BilevelType);
if (IsGrayImage(image,exception) != MagickFalse)
{
if (image->matte != MagickFalse)
return(GrayscaleMatteType);
return(GrayscaleType);
}
if (IsPaletteImage(image,exception) != MagickFalse)
{
if (image->matte != MagickFalse)
return(PaletteMatteType);
return(PaletteType);
}
if (image->matte != MagickFalse)
return(TrueColorMatteType);
return(TrueColorType);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% I d e n t i f y I m a g e G r a y %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% either 0 or QuantumRange. Otherwise undefined is returned.
%
% The format of the IdentifyImageGray method is:
%
% ImageType IdentifyImageGray(const Image *image,ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport ImageType IdentifyImageGray(const Image *image,
ExceptionInfo *exception)
{
CacheView
*image_view;
ImageType
type;
register const PixelPacket
*p;
register ssize_t
x;
ssize_t
y;
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
if ((image->type == BilevelType) || (image->type == GrayscaleType) ||
(image->type == GrayscaleMatteType))
return(image->type);
if (IssRGBCompatibleColorspace(image->colorspace) == MagickFalse)
return(UndefinedType);
type=BilevelType;
image_view=AcquireVirtualCacheView(image,exception);
for (y=0; y < (ssize_t) image->rows; y++)
{
p=GetCacheViewVirtualPixels(image_view,0,y,image->columns,1,exception);
if (p == (const PixelPacket *) NULL)
break;
for (x=0; x < (ssize_t) image->columns; x++)
{
if (IsPixelGray(p) == MagickFalse)
{
type=UndefinedType;
break;
}
if ((type == BilevelType) && (IsPixelMonochrome(p) == MagickFalse))
type=GrayscaleType;
p++;
}
if (type == UndefinedType)
break;
}
image_view=DestroyCacheView(image_view);
if ((type == GrayscaleType) && (image->matte != MagickFalse))
type=GrayscaleMatteType;
return(type);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% I d e n t i f y I m a g e M o n o c h r o m e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% IdentifyImageMonochrome() returns MagickTrue if all the pixels in the image
% have the same red, green, and blue intensities and the intensity is either
% 0 or QuantumRange.
%
% The format of the IdentifyImageMonochrome method is:
%
% MagickBooleanType IdentifyImageMonochrome(const Image *image,
% ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport MagickBooleanType IdentifyImageMonochrome(const Image *image,
ExceptionInfo *exception)
{
CacheView
*image_view;
ImageType
type;
register ssize_t
x;
register const PixelPacket
*p;
ssize_t
y;
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
if (image->type == BilevelType)
return(MagickTrue);
if (IssRGBCompatibleColorspace(image->colorspace) == MagickFalse)
return(MagickFalse);
type=BilevelType;
image_view=AcquireVirtualCacheView(image,exception);
for (y=0; y < (ssize_t) image->rows; y++)
{
p=GetCacheViewVirtualPixels(image_view,0,y,image->columns,1,exception);
if (p == (const PixelPacket *) NULL)
break;
for (x=0; x < (ssize_t) image->columns; x++)
{
if (IsPixelMonochrome(p) == MagickFalse)
{
type=UndefinedType;
break;
}
p++;
}
if (type == UndefinedType)
break;
}
image_view=DestroyCacheView(image_view);
if (type == BilevelType)
return(MagickTrue);
return(MagickFalse);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% I d e n t i f y I m a g e T y p e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% IdentifyImageType() returns the potential type of image:
%
% Bilevel Grayscale GrayscaleMatte
% Palette PaletteMatte TrueColor
% TrueColorMatte ColorSeparation ColorSeparationMatte
%
% To ensure the image type matches its potential, use SetImageType():
%
% (void) SetImageType(image,IdentifyImageType(image,exception),exception);
%
% The format of the IdentifyImageType method is:
%
% ImageType IdentifyImageType(const Image *image,ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport ImageType IdentifyImageType(const Image *image,
ExceptionInfo *exception)
{
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
if (image->colorspace == CMYKColorspace)
{
if (image->matte == MagickFalse)
return(ColorSeparationType);
return(ColorSeparationMatteType);
}
if (IdentifyImageMonochrome(image,exception) != MagickFalse)
return(BilevelType);
if (IdentifyImageGray(image,exception) != UndefinedType)
{
if (image->matte != MagickFalse)
return(GrayscaleMatteType);
return(GrayscaleType);
}
if (IdentifyPaletteImage(image,exception) != MagickFalse)
{
if (image->matte != MagickFalse)
return(PaletteMatteType);
return(PaletteType);
}
if (image->matte != MagickFalse)
return(TrueColorMatteType);
return(TrueColorType);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% I s G r a y I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% IsGrayImage() returns MagickTrue if the type of the image is grayscale or
% bi-level.
%
% The format of the IsGrayImage method is:
%
% MagickBooleanType IsGrayImage(const Image *image,
% ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport MagickBooleanType IsGrayImage(const Image *image,
ExceptionInfo *exception)
{
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if ((image->type == BilevelType) || (image->type == GrayscaleType) ||
(image->type == GrayscaleMatteType))
return(MagickTrue);
return(MagickFalse);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% I s M o n o c h r o m e I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% IsMonochromeImage() returns MagickTrue if type of the image is bi-level.
%
% The format of the IsMonochromeImage method is:
%
% MagickBooleanType IsMonochromeImage(const Image *image,
% ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport MagickBooleanType IsMonochromeImage(const Image *image,
ExceptionInfo *exception)
{
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->type == BilevelType)
return(MagickTrue);
return(MagickFalse);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% I s O p a q u e I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% IsOpaqueImage() returns MagickTrue if none of the pixels in the image have
% an opacity value other than opaque (0).
%
% The format of the IsOpaqueImage method is:
%
% MagickBooleanType IsOpaqueImage(const Image *image,
% ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport MagickBooleanType IsOpaqueImage(const Image *image,
ExceptionInfo *exception)
{
CacheView
*image_view;
register const PixelPacket
*p;
register ssize_t
x;
ssize_t
y;
/*
Determine if image is opaque.
*/
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
if (image->matte == MagickFalse)
return(MagickTrue);
image_view=AcquireVirtualCacheView(image,exception);
for (y=0; y < (ssize_t) image->rows; y++)
{
p=GetCacheViewVirtualPixels(image_view,0,y,image->columns,1,exception);
if (p == (const PixelPacket *) NULL)
break;
for (x=0; x < (ssize_t) image->columns; x++)
{
if (GetPixelOpacity(p) != OpaqueOpacity)
break;
p++;
}
if (x < (ssize_t) image->columns)
break;
}
image_view=DestroyCacheView(image_view);
return(y < (ssize_t) image->rows ? MagickFalse : MagickTrue);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% S e t I m a g e C h a n n e l D e p t h %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% SetImageChannelDepth() sets the depth of the image.
%
% The format of the SetImageChannelDepth method is:
%
% MagickBooleanType SetImageDepth(Image *image,const size_t depth)
% MagickBooleanType SetImageChannelDepth(Image *image,
% const ChannelType channel,const size_t depth)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o channel: the channel.
%
% o depth: the image depth.
%
*/
MagickExport MagickBooleanType SetImageDepth(Image *image,
const size_t depth)
{
return(SetImageChannelDepth(image,CompositeChannels,depth));
}
MagickExport MagickBooleanType SetImageChannelDepth(Image *image,
const ChannelType channel,const size_t depth)
{
CacheView
*image_view;
ExceptionInfo
*exception;
MagickBooleanType
status;
QuantumAny
range;
ssize_t
y;
assert(image != (Image *) NULL);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"...");
assert(image->signature == MagickCoreSignature);
if (depth >= MAGICKCORE_QUANTUM_DEPTH)
{
image->depth=depth;
return(MagickTrue);
}
range=GetQuantumRange(depth);
if (image->storage_class == PseudoClass)
{
register ssize_t
i;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static) shared(status) \
magick_number_threads(image,image,image->rows,1)
#endif
for (i=0; i < (ssize_t) image->colors; i++)
{
if ((channel & RedChannel) != 0)
image->colormap[i].red=ScaleAnyToQuantum(ScaleQuantumToAny(
ClampPixel((MagickRealType) image->colormap[i].red),range),range);
if ((channel & GreenChannel) != 0)
image->colormap[i].green=ScaleAnyToQuantum(ScaleQuantumToAny(
ClampPixel((MagickRealType) image->colormap[i].green),range),range);
if ((channel & BlueChannel) != 0)
image->colormap[i].blue=ScaleAnyToQuantum(ScaleQuantumToAny(
ClampPixel((MagickRealType) image->colormap[i].blue),range),range);
if ((channel & OpacityChannel) != 0)
image->colormap[i].opacity=ScaleAnyToQuantum(ScaleQuantumToAny(
ClampPixel((MagickRealType) image->colormap[i].opacity),range),
range);
}
}
status=MagickTrue;
exception=(&image->exception);
image_view=AcquireAuthenticCacheView(image,exception);
#if !defined(MAGICKCORE_HDRI_SUPPORT)
DisableMSCWarning(4127)
if (1UL*QuantumRange <= MaxMap)
RestoreMSCWarning
{
Quantum
*depth_map;
register ssize_t
i;
/*
Scale pixels to desired (optimized with depth map).
*/
depth_map=(Quantum *) AcquireQuantumMemory(MaxMap+1,sizeof(*depth_map));
if (depth_map == (Quantum *) NULL)
ThrowFatalException(ResourceLimitFatalError,"MemoryAllocationFailed");
for (i=0; i <= (ssize_t) MaxMap; i++)
depth_map[i]=ScaleAnyToQuantum(ScaleQuantumToAny((Quantum) i,range),
range);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static) shared(status) \
magick_number_threads(image,image,image->rows,1)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
register ssize_t
x;
register PixelPacket
*magick_restrict q;
if (status == MagickFalse)
continue;
q=GetCacheViewAuthenticPixels(image_view,0,y,image->columns,1,
exception);
if (q == (PixelPacket *) NULL)
{
status=MagickFalse;
continue;
}
for (x=0; x < (ssize_t) image->columns; x++)
{
if ((channel & RedChannel) != 0)
SetPixelRed(q,depth_map[ScaleQuantumToMap(GetPixelRed(q))]);
if ((channel & GreenChannel) != 0)
SetPixelGreen(q,depth_map[ScaleQuantumToMap(GetPixelGreen(q))]);
if ((channel & BlueChannel) != 0)
SetPixelBlue(q,depth_map[ScaleQuantumToMap(GetPixelBlue(q))]);
if (((channel & OpacityChannel) != 0) &&
(image->matte != MagickFalse))
SetPixelOpacity(q,depth_map[ScaleQuantumToMap(GetPixelOpacity(q))]);
q++;
}
if (SyncCacheViewAuthenticPixels(image_view,exception) == MagickFalse)
{
status=MagickFalse;
continue;
}
}
image_view=DestroyCacheView(image_view);
depth_map=(Quantum *) RelinquishMagickMemory(depth_map);
if (status != MagickFalse)
image->depth=depth;
return(status);
}
#endif
/*
Scale pixels to desired depth.
*/
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static) shared(status) \
magick_number_threads(image,image,image->rows,1)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
register ssize_t
x;
register PixelPacket
*magick_restrict q;
if (status == MagickFalse)
continue;
q=GetCacheViewAuthenticPixels(image_view,0,y,image->columns,1,exception);
if (q == (PixelPacket *) NULL)
{
status=MagickFalse;
continue;
}
for (x=0; x < (ssize_t) image->columns; x++)
{
if ((channel & RedChannel) != 0)
SetPixelRed(q,ScaleAnyToQuantum(ScaleQuantumToAny(ClampPixel(
(MagickRealType) GetPixelRed(q)),range),range));
if ((channel & GreenChannel) != 0)
SetPixelGreen(q,ScaleAnyToQuantum(ScaleQuantumToAny(ClampPixel(
(MagickRealType) GetPixelGreen(q)),range),range));
if ((channel & BlueChannel) != 0)
SetPixelBlue(q,ScaleAnyToQuantum(ScaleQuantumToAny(ClampPixel(
(MagickRealType) GetPixelBlue(q)),range),range));
if (((channel & OpacityChannel) != 0) && (image->matte != MagickFalse))
SetPixelOpacity(q,ScaleAnyToQuantum(ScaleQuantumToAny(ClampPixel(
(MagickRealType) GetPixelOpacity(q)),range),range));
q++;
}
if (SyncCacheViewAuthenticPixels(image_view,exception) == MagickFalse)
{
status=MagickFalse;
continue;
}
}
image_view=DestroyCacheView(image_view);
if (status != MagickFalse)
image->depth=depth;
return(status);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% S e t I m a g e T y p e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% SetImageType() sets the type of image. Choose from these types:
%
% BilevelType, GrayscaleType, GrayscaleMatteType, PaletteType,
% PaletteMatteType, TrueColorType, TrueColorMatteType,
% ColorSeparationType, ColorSeparationMatteType, OptimizeType
%
% The format of the SetImageType method is:
%
% MagickBooleanType SetImageType(Image *image,const ImageType type)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o type: Image type.
%
*/
MagickExport MagickBooleanType SetImageType(Image *image,const ImageType type)
{
const char
*artifact;
ImageInfo
*image_info;
MagickBooleanType
status;
QuantizeInfo
*quantize_info;
assert(image != (Image *) NULL);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"...");
assert(image->signature == MagickCoreSignature);
status=MagickTrue;
image_info=AcquireImageInfo();
image_info->dither=image->dither;
artifact=GetImageArtifact(image,"dither");
if (artifact != (const char *) NULL)
(void) SetImageOption(image_info,"dither",artifact);
switch (type)
{
case BilevelType:
{
status=TransformImageColorspace(image,GRAYColorspace);
(void) NormalizeImage(image);
quantize_info=AcquireQuantizeInfo(image_info);
quantize_info->number_colors=2;
quantize_info->colorspace=GRAYColorspace;
status=QuantizeImage(quantize_info,image);
quantize_info=DestroyQuantizeInfo(quantize_info);
image->matte=MagickFalse;
break;
}
case GrayscaleType:
{
status=TransformImageColorspace(image,GRAYColorspace);
image->matte=MagickFalse;
break;
}
case GrayscaleMatteType:
{
status=TransformImageColorspace(image,GRAYColorspace);
if (image->matte == MagickFalse)
(void) SetImageAlphaChannel(image,OpaqueAlphaChannel);
break;
}
case PaletteType:
{
status=TransformImageColorspace(image,sRGBColorspace);
if ((image->storage_class == DirectClass) || (image->colors > 256))
{
quantize_info=AcquireQuantizeInfo(image_info);
quantize_info->number_colors=256;
status=QuantizeImage(quantize_info,image);
quantize_info=DestroyQuantizeInfo(quantize_info);
}
image->matte=MagickFalse;
break;
}
case PaletteBilevelMatteType:
{
status=TransformImageColorspace(image,sRGBColorspace);
if (image->matte == MagickFalse)
(void) SetImageAlphaChannel(image,OpaqueAlphaChannel);
(void) BilevelImageChannel(image,AlphaChannel,(double) QuantumRange/2.0);
quantize_info=AcquireQuantizeInfo(image_info);
status=QuantizeImage(quantize_info,image);
quantize_info=DestroyQuantizeInfo(quantize_info);
break;
}
case PaletteMatteType:
{
status=TransformImageColorspace(image,sRGBColorspace);
if (image->matte == MagickFalse)
(void) SetImageAlphaChannel(image,OpaqueAlphaChannel);
quantize_info=AcquireQuantizeInfo(image_info);
quantize_info->colorspace=TransparentColorspace;
status=QuantizeImage(quantize_info,image);
quantize_info=DestroyQuantizeInfo(quantize_info);
break;
}
case TrueColorType:
{
status=TransformImageColorspace(image,sRGBColorspace);
if (image->storage_class != DirectClass)
status=SetImageStorageClass(image,DirectClass);
image->matte=MagickFalse;
break;
}
case TrueColorMatteType:
{
status=TransformImageColorspace(image,sRGBColorspace);
if (image->storage_class != DirectClass)
status=SetImageStorageClass(image,DirectClass);
if (image->matte == MagickFalse)
(void) SetImageAlphaChannel(image,OpaqueAlphaChannel);
break;
}
case ColorSeparationType:
{
status=TransformImageColorspace(image,CMYKColorspace);
if (image->storage_class != DirectClass)
status=SetImageStorageClass(image,DirectClass);
image->matte=MagickFalse;
break;
}
case ColorSeparationMatteType:
{
status=TransformImageColorspace(image,CMYKColorspace);
if (image->storage_class != DirectClass)
status=SetImageStorageClass(image,DirectClass);
if (image->matte == MagickFalse)
(void) SetImageAlphaChannel(image,OpaqueAlphaChannel);
break;
}
case OptimizeType:
case UndefinedType:
break;
}
image_info=DestroyImageInfo(image_info);
if (status == MagickFalse)
return(MagickFalse);
image->type=type;
return(MagickTrue);
}
|
visual-effects.c | /*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% V V IIIII SSSSS U U AAA L %
% V V I SS U U A A L %
% V V I SSS U U AAAAA L %
% V V I SS U U A A L %
% V IIIII SSSSS UUU A A LLLLL %
% %
% EEEEE FFFFF FFFFF EEEEE CCCC TTTTT SSSSS %
% E F F E C T SS %
% EEE FFF FFF EEE C T SSS %
% E F F E C T SS %
% EEEEE F F EEEEE CCCC T SSSSS %
% %
% %
% MagickCore Image Special Effects Methods %
% %
% Software Design %
% Cristy %
% October 1996 %
% %
% %
% %
% Copyright @ 1999 ImageMagick Studio LLC, a non-profit organization %
% dedicated to making software imaging solutions freely available. %
% %
% You may not use this file except in compliance with the License. You may %
% obtain a copy of the License at %
% %
% https://imagemagick.org/script/license.php %
% %
% Unless required by applicable law or agreed to in writing, software %
% distributed under the License is distributed on an "AS IS" BASIS, %
% WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. %
% See the License for the specific language governing permissions and %
% limitations under the License. %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
%
%
*/
/*
Include declarations.
*/
#include "MagickCore/studio.h"
#include "MagickCore/accelerate-private.h"
#include "MagickCore/annotate.h"
#include "MagickCore/artifact.h"
#include "MagickCore/attribute.h"
#include "MagickCore/cache.h"
#include "MagickCore/cache-view.h"
#include "MagickCore/channel.h"
#include "MagickCore/color.h"
#include "MagickCore/color-private.h"
#include "MagickCore/colorspace-private.h"
#include "MagickCore/composite.h"
#include "MagickCore/decorate.h"
#include "MagickCore/distort.h"
#include "MagickCore/draw.h"
#include "MagickCore/effect.h"
#include "MagickCore/enhance.h"
#include "MagickCore/exception.h"
#include "MagickCore/exception-private.h"
#include "MagickCore/gem.h"
#include "MagickCore/gem-private.h"
#include "MagickCore/geometry.h"
#include "MagickCore/layer.h"
#include "MagickCore/list.h"
#include "MagickCore/log.h"
#include "MagickCore/image.h"
#include "MagickCore/image-private.h"
#include "MagickCore/magick.h"
#include "MagickCore/memory_.h"
#include "MagickCore/memory-private.h"
#include "MagickCore/monitor.h"
#include "MagickCore/monitor-private.h"
#include "MagickCore/option.h"
#include "MagickCore/pixel.h"
#include "MagickCore/pixel-accessor.h"
#include "MagickCore/property.h"
#include "MagickCore/quantum.h"
#include "MagickCore/quantum-private.h"
#include "MagickCore/random_.h"
#include "MagickCore/random-private.h"
#include "MagickCore/resample.h"
#include "MagickCore/resample-private.h"
#include "MagickCore/resize.h"
#include "MagickCore/resource_.h"
#include "MagickCore/splay-tree.h"
#include "MagickCore/statistic.h"
#include "MagickCore/string_.h"
#include "MagickCore/string-private.h"
#include "MagickCore/thread-private.h"
#include "MagickCore/threshold.h"
#include "MagickCore/transform.h"
#include "MagickCore/transform-private.h"
#include "MagickCore/utility.h"
#include "MagickCore/visual-effects.h"
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% A d d N o i s e I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% AddNoiseImage() adds random noise to the image.
%
% The format of the AddNoiseImage method is:
%
% Image *AddNoiseImage(const Image *image,const NoiseType noise_type,
% const double attenuate,ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o channel: the channel type.
%
% o noise_type: The type of noise: Uniform, Gaussian, Multiplicative,
% Impulse, Laplacian, or Poisson.
%
% o attenuate: attenuate the random distribution.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport Image *AddNoiseImage(const Image *image,const NoiseType noise_type,
const double attenuate,ExceptionInfo *exception)
{
#define AddNoiseImageTag "AddNoise/Image"
CacheView
*image_view,
*noise_view;
Image
*noise_image;
MagickBooleanType
status;
MagickOffsetType
progress;
RandomInfo
**magick_restrict random_info;
ssize_t
y;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
unsigned long
key;
#endif
/*
Initialize noise image attributes.
*/
assert(image != (const Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
#if defined(MAGICKCORE_OPENCL_SUPPORT)
noise_image=AccelerateAddNoiseImage(image,noise_type,attenuate,exception);
if (noise_image != (Image *) NULL)
return(noise_image);
#endif
noise_image=CloneImage(image,0,0,MagickTrue,exception);
if (noise_image == (Image *) NULL)
return((Image *) NULL);
if (SetImageStorageClass(noise_image,DirectClass,exception) == MagickFalse)
{
noise_image=DestroyImage(noise_image);
return((Image *) NULL);
}
/*
Add noise in each row.
*/
status=MagickTrue;
progress=0;
random_info=AcquireRandomInfoTLS();
image_view=AcquireVirtualCacheView(image,exception);
noise_view=AcquireAuthenticCacheView(noise_image,exception);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
key=GetRandomSecretKey(random_info[0]);
#pragma omp parallel for schedule(static) shared(progress,status) \
magick_number_threads(image,noise_image,image->rows,key == ~0UL)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
const int
id = GetOpenMPThreadId();
MagickBooleanType
sync;
const Quantum
*magick_restrict p;
ssize_t
x;
Quantum
*magick_restrict q;
if (status == MagickFalse)
continue;
p=GetCacheViewVirtualPixels(image_view,0,y,image->columns,1,exception);
q=QueueCacheViewAuthenticPixels(noise_view,0,y,noise_image->columns,1,
exception);
if ((p == (const Quantum *) NULL) || (q == (Quantum *) NULL))
{
status=MagickFalse;
continue;
}
for (x=0; x < (ssize_t) image->columns; x++)
{
ssize_t
i;
for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
{
PixelChannel channel = GetPixelChannelChannel(image,i);
PixelTrait traits = GetPixelChannelTraits(image,channel);
PixelTrait noise_traits=GetPixelChannelTraits(noise_image,channel);
if ((traits == UndefinedPixelTrait) ||
(noise_traits == UndefinedPixelTrait))
continue;
if ((noise_traits & CopyPixelTrait) != 0)
{
SetPixelChannel(noise_image,channel,p[i],q);
continue;
}
SetPixelChannel(noise_image,channel,ClampToQuantum(
GenerateDifferentialNoise(random_info[id],p[i],noise_type,attenuate)),
q);
}
p+=GetPixelChannels(image);
q+=GetPixelChannels(noise_image);
}
sync=SyncCacheViewAuthenticPixels(noise_view,exception);
if (sync == MagickFalse)
status=MagickFalse;
if (image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp atomic
#endif
progress++;
proceed=SetImageProgress(image,AddNoiseImageTag,progress,image->rows);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
noise_view=DestroyCacheView(noise_view);
image_view=DestroyCacheView(image_view);
random_info=DestroyRandomInfoTLS(random_info);
if (status == MagickFalse)
noise_image=DestroyImage(noise_image);
return(noise_image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% B l u e S h i f t I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% BlueShiftImage() mutes the colors of the image to simulate a scene at
% nighttime in the moonlight.
%
% The format of the BlueShiftImage method is:
%
% Image *BlueShiftImage(const Image *image,const double factor,
% ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o factor: the shift factor.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport Image *BlueShiftImage(const Image *image,const double factor,
ExceptionInfo *exception)
{
#define BlueShiftImageTag "BlueShift/Image"
CacheView
*image_view,
*shift_view;
Image
*shift_image;
MagickBooleanType
status;
MagickOffsetType
progress;
ssize_t
y;
/*
Allocate blue shift image.
*/
assert(image != (const Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
shift_image=CloneImage(image,0,0,MagickTrue,exception);
if (shift_image == (Image *) NULL)
return((Image *) NULL);
if (SetImageStorageClass(shift_image,DirectClass,exception) == MagickFalse)
{
shift_image=DestroyImage(shift_image);
return((Image *) NULL);
}
/*
Blue-shift DirectClass image.
*/
status=MagickTrue;
progress=0;
image_view=AcquireVirtualCacheView(image,exception);
shift_view=AcquireAuthenticCacheView(shift_image,exception);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static) shared(progress,status) \
magick_number_threads(image,shift_image,image->rows,1)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
MagickBooleanType
sync;
PixelInfo
pixel;
Quantum
quantum;
const Quantum
*magick_restrict p;
ssize_t
x;
Quantum
*magick_restrict q;
if (status == MagickFalse)
continue;
p=GetCacheViewVirtualPixels(image_view,0,y,image->columns,1,exception);
q=QueueCacheViewAuthenticPixels(shift_view,0,y,shift_image->columns,1,
exception);
if ((p == (const Quantum *) NULL) || (q == (Quantum *) NULL))
{
status=MagickFalse;
continue;
}
for (x=0; x < (ssize_t) image->columns; x++)
{
quantum=GetPixelRed(image,p);
if (GetPixelGreen(image,p) < quantum)
quantum=GetPixelGreen(image,p);
if (GetPixelBlue(image,p) < quantum)
quantum=GetPixelBlue(image,p);
pixel.red=0.5*(GetPixelRed(image,p)+factor*quantum);
pixel.green=0.5*(GetPixelGreen(image,p)+factor*quantum);
pixel.blue=0.5*(GetPixelBlue(image,p)+factor*quantum);
quantum=GetPixelRed(image,p);
if (GetPixelGreen(image,p) > quantum)
quantum=GetPixelGreen(image,p);
if (GetPixelBlue(image,p) > quantum)
quantum=GetPixelBlue(image,p);
pixel.red=0.5*(pixel.red+factor*quantum);
pixel.green=0.5*(pixel.green+factor*quantum);
pixel.blue=0.5*(pixel.blue+factor*quantum);
SetPixelRed(shift_image,ClampToQuantum(pixel.red),q);
SetPixelGreen(shift_image,ClampToQuantum(pixel.green),q);
SetPixelBlue(shift_image,ClampToQuantum(pixel.blue),q);
p+=GetPixelChannels(image);
q+=GetPixelChannels(shift_image);
}
sync=SyncCacheViewAuthenticPixels(shift_view,exception);
if (sync == MagickFalse)
status=MagickFalse;
if (image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp atomic
#endif
progress++;
proceed=SetImageProgress(image,BlueShiftImageTag,progress,image->rows);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
image_view=DestroyCacheView(image_view);
shift_view=DestroyCacheView(shift_view);
if (status == MagickFalse)
shift_image=DestroyImage(shift_image);
return(shift_image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% C h a r c o a l I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% CharcoalImage() creates a new image that is a copy of an existing one with
% the edge highlighted. It allocates the memory necessary for the new Image
% structure and returns a pointer to the new image.
%
% The format of the CharcoalImage method is:
%
% Image *CharcoalImage(const Image *image,const double radius,
% const double sigma,ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o radius: the radius of the pixel neighborhood.
%
% o sigma: the standard deviation of the Gaussian, in pixels.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport Image *CharcoalImage(const Image *image,const double radius,
const double sigma,ExceptionInfo *exception)
{
Image
*charcoal_image,
*edge_image;
MagickBooleanType
status;
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
edge_image=EdgeImage(image,radius,exception);
if (edge_image == (Image *) NULL)
return((Image *) NULL);
edge_image->alpha_trait=UndefinedPixelTrait;
charcoal_image=(Image *) NULL;
status=ClampImage(edge_image,exception);
if (status != MagickFalse)
charcoal_image=BlurImage(edge_image,radius,sigma,exception);
edge_image=DestroyImage(edge_image);
if (charcoal_image == (Image *) NULL)
return((Image *) NULL);
status=NormalizeImage(charcoal_image,exception);
if (status != MagickFalse)
status=NegateImage(charcoal_image,MagickFalse,exception);
if (status != MagickFalse)
status=GrayscaleImage(charcoal_image,image->intensity,exception);
if (status == MagickFalse)
charcoal_image=DestroyImage(charcoal_image);
return(charcoal_image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% C o l o r i z e I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% ColorizeImage() blends the fill color with each pixel in the image.
% A percentage blend is specified with opacity. Control the application
% of different color components by specifying a different percentage for
% each component (e.g. 90/100/10 is 90% red, 100% green, and 10% blue).
%
% The format of the ColorizeImage method is:
%
% Image *ColorizeImage(const Image *image,const char *blend,
% const PixelInfo *colorize,ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o blend: A character string indicating the level of blending as a
% percentage.
%
% o colorize: A color value.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport Image *ColorizeImage(const Image *image,const char *blend,
const PixelInfo *colorize,ExceptionInfo *exception)
{
#define ColorizeImageTag "Colorize/Image"
#define Colorize(pixel,blend_percentage,colorize) \
(((pixel)*(100.0-(blend_percentage))+(colorize)*(blend_percentage))/100.0)
CacheView
*image_view;
GeometryInfo
geometry_info;
Image
*colorize_image;
MagickBooleanType
status;
MagickOffsetType
progress;
MagickStatusType
flags;
PixelInfo
blend_percentage;
ssize_t
y;
/*
Allocate colorized image.
*/
assert(image != (const Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
colorize_image=CloneImage(image,0,0,MagickTrue,exception);
if (colorize_image == (Image *) NULL)
return((Image *) NULL);
if (SetImageStorageClass(colorize_image,DirectClass,exception) == MagickFalse)
{
colorize_image=DestroyImage(colorize_image);
return((Image *) NULL);
}
if ((IsGrayColorspace(colorize_image->colorspace) != MagickFalse) ||
(IsPixelInfoGray(colorize) != MagickFalse))
(void) SetImageColorspace(colorize_image,sRGBColorspace,exception);
if ((colorize_image->alpha_trait == UndefinedPixelTrait) &&
(colorize->alpha_trait != UndefinedPixelTrait))
(void) SetImageAlpha(colorize_image,OpaqueAlpha,exception);
if (blend == (const char *) NULL)
return(colorize_image);
GetPixelInfo(colorize_image,&blend_percentage);
flags=ParseGeometry(blend,&geometry_info);
blend_percentage.red=geometry_info.rho;
blend_percentage.green=geometry_info.rho;
blend_percentage.blue=geometry_info.rho;
blend_percentage.black=geometry_info.rho;
blend_percentage.alpha=(MagickRealType) TransparentAlpha;
if ((flags & SigmaValue) != 0)
blend_percentage.green=geometry_info.sigma;
if ((flags & XiValue) != 0)
blend_percentage.blue=geometry_info.xi;
if ((flags & PsiValue) != 0)
blend_percentage.alpha=geometry_info.psi;
if (blend_percentage.colorspace == CMYKColorspace)
{
if ((flags & PsiValue) != 0)
blend_percentage.black=geometry_info.psi;
if ((flags & ChiValue) != 0)
blend_percentage.alpha=geometry_info.chi;
}
/*
Colorize DirectClass image.
*/
status=MagickTrue;
progress=0;
image_view=AcquireAuthenticCacheView(colorize_image,exception);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static) shared(progress,status) \
magick_number_threads(colorize_image,colorize_image,colorize_image->rows,1)
#endif
for (y=0; y < (ssize_t) colorize_image->rows; y++)
{
MagickBooleanType
sync;
Quantum
*magick_restrict q;
ssize_t
x;
if (status == MagickFalse)
continue;
q=GetCacheViewAuthenticPixels(image_view,0,y,colorize_image->columns,1,
exception);
if (q == (Quantum *) NULL)
{
status=MagickFalse;
continue;
}
for (x=0; x < (ssize_t) colorize_image->columns; x++)
{
ssize_t
i;
for (i=0; i < (ssize_t) GetPixelChannels(colorize_image); i++)
{
PixelTrait traits = GetPixelChannelTraits(colorize_image,
(PixelChannel) i);
if (traits == UndefinedPixelTrait)
continue;
if ((traits & CopyPixelTrait) != 0)
continue;
SetPixelChannel(colorize_image,(PixelChannel) i,ClampToQuantum(
Colorize(q[i],GetPixelInfoChannel(&blend_percentage,(PixelChannel) i),
GetPixelInfoChannel(colorize,(PixelChannel) i))),q);
}
q+=GetPixelChannels(colorize_image);
}
sync=SyncCacheViewAuthenticPixels(image_view,exception);
if (sync == MagickFalse)
status=MagickFalse;
if (image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp atomic
#endif
progress++;
proceed=SetImageProgress(image,ColorizeImageTag,progress,
colorize_image->rows);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
image_view=DestroyCacheView(image_view);
if (status == MagickFalse)
colorize_image=DestroyImage(colorize_image);
return(colorize_image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% C o l o r M a t r i x I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% ColorMatrixImage() applies color transformation to an image. This method
% permits saturation changes, hue rotation, luminance to alpha, and various
% other effects. Although variable-sized transformation matrices can be used,
% typically one uses a 5x5 matrix for an RGBA image and a 6x6 for CMYKA
% (or RGBA with offsets). The matrix is similar to those used by Adobe Flash
% except offsets are in column 6 rather than 5 (in support of CMYKA images)
% and offsets are normalized (divide Flash offset by 255).
%
% The format of the ColorMatrixImage method is:
%
% Image *ColorMatrixImage(const Image *image,
% const KernelInfo *color_matrix,ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o color_matrix: the color matrix.
%
% o exception: return any errors or warnings in this structure.
%
*/
/* FUTURE: modify to make use of a MagickMatrix Mutliply function
That should be provided in "matrix.c"
(ASIDE: actually distorts should do this too but currently doesn't)
*/
MagickExport Image *ColorMatrixImage(const Image *image,
const KernelInfo *color_matrix,ExceptionInfo *exception)
{
#define ColorMatrixImageTag "ColorMatrix/Image"
CacheView
*color_view,
*image_view;
double
ColorMatrix[6][6] =
{
{ 1.0, 0.0, 0.0, 0.0, 0.0, 0.0 },
{ 0.0, 1.0, 0.0, 0.0, 0.0, 0.0 },
{ 0.0, 0.0, 1.0, 0.0, 0.0, 0.0 },
{ 0.0, 0.0, 0.0, 1.0, 0.0, 0.0 },
{ 0.0, 0.0, 0.0, 0.0, 1.0, 0.0 },
{ 0.0, 0.0, 0.0, 0.0, 0.0, 1.0 }
};
Image
*color_image;
MagickBooleanType
status;
MagickOffsetType
progress;
ssize_t
i;
ssize_t
u,
v,
y;
/*
Map given color_matrix, into a 6x6 matrix RGBKA and a constant
*/
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
i=0;
for (v=0; v < (ssize_t) color_matrix->height; v++)
for (u=0; u < (ssize_t) color_matrix->width; u++)
{
if ((v < 6) && (u < 6))
ColorMatrix[v][u]=color_matrix->values[i];
i++;
}
/*
Initialize color image.
*/
color_image=CloneImage(image,0,0,MagickTrue,exception);
if (color_image == (Image *) NULL)
return((Image *) NULL);
if (SetImageStorageClass(color_image,DirectClass,exception) == MagickFalse)
{
color_image=DestroyImage(color_image);
return((Image *) NULL);
}
if (image->debug != MagickFalse)
{
char
format[MagickPathExtent],
*message;
(void) LogMagickEvent(TransformEvent,GetMagickModule(),
" ColorMatrix image with color matrix:");
message=AcquireString("");
for (v=0; v < 6; v++)
{
*message='\0';
(void) FormatLocaleString(format,MagickPathExtent,"%.20g: ",(double) v);
(void) ConcatenateString(&message,format);
for (u=0; u < 6; u++)
{
(void) FormatLocaleString(format,MagickPathExtent,"%+f ",
ColorMatrix[v][u]);
(void) ConcatenateString(&message,format);
}
(void) LogMagickEvent(TransformEvent,GetMagickModule(),"%s",message);
}
message=DestroyString(message);
}
/*
Apply the ColorMatrix to image.
*/
status=MagickTrue;
progress=0;
image_view=AcquireVirtualCacheView(image,exception);
color_view=AcquireAuthenticCacheView(color_image,exception);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static) shared(progress,status) \
magick_number_threads(image,color_image,image->rows,1)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
PixelInfo
pixel;
const Quantum
*magick_restrict p;
Quantum
*magick_restrict q;
ssize_t
x;
if (status == MagickFalse)
continue;
p=GetCacheViewVirtualPixels(image_view,0,y,image->columns,1,exception);
q=GetCacheViewAuthenticPixels(color_view,0,y,color_image->columns,1,
exception);
if ((p == (const Quantum *) NULL) || (q == (Quantum *) NULL))
{
status=MagickFalse;
continue;
}
GetPixelInfo(image,&pixel);
for (x=0; x < (ssize_t) image->columns; x++)
{
ssize_t
h;
size_t
height;
GetPixelInfoPixel(image,p,&pixel);
height=color_matrix->height > 6 ? 6UL : color_matrix->height;
for (h=0; h < (ssize_t) height; h++)
{
double
sum;
sum=ColorMatrix[h][0]*GetPixelRed(image,p)+ColorMatrix[h][1]*
GetPixelGreen(image,p)+ColorMatrix[h][2]*GetPixelBlue(image,p);
if (image->colorspace == CMYKColorspace)
sum+=ColorMatrix[h][3]*GetPixelBlack(image,p);
if (image->alpha_trait != UndefinedPixelTrait)
sum+=ColorMatrix[h][4]*GetPixelAlpha(image,p);
sum+=QuantumRange*ColorMatrix[h][5];
switch (h)
{
case 0: pixel.red=sum; break;
case 1: pixel.green=sum; break;
case 2: pixel.blue=sum; break;
case 3: pixel.black=sum; break;
case 4: pixel.alpha=sum; break;
default: break;
}
}
SetPixelViaPixelInfo(color_image,&pixel,q);
p+=GetPixelChannels(image);
q+=GetPixelChannels(color_image);
}
if (SyncCacheViewAuthenticPixels(color_view,exception) == MagickFalse)
status=MagickFalse;
if (image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp atomic
#endif
progress++;
proceed=SetImageProgress(image,ColorMatrixImageTag,progress,
image->rows);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
color_view=DestroyCacheView(color_view);
image_view=DestroyCacheView(image_view);
if (status == MagickFalse)
color_image=DestroyImage(color_image);
return(color_image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% I m p l o d e I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% ImplodeImage() creates a new image that is a copy of an existing
% one with the image pixels "implode" by the specified percentage. It
% allocates the memory necessary for the new Image structure and returns a
% pointer to the new image.
%
% The format of the ImplodeImage method is:
%
% Image *ImplodeImage(const Image *image,const double amount,
% const PixelInterpolateMethod method,ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o implode_image: Method ImplodeImage returns a pointer to the image
% after it is implode. A null image is returned if there is a memory
% shortage.
%
% o image: the image.
%
% o amount: Define the extent of the implosion.
%
% o method: the pixel interpolation method.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport Image *ImplodeImage(const Image *image,const double amount,
const PixelInterpolateMethod method,ExceptionInfo *exception)
{
#define ImplodeImageTag "Implode/Image"
CacheView
*canvas_view,
*implode_view,
*interpolate_view;
double
radius;
Image
*canvas_image,
*implode_image;
MagickBooleanType
status;
MagickOffsetType
progress;
PointInfo
center,
scale;
ssize_t
y;
/*
Initialize implode image attributes.
*/
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
canvas_image=CloneImage(image,0,0,MagickTrue,exception);
if (canvas_image == (Image *) NULL)
return((Image *) NULL);
if ((canvas_image->alpha_trait == UndefinedPixelTrait) &&
(canvas_image->background_color.alpha != OpaqueAlpha))
(void) SetImageAlphaChannel(canvas_image,OpaqueAlphaChannel,exception);
implode_image=CloneImage(canvas_image,0,0,MagickTrue,exception);
if (implode_image == (Image *) NULL)
{
canvas_image=DestroyImage(canvas_image);
return((Image *) NULL);
}
if (SetImageStorageClass(implode_image,DirectClass,exception) == MagickFalse)
{
canvas_image=DestroyImage(canvas_image);
implode_image=DestroyImage(implode_image);
return((Image *) NULL);
}
/*
Compute scaling factor.
*/
scale.x=1.0;
scale.y=1.0;
center.x=0.5*canvas_image->columns;
center.y=0.5*canvas_image->rows;
radius=center.x;
if (canvas_image->columns > canvas_image->rows)
scale.y=(double) canvas_image->columns*PerceptibleReciprocal((double)
canvas_image->rows);
else
if (canvas_image->columns < canvas_image->rows)
{
scale.x=(double) canvas_image->rows*PerceptibleReciprocal((double)
canvas_image->columns);
radius=center.y;
}
/*
Implode image.
*/
status=MagickTrue;
progress=0;
canvas_view=AcquireVirtualCacheView(canvas_image,exception);
interpolate_view=AcquireVirtualCacheView(canvas_image,exception);
implode_view=AcquireAuthenticCacheView(implode_image,exception);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static) shared(progress,status) \
magick_number_threads(canvas_image,implode_image,canvas_image->rows,1)
#endif
for (y=0; y < (ssize_t) canvas_image->rows; y++)
{
double
distance;
PointInfo
delta;
const Quantum
*magick_restrict p;
ssize_t
x;
Quantum
*magick_restrict q;
if (status == MagickFalse)
continue;
p=GetCacheViewVirtualPixels(canvas_view,0,y,canvas_image->columns,1,
exception);
q=QueueCacheViewAuthenticPixels(implode_view,0,y,implode_image->columns,1,
exception);
if ((p == (const Quantum *) NULL) || (q == (Quantum *) NULL))
{
status=MagickFalse;
continue;
}
delta.y=scale.y*(double) (y-center.y);
for (x=0; x < (ssize_t) canvas_image->columns; x++)
{
ssize_t
i;
/*
Determine if the pixel is within an ellipse.
*/
delta.x=scale.x*(double) (x-center.x);
distance=delta.x*delta.x+delta.y*delta.y;
if (distance >= (radius*radius))
for (i=0; i < (ssize_t) GetPixelChannels(canvas_image); i++)
{
PixelChannel channel = GetPixelChannelChannel(canvas_image,i);
PixelTrait traits = GetPixelChannelTraits(canvas_image,channel);
PixelTrait implode_traits = GetPixelChannelTraits(implode_image,
channel);
if ((traits == UndefinedPixelTrait) ||
(implode_traits == UndefinedPixelTrait))
continue;
SetPixelChannel(implode_image,channel,p[i],q);
}
else
{
double
factor;
/*
Implode the pixel.
*/
factor=1.0;
if (distance > 0.0)
factor=pow(sin(MagickPI*sqrt((double) distance)*PerceptibleReciprocal(radius)/2),-amount);
status=InterpolatePixelChannels(canvas_image,interpolate_view,
implode_image,method,(double) (factor*delta.x*PerceptibleReciprocal(scale.x)+center.x),
(double) (factor*delta.y*PerceptibleReciprocal(scale.y)+center.y),q,exception);
if (status == MagickFalse)
break;
}
p+=GetPixelChannels(canvas_image);
q+=GetPixelChannels(implode_image);
}
if (SyncCacheViewAuthenticPixels(implode_view,exception) == MagickFalse)
status=MagickFalse;
if (canvas_image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp atomic
#endif
progress++;
proceed=SetImageProgress(canvas_image,ImplodeImageTag,progress,
canvas_image->rows);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
implode_view=DestroyCacheView(implode_view);
interpolate_view=DestroyCacheView(interpolate_view);
canvas_view=DestroyCacheView(canvas_view);
canvas_image=DestroyImage(canvas_image);
if (status == MagickFalse)
implode_image=DestroyImage(implode_image);
return(implode_image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% M o r p h I m a g e s %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% The MorphImages() method requires a minimum of two images. The first
% image is transformed into the second by a number of intervening images
% as specified by frames.
%
% The format of the MorphImage method is:
%
% Image *MorphImages(const Image *image,const size_t number_frames,
% ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o number_frames: Define the number of in-between image to generate.
% The more in-between frames, the smoother the morph.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport Image *MorphImages(const Image *image,const size_t number_frames,
ExceptionInfo *exception)
{
#define MorphImageTag "Morph/Image"
double
alpha,
beta;
Image
*morph_image,
*morph_images;
MagickBooleanType
status;
MagickOffsetType
scene;
const Image
*next;
ssize_t
n;
ssize_t
y;
/*
Clone first frame in sequence.
*/
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
morph_images=CloneImage(image,0,0,MagickTrue,exception);
if (morph_images == (Image *) NULL)
return((Image *) NULL);
if (GetNextImageInList(image) == (Image *) NULL)
{
/*
Morph single image.
*/
for (n=1; n < (ssize_t) number_frames; n++)
{
morph_image=CloneImage(image,0,0,MagickTrue,exception);
if (morph_image == (Image *) NULL)
{
morph_images=DestroyImageList(morph_images);
return((Image *) NULL);
}
AppendImageToList(&morph_images,morph_image);
if (image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
proceed=SetImageProgress(image,MorphImageTag,(MagickOffsetType) n,
number_frames);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
return(GetFirstImageInList(morph_images));
}
/*
Morph image sequence.
*/
status=MagickTrue;
scene=0;
next=image;
for ( ; GetNextImageInList(next) != (Image *) NULL; next=GetNextImageInList(next))
{
for (n=0; n < (ssize_t) number_frames; n++)
{
CacheView
*image_view,
*morph_view;
beta=(double) (n+1.0)/(double) (number_frames+1.0);
alpha=1.0-beta;
morph_image=ResizeImage(next,(size_t) (alpha*next->columns+beta*
GetNextImageInList(next)->columns+0.5),(size_t) (alpha*next->rows+beta*
GetNextImageInList(next)->rows+0.5),next->filter,exception);
if (morph_image == (Image *) NULL)
{
morph_images=DestroyImageList(morph_images);
return((Image *) NULL);
}
status=SetImageStorageClass(morph_image,DirectClass,exception);
if (status == MagickFalse)
{
morph_image=DestroyImage(morph_image);
return((Image *) NULL);
}
AppendImageToList(&morph_images,morph_image);
morph_images=GetLastImageInList(morph_images);
morph_image=ResizeImage(GetNextImageInList(next),morph_images->columns,
morph_images->rows,GetNextImageInList(next)->filter,exception);
if (morph_image == (Image *) NULL)
{
morph_images=DestroyImageList(morph_images);
return((Image *) NULL);
}
image_view=AcquireVirtualCacheView(morph_image,exception);
morph_view=AcquireAuthenticCacheView(morph_images,exception);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static) shared(status) \
magick_number_threads(morph_image,morph_image,morph_image->rows,1)
#endif
for (y=0; y < (ssize_t) morph_images->rows; y++)
{
MagickBooleanType
sync;
const Quantum
*magick_restrict p;
ssize_t
x;
Quantum
*magick_restrict q;
if (status == MagickFalse)
continue;
p=GetCacheViewVirtualPixels(image_view,0,y,morph_image->columns,1,
exception);
q=GetCacheViewAuthenticPixels(morph_view,0,y,morph_images->columns,1,
exception);
if ((p == (const Quantum *) NULL) || (q == (Quantum *) NULL))
{
status=MagickFalse;
continue;
}
for (x=0; x < (ssize_t) morph_images->columns; x++)
{
ssize_t
i;
for (i=0; i < (ssize_t) GetPixelChannels(morph_image); i++)
{
PixelChannel channel = GetPixelChannelChannel(morph_image,i);
PixelTrait traits = GetPixelChannelTraits(morph_image,channel);
PixelTrait morph_traits=GetPixelChannelTraits(morph_images,channel);
if ((traits == UndefinedPixelTrait) ||
(morph_traits == UndefinedPixelTrait))
continue;
if ((morph_traits & CopyPixelTrait) != 0)
{
SetPixelChannel(morph_image,channel,p[i],q);
continue;
}
SetPixelChannel(morph_image,channel,ClampToQuantum(alpha*
GetPixelChannel(morph_images,channel,q)+beta*p[i]),q);
}
p+=GetPixelChannels(morph_image);
q+=GetPixelChannels(morph_images);
}
sync=SyncCacheViewAuthenticPixels(morph_view,exception);
if (sync == MagickFalse)
status=MagickFalse;
}
morph_view=DestroyCacheView(morph_view);
image_view=DestroyCacheView(image_view);
morph_image=DestroyImage(morph_image);
}
if (n < (ssize_t) number_frames)
break;
/*
Clone last frame in sequence.
*/
morph_image=CloneImage(GetNextImageInList(next),0,0,MagickTrue,exception);
if (morph_image == (Image *) NULL)
{
morph_images=DestroyImageList(morph_images);
return((Image *) NULL);
}
AppendImageToList(&morph_images,morph_image);
morph_images=GetLastImageInList(morph_images);
if (image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
proceed=SetImageProgress(image,MorphImageTag,scene,
GetImageListLength(image));
if (proceed == MagickFalse)
status=MagickFalse;
}
scene++;
}
if (GetNextImageInList(next) != (Image *) NULL)
{
morph_images=DestroyImageList(morph_images);
return((Image *) NULL);
}
return(GetFirstImageInList(morph_images));
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% P l a s m a I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% PlasmaImage() initializes an image with plasma fractal values. The image
% must be initialized with a base color and the random number generator
% seeded before this method is called.
%
% The format of the PlasmaImage method is:
%
% MagickBooleanType PlasmaImage(Image *image,const SegmentInfo *segment,
% size_t attenuate,size_t depth,ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o segment: Define the region to apply plasma fractals values.
%
% o attenuate: Define the plasma attenuation factor.
%
% o depth: Limit the plasma recursion depth.
%
% o exception: return any errors or warnings in this structure.
%
*/
static inline Quantum PlasmaPixel(RandomInfo *magick_restrict random_info,
const double pixel,const double noise)
{
MagickRealType
plasma;
plasma=pixel+noise*GetPseudoRandomValue(random_info)-noise/2.0;
return(ClampToQuantum(plasma));
}
static MagickBooleanType PlasmaImageProxy(Image *image,CacheView *image_view,
CacheView *u_view,CacheView *v_view,RandomInfo *magick_restrict random_info,
const SegmentInfo *magick_restrict segment,size_t attenuate,size_t depth,
ExceptionInfo *exception)
{
double
plasma;
MagickStatusType
status;
const Quantum
*magick_restrict u,
*magick_restrict v;
Quantum
*magick_restrict q;
ssize_t
i;
ssize_t
x,
x_mid,
y,
y_mid;
if ((fabs(segment->x2-segment->x1) < MagickEpsilon) &&
(fabs(segment->y2-segment->y1) < MagickEpsilon))
return(MagickTrue);
if (depth != 0)
{
SegmentInfo
local_info;
/*
Divide the area into quadrants and recurse.
*/
depth--;
attenuate++;
x_mid=CastDoubleToLong(ceil((segment->x1+segment->x2)/2-0.5));
y_mid=CastDoubleToLong(ceil((segment->y1+segment->y2)/2-0.5));
local_info=(*segment);
local_info.x2=(double) x_mid;
local_info.y2=(double) y_mid;
status=PlasmaImageProxy(image,image_view,u_view,v_view,random_info,
&local_info,attenuate,depth,exception);
local_info=(*segment);
local_info.y1=(double) y_mid;
local_info.x2=(double) x_mid;
status&=PlasmaImageProxy(image,image_view,u_view,v_view,random_info,
&local_info,attenuate,depth,exception);
local_info=(*segment);
local_info.x1=(double) x_mid;
local_info.y2=(double) y_mid;
status&=PlasmaImageProxy(image,image_view,u_view,v_view,random_info,
&local_info,attenuate,depth,exception);
local_info=(*segment);
local_info.x1=(double) x_mid;
local_info.y1=(double) y_mid;
status&=PlasmaImageProxy(image,image_view,u_view,v_view,random_info,
&local_info,attenuate,depth,exception);
return(status == 0 ? MagickFalse : MagickTrue);
}
x_mid=CastDoubleToLong(ceil((segment->x1+segment->x2)/2-0.5));
y_mid=CastDoubleToLong(ceil((segment->y1+segment->y2)/2-0.5));
if ((fabs(segment->x1-x_mid) < MagickEpsilon) &&
(fabs(segment->x2-x_mid) < MagickEpsilon) &&
(fabs(segment->y1-y_mid) < MagickEpsilon) &&
(fabs(segment->y2-y_mid) < MagickEpsilon))
return(MagickFalse);
/*
Average pixels and apply plasma.
*/
status=MagickTrue;
plasma=(double) QuantumRange/(2.0*attenuate);
if ((fabs(segment->x1-x_mid) >= MagickEpsilon) ||
(fabs(segment->x2-x_mid) >= MagickEpsilon))
{
/*
Left pixel.
*/
x=CastDoubleToLong(ceil(segment->x1-0.5));
u=GetCacheViewVirtualPixels(u_view,x,CastDoubleToLong(ceil(
segment->y1-0.5)),1,1,exception);
v=GetCacheViewVirtualPixels(v_view,x,CastDoubleToLong(ceil(
segment->y2-0.5)),1,1,exception);
q=QueueCacheViewAuthenticPixels(image_view,x,y_mid,1,1,exception);
if ((u == (const Quantum *) NULL) || (v == (const Quantum *) NULL) ||
(q == (Quantum *) NULL))
return(MagickTrue);
for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
{
PixelChannel channel = GetPixelChannelChannel(image,i);
PixelTrait traits = GetPixelChannelTraits(image,channel);
if (traits == UndefinedPixelTrait)
continue;
q[i]=PlasmaPixel(random_info,((double) u[i]+v[i])/2.0,plasma);
}
status=SyncCacheViewAuthenticPixels(image_view,exception);
if (fabs(segment->x1-segment->x2) >= MagickEpsilon)
{
/*
Right pixel.
*/
x=CastDoubleToLong(ceil(segment->x2-0.5));
u=GetCacheViewVirtualPixels(u_view,x,CastDoubleToLong(ceil(
segment->y1-0.5)),1,1,exception);
v=GetCacheViewVirtualPixels(v_view,x,CastDoubleToLong(ceil(
segment->y2-0.5)),1,1,exception);
q=QueueCacheViewAuthenticPixels(image_view,x,y_mid,1,1,exception);
if ((u == (const Quantum *) NULL) || (v == (const Quantum *) NULL) ||
(q == (Quantum *) NULL))
return(MagickFalse);
for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
{
PixelChannel channel = GetPixelChannelChannel(image,i);
PixelTrait traits = GetPixelChannelTraits(image,channel);
if (traits == UndefinedPixelTrait)
continue;
q[i]=PlasmaPixel(random_info,((double) u[i]+v[i])/2.0,plasma);
}
status=SyncCacheViewAuthenticPixels(image_view,exception);
}
}
if ((fabs(segment->y1-y_mid) >= MagickEpsilon) ||
(fabs(segment->y2-y_mid) >= MagickEpsilon))
{
if ((fabs(segment->x1-x_mid) >= MagickEpsilon) ||
(fabs(segment->y2-y_mid) >= MagickEpsilon))
{
/*
Bottom pixel.
*/
y=CastDoubleToLong(ceil(segment->y2-0.5));
u=GetCacheViewVirtualPixels(u_view,CastDoubleToLong(ceil(
segment->x1-0.5)),y,1,1,exception);
v=GetCacheViewVirtualPixels(v_view,CastDoubleToLong(ceil(
segment->x2-0.5)),y,1,1,exception);
q=QueueCacheViewAuthenticPixels(image_view,x_mid,y,1,1,exception);
if ((u == (const Quantum *) NULL) || (v == (const Quantum *) NULL) ||
(q == (Quantum *) NULL))
return(MagickTrue);
for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
{
PixelChannel channel = GetPixelChannelChannel(image,i);
PixelTrait traits = GetPixelChannelTraits(image,channel);
if (traits == UndefinedPixelTrait)
continue;
q[i]=PlasmaPixel(random_info,((double) u[i]+v[i])/2.0,plasma);
}
status=SyncCacheViewAuthenticPixels(image_view,exception);
}
if (fabs(segment->y1-segment->y2) >= MagickEpsilon)
{
/*
Top pixel.
*/
y=CastDoubleToLong(ceil(segment->y1-0.5));
u=GetCacheViewVirtualPixels(u_view,CastDoubleToLong(ceil(
segment->x1-0.5)),y,1,1,exception);
v=GetCacheViewVirtualPixels(v_view,CastDoubleToLong(ceil(
segment->x2-0.5)),y,1,1,exception);
q=QueueCacheViewAuthenticPixels(image_view,x_mid,y,1,1,exception);
if ((u == (const Quantum *) NULL) || (v == (const Quantum *) NULL) ||
(q == (Quantum *) NULL))
return(MagickTrue);
for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
{
PixelChannel channel = GetPixelChannelChannel(image,i);
PixelTrait traits = GetPixelChannelTraits(image,channel);
if (traits == UndefinedPixelTrait)
continue;
q[i]=PlasmaPixel(random_info,((double) u[i]+v[i])/2.0,plasma);
}
status=SyncCacheViewAuthenticPixels(image_view,exception);
}
}
if ((fabs(segment->x1-segment->x2) >= MagickEpsilon) ||
(fabs(segment->y1-segment->y2) >= MagickEpsilon))
{
/*
Middle pixel.
*/
x=CastDoubleToLong(ceil(segment->x1-0.5));
y=CastDoubleToLong(ceil(segment->y1-0.5));
u=GetCacheViewVirtualPixels(u_view,x,y,1,1,exception);
x=CastDoubleToLong(ceil(segment->x2-0.5));
y=CastDoubleToLong(ceil(segment->y2-0.5));
v=GetCacheViewVirtualPixels(v_view,x,y,1,1,exception);
q=QueueCacheViewAuthenticPixels(image_view,x_mid,y_mid,1,1,exception);
if ((u == (const Quantum *) NULL) || (v == (const Quantum *) NULL) ||
(q == (Quantum *) NULL))
return(MagickTrue);
for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
{
PixelChannel channel = GetPixelChannelChannel(image,i);
PixelTrait traits = GetPixelChannelTraits(image,channel);
if (traits == UndefinedPixelTrait)
continue;
q[i]=PlasmaPixel(random_info,((double) u[i]+v[i])/2.0,plasma);
}
status=SyncCacheViewAuthenticPixels(image_view,exception);
}
if ((fabs(segment->x2-segment->x1) < 3.0) &&
(fabs(segment->y2-segment->y1) < 3.0))
return(status == 0 ? MagickFalse : MagickTrue);
return(MagickFalse);
}
MagickExport MagickBooleanType PlasmaImage(Image *image,
const SegmentInfo *segment,size_t attenuate,size_t depth,
ExceptionInfo *exception)
{
CacheView
*image_view,
*u_view,
*v_view;
MagickBooleanType
status;
RandomInfo
*random_info;
assert(image != (Image *) NULL);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"...");
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"...");
if (SetImageStorageClass(image,DirectClass,exception) == MagickFalse)
return(MagickFalse);
image_view=AcquireAuthenticCacheView(image,exception);
u_view=AcquireVirtualCacheView(image,exception);
v_view=AcquireVirtualCacheView(image,exception);
random_info=AcquireRandomInfo();
status=PlasmaImageProxy(image,image_view,u_view,v_view,random_info,segment,
attenuate,depth,exception);
random_info=DestroyRandomInfo(random_info);
v_view=DestroyCacheView(v_view);
u_view=DestroyCacheView(u_view);
image_view=DestroyCacheView(image_view);
return(status);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% P o l a r o i d I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% PolaroidImage() simulates a Polaroid picture.
%
% The format of the PolaroidImage method is:
%
% Image *PolaroidImage(const Image *image,const DrawInfo *draw_info,
% const char *caption,const double angle,
% const PixelInterpolateMethod method,ExceptionInfo exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o draw_info: the draw info.
%
% o caption: the Polaroid caption.
%
% o angle: Apply the effect along this angle.
%
% o method: the pixel interpolation method.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport Image *PolaroidImage(const Image *image,const DrawInfo *draw_info,
const char *caption,const double angle,const PixelInterpolateMethod method,
ExceptionInfo *exception)
{
Image
*bend_image,
*caption_image,
*flop_image,
*picture_image,
*polaroid_image,
*rotate_image,
*trim_image;
size_t
height;
ssize_t
quantum;
/*
Simulate a Polaroid picture.
*/
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
quantum=(ssize_t) MagickMax(MagickMax((double) image->columns,(double)
image->rows)/25.0,10.0);
height=image->rows+2*quantum;
caption_image=(Image *) NULL;
if (caption != (const char *) NULL)
{
char
*text;
/*
Generate caption image.
*/
caption_image=CloneImage(image,image->columns,1,MagickTrue,exception);
if (caption_image == (Image *) NULL)
return((Image *) NULL);
text=InterpretImageProperties((ImageInfo *) NULL,(Image *) image,caption,
exception);
if (text != (char *) NULL)
{
char
geometry[MagickPathExtent];
DrawInfo
*annotate_info;
MagickBooleanType
status;
ssize_t
count;
TypeMetric
metrics;
annotate_info=CloneDrawInfo((const ImageInfo *) NULL,draw_info);
(void) CloneString(&annotate_info->text,text);
count=FormatMagickCaption(caption_image,annotate_info,MagickTrue,
&metrics,&text,exception);
status=SetImageExtent(caption_image,image->columns,(size_t)
((count+1)*(metrics.ascent-metrics.descent)+0.5),exception);
if (status == MagickFalse)
caption_image=DestroyImage(caption_image);
else
{
caption_image->background_color=image->border_color;
(void) SetImageBackgroundColor(caption_image,exception);
(void) CloneString(&annotate_info->text,text);
(void) FormatLocaleString(geometry,MagickPathExtent,"+0+%.20g",
metrics.ascent);
if (annotate_info->gravity == UndefinedGravity)
(void) CloneString(&annotate_info->geometry,AcquireString(
geometry));
(void) AnnotateImage(caption_image,annotate_info,exception);
height+=caption_image->rows;
}
annotate_info=DestroyDrawInfo(annotate_info);
text=DestroyString(text);
}
}
picture_image=CloneImage(image,image->columns+2*quantum,height,MagickTrue,
exception);
if (picture_image == (Image *) NULL)
{
if (caption_image != (Image *) NULL)
caption_image=DestroyImage(caption_image);
return((Image *) NULL);
}
picture_image->background_color=image->border_color;
(void) SetImageBackgroundColor(picture_image,exception);
(void) CompositeImage(picture_image,image,OverCompositeOp,MagickTrue,quantum,
quantum,exception);
if (caption_image != (Image *) NULL)
{
(void) CompositeImage(picture_image,caption_image,OverCompositeOp,
MagickTrue,quantum,(ssize_t) (image->rows+3*quantum/2),exception);
caption_image=DestroyImage(caption_image);
}
(void) QueryColorCompliance("none",AllCompliance,
&picture_image->background_color,exception);
(void) SetImageAlphaChannel(picture_image,OpaqueAlphaChannel,exception);
rotate_image=RotateImage(picture_image,90.0,exception);
picture_image=DestroyImage(picture_image);
if (rotate_image == (Image *) NULL)
return((Image *) NULL);
picture_image=rotate_image;
bend_image=WaveImage(picture_image,0.01*picture_image->rows,2.0*
picture_image->columns,method,exception);
picture_image=DestroyImage(picture_image);
if (bend_image == (Image *) NULL)
return((Image *) NULL);
picture_image=bend_image;
rotate_image=RotateImage(picture_image,-90.0,exception);
picture_image=DestroyImage(picture_image);
if (rotate_image == (Image *) NULL)
return((Image *) NULL);
picture_image=rotate_image;
picture_image->background_color=image->background_color;
polaroid_image=ShadowImage(picture_image,80.0,2.0,quantum/3,quantum/3,
exception);
if (polaroid_image == (Image *) NULL)
{
picture_image=DestroyImage(picture_image);
return(picture_image);
}
flop_image=FlopImage(polaroid_image,exception);
polaroid_image=DestroyImage(polaroid_image);
if (flop_image == (Image *) NULL)
{
picture_image=DestroyImage(picture_image);
return(picture_image);
}
polaroid_image=flop_image;
(void) CompositeImage(polaroid_image,picture_image,OverCompositeOp,
MagickTrue,(ssize_t) (-0.01*picture_image->columns/2.0),0L,exception);
picture_image=DestroyImage(picture_image);
(void) QueryColorCompliance("none",AllCompliance,
&polaroid_image->background_color,exception);
rotate_image=RotateImage(polaroid_image,angle,exception);
polaroid_image=DestroyImage(polaroid_image);
if (rotate_image == (Image *) NULL)
return((Image *) NULL);
polaroid_image=rotate_image;
trim_image=TrimImage(polaroid_image,exception);
polaroid_image=DestroyImage(polaroid_image);
if (trim_image == (Image *) NULL)
return((Image *) NULL);
polaroid_image=trim_image;
return(polaroid_image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% S e p i a T o n e I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% MagickSepiaToneImage() applies a special effect to the image, similar to the
% effect achieved in a photo darkroom by sepia toning. Threshold ranges from
% 0 to QuantumRange and is a measure of the extent of the sepia toning. A
% threshold of 80% is a good starting point for a reasonable tone.
%
% The format of the SepiaToneImage method is:
%
% Image *SepiaToneImage(const Image *image,const double threshold,
% ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o threshold: the tone threshold.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport Image *SepiaToneImage(const Image *image,const double threshold,
ExceptionInfo *exception)
{
#define SepiaToneImageTag "SepiaTone/Image"
CacheView
*image_view,
*sepia_view;
Image
*sepia_image;
MagickBooleanType
status;
MagickOffsetType
progress;
ssize_t
y;
/*
Initialize sepia-toned image attributes.
*/
assert(image != (const Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
sepia_image=CloneImage(image,0,0,MagickTrue,exception);
if (sepia_image == (Image *) NULL)
return((Image *) NULL);
if (SetImageStorageClass(sepia_image,DirectClass,exception) == MagickFalse)
{
sepia_image=DestroyImage(sepia_image);
return((Image *) NULL);
}
/*
Tone each row of the image.
*/
status=MagickTrue;
progress=0;
image_view=AcquireVirtualCacheView(image,exception);
sepia_view=AcquireAuthenticCacheView(sepia_image,exception);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static) shared(progress,status) \
magick_number_threads(image,sepia_image,image->rows,1)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
const Quantum
*magick_restrict p;
ssize_t
x;
Quantum
*magick_restrict q;
if (status == MagickFalse)
continue;
p=GetCacheViewVirtualPixels(image_view,0,y,image->columns,1,exception);
q=GetCacheViewAuthenticPixels(sepia_view,0,y,sepia_image->columns,1,
exception);
if ((p == (const Quantum *) NULL) || (q == (Quantum *) NULL))
{
status=MagickFalse;
continue;
}
for (x=0; x < (ssize_t) image->columns; x++)
{
double
intensity,
tone;
intensity=GetPixelIntensity(image,p);
tone=intensity > threshold ? (double) QuantumRange : intensity+
(double) QuantumRange-threshold;
SetPixelRed(sepia_image,ClampToQuantum(tone),q);
tone=intensity > (7.0*threshold/6.0) ? (double) QuantumRange :
intensity+(double) QuantumRange-7.0*threshold/6.0;
SetPixelGreen(sepia_image,ClampToQuantum(tone),q);
tone=intensity < (threshold/6.0) ? 0 : intensity-threshold/6.0;
SetPixelBlue(sepia_image,ClampToQuantum(tone),q);
tone=threshold/7.0;
if ((double) GetPixelGreen(image,q) < tone)
SetPixelGreen(sepia_image,ClampToQuantum(tone),q);
if ((double) GetPixelBlue(image,q) < tone)
SetPixelBlue(sepia_image,ClampToQuantum(tone),q);
SetPixelAlpha(sepia_image,GetPixelAlpha(image,p),q);
p+=GetPixelChannels(image);
q+=GetPixelChannels(sepia_image);
}
if (SyncCacheViewAuthenticPixels(sepia_view,exception) == MagickFalse)
status=MagickFalse;
if (image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp atomic
#endif
progress++;
proceed=SetImageProgress(image,SepiaToneImageTag,progress,image->rows);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
sepia_view=DestroyCacheView(sepia_view);
image_view=DestroyCacheView(image_view);
(void) NormalizeImage(sepia_image,exception);
(void) ContrastImage(sepia_image,MagickTrue,exception);
if (status == MagickFalse)
sepia_image=DestroyImage(sepia_image);
return(sepia_image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% S h a d o w I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% ShadowImage() simulates a shadow from the specified image and returns it.
%
% The format of the ShadowImage method is:
%
% Image *ShadowImage(const Image *image,const double alpha,
% const double sigma,const ssize_t x_offset,const ssize_t y_offset,
% ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o alpha: percentage transparency.
%
% o sigma: the standard deviation of the Gaussian, in pixels.
%
% o x_offset: the shadow x-offset.
%
% o y_offset: the shadow y-offset.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport Image *ShadowImage(const Image *image,const double alpha,
const double sigma,const ssize_t x_offset,const ssize_t y_offset,
ExceptionInfo *exception)
{
#define ShadowImageTag "Shadow/Image"
CacheView
*image_view;
ChannelType
channel_mask;
Image
*border_image,
*clone_image,
*shadow_image;
MagickBooleanType
status;
PixelInfo
background_color;
RectangleInfo
border_info;
ssize_t
y;
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
clone_image=CloneImage(image,0,0,MagickTrue,exception);
if (clone_image == (Image *) NULL)
return((Image *) NULL);
if (IsGrayColorspace(image->colorspace) != MagickFalse)
(void) SetImageColorspace(clone_image,sRGBColorspace,exception);
(void) SetImageVirtualPixelMethod(clone_image,EdgeVirtualPixelMethod,
exception);
border_info.width=(size_t) floor(2.0*sigma+0.5);
border_info.height=(size_t) floor(2.0*sigma+0.5);
border_info.x=0;
border_info.y=0;
(void) QueryColorCompliance("none",AllCompliance,&clone_image->border_color,
exception);
clone_image->alpha_trait=BlendPixelTrait;
border_image=BorderImage(clone_image,&border_info,OverCompositeOp,exception);
clone_image=DestroyImage(clone_image);
if (border_image == (Image *) NULL)
return((Image *) NULL);
if (border_image->alpha_trait == UndefinedPixelTrait)
(void) SetImageAlphaChannel(border_image,OpaqueAlphaChannel,exception);
/*
Shadow image.
*/
status=MagickTrue;
background_color=border_image->background_color;
background_color.alpha_trait=BlendPixelTrait;
image_view=AcquireAuthenticCacheView(border_image,exception);
for (y=0; y < (ssize_t) border_image->rows; y++)
{
Quantum
*magick_restrict q;
ssize_t
x;
if (status == MagickFalse)
continue;
q=QueueCacheViewAuthenticPixels(image_view,0,y,border_image->columns,1,
exception);
if (q == (Quantum *) NULL)
{
status=MagickFalse;
continue;
}
for (x=0; x < (ssize_t) border_image->columns; x++)
{
if (border_image->alpha_trait != UndefinedPixelTrait)
background_color.alpha=GetPixelAlpha(border_image,q)*alpha/100.0;
SetPixelViaPixelInfo(border_image,&background_color,q);
q+=GetPixelChannels(border_image);
}
if (SyncCacheViewAuthenticPixels(image_view,exception) == MagickFalse)
status=MagickFalse;
}
image_view=DestroyCacheView(image_view);
if (status == MagickFalse)
{
border_image=DestroyImage(border_image);
return((Image *) NULL);
}
channel_mask=SetImageChannelMask(border_image,AlphaChannel);
shadow_image=BlurImage(border_image,0.0,sigma,exception);
border_image=DestroyImage(border_image);
if (shadow_image == (Image *) NULL)
return((Image *) NULL);
(void) SetPixelChannelMask(shadow_image,channel_mask);
if (shadow_image->page.width == 0)
shadow_image->page.width=shadow_image->columns;
if (shadow_image->page.height == 0)
shadow_image->page.height=shadow_image->rows;
shadow_image->page.width+=x_offset-(ssize_t) border_info.width;
shadow_image->page.height+=y_offset-(ssize_t) border_info.height;
shadow_image->page.x+=x_offset-(ssize_t) border_info.width;
shadow_image->page.y+=y_offset-(ssize_t) border_info.height;
return(shadow_image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% S k e t c h I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% SketchImage() simulates a pencil sketch. We convolve the image with a
% Gaussian operator of the given radius and standard deviation (sigma). For
% reasonable results, radius should be larger than sigma. Use a radius of 0
% and SketchImage() selects a suitable radius for you. Angle gives the angle
% of the sketch.
%
% The format of the SketchImage method is:
%
% Image *SketchImage(const Image *image,const double radius,
% const double sigma,const double angle,ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o radius: the radius of the Gaussian, in pixels, not counting the
% center pixel.
%
% o sigma: the standard deviation of the Gaussian, in pixels.
%
% o angle: apply the effect along this angle.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport Image *SketchImage(const Image *image,const double radius,
const double sigma,const double angle,ExceptionInfo *exception)
{
CacheView
*random_view;
Image
*blend_image,
*blur_image,
*dodge_image,
*random_image,
*sketch_image;
MagickBooleanType
status;
RandomInfo
**magick_restrict random_info;
ssize_t
y;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
unsigned long
key;
#endif
/*
Sketch image.
*/
random_image=CloneImage(image,image->columns << 1,image->rows << 1,
MagickTrue,exception);
if (random_image == (Image *) NULL)
return((Image *) NULL);
status=MagickTrue;
random_info=AcquireRandomInfoTLS();
random_view=AcquireAuthenticCacheView(random_image,exception);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
key=GetRandomSecretKey(random_info[0]);
#pragma omp parallel for schedule(static) shared(status) \
magick_number_threads(random_image,random_image,random_image->rows,key == ~0UL)
#endif
for (y=0; y < (ssize_t) random_image->rows; y++)
{
const int
id = GetOpenMPThreadId();
Quantum
*magick_restrict q;
ssize_t
x;
if (status == MagickFalse)
continue;
q=QueueCacheViewAuthenticPixels(random_view,0,y,random_image->columns,1,
exception);
if (q == (Quantum *) NULL)
{
status=MagickFalse;
continue;
}
for (x=0; x < (ssize_t) random_image->columns; x++)
{
double
value;
ssize_t
i;
value=GetPseudoRandomValue(random_info[id]);
for (i=0; i < (ssize_t) GetPixelChannels(random_image); i++)
{
PixelChannel channel = GetPixelChannelChannel(image,i);
PixelTrait traits = GetPixelChannelTraits(image,channel);
if (traits == UndefinedPixelTrait)
continue;
q[i]=ClampToQuantum(QuantumRange*value);
}
q+=GetPixelChannels(random_image);
}
if (SyncCacheViewAuthenticPixels(random_view,exception) == MagickFalse)
status=MagickFalse;
}
random_view=DestroyCacheView(random_view);
random_info=DestroyRandomInfoTLS(random_info);
if (status == MagickFalse)
{
random_image=DestroyImage(random_image);
return(random_image);
}
blur_image=MotionBlurImage(random_image,radius,sigma,angle,exception);
random_image=DestroyImage(random_image);
if (blur_image == (Image *) NULL)
return((Image *) NULL);
dodge_image=EdgeImage(blur_image,radius,exception);
blur_image=DestroyImage(blur_image);
if (dodge_image == (Image *) NULL)
return((Image *) NULL);
status=ClampImage(dodge_image,exception);
if (status != MagickFalse)
status=NormalizeImage(dodge_image,exception);
if (status != MagickFalse)
status=NegateImage(dodge_image,MagickFalse,exception);
if (status != MagickFalse)
status=TransformImage(&dodge_image,(char *) NULL,"50%",exception);
sketch_image=CloneImage(image,0,0,MagickTrue,exception);
if (sketch_image == (Image *) NULL)
{
dodge_image=DestroyImage(dodge_image);
return((Image *) NULL);
}
(void) CompositeImage(sketch_image,dodge_image,ColorDodgeCompositeOp,
MagickTrue,0,0,exception);
dodge_image=DestroyImage(dodge_image);
blend_image=CloneImage(image,0,0,MagickTrue,exception);
if (blend_image == (Image *) NULL)
{
sketch_image=DestroyImage(sketch_image);
return((Image *) NULL);
}
if (blend_image->alpha_trait != BlendPixelTrait)
(void) SetImageAlpha(blend_image,TransparentAlpha,exception);
(void) SetImageArtifact(blend_image,"compose:args","20x80");
(void) CompositeImage(sketch_image,blend_image,BlendCompositeOp,MagickTrue,
0,0,exception);
blend_image=DestroyImage(blend_image);
return(sketch_image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% S o l a r i z e I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% SolarizeImage() applies a special effect to the image, similar to the effect
% achieved in a photo darkroom by selectively exposing areas of photo
% sensitive paper to light. Threshold ranges from 0 to QuantumRange and is a
% measure of the extent of the solarization.
%
% The format of the SolarizeImage method is:
%
% MagickBooleanType SolarizeImage(Image *image,const double threshold,
% ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o threshold: Define the extent of the solarization.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport MagickBooleanType SolarizeImage(Image *image,
const double threshold,ExceptionInfo *exception)
{
#define SolarizeImageTag "Solarize/Image"
CacheView
*image_view;
MagickBooleanType
status;
MagickOffsetType
progress;
ssize_t
y;
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
if (IsGrayColorspace(image->colorspace) != MagickFalse)
(void) SetImageColorspace(image,sRGBColorspace,exception);
if (image->storage_class == PseudoClass)
{
ssize_t
i;
/*
Solarize colormap.
*/
for (i=0; i < (ssize_t) image->colors; i++)
{
if ((double) image->colormap[i].red > threshold)
image->colormap[i].red=QuantumRange-image->colormap[i].red;
if ((double) image->colormap[i].green > threshold)
image->colormap[i].green=QuantumRange-image->colormap[i].green;
if ((double) image->colormap[i].blue > threshold)
image->colormap[i].blue=QuantumRange-image->colormap[i].blue;
}
return(SyncImage(image,exception));
}
/*
Solarize image.
*/
status=MagickTrue;
progress=0;
image_view=AcquireAuthenticCacheView(image,exception);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static) shared(progress,status) \
magick_number_threads(image,image,image->rows,1)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
ssize_t
x;
Quantum
*magick_restrict q;
if (status == MagickFalse)
continue;
q=GetCacheViewAuthenticPixels(image_view,0,y,image->columns,1,exception);
if (q == (Quantum *) NULL)
{
status=MagickFalse;
continue;
}
for (x=0; x < (ssize_t) image->columns; x++)
{
ssize_t
i;
for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
{
PixelChannel channel = GetPixelChannelChannel(image,i);
PixelTrait traits = GetPixelChannelTraits(image,channel);
if ((traits & UpdatePixelTrait) == 0)
continue;
if ((double) q[i] > threshold)
q[i]=QuantumRange-q[i];
}
q+=GetPixelChannels(image);
}
if (SyncCacheViewAuthenticPixels(image_view,exception) == MagickFalse)
status=MagickFalse;
if (image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp atomic
#endif
progress++;
proceed=SetImageProgress(image,SolarizeImageTag,progress,image->rows);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
image_view=DestroyCacheView(image_view);
return(status);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% S t e g a n o I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% SteganoImage() hides a digital watermark within the image. Recover
% the hidden watermark later to prove that the authenticity of an image.
% Offset defines the start position within the image to hide the watermark.
%
% The format of the SteganoImage method is:
%
% Image *SteganoImage(const Image *image,Image *watermark,
% ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o watermark: the watermark image.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport Image *SteganoImage(const Image *image,const Image *watermark,
ExceptionInfo *exception)
{
#define GetBit(alpha,i) ((((size_t) (alpha) >> (size_t) (i)) & 0x01) != 0)
#define SetBit(alpha,i,set) (Quantum) ((set) != 0 ? (size_t) (alpha) \
| (one << (size_t) (i)) : (size_t) (alpha) & ~(one << (size_t) (i)))
#define SteganoImageTag "Stegano/Image"
CacheView
*stegano_view,
*watermark_view;
Image
*stegano_image;
int
c;
MagickBooleanType
status;
PixelInfo
pixel;
Quantum
*q;
ssize_t
x;
size_t
depth,
one;
ssize_t
i,
j,
k,
y;
/*
Initialize steganographic image attributes.
*/
assert(image != (const Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(watermark != (const Image *) NULL);
assert(watermark->signature == MagickCoreSignature);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
one=1UL;
stegano_image=CloneImage(image,0,0,MagickTrue,exception);
if (stegano_image == (Image *) NULL)
return((Image *) NULL);
stegano_image->depth=MAGICKCORE_QUANTUM_DEPTH;
if (SetImageStorageClass(stegano_image,DirectClass,exception) == MagickFalse)
{
stegano_image=DestroyImage(stegano_image);
return((Image *) NULL);
}
/*
Hide watermark in low-order bits of image.
*/
c=0;
i=0;
j=0;
depth=stegano_image->depth;
k=stegano_image->offset;
status=MagickTrue;
watermark_view=AcquireVirtualCacheView(watermark,exception);
stegano_view=AcquireAuthenticCacheView(stegano_image,exception);
for (i=(ssize_t) depth-1; (i >= 0) && (j < (ssize_t) depth); i--)
{
for (y=0; (y < (ssize_t) watermark->rows) && (j < (ssize_t) depth); y++)
{
for (x=0; (x < (ssize_t) watermark->columns) && (j < (ssize_t) depth); x++)
{
ssize_t
offset;
(void) GetOneCacheViewVirtualPixelInfo(watermark_view,x,y,&pixel,
exception);
offset=k/(ssize_t) stegano_image->columns;
if (offset >= (ssize_t) stegano_image->rows)
break;
q=GetCacheViewAuthenticPixels(stegano_view,k % (ssize_t)
stegano_image->columns,k/(ssize_t) stegano_image->columns,1,1,
exception);
if (q == (Quantum *) NULL)
break;
switch (c)
{
case 0:
{
SetPixelRed(stegano_image,SetBit(GetPixelRed(stegano_image,q),j,
GetBit(GetPixelInfoIntensity(stegano_image,&pixel),i)),q);
break;
}
case 1:
{
SetPixelGreen(stegano_image,SetBit(GetPixelGreen(stegano_image,q),j,
GetBit(GetPixelInfoIntensity(stegano_image,&pixel),i)),q);
break;
}
case 2:
{
SetPixelBlue(stegano_image,SetBit(GetPixelBlue(stegano_image,q),j,
GetBit(GetPixelInfoIntensity(stegano_image,&pixel),i)),q);
break;
}
}
if (SyncCacheViewAuthenticPixels(stegano_view,exception) == MagickFalse)
break;
c++;
if (c == 3)
c=0;
k++;
if (k == (ssize_t) (stegano_image->columns*stegano_image->columns))
k=0;
if (k == stegano_image->offset)
j++;
}
}
if (image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
proceed=SetImageProgress(image,SteganoImageTag,(MagickOffsetType)
(depth-i),depth);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
stegano_view=DestroyCacheView(stegano_view);
watermark_view=DestroyCacheView(watermark_view);
if (status == MagickFalse)
stegano_image=DestroyImage(stegano_image);
return(stegano_image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% S t e r e o A n a g l y p h I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% StereoAnaglyphImage() combines two images and produces a single image that
% is the composite of a left and right image of a stereo pair. Special
% red-green stereo glasses are required to view this effect.
%
% The format of the StereoAnaglyphImage method is:
%
% Image *StereoImage(const Image *left_image,const Image *right_image,
% ExceptionInfo *exception)
% Image *StereoAnaglyphImage(const Image *left_image,
% const Image *right_image,const ssize_t x_offset,const ssize_t y_offset,
% ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o left_image: the left image.
%
% o right_image: the right image.
%
% o exception: return any errors or warnings in this structure.
%
% o x_offset: amount, in pixels, by which the left image is offset to the
% right of the right image.
%
% o y_offset: amount, in pixels, by which the left image is offset to the
% bottom of the right image.
%
%
*/
MagickExport Image *StereoImage(const Image *left_image,
const Image *right_image,ExceptionInfo *exception)
{
return(StereoAnaglyphImage(left_image,right_image,0,0,exception));
}
MagickExport Image *StereoAnaglyphImage(const Image *left_image,
const Image *right_image,const ssize_t x_offset,const ssize_t y_offset,
ExceptionInfo *exception)
{
#define StereoImageTag "Stereo/Image"
const Image
*image;
Image
*stereo_image;
MagickBooleanType
status;
ssize_t
y;
assert(left_image != (const Image *) NULL);
assert(left_image->signature == MagickCoreSignature);
if (left_image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",
left_image->filename);
assert(right_image != (const Image *) NULL);
assert(right_image->signature == MagickCoreSignature);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
image=left_image;
if ((left_image->columns != right_image->columns) ||
(left_image->rows != right_image->rows))
ThrowImageException(ImageError,"LeftAndRightImageSizesDiffer");
/*
Initialize stereo image attributes.
*/
stereo_image=CloneImage(left_image,left_image->columns,left_image->rows,
MagickTrue,exception);
if (stereo_image == (Image *) NULL)
return((Image *) NULL);
if (SetImageStorageClass(stereo_image,DirectClass,exception) == MagickFalse)
{
stereo_image=DestroyImage(stereo_image);
return((Image *) NULL);
}
(void) SetImageColorspace(stereo_image,sRGBColorspace,exception);
/*
Copy left image to red channel and right image to blue channel.
*/
status=MagickTrue;
for (y=0; y < (ssize_t) stereo_image->rows; y++)
{
const Quantum
*magick_restrict p,
*magick_restrict q;
ssize_t
x;
Quantum
*magick_restrict r;
p=GetVirtualPixels(left_image,-x_offset,y-y_offset,image->columns,1,
exception);
q=GetVirtualPixels(right_image,0,y,right_image->columns,1,exception);
r=QueueAuthenticPixels(stereo_image,0,y,stereo_image->columns,1,exception);
if ((p == (const Quantum *) NULL) || (q == (Quantum *) NULL) ||
(r == (Quantum *) NULL))
break;
for (x=0; x < (ssize_t) stereo_image->columns; x++)
{
SetPixelRed(stereo_image,GetPixelRed(left_image,p),r);
SetPixelGreen(stereo_image,GetPixelGreen(right_image,q),r);
SetPixelBlue(stereo_image,GetPixelBlue(right_image,q),r);
if ((GetPixelAlphaTraits(stereo_image) & CopyPixelTrait) != 0)
SetPixelAlpha(stereo_image,(GetPixelAlpha(left_image,p)+
GetPixelAlpha(right_image,q))/2,r);
p+=GetPixelChannels(left_image);
q+=GetPixelChannels(right_image);
r+=GetPixelChannels(stereo_image);
}
if (SyncAuthenticPixels(stereo_image,exception) == MagickFalse)
break;
if (image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
proceed=SetImageProgress(image,StereoImageTag,(MagickOffsetType) y,
stereo_image->rows);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
if (status == MagickFalse)
stereo_image=DestroyImage(stereo_image);
return(stereo_image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% S w i r l I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% SwirlImage() swirls the pixels about the center of the image, where
% degrees indicates the sweep of the arc through which each pixel is moved.
% You get a more dramatic effect as the degrees move from 1 to 360.
%
% The format of the SwirlImage method is:
%
% Image *SwirlImage(const Image *image,double degrees,
% const PixelInterpolateMethod method,ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o degrees: Define the tightness of the swirling effect.
%
% o method: the pixel interpolation method.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport Image *SwirlImage(const Image *image,double degrees,
const PixelInterpolateMethod method,ExceptionInfo *exception)
{
#define SwirlImageTag "Swirl/Image"
CacheView
*canvas_view,
*interpolate_view,
*swirl_view;
double
radius;
Image
*canvas_image,
*swirl_image;
MagickBooleanType
status;
MagickOffsetType
progress;
PointInfo
center,
scale;
ssize_t
y;
/*
Initialize swirl image attributes.
*/
assert(image != (const Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
canvas_image=CloneImage(image,0,0,MagickTrue,exception);
if (canvas_image == (Image *) NULL)
return((Image *) NULL);
swirl_image=CloneImage(canvas_image,0,0,MagickTrue,exception);
if (swirl_image == (Image *) NULL)
{
canvas_image=DestroyImage(canvas_image);
return((Image *) NULL);
}
if (SetImageStorageClass(swirl_image,DirectClass,exception) == MagickFalse)
{
canvas_image=DestroyImage(canvas_image);
swirl_image=DestroyImage(swirl_image);
return((Image *) NULL);
}
if (swirl_image->background_color.alpha_trait != UndefinedPixelTrait)
(void) SetImageAlphaChannel(swirl_image,OnAlphaChannel,exception);
/*
Compute scaling factor.
*/
center.x=(double) canvas_image->columns/2.0;
center.y=(double) canvas_image->rows/2.0;
radius=MagickMax(center.x,center.y);
scale.x=1.0;
scale.y=1.0;
if (canvas_image->columns > canvas_image->rows)
scale.y=(double) canvas_image->columns/(double) canvas_image->rows;
else
if (canvas_image->columns < canvas_image->rows)
scale.x=(double) canvas_image->rows/(double) canvas_image->columns;
degrees=(double) DegreesToRadians(degrees);
/*
Swirl image.
*/
status=MagickTrue;
progress=0;
canvas_view=AcquireVirtualCacheView(canvas_image,exception);
interpolate_view=AcquireVirtualCacheView(image,exception);
swirl_view=AcquireAuthenticCacheView(swirl_image,exception);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static) shared(progress,status) \
magick_number_threads(canvas_image,swirl_image,canvas_image->rows,1)
#endif
for (y=0; y < (ssize_t) canvas_image->rows; y++)
{
double
distance;
PointInfo
delta;
const Quantum
*magick_restrict p;
ssize_t
x;
Quantum
*magick_restrict q;
if (status == MagickFalse)
continue;
p=GetCacheViewVirtualPixels(canvas_view,0,y,canvas_image->columns,1,
exception);
q=QueueCacheViewAuthenticPixels(swirl_view,0,y,swirl_image->columns,1,
exception);
if ((p == (const Quantum *) NULL) || (q == (Quantum *) NULL))
{
status=MagickFalse;
continue;
}
delta.y=scale.y*(double) (y-center.y);
for (x=0; x < (ssize_t) canvas_image->columns; x++)
{
/*
Determine if the pixel is within an ellipse.
*/
delta.x=scale.x*(double) (x-center.x);
distance=delta.x*delta.x+delta.y*delta.y;
if (distance >= (radius*radius))
{
ssize_t
i;
for (i=0; i < (ssize_t) GetPixelChannels(canvas_image); i++)
{
PixelChannel channel = GetPixelChannelChannel(canvas_image,i);
PixelTrait traits = GetPixelChannelTraits(canvas_image,channel);
PixelTrait swirl_traits = GetPixelChannelTraits(swirl_image,
channel);
if ((traits == UndefinedPixelTrait) ||
(swirl_traits == UndefinedPixelTrait))
continue;
SetPixelChannel(swirl_image,channel,p[i],q);
}
}
else
{
double
cosine,
factor,
sine;
/*
Swirl the pixel.
*/
factor=1.0-sqrt((double) distance)/radius;
sine=sin((double) (degrees*factor*factor));
cosine=cos((double) (degrees*factor*factor));
status=InterpolatePixelChannels(canvas_image,interpolate_view,
swirl_image,method,((cosine*delta.x-sine*delta.y)/scale.x+center.x),
(double) ((sine*delta.x+cosine*delta.y)/scale.y+center.y),q,
exception);
if (status == MagickFalse)
break;
}
p+=GetPixelChannels(canvas_image);
q+=GetPixelChannels(swirl_image);
}
if (SyncCacheViewAuthenticPixels(swirl_view,exception) == MagickFalse)
status=MagickFalse;
if (canvas_image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp atomic
#endif
progress++;
proceed=SetImageProgress(canvas_image,SwirlImageTag,progress,
canvas_image->rows);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
swirl_view=DestroyCacheView(swirl_view);
interpolate_view=DestroyCacheView(interpolate_view);
canvas_view=DestroyCacheView(canvas_view);
canvas_image=DestroyImage(canvas_image);
if (status == MagickFalse)
swirl_image=DestroyImage(swirl_image);
return(swirl_image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% T i n t I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% TintImage() applies a color vector to each pixel in the image. The length
% of the vector is 0 for black and white and at its maximum for the midtones.
% The vector weighting function is f(x)=(1-(4.0*((x-0.5)*(x-0.5))))
%
% The format of the TintImage method is:
%
% Image *TintImage(const Image *image,const char *blend,
% const PixelInfo *tint,ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o blend: A color value used for tinting.
%
% o tint: A color value used for tinting.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport Image *TintImage(const Image *image,const char *blend,
const PixelInfo *tint,ExceptionInfo *exception)
{
#define TintImageTag "Tint/Image"
CacheView
*image_view,
*tint_view;
double
intensity;
GeometryInfo
geometry_info;
Image
*tint_image;
MagickBooleanType
status;
MagickOffsetType
progress;
PixelInfo
color_vector;
MagickStatusType
flags;
ssize_t
y;
/*
Allocate tint image.
*/
assert(image != (const Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
tint_image=CloneImage(image,0,0,MagickTrue,exception);
if (tint_image == (Image *) NULL)
return((Image *) NULL);
if (SetImageStorageClass(tint_image,DirectClass,exception) == MagickFalse)
{
tint_image=DestroyImage(tint_image);
return((Image *) NULL);
}
if ((IsGrayColorspace(image->colorspace) != MagickFalse) &&
(IsPixelInfoGray(tint) == MagickFalse))
(void) SetImageColorspace(tint_image,sRGBColorspace,exception);
if (blend == (const char *) NULL)
return(tint_image);
/*
Determine RGB values of the color.
*/
GetPixelInfo(image,&color_vector);
flags=ParseGeometry(blend,&geometry_info);
color_vector.red=geometry_info.rho;
color_vector.green=geometry_info.rho;
color_vector.blue=geometry_info.rho;
color_vector.alpha=(MagickRealType) OpaqueAlpha;
if ((flags & SigmaValue) != 0)
color_vector.green=geometry_info.sigma;
if ((flags & XiValue) != 0)
color_vector.blue=geometry_info.xi;
if ((flags & PsiValue) != 0)
color_vector.alpha=geometry_info.psi;
if (image->colorspace == CMYKColorspace)
{
color_vector.black=geometry_info.rho;
if ((flags & PsiValue) != 0)
color_vector.black=geometry_info.psi;
if ((flags & ChiValue) != 0)
color_vector.alpha=geometry_info.chi;
}
intensity=(double) GetPixelInfoIntensity((const Image *) NULL,tint);
color_vector.red=(double) (color_vector.red*tint->red/100.0-intensity);
color_vector.green=(double) (color_vector.green*tint->green/100.0-intensity);
color_vector.blue=(double) (color_vector.blue*tint->blue/100.0-intensity);
color_vector.black=(double) (color_vector.black*tint->black/100.0-intensity);
color_vector.alpha=(double) (color_vector.alpha*tint->alpha/100.0-intensity);
/*
Tint image.
*/
status=MagickTrue;
progress=0;
image_view=AcquireVirtualCacheView(image,exception);
tint_view=AcquireAuthenticCacheView(tint_image,exception);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static) shared(progress,status) \
magick_number_threads(image,tint_image,image->rows,1)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
const Quantum
*magick_restrict p;
Quantum
*magick_restrict q;
ssize_t
x;
if (status == MagickFalse)
continue;
p=GetCacheViewVirtualPixels(image_view,0,y,image->columns,1,exception);
q=QueueCacheViewAuthenticPixels(tint_view,0,y,tint_image->columns,1,
exception);
if ((p == (const Quantum *) NULL) || (q == (Quantum *) NULL))
{
status=MagickFalse;
continue;
}
for (x=0; x < (ssize_t) image->columns; x++)
{
PixelInfo
pixel;
double
weight;
GetPixelInfo(image,&pixel);
weight=QuantumScale*GetPixelRed(image,p)-0.5;
pixel.red=(MagickRealType) GetPixelRed(image,p)+color_vector.red*
(1.0-(4.0*(weight*weight)));
weight=QuantumScale*GetPixelGreen(image,p)-0.5;
pixel.green=(MagickRealType) GetPixelGreen(image,p)+color_vector.green*
(1.0-(4.0*(weight*weight)));
weight=QuantumScale*GetPixelBlue(image,p)-0.5;
pixel.blue=(MagickRealType) GetPixelBlue(image,p)+color_vector.blue*
(1.0-(4.0*(weight*weight)));
weight=QuantumScale*GetPixelBlack(image,p)-0.5;
pixel.black=(MagickRealType) GetPixelBlack(image,p)+color_vector.black*
(1.0-(4.0*(weight*weight)));
pixel.alpha=(MagickRealType) GetPixelAlpha(image,p);
SetPixelViaPixelInfo(tint_image,&pixel,q);
p+=GetPixelChannels(image);
q+=GetPixelChannels(tint_image);
}
if (SyncCacheViewAuthenticPixels(tint_view,exception) == MagickFalse)
status=MagickFalse;
if (image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp atomic
#endif
progress++;
proceed=SetImageProgress(image,TintImageTag,progress,image->rows);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
tint_view=DestroyCacheView(tint_view);
image_view=DestroyCacheView(image_view);
if (status == MagickFalse)
tint_image=DestroyImage(tint_image);
return(tint_image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% V i g n e t t e I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% VignetteImage() softens the edges of the image in vignette style.
%
% The format of the VignetteImage method is:
%
% Image *VignetteImage(const Image *image,const double radius,
% const double sigma,const ssize_t x,const ssize_t y,
% ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o radius: the radius of the pixel neighborhood.
%
% o sigma: the standard deviation of the Gaussian, in pixels.
%
% o x, y: Define the x and y ellipse offset.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport Image *VignetteImage(const Image *image,const double radius,
const double sigma,const ssize_t x,const ssize_t y,ExceptionInfo *exception)
{
char
ellipse[MagickPathExtent];
DrawInfo
*draw_info;
Image
*canvas,
*blur_image,
*oval_image,
*vignette_image;
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
canvas=CloneImage(image,0,0,MagickTrue,exception);
if (canvas == (Image *) NULL)
return((Image *) NULL);
if (SetImageStorageClass(canvas,DirectClass,exception) == MagickFalse)
{
canvas=DestroyImage(canvas);
return((Image *) NULL);
}
canvas->alpha_trait=BlendPixelTrait;
oval_image=CloneImage(canvas,canvas->columns,canvas->rows,MagickTrue,
exception);
if (oval_image == (Image *) NULL)
{
canvas=DestroyImage(canvas);
return((Image *) NULL);
}
(void) QueryColorCompliance("#000000",AllCompliance,
&oval_image->background_color,exception);
(void) SetImageBackgroundColor(oval_image,exception);
draw_info=CloneDrawInfo((const ImageInfo *) NULL,(const DrawInfo *) NULL);
(void) QueryColorCompliance("#ffffff",AllCompliance,&draw_info->fill,
exception);
(void) QueryColorCompliance("#ffffff",AllCompliance,&draw_info->stroke,
exception);
(void) FormatLocaleString(ellipse,MagickPathExtent,"ellipse %g,%g,%g,%g,"
"0.0,360.0",image->columns/2.0,image->rows/2.0,image->columns/2.0-x,
image->rows/2.0-y);
draw_info->primitive=AcquireString(ellipse);
(void) DrawImage(oval_image,draw_info,exception);
draw_info=DestroyDrawInfo(draw_info);
blur_image=BlurImage(oval_image,radius,sigma,exception);
oval_image=DestroyImage(oval_image);
if (blur_image == (Image *) NULL)
{
canvas=DestroyImage(canvas);
return((Image *) NULL);
}
blur_image->alpha_trait=UndefinedPixelTrait;
(void) CompositeImage(canvas,blur_image,IntensityCompositeOp,MagickTrue,
0,0,exception);
blur_image=DestroyImage(blur_image);
vignette_image=MergeImageLayers(canvas,FlattenLayer,exception);
canvas=DestroyImage(canvas);
if (vignette_image != (Image *) NULL)
(void) TransformImageColorspace(vignette_image,image->colorspace,exception);
return(vignette_image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% W a v e I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% WaveImage() creates a "ripple" effect in the image by shifting the pixels
% vertically along a sine wave whose amplitude and wavelength is specified
% by the given parameters.
%
% The format of the WaveImage method is:
%
% Image *WaveImage(const Image *image,const double amplitude,
% const double wave_length,const PixelInterpolateMethod method,
% ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o amplitude, wave_length: Define the amplitude and wave length of the
% sine wave.
%
% o interpolate: the pixel interpolation method.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport Image *WaveImage(const Image *image,const double amplitude,
const double wave_length,const PixelInterpolateMethod method,
ExceptionInfo *exception)
{
#define WaveImageTag "Wave/Image"
CacheView
*canvas_image_view,
*wave_view;
float
*sine_map;
Image
*canvas_image,
*wave_image;
MagickBooleanType
status;
MagickOffsetType
progress;
ssize_t
i;
ssize_t
y;
/*
Initialize wave image attributes.
*/
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
canvas_image=CloneImage(image,0,0,MagickTrue,exception);
if (canvas_image == (Image *) NULL)
return((Image *) NULL);
if ((canvas_image->alpha_trait == UndefinedPixelTrait) &&
(canvas_image->background_color.alpha != OpaqueAlpha))
(void) SetImageAlpha(canvas_image,OpaqueAlpha,exception);
wave_image=CloneImage(canvas_image,canvas_image->columns,(size_t)
(canvas_image->rows+2.0*fabs(amplitude)),MagickTrue,exception);
if (wave_image == (Image *) NULL)
{
canvas_image=DestroyImage(canvas_image);
return((Image *) NULL);
}
if (SetImageStorageClass(wave_image,DirectClass,exception) == MagickFalse)
{
canvas_image=DestroyImage(canvas_image);
wave_image=DestroyImage(wave_image);
return((Image *) NULL);
}
/*
Allocate sine map.
*/
sine_map=(float *) AcquireQuantumMemory((size_t) wave_image->columns,
sizeof(*sine_map));
if (sine_map == (float *) NULL)
{
canvas_image=DestroyImage(canvas_image);
wave_image=DestroyImage(wave_image);
ThrowImageException(ResourceLimitError,"MemoryAllocationFailed");
}
for (i=0; i < (ssize_t) wave_image->columns; i++)
sine_map[i]=(float) fabs(amplitude)+amplitude*sin((double)
((2.0*MagickPI*i)*PerceptibleReciprocal(wave_length)));
/*
Wave image.
*/
status=MagickTrue;
progress=0;
canvas_image_view=AcquireVirtualCacheView(canvas_image,exception);
wave_view=AcquireAuthenticCacheView(wave_image,exception);
(void) SetCacheViewVirtualPixelMethod(canvas_image_view,
BackgroundVirtualPixelMethod);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static) shared(progress,status) \
magick_number_threads(canvas_image,wave_image,wave_image->rows,1)
#endif
for (y=0; y < (ssize_t) wave_image->rows; y++)
{
const Quantum
*magick_restrict p;
Quantum
*magick_restrict q;
ssize_t
x;
if (status == MagickFalse)
continue;
p=GetCacheViewVirtualPixels(canvas_image_view,0,y,canvas_image->columns,1,
exception);
q=QueueCacheViewAuthenticPixels(wave_view,0,y,wave_image->columns,1,
exception);
if ((p == (const Quantum *) NULL) || (q == (Quantum *) NULL))
{
status=MagickFalse;
continue;
}
for (x=0; x < (ssize_t) wave_image->columns; x++)
{
status=InterpolatePixelChannels(canvas_image,canvas_image_view,
wave_image,method,(double) x,(double) (y-sine_map[x]),q,exception);
if (status == MagickFalse)
break;
p+=GetPixelChannels(canvas_image);
q+=GetPixelChannels(wave_image);
}
if (SyncCacheViewAuthenticPixels(wave_view,exception) == MagickFalse)
status=MagickFalse;
if (image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp atomic
#endif
progress++;
proceed=SetImageProgress(canvas_image,WaveImageTag,progress,
canvas_image->rows);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
wave_view=DestroyCacheView(wave_view);
canvas_image_view=DestroyCacheView(canvas_image_view);
canvas_image=DestroyImage(canvas_image);
sine_map=(float *) RelinquishMagickMemory(sine_map);
if (status == MagickFalse)
wave_image=DestroyImage(wave_image);
return(wave_image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% W a v e l e t D e n o i s e I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% WaveletDenoiseImage() removes noise from the image using a wavelet
% transform. The wavelet transform is a fast hierarchical scheme for
% processing an image using a set of consecutive lowpass and high_pass filters,
% followed by a decimation. This results in a decomposition into different
% scales which can be regarded as different “frequency bands”, determined by
% the mother wavelet. Adapted from dcraw.c by David Coffin.
%
% The format of the WaveletDenoiseImage method is:
%
% Image *WaveletDenoiseImage(const Image *image,const double threshold,
% const double softness,ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o threshold: set the threshold for smoothing.
%
% o softness: attenuate the smoothing threshold.
%
% o exception: return any errors or warnings in this structure.
%
*/
static inline void HatTransform(const float *magick_restrict pixels,
const size_t stride,const size_t extent,const size_t scale,float *kernel)
{
const float
*magick_restrict p,
*magick_restrict q,
*magick_restrict r;
ssize_t
i;
p=pixels;
q=pixels+scale*stride;
r=pixels+scale*stride;
for (i=0; i < (ssize_t) scale; i++)
{
kernel[i]=0.25f*(*p+(*p)+(*q)+(*r));
p+=stride;
q-=stride;
r+=stride;
}
for ( ; i < (ssize_t) (extent-scale); i++)
{
kernel[i]=0.25f*(2.0f*(*p)+*(p-scale*stride)+*(p+scale*stride));
p+=stride;
}
q=p-scale*stride;
r=pixels+stride*(extent-2);
for ( ; i < (ssize_t) extent; i++)
{
kernel[i]=0.25f*(*p+(*p)+(*q)+(*r));
p+=stride;
q+=stride;
r-=stride;
}
}
MagickExport Image *WaveletDenoiseImage(const Image *image,
const double threshold,const double softness,ExceptionInfo *exception)
{
CacheView
*image_view,
*noise_view;
float
*kernel,
*pixels;
Image
*noise_image;
MagickBooleanType
status;
MagickSizeType
number_pixels;
MemoryInfo
*pixels_info;
ssize_t
channel;
static const float
noise_levels[] = { 0.8002f, 0.2735f, 0.1202f, 0.0585f, 0.0291f, 0.0152f,
0.0080f, 0.0044f };
/*
Initialize noise image attributes.
*/
assert(image != (const Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
#if defined(MAGICKCORE_OPENCL_SUPPORT)
noise_image=AccelerateWaveletDenoiseImage(image,threshold,exception);
if (noise_image != (Image *) NULL)
return(noise_image);
#endif
noise_image=CloneImage(image,0,0,MagickTrue,exception);
if (noise_image == (Image *) NULL)
return((Image *) NULL);
if (SetImageStorageClass(noise_image,DirectClass,exception) == MagickFalse)
{
noise_image=DestroyImage(noise_image);
return((Image *) NULL);
}
if (AcquireMagickResource(WidthResource,4*image->columns) == MagickFalse)
ThrowImageException(ResourceLimitError,"MemoryAllocationFailed");
pixels_info=AcquireVirtualMemory(3*image->columns,image->rows*
sizeof(*pixels));
kernel=(float *) AcquireQuantumMemory(MagickMax(image->rows,image->columns)+1,
GetOpenMPMaximumThreads()*sizeof(*kernel));
if ((pixels_info == (MemoryInfo *) NULL) || (kernel == (float *) NULL))
{
if (kernel != (float *) NULL)
kernel=(float *) RelinquishMagickMemory(kernel);
if (pixels_info != (MemoryInfo *) NULL)
pixels_info=RelinquishVirtualMemory(pixels_info);
ThrowImageException(ResourceLimitError,"MemoryAllocationFailed");
}
pixels=(float *) GetVirtualMemoryBlob(pixels_info);
status=MagickTrue;
number_pixels=(MagickSizeType) image->columns*image->rows;
image_view=AcquireAuthenticCacheView(image,exception);
noise_view=AcquireAuthenticCacheView(noise_image,exception);
for (channel=0; channel < (ssize_t) GetPixelChannels(image); channel++)
{
ssize_t
i;
size_t
high_pass,
low_pass;
ssize_t
level,
y;
PixelChannel
pixel_channel;
PixelTrait
traits;
if (status == MagickFalse)
continue;
traits=GetPixelChannelTraits(image,(PixelChannel) channel);
if (traits == UndefinedPixelTrait)
continue;
pixel_channel=GetPixelChannelChannel(image,channel);
if ((pixel_channel != RedPixelChannel) &&
(pixel_channel != GreenPixelChannel) &&
(pixel_channel != BluePixelChannel))
continue;
/*
Copy channel from image to wavelet pixel array.
*/
i=0;
for (y=0; y < (ssize_t) image->rows; y++)
{
const Quantum
*magick_restrict p;
ssize_t
x;
p=GetCacheViewAuthenticPixels(image_view,0,y,image->columns,1,exception);
if (p == (const Quantum *) NULL)
{
status=MagickFalse;
break;
}
for (x=0; x < (ssize_t) image->columns; x++)
{
pixels[i++]=(float) p[channel];
p+=GetPixelChannels(image);
}
}
/*
Low pass filter outputs are called approximation kernel & high pass
filters are referred to as detail kernel. The detail kernel
have high values in the noisy parts of the signal.
*/
high_pass=0;
for (level=0; level < 5; level++)
{
double
magnitude;
ssize_t
x;
low_pass=(size_t) (number_pixels*((level & 0x01)+1));
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static,1) \
magick_number_threads(image,image,image->rows,1)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
const int
id = GetOpenMPThreadId();
float
*magick_restrict p,
*magick_restrict q;
ssize_t
c;
p=kernel+id*image->columns;
q=pixels+y*image->columns;
HatTransform(q+high_pass,1,image->columns,((size_t) 1UL << level),p);
q+=low_pass;
for (c=0; c < (ssize_t) image->columns; c++)
*q++=(*p++);
}
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static,1) \
magick_number_threads(image,image,image->columns,1)
#endif
for (x=0; x < (ssize_t) image->columns; x++)
{
const int
id = GetOpenMPThreadId();
float
*magick_restrict p,
*magick_restrict q;
ssize_t
r;
p=kernel+id*image->rows;
q=pixels+x+low_pass;
HatTransform(q,image->columns,image->rows,((size_t) 1UL << level),p);
for (r=0; r < (ssize_t) image->rows; r++)
{
*q=(*p++);
q+=image->columns;
}
}
/*
To threshold, each coefficient is compared to a threshold value and
attenuated / shrunk by some factor.
*/
magnitude=threshold*noise_levels[level];
for (i=0; i < (ssize_t) number_pixels; ++i)
{
pixels[high_pass+i]-=pixels[low_pass+i];
if (pixels[high_pass+i] < -magnitude)
pixels[high_pass+i]+=magnitude-softness*magnitude;
else
if (pixels[high_pass+i] > magnitude)
pixels[high_pass+i]-=magnitude-softness*magnitude;
else
pixels[high_pass+i]*=softness;
if (high_pass != 0)
pixels[i]+=pixels[high_pass+i];
}
high_pass=low_pass;
}
/*
Reconstruct image from the thresholded wavelet kernel.
*/
i=0;
for (y=0; y < (ssize_t) image->rows; y++)
{
MagickBooleanType
sync;
Quantum
*magick_restrict q;
ssize_t
x;
ssize_t
offset;
q=GetCacheViewAuthenticPixels(noise_view,0,y,noise_image->columns,1,
exception);
if (q == (Quantum *) NULL)
{
status=MagickFalse;
break;
}
offset=GetPixelChannelOffset(noise_image,pixel_channel);
for (x=0; x < (ssize_t) image->columns; x++)
{
MagickRealType
pixel;
pixel=(MagickRealType) pixels[i]+pixels[low_pass+i];
q[offset]=ClampToQuantum(pixel);
i++;
q+=GetPixelChannels(noise_image);
}
sync=SyncCacheViewAuthenticPixels(noise_view,exception);
if (sync == MagickFalse)
status=MagickFalse;
}
if (image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
proceed=SetImageProgress(image,AddNoiseImageTag,(MagickOffsetType)
channel,GetPixelChannels(image));
if (proceed == MagickFalse)
status=MagickFalse;
}
}
noise_view=DestroyCacheView(noise_view);
image_view=DestroyCacheView(image_view);
kernel=(float *) RelinquishMagickMemory(kernel);
pixels_info=RelinquishVirtualMemory(pixels_info);
if (status == MagickFalse)
noise_image=DestroyImage(noise_image);
return(noise_image);
}
|
LLT_ROF_core.c | /*
This work is part of the Core Imaging Library developed by
Visual Analytics and Imaging System Group of the Science Technology
Facilities Council, STFC
Copyright 2017 Daniil Kazantsev
Copyright 2017 Srikanth Nagella, Edoardo Pasca
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
*/
#include "LLT_ROF_core.h"
#define EPS_LLT 1.0e-12
#define EPS_ROF 1.0e-12
#define MAX(x, y) (((x) > (y)) ? (x) : (y))
#define MIN(x, y) (((x) < (y)) ? (x) : (y))
/*sign function*/
int signLLT(float x) {
return (x > 0) - (x < 0);
}
/* C-OMP implementation of Lysaker, Lundervold and Tai (LLT) model [1] combined with Rudin-Osher-Fatemi [2] TV regularisation penalty.
*
* This penalty can deliver visually pleasant piecewise-smooth recovery if regularisation parameters are selected well.
* The rule of thumb for selection is to start with lambdaLLT = 0 (just the ROF-TV model) and then proceed to increase
* lambdaLLT starting with smaller values.
*
* Input Parameters:
* 1. U0 - original noise image/volume
* 2. lambdaROF - ROF-related regularisation parameter
* 3. lambdaLLT - LLT-related regularisation parameter
* 4. tau - time-marching step
* 5. iter - iterations number (for both models)
* 6. eplsilon: tolerance constant
*
* Output:
* [1] Filtered/regularized image/volume
* [2] Information vector which contains [iteration no., reached tolerance]
*
* References:
* [1] Lysaker, M., Lundervold, A. and Tai, X.C., 2003. Noise removal using fourth-order partial differential equation with applications to medical magnetic resonance images in space and time. IEEE Transactions on image processing, 12(12), pp.1579-1590.
* [2] Rudin, Osher, Fatemi, "Nonlinear Total Variation based noise removal algorithms"
*/
float LLT_ROF_CPU_main(float *Input, float *Output, float *infovector, float lambdaROF, float lambdaLLT, int iterationsNumb, float tau, float epsil, int dimX, int dimY, int dimZ)
{
long DimTotal;
int ll, j;
float re, re1;
re = 0.0f; re1 = 0.0f;
int count = 0;
float *D1_LLT=NULL, *D2_LLT=NULL, *D3_LLT=NULL, *D1_ROF=NULL, *D2_ROF=NULL, *D3_ROF=NULL, *Output_prev=NULL;
DimTotal = (long)(dimX*dimY*dimZ);
D1_ROF = calloc(DimTotal, sizeof(float));
D2_ROF = calloc(DimTotal, sizeof(float));
D3_ROF = calloc(DimTotal, sizeof(float));
D1_LLT = calloc(DimTotal, sizeof(float));
D2_LLT = calloc(DimTotal, sizeof(float));
D3_LLT = calloc(DimTotal, sizeof(float));
copyIm(Input, Output, (long)(dimX), (long)(dimY), (long)(dimZ)); /* initialize */
if (epsil != 0.0f) Output_prev = calloc(DimTotal, sizeof(float));
for(ll = 0; ll < iterationsNumb; ll++) {
if ((epsil != 0.0f) && (ll % 5 == 0)) copyIm(Output, Output_prev, (long)(dimX), (long)(dimY), (long)(dimZ));
if (dimZ == 1) {
/* 2D case */
/****************ROF******************/
/* calculate first-order differences */
D1_func_ROF(Output, D1_ROF, (long)(dimX), (long)(dimY), 1l);
D2_func_ROF(Output, D2_ROF, (long)(dimX), (long)(dimY), 1l);
/****************LLT******************/
/* estimate second-order derrivatives */
der2D_LLT(Output, D1_LLT, D2_LLT, (long)(dimX), (long)(dimY), 1l);
/* Joint update for ROF and LLT models */
Update2D_LLT_ROF(Input, Output, D1_LLT, D2_LLT, D1_ROF, D2_ROF, lambdaROF, lambdaLLT, tau, (long)(dimX), (long)(dimY), 1l);
}
else {
/* 3D case */
/* calculate first-order differences */
D1_func_ROF(Output, D1_ROF, (long)(dimX), (long)(dimY), (long)(dimZ));
D2_func_ROF(Output, D2_ROF, (long)(dimX), (long)(dimY), (long)(dimZ));
D3_func_ROF(Output, D3_ROF, (long)(dimX), (long)(dimY), (long)(dimZ));
/****************LLT******************/
/* estimate second-order derrivatives */
der3D_LLT(Output, D1_LLT, D2_LLT, D3_LLT,(long)(dimX), (long)(dimY), (long)(dimZ));
/* Joint update for ROF and LLT models */
Update3D_LLT_ROF(Input, Output, D1_LLT, D2_LLT, D3_LLT, D1_ROF, D2_ROF, D3_ROF, lambdaROF, lambdaLLT, tau, (long)(dimX), (long)(dimY), (long)(dimZ));
}
/* check early stopping criteria */
if ((epsil != 0.0f) && (ll % 5 == 0)) {
re = 0.0f; re1 = 0.0f;
for(j=0; j<DimTotal; j++)
{
re += powf(Output[j] - Output_prev[j],2);
re1 += powf(Output[j],2);
}
re = sqrtf(re)/sqrtf(re1);
if (re < epsil) count++;
if (count > 3) break;
}
} /*end of iterations*/
free(D1_LLT);free(D2_LLT);free(D3_LLT);
free(D1_ROF);free(D2_ROF);free(D3_ROF);
if (epsil != 0.0f) free(Output_prev);
/*adding info into info_vector */
infovector[0] = (float)(ll); /*iterations number (if stopped earlier based on tolerance)*/
infovector[1] = re; /* reached tolerance */
return 0;
}
/*************************************************************************/
/**********************LLT-related functions *****************************/
/*************************************************************************/
float der2D_LLT(float *U, float *D1, float *D2, long dimX, long dimY, long dimZ)
{
long i, j, index, i_p, i_m, j_m, j_p;
float dxx, dyy, denom_xx, denom_yy;
#pragma omp parallel for shared(U,D1,D2) private(i, j, index, i_p, i_m, j_m, j_p, denom_xx, denom_yy, dxx, dyy)
for (i = 0; i<dimX; i++) {
for (j = 0; j<dimY; j++) {
index = j*dimX+i;
/* symmetric boundary conditions (Neuman) */
i_p = i + 1; if (i_p == dimX) i_p = i - 1;
i_m = i - 1; if (i_m < 0) i_m = i + 1;
j_p = j + 1; if (j_p == dimY) j_p = j - 1;
j_m = j - 1; if (j_m < 0) j_m = j + 1;
dxx = U[j*dimX+i_p] - 2.0f*U[index] + U[j*dimX+i_m];
dyy = U[j_p*dimX+i] - 2.0f*U[index] + U[j_m*dimX+i];
denom_xx = fabs(dxx) + EPS_LLT;
denom_yy = fabs(dyy) + EPS_LLT;
D1[index] = dxx / denom_xx;
D2[index] = dyy / denom_yy;
}
}
return 1;
}
float der3D_LLT(float *U, float *D1, float *D2, float *D3, long dimX, long dimY, long dimZ)
{
long i, j, k, i_p, i_m, j_m, j_p, k_p, k_m, index;
float dxx, dyy, dzz, denom_xx, denom_yy, denom_zz;
#pragma omp parallel for shared(U,D1,D2,D3) private(i, j, index, k, i_p, i_m, j_m, j_p, k_p, k_m, denom_xx, denom_yy, denom_zz, dxx, dyy, dzz)
for (i = 0; i<dimX; i++) {
for (j = 0; j<dimY; j++) {
for (k = 0; k<dimZ; k++) {
/* symmetric boundary conditions (Neuman) */
i_p = i + 1; if (i_p == dimX) i_p = i - 1;
i_m = i - 1; if (i_m < 0) i_m = i + 1;
j_p = j + 1; if (j_p == dimY) j_p = j - 1;
j_m = j - 1; if (j_m < 0) j_m = j + 1;
k_p = k + 1; if (k_p == dimZ) k_p = k - 1;
k_m = k - 1; if (k_m < 0) k_m = k + 1;
index = (dimX*dimY)*k + j*dimX+i;
dxx = U[(dimX*dimY)*k + j*dimX+i_p] - 2.0f*U[index] + U[(dimX*dimY)*k + j*dimX+i_m];
dyy = U[(dimX*dimY)*k + j_p*dimX+i] - 2.0f*U[index] + U[(dimX*dimY)*k + j_m*dimX+i];
dzz = U[(dimX*dimY)*k_p + j*dimX+i] - 2.0f*U[index] + U[(dimX*dimY)*k_m + j*dimX+i];
denom_xx = fabs(dxx) + EPS_LLT;
denom_yy = fabs(dyy) + EPS_LLT;
denom_zz = fabs(dzz) + EPS_LLT;
D1[index] = dxx / denom_xx;
D2[index] = dyy / denom_yy;
D3[index] = dzz / denom_zz;
}
}
}
return 1;
}
/*************************************************************************/
/**********************ROF-related functions *****************************/
/*************************************************************************/
/* calculate differences 1 */
float D1_func_ROF(float *A, float *D1, long dimX, long dimY, long dimZ)
{
float NOMx_1, NOMy_1, NOMy_0, NOMz_1, NOMz_0, denom1, denom2,denom3, T1;
long i,j,k,i1,i2,k1,j1,j2,k2,index;
if (dimZ > 1) {
#pragma omp parallel for shared (A, D1, dimX, dimY, dimZ) private(index, i, j, k, i1, j1, k1, i2, j2, k2, NOMx_1,NOMy_1,NOMy_0,NOMz_1,NOMz_0,denom1,denom2,denom3,T1)
for(j=0; j<dimY; j++) {
for(i=0; i<dimX; i++) {
for(k=0; k<dimZ; k++) {
index = (dimX*dimY)*k + j*dimX+i;
/* symmetric boundary conditions (Neuman) */
i1 = i + 1; if (i1 >= dimX) i1 = i-1;
i2 = i - 1; if (i2 < 0) i2 = i+1;
j1 = j + 1; if (j1 >= dimY) j1 = j-1;
j2 = j - 1; if (j2 < 0) j2 = j+1;
k1 = k + 1; if (k1 >= dimZ) k1 = k-1;
k2 = k - 1; if (k2 < 0) k2 = k+1;
/* Forward-backward differences */
NOMx_1 = A[(dimX*dimY)*k + j1*dimX + i] - A[index]; /* x+ */
NOMy_1 = A[(dimX*dimY)*k + j*dimX + i1] - A[index]; /* y+ */
/*NOMx_0 = (A[(i)*dimY + j] - A[(i2)*dimY + j]); */ /* x- */
NOMy_0 = A[index] - A[(dimX*dimY)*k + j*dimX + i2]; /* y- */
NOMz_1 = A[(dimX*dimY)*k1 + j*dimX + i] - A[index]; /* z+ */
NOMz_0 = A[index] - A[(dimX*dimY)*k2 + j*dimX + i]; /* z- */
denom1 = NOMx_1*NOMx_1;
denom2 = 0.5f*(signLLT(NOMy_1) + signLLT(NOMy_0))*(MIN(fabs(NOMy_1),fabs(NOMy_0)));
denom2 = denom2*denom2;
denom3 = 0.5f*(signLLT(NOMz_1) + signLLT(NOMz_0))*(MIN(fabs(NOMz_1),fabs(NOMz_0)));
denom3 = denom3*denom3;
T1 = sqrt(denom1 + denom2 + denom3 + EPS_ROF);
D1[index] = NOMx_1/T1;
}}}
}
else {
#pragma omp parallel for shared (A, D1, dimX, dimY) private(i, j, i1, j1, i2, j2,NOMx_1,NOMy_1,NOMy_0,denom1,denom2,T1,index)
for(j=0; j<dimY; j++) {
for(i=0; i<dimX; i++) {
index = j*dimX+i;
/* symmetric boundary conditions (Neuman) */
i1 = i + 1; if (i1 >= dimX) i1 = i-1;
i2 = i - 1; if (i2 < 0) i2 = i+1;
j1 = j + 1; if (j1 >= dimY) j1 = j-1;
j2 = j - 1; if (j2 < 0) j2 = j+1;
/* Forward-backward differences */
NOMx_1 = A[j1*dimX + i] - A[index]; /* x+ */
NOMy_1 = A[j*dimX + i1] - A[index]; /* y+ */
/*NOMx_0 = (A[(i)*dimY + j] - A[(i2)*dimY + j]); */ /* x- */
NOMy_0 = A[index] - A[(j)*dimX + i2]; /* y- */
denom1 = NOMx_1*NOMx_1;
denom2 = 0.5f*(signLLT(NOMy_1) + signLLT(NOMy_0))*(MIN(fabs(NOMy_1),fabs(NOMy_0)));
denom2 = denom2*denom2;
T1 = sqrtf(denom1 + denom2 + EPS_ROF);
D1[index] = NOMx_1/T1;
}}
}
return *D1;
}
/* calculate differences 2 */
float D2_func_ROF(float *A, float *D2, long dimX, long dimY, long dimZ)
{
float NOMx_1, NOMy_1, NOMx_0, NOMz_1, NOMz_0, denom1, denom2, denom3, T2;
long i,j,k,i1,i2,k1,j1,j2,k2,index;
if (dimZ > 1) {
#pragma omp parallel for shared (A, D2, dimX, dimY, dimZ) private(index, i, j, k, i1, j1, k1, i2, j2, k2, NOMx_1, NOMy_1, NOMx_0, NOMz_1, NOMz_0, denom1, denom2, denom3, T2)
for(j=0; j<dimY; j++) {
for(i=0; i<dimX; i++) {
for(k=0; k<dimZ; k++) {
index = (dimX*dimY)*k + j*dimX+i;
/* symmetric boundary conditions (Neuman) */
i1 = i + 1; if (i1 >= dimX) i1 = i-1;
i2 = i - 1; if (i2 < 0) i2 = i+1;
j1 = j + 1; if (j1 >= dimY) j1 = j-1;
j2 = j - 1; if (j2 < 0) j2 = j+1;
k1 = k + 1; if (k1 >= dimZ) k1 = k-1;
k2 = k - 1; if (k2 < 0) k2 = k+1;
/* Forward-backward differences */
NOMx_1 = A[(dimX*dimY)*k + (j1)*dimX + i] - A[index]; /* x+ */
NOMy_1 = A[(dimX*dimY)*k + (j)*dimX + i1] - A[index]; /* y+ */
NOMx_0 = A[index] - A[(dimX*dimY)*k + (j2)*dimX + i]; /* x- */
NOMz_1 = A[(dimX*dimY)*k1 + j*dimX + i] - A[index]; /* z+ */
NOMz_0 = A[index] - A[(dimX*dimY)*k2 + (j)*dimX + i]; /* z- */
denom1 = NOMy_1*NOMy_1;
denom2 = 0.5f*(signLLT(NOMx_1) + signLLT(NOMx_0))*(MIN(fabs(NOMx_1),fabs(NOMx_0)));
denom2 = denom2*denom2;
denom3 = 0.5f*(signLLT(NOMz_1) + signLLT(NOMz_0))*(MIN(fabs(NOMz_1),fabs(NOMz_0)));
denom3 = denom3*denom3;
T2 = sqrtf(denom1 + denom2 + denom3 + EPS_ROF);
D2[index] = NOMy_1/T2;
}}}
}
else {
#pragma omp parallel for shared (A, D2, dimX, dimY) private(i, j, i1, j1, i2, j2, NOMx_1,NOMy_1,NOMx_0,denom1,denom2,T2,index)
for(j=0; j<dimY; j++) {
for(i=0; i<dimX; i++) {
index = j*dimX+i;
/* symmetric boundary conditions (Neuman) */
i1 = i + 1; if (i1 >= dimX) i1 = i-1;
i2 = i - 1; if (i2 < 0) i2 = i+1;
j1 = j + 1; if (j1 >= dimY) j1 = j-1;
j2 = j - 1; if (j2 < 0) j2 = j+1;
/* Forward-backward differences */
NOMx_1 = A[j1*dimX + i] - A[index]; /* x+ */
NOMy_1 = A[j*dimX + i1] - A[index]; /* y+ */
NOMx_0 = A[index] - A[j2*dimX + i]; /* x- */
/*NOMy_0 = A[(i)*dimY + j] - A[(i)*dimY + j2]; */ /* y- */
denom1 = NOMy_1*NOMy_1;
denom2 = 0.5f*(signLLT(NOMx_1) + signLLT(NOMx_0))*(MIN(fabs(NOMx_1),fabs(NOMx_0)));
denom2 = denom2*denom2;
T2 = sqrtf(denom1 + denom2 + EPS_ROF);
D2[index] = NOMy_1/T2;
}}
}
return *D2;
}
/* calculate differences 3 */
float D3_func_ROF(float *A, float *D3, long dimX, long dimY, long dimZ)
{
float NOMx_1, NOMy_1, NOMx_0, NOMy_0, NOMz_1, denom1, denom2, denom3, T3;
long index,i,j,k,i1,i2,k1,j1,j2,k2;
#pragma omp parallel for shared (A, D3, dimX, dimY, dimZ) private(index, i, j, k, i1, j1, k1, i2, j2, k2, NOMx_1, NOMy_1, NOMy_0, NOMx_0, NOMz_1, denom1, denom2, denom3, T3)
for(j=0; j<dimY; j++) {
for(i=0; i<dimX; i++) {
for(k=0; k<dimZ; k++) {
index = (dimX*dimY)*k + j*dimX+i;
/* symmetric boundary conditions (Neuman) */
i1 = i + 1; if (i1 >= dimX) i1 = i-1;
i2 = i - 1; if (i2 < 0) i2 = i+1;
j1 = j + 1; if (j1 >= dimY) j1 = j-1;
j2 = j - 1; if (j2 < 0) j2 = j+1;
k1 = k + 1; if (k1 >= dimZ) k1 = k-1;
k2 = k - 1; if (k2 < 0) k2 = k+1;
/* Forward-backward differences */
NOMx_1 = A[(dimX*dimY)*k + (j1)*dimX + i] - A[index]; /* x+ */
NOMy_1 = A[(dimX*dimY)*k + (j)*dimX + i1] - A[index]; /* y+ */
NOMy_0 = A[index] - A[(dimX*dimY)*k + (j)*dimX + i2]; /* y- */
NOMx_0 = A[index] - A[(dimX*dimY)*k + (j2)*dimX + i]; /* x- */
NOMz_1 = A[(dimX*dimY)*k1 + j*dimX + i] - A[index]; /* z+ */
/*NOMz_0 = A[(dimX*dimY)*k + (i)*dimY + j] - A[(dimX*dimY)*k2 + (i)*dimY + j]; */ /* z- */
denom1 = NOMz_1*NOMz_1;
denom2 = 0.5f*(signLLT(NOMx_1) + signLLT(NOMx_0))*(MIN(fabs(NOMx_1),fabs(NOMx_0)));
denom2 = denom2*denom2;
denom3 = 0.5f*(signLLT(NOMy_1) + signLLT(NOMy_0))*(MIN(fabs(NOMy_1),fabs(NOMy_0)));
denom3 = denom3*denom3;
T3 = sqrtf(denom1 + denom2 + denom3 + EPS_ROF);
D3[index] = NOMz_1/T3;
}}}
return *D3;
}
/*************************************************************************/
/**********************ROF-LLT-related functions *************************/
/*************************************************************************/
float Update2D_LLT_ROF(float *U0, float *U, float *D1_LLT, float *D2_LLT, float *D1_ROF, float *D2_ROF, float lambdaROF, float lambdaLLT, float tau, long dimX, long dimY, long dimZ)
{
long i, j, index, i_p, i_m, j_m, j_p;
float div, laplc, dxx, dyy, dv1, dv2;
#pragma omp parallel for shared(U,U0) private(i, j, index, i_p, i_m, j_m, j_p, laplc, div, dxx, dyy, dv1, dv2)
for (i = 0; i<dimX; i++) {
for (j = 0; j<dimY; j++) {
index = j*dimX+i;
/* symmetric boundary conditions (Neuman) */
i_p = i + 1; if (i_p == dimX) i_p = i - 1;
i_m = i - 1; if (i_m < 0) i_m = i + 1;
j_p = j + 1; if (j_p == dimY) j_p = j - 1;
j_m = j - 1; if (j_m < 0) j_m = j + 1;
/*LLT-related part*/
dxx = D1_LLT[j*dimX+i_p] - 2.0f*D1_LLT[index] + D1_LLT[j*dimX+i_m];
dyy = D2_LLT[j_p*dimX+i] - 2.0f*D2_LLT[index] + D2_LLT[j_m*dimX+i];
laplc = dxx + dyy; /*build Laplacian*/
/*ROF-related part*/
dv1 = D1_ROF[index] - D1_ROF[j_m*dimX + i];
dv2 = D2_ROF[index] - D2_ROF[j*dimX + i_m];
div = dv1 + dv2; /*build Divirgent*/
/*combine all into one cost function to minimise */
U[index] += tau*(lambdaROF*(div) - lambdaLLT*(laplc) - (U[index] - U0[index]));
}
}
return *U;
}
float Update3D_LLT_ROF(float *U0, float *U, float *D1_LLT, float *D2_LLT, float *D3_LLT, float *D1_ROF, float *D2_ROF, float *D3_ROF, float lambdaROF, float lambdaLLT, float tau, long dimX, long dimY, long dimZ)
{
long i, j, k, i_p, i_m, j_m, j_p, k_p, k_m, index;
float div, laplc, dxx, dyy, dzz, dv1, dv2, dv3;
#pragma omp parallel for shared(U,U0) private(i, j, k, index, i_p, i_m, j_m, j_p, k_p, k_m, laplc, div, dxx, dyy, dzz, dv1, dv2, dv3)
for (i = 0; i<dimX; i++) {
for (j = 0; j<dimY; j++) {
for (k = 0; k<dimZ; k++) {
/* symmetric boundary conditions (Neuman) */
i_p = i + 1; if (i_p == dimX) i_p = i - 1;
i_m = i - 1; if (i_m < 0) i_m = i + 1;
j_p = j + 1; if (j_p == dimY) j_p = j - 1;
j_m = j - 1; if (j_m < 0) j_m = j + 1;
k_p = k + 1; if (k_p == dimZ) k_p = k - 1;
k_m = k - 1; if (k_m < 0) k_m = k + 1;
index = (dimX*dimY)*k + j*dimX+i;
/*LLT-related part*/
dxx = D1_LLT[(dimX*dimY)*k + j*dimX+i_p] - 2.0f*D1_LLT[index] + D1_LLT[(dimX*dimY)*k + j*dimX+i_m];
dyy = D2_LLT[(dimX*dimY)*k + j_p*dimX+i] - 2.0f*D2_LLT[index] + D2_LLT[(dimX*dimY)*k + j_m*dimX+i];
dzz = D3_LLT[(dimX*dimY)*k_p + j*dimX+i] - 2.0f*D3_LLT[index] + D3_LLT[(dimX*dimY)*k_m + j*dimX+i];
laplc = dxx + dyy + dzz; /*build Laplacian*/
/*ROF-related part*/
dv1 = D1_ROF[index] - D1_ROF[(dimX*dimY)*k + j_m*dimX+i];
dv2 = D2_ROF[index] - D2_ROF[(dimX*dimY)*k + j*dimX+i_m];
dv3 = D3_ROF[index] - D3_ROF[(dimX*dimY)*k_m + j*dimX+i];
div = dv1 + dv2 + dv3; /*build Divirgent*/
/*combine all into one cost function to minimise */
U[index] += tau*(lambdaROF*(div) - lambdaLLT*(laplc) - (U[index] - U0[index]));
}
}
}
return *U;
}
|
GB_unaryop__abs_int8_bool.c | //------------------------------------------------------------------------------
// GB_unaryop: hard-coded functions for each built-in unary operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2019, All Rights Reserved.
// http://suitesparse.com See GraphBLAS/Doc/License.txt for license.
//------------------------------------------------------------------------------
// If this file is in the Generated/ folder, do not edit it (auto-generated).
#include "GB.h"
#ifndef GBCOMPACT
#include "GB_control.h"
#include "GB_iterator.h"
#include "GB_unaryop__include.h"
// C=unop(A) is defined by the following types and operators:
// op(A) function: GB_unop__abs_int8_bool
// op(A') function: GB_tran__abs_int8_bool
// C type: int8_t
// A type: bool
// cast: int8_t cij = (int8_t) aij
// unaryop: cij = GB_IABS (aij)
#define GB_ATYPE \
bool
#define GB_CTYPE \
int8_t
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA) \
bool aij = Ax [pA]
#define GB_CX(p) Cx [p]
// unary operator
#define GB_OP(z, x) \
z = GB_IABS (x) ;
// casting
#define GB_CASTING(z, x) \
int8_t z = (int8_t) x ;
// cij = op (cast (aij))
#define GB_CAST_OP(pC,pA) \
{ \
/* aij = Ax [pA] */ \
GB_GETA (aij, Ax, pA) ; \
/* Cx [pC] = op (cast (aij)) */ \
GB_CASTING (x, aij) ; \
GB_OP (GB_CX (pC), x) ; \
}
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_ABS || GxB_NO_INT8 || GxB_NO_BOOL)
//------------------------------------------------------------------------------
// Cx = op (cast (Ax)): apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_unop__abs_int8_bool
(
int8_t *restrict Cx,
const bool *restrict Ax,
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (int64_t p = 0 ; p < anz ; p++)
{
GB_CAST_OP (p, p) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (cast (A')): transpose, typecast, and apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_tran__abs_int8_bool
(
GrB_Matrix C,
const GrB_Matrix A,
int64_t **Rowcounts,
GBI_single_iterator Iter,
const int64_t *restrict A_slice,
int naslice
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#define GB_PHASE_2_OF_2
#include "GB_unaryop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
pentagon.h | // This code is modified from AutoMine and GraphZero
// Daniel Mawhirter and Bo Wu. SOSP 2019.
// AutoMine: Harmonizing High-Level Abstraction and High Performance for Graph Mining
#pragma omp parallel for schedule(dynamic,1) reduction(+:counter)
for(vidType v0 = 0; v0 < g.V(); v0++) {
for (auto v1 : g.N(v0)) {
if (v1 >= v0) break;
auto y1 = g.N(v1);
for (auto v2 : g.N(v0)) {
if (v2 >= v1) break;
for (auto v3 : g.N(v2)) {
if (v3 >= v0) break;
if (v3 == v1) continue;
auto y3 = g.N(v3);
counter += intersection_num_bound_except(y1, y3, v0, v2);
}
}
}
}
|
StmtOpenMP.h | //===- StmtOpenMP.h - Classes for OpenMP directives ------------*- C++ -*-===//
//
// The LLVM Compiler Infrastructure
//
// This file is distributed under the University of Illinois Open Source
// License. See LICENSE.TXT for details.
//
//===----------------------------------------------------------------------===//
/// \file
/// \brief This file defines OpenMP AST classes for executable directives and
/// clauses.
///
//===----------------------------------------------------------------------===//
#ifndef LLVM_CLANG_AST_STMTOPENMP_H
#define LLVM_CLANG_AST_STMTOPENMP_H
#include "clang/AST/Expr.h"
#include "clang/AST/OpenMPClause.h"
#include "clang/AST/Stmt.h"
#include "clang/Basic/OpenMPKinds.h"
#include "clang/Basic/SourceLocation.h"
namespace clang {
//===----------------------------------------------------------------------===//
// AST classes for directives.
//===----------------------------------------------------------------------===//
/// \brief This is a basic class for representing single OpenMP executable
/// directive.
///
class OMPExecutableDirective : public Stmt {
friend class ASTStmtReader;
/// \brief Kind of the directive.
OpenMPDirectiveKind Kind;
/// \brief Starting location of the directive (directive keyword).
SourceLocation StartLoc;
/// \brief Ending location of the directive.
SourceLocation EndLoc;
/// \brief Numbers of clauses.
const unsigned NumClauses;
/// \brief Number of child expressions/stmts.
const unsigned NumChildren;
/// \brief Offset from this to the start of clauses.
/// There are NumClauses pointers to clauses, they are followed by
/// NumChildren pointers to child stmts/exprs (if the directive type
/// requires an associated stmt, then it has to be the first of them).
const unsigned ClausesOffset;
/// \brief Get the clauses storage.
MutableArrayRef<OMPClause *> getClauses() {
OMPClause **ClauseStorage = reinterpret_cast<OMPClause **>(
reinterpret_cast<char *>(this) + ClausesOffset);
return MutableArrayRef<OMPClause *>(ClauseStorage, NumClauses);
}
protected:
/// \brief Build instance of directive of class \a K.
///
/// \param SC Statement class.
/// \param K Kind of OpenMP directive.
/// \param StartLoc Starting location of the directive (directive keyword).
/// \param EndLoc Ending location of the directive.
///
template <typename T>
OMPExecutableDirective(const T *, StmtClass SC, OpenMPDirectiveKind K,
SourceLocation StartLoc, SourceLocation EndLoc,
unsigned NumClauses, unsigned NumChildren)
: Stmt(SC), Kind(K), StartLoc(std::move(StartLoc)),
EndLoc(std::move(EndLoc)), NumClauses(NumClauses),
NumChildren(NumChildren),
ClausesOffset(llvm::alignTo(sizeof(T), alignof(OMPClause *))) {}
/// \brief Sets the list of variables for this clause.
///
/// \param Clauses The list of clauses for the directive.
///
void setClauses(ArrayRef<OMPClause *> Clauses);
/// \brief Set the associated statement for the directive.
///
/// /param S Associated statement.
///
void setAssociatedStmt(Stmt *S) {
assert(hasAssociatedStmt() && "no associated statement.");
*child_begin() = S;
}
public:
/// \brief Iterates over a filtered subrange of clauses applied to a
/// directive.
///
/// This iterator visits only clauses of type SpecificClause.
template <typename SpecificClause>
class specific_clause_iterator
: public llvm::iterator_adaptor_base<
specific_clause_iterator<SpecificClause>,
ArrayRef<OMPClause *>::const_iterator, std::forward_iterator_tag,
const SpecificClause *, ptrdiff_t, const SpecificClause *,
const SpecificClause *> {
ArrayRef<OMPClause *>::const_iterator End;
void SkipToNextClause() {
while (this->I != End && !isa<SpecificClause>(*this->I))
++this->I;
}
public:
explicit specific_clause_iterator(ArrayRef<OMPClause *> Clauses)
: specific_clause_iterator::iterator_adaptor_base(Clauses.begin()),
End(Clauses.end()) {
SkipToNextClause();
}
const SpecificClause *operator*() const {
return cast<SpecificClause>(*this->I);
}
const SpecificClause *operator->() const { return **this; }
specific_clause_iterator &operator++() {
++this->I;
SkipToNextClause();
return *this;
}
};
template <typename SpecificClause>
static llvm::iterator_range<specific_clause_iterator<SpecificClause>>
getClausesOfKind(ArrayRef<OMPClause *> Clauses) {
return {specific_clause_iterator<SpecificClause>(Clauses),
specific_clause_iterator<SpecificClause>(
llvm::makeArrayRef(Clauses.end(), 0))};
}
template <typename SpecificClause>
llvm::iterator_range<specific_clause_iterator<SpecificClause>>
getClausesOfKind() const {
return getClausesOfKind<SpecificClause>(clauses());
}
/// Gets a single clause of the specified kind associated with the
/// current directive iff there is only one clause of this kind (and assertion
/// is fired if there is more than one clause is associated with the
/// directive). Returns nullptr if no clause of this kind is associated with
/// the directive.
template <typename SpecificClause>
const SpecificClause *getSingleClause() const {
auto Clauses = getClausesOfKind<SpecificClause>();
if (Clauses.begin() != Clauses.end()) {
assert(std::next(Clauses.begin()) == Clauses.end() &&
"There are at least 2 clauses of the specified kind");
return *Clauses.begin();
}
return nullptr;
}
/// Returns true if the current directive has one or more clauses of a
/// specific kind.
template <typename SpecificClause>
bool hasClausesOfKind() const {
auto Clauses = getClausesOfKind<SpecificClause>();
return Clauses.begin() != Clauses.end();
}
/// \brief Returns starting location of directive kind.
SourceLocation getLocStart() const { return StartLoc; }
/// \brief Returns ending location of directive.
SourceLocation getLocEnd() const { return EndLoc; }
/// \brief Set starting location of directive kind.
///
/// \param Loc New starting location of directive.
///
void setLocStart(SourceLocation Loc) { StartLoc = Loc; }
/// \brief Set ending location of directive.
///
/// \param Loc New ending location of directive.
///
void setLocEnd(SourceLocation Loc) { EndLoc = Loc; }
/// \brief Get number of clauses.
unsigned getNumClauses() const { return NumClauses; }
/// \brief Returns specified clause.
///
/// \param i Number of clause.
///
OMPClause *getClause(unsigned i) const { return clauses()[i]; }
/// \brief Returns true if directive has associated statement.
bool hasAssociatedStmt() const { return NumChildren > 0; }
/// \brief Returns statement associated with the directive.
const Stmt *getAssociatedStmt() const {
assert(hasAssociatedStmt() && "no associated statement.");
return *child_begin();
}
Stmt *getAssociatedStmt() {
assert(hasAssociatedStmt() && "no associated statement.");
return *child_begin();
}
/// \brief Returns the captured statement associated with the
/// component region within the (combined) directive.
//
// \param RegionKind Component region kind.
const CapturedStmt *getCapturedStmt(OpenMPDirectiveKind RegionKind) const {
SmallVector<OpenMPDirectiveKind, 4> CaptureRegions;
getOpenMPCaptureRegions(CaptureRegions, getDirectiveKind());
assert(std::any_of(
CaptureRegions.begin(), CaptureRegions.end(),
[=](const OpenMPDirectiveKind K) { return K == RegionKind; }) &&
"RegionKind not found in OpenMP CaptureRegions.");
auto *CS = cast<CapturedStmt>(getAssociatedStmt());
for (auto ThisCaptureRegion : CaptureRegions) {
if (ThisCaptureRegion == RegionKind)
return CS;
CS = cast<CapturedStmt>(CS->getCapturedStmt());
}
llvm_unreachable("Incorrect RegionKind specified for directive.");
}
/// Get innermost captured statement for the construct.
CapturedStmt *getInnermostCapturedStmt() {
assert(hasAssociatedStmt() && getAssociatedStmt() &&
"Must have associated statement.");
SmallVector<OpenMPDirectiveKind, 4> CaptureRegions;
getOpenMPCaptureRegions(CaptureRegions, getDirectiveKind());
assert(!CaptureRegions.empty() &&
"At least one captured statement must be provided.");
auto *CS = cast<CapturedStmt>(getAssociatedStmt());
for (unsigned Level = CaptureRegions.size(); Level > 1; --Level)
CS = cast<CapturedStmt>(CS->getCapturedStmt());
return CS;
}
const CapturedStmt *getInnermostCapturedStmt() const {
return const_cast<OMPExecutableDirective *>(this)
->getInnermostCapturedStmt();
}
OpenMPDirectiveKind getDirectiveKind() const { return Kind; }
static bool classof(const Stmt *S) {
return S->getStmtClass() >= firstOMPExecutableDirectiveConstant &&
S->getStmtClass() <= lastOMPExecutableDirectiveConstant;
}
child_range children() {
if (!hasAssociatedStmt())
return child_range(child_iterator(), child_iterator());
Stmt **ChildStorage = reinterpret_cast<Stmt **>(getClauses().end());
return child_range(ChildStorage, ChildStorage + NumChildren);
}
ArrayRef<OMPClause *> clauses() { return getClauses(); }
ArrayRef<OMPClause *> clauses() const {
return const_cast<OMPExecutableDirective *>(this)->getClauses();
}
};
/// \brief This represents '#pragma omp parallel' directive.
///
/// \code
/// #pragma omp parallel private(a,b) reduction(+: c,d)
/// \endcode
/// In this example directive '#pragma omp parallel' has clauses 'private'
/// with the variables 'a' and 'b' and 'reduction' with operator '+' and
/// variables 'c' and 'd'.
///
class OMPParallelDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
/// \brief true if the construct has inner cancel directive.
bool HasCancel;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive (directive keyword).
/// \param EndLoc Ending Location of the directive.
///
OMPParallelDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned NumClauses)
: OMPExecutableDirective(this, OMPParallelDirectiveClass, OMPD_parallel,
StartLoc, EndLoc, NumClauses, 1),
HasCancel(false) {}
/// \brief Build an empty directive.
///
/// \param NumClauses Number of clauses.
///
explicit OMPParallelDirective(unsigned NumClauses)
: OMPExecutableDirective(this, OMPParallelDirectiveClass, OMPD_parallel,
SourceLocation(), SourceLocation(), NumClauses,
1),
HasCancel(false) {}
/// \brief Set cancel state.
void setHasCancel(bool Has) { HasCancel = Has; }
public:
/// \brief Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement associated with the directive.
/// \param HasCancel true if this directive has inner cancel directive.
///
static OMPParallelDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
ArrayRef<OMPClause *> Clauses, Stmt *AssociatedStmt, bool HasCancel);
/// \brief Creates an empty directive with the place for \a N clauses.
///
/// \param C AST context.
/// \param NumClauses Number of clauses.
///
static OMPParallelDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses, EmptyShell);
/// \brief Return true if current directive has inner cancel directive.
bool hasCancel() const { return HasCancel; }
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPParallelDirectiveClass;
}
};
/// \brief This is a common base class for loop directives ('omp simd', 'omp
/// for', 'omp for simd' etc.). It is responsible for the loop code generation.
///
class OMPLoopDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
/// \brief Number of collapsed loops as specified by 'collapse' clause.
unsigned CollapsedNum;
/// \brief Offsets to the stored exprs.
/// This enumeration contains offsets to all the pointers to children
/// expressions stored in OMPLoopDirective.
/// The first 9 children are necessary for all the loop directives,
/// the next 8 are specific to the worksharing ones, and the next 11 are
/// used for combined constructs containing two pragmas associated to loops.
/// After the fixed children, three arrays of length CollapsedNum are
/// allocated: loop counters, their updates and final values.
/// PrevLowerBound and PrevUpperBound are used to communicate blocking
/// information in composite constructs which require loop blocking
/// DistInc is used to generate the increment expression for the distribute
/// loop when combined with a further nested loop
/// PrevEnsureUpperBound is used as the EnsureUpperBound expression for the
/// for loop when combined with a previous distribute loop in the same pragma
/// (e.g. 'distribute parallel for')
///
enum {
AssociatedStmtOffset = 0,
IterationVariableOffset = 1,
LastIterationOffset = 2,
CalcLastIterationOffset = 3,
PreConditionOffset = 4,
CondOffset = 5,
InitOffset = 6,
IncOffset = 7,
PreInitsOffset = 8,
// The '...End' enumerators do not correspond to child expressions - they
// specify the offset to the end (and start of the following counters/
// updates/finals arrays).
DefaultEnd = 9,
// The following 8 exprs are used by worksharing and distribute loops only.
IsLastIterVariableOffset = 9,
LowerBoundVariableOffset = 10,
UpperBoundVariableOffset = 11,
StrideVariableOffset = 12,
EnsureUpperBoundOffset = 13,
NextLowerBoundOffset = 14,
NextUpperBoundOffset = 15,
NumIterationsOffset = 16,
// Offset to the end for worksharing loop directives.
WorksharingEnd = 17,
PrevLowerBoundVariableOffset = 17,
PrevUpperBoundVariableOffset = 18,
DistIncOffset = 19,
PrevEnsureUpperBoundOffset = 20,
CombinedLowerBoundVariableOffset = 21,
CombinedUpperBoundVariableOffset = 22,
CombinedEnsureUpperBoundOffset = 23,
CombinedInitOffset = 24,
CombinedConditionOffset = 25,
CombinedNextLowerBoundOffset = 26,
CombinedNextUpperBoundOffset = 27,
// Offset to the end (and start of the following counters/updates/finals
// arrays) for combined distribute loop directives.
CombinedDistributeEnd = 28,
};
/// \brief Get the counters storage.
MutableArrayRef<Expr *> getCounters() {
Expr **Storage = reinterpret_cast<Expr **>(
&(*(std::next(child_begin(), getArraysOffset(getDirectiveKind())))));
return MutableArrayRef<Expr *>(Storage, CollapsedNum);
}
/// \brief Get the private counters storage.
MutableArrayRef<Expr *> getPrivateCounters() {
Expr **Storage = reinterpret_cast<Expr **>(&*std::next(
child_begin(), getArraysOffset(getDirectiveKind()) + CollapsedNum));
return MutableArrayRef<Expr *>(Storage, CollapsedNum);
}
/// \brief Get the updates storage.
MutableArrayRef<Expr *> getInits() {
Expr **Storage = reinterpret_cast<Expr **>(
&*std::next(child_begin(),
getArraysOffset(getDirectiveKind()) + 2 * CollapsedNum));
return MutableArrayRef<Expr *>(Storage, CollapsedNum);
}
/// \brief Get the updates storage.
MutableArrayRef<Expr *> getUpdates() {
Expr **Storage = reinterpret_cast<Expr **>(
&*std::next(child_begin(),
getArraysOffset(getDirectiveKind()) + 3 * CollapsedNum));
return MutableArrayRef<Expr *>(Storage, CollapsedNum);
}
/// \brief Get the final counter updates storage.
MutableArrayRef<Expr *> getFinals() {
Expr **Storage = reinterpret_cast<Expr **>(
&*std::next(child_begin(),
getArraysOffset(getDirectiveKind()) + 4 * CollapsedNum));
return MutableArrayRef<Expr *>(Storage, CollapsedNum);
}
protected:
/// \brief Build instance of loop directive of class \a Kind.
///
/// \param SC Statement class.
/// \param Kind Kind of OpenMP directive.
/// \param StartLoc Starting location of the directive (directive keyword).
/// \param EndLoc Ending location of the directive.
/// \param CollapsedNum Number of collapsed loops from 'collapse' clause.
/// \param NumClauses Number of clauses.
/// \param NumSpecialChildren Number of additional directive-specific stmts.
///
template <typename T>
OMPLoopDirective(const T *That, StmtClass SC, OpenMPDirectiveKind Kind,
SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, unsigned NumClauses,
unsigned NumSpecialChildren = 0)
: OMPExecutableDirective(That, SC, Kind, StartLoc, EndLoc, NumClauses,
numLoopChildren(CollapsedNum, Kind) +
NumSpecialChildren),
CollapsedNum(CollapsedNum) {}
/// \brief Offset to the start of children expression arrays.
static unsigned getArraysOffset(OpenMPDirectiveKind Kind) {
if (isOpenMPLoopBoundSharingDirective(Kind))
return CombinedDistributeEnd;
if (isOpenMPWorksharingDirective(Kind) || isOpenMPTaskLoopDirective(Kind) ||
isOpenMPDistributeDirective(Kind))
return WorksharingEnd;
return DefaultEnd;
}
/// \brief Children number.
static unsigned numLoopChildren(unsigned CollapsedNum,
OpenMPDirectiveKind Kind) {
return getArraysOffset(Kind) + 5 * CollapsedNum; // Counters,
// PrivateCounters, Inits,
// Updates and Finals
}
void setIterationVariable(Expr *IV) {
*std::next(child_begin(), IterationVariableOffset) = IV;
}
void setLastIteration(Expr *LI) {
*std::next(child_begin(), LastIterationOffset) = LI;
}
void setCalcLastIteration(Expr *CLI) {
*std::next(child_begin(), CalcLastIterationOffset) = CLI;
}
void setPreCond(Expr *PC) {
*std::next(child_begin(), PreConditionOffset) = PC;
}
void setCond(Expr *Cond) {
*std::next(child_begin(), CondOffset) = Cond;
}
void setInit(Expr *Init) { *std::next(child_begin(), InitOffset) = Init; }
void setInc(Expr *Inc) { *std::next(child_begin(), IncOffset) = Inc; }
void setPreInits(Stmt *PreInits) {
*std::next(child_begin(), PreInitsOffset) = PreInits;
}
void setIsLastIterVariable(Expr *IL) {
assert((isOpenMPWorksharingDirective(getDirectiveKind()) ||
isOpenMPTaskLoopDirective(getDirectiveKind()) ||
isOpenMPDistributeDirective(getDirectiveKind())) &&
"expected worksharing loop directive");
*std::next(child_begin(), IsLastIterVariableOffset) = IL;
}
void setLowerBoundVariable(Expr *LB) {
assert((isOpenMPWorksharingDirective(getDirectiveKind()) ||
isOpenMPTaskLoopDirective(getDirectiveKind()) ||
isOpenMPDistributeDirective(getDirectiveKind())) &&
"expected worksharing loop directive");
*std::next(child_begin(), LowerBoundVariableOffset) = LB;
}
void setUpperBoundVariable(Expr *UB) {
assert((isOpenMPWorksharingDirective(getDirectiveKind()) ||
isOpenMPTaskLoopDirective(getDirectiveKind()) ||
isOpenMPDistributeDirective(getDirectiveKind())) &&
"expected worksharing loop directive");
*std::next(child_begin(), UpperBoundVariableOffset) = UB;
}
void setStrideVariable(Expr *ST) {
assert((isOpenMPWorksharingDirective(getDirectiveKind()) ||
isOpenMPTaskLoopDirective(getDirectiveKind()) ||
isOpenMPDistributeDirective(getDirectiveKind())) &&
"expected worksharing loop directive");
*std::next(child_begin(), StrideVariableOffset) = ST;
}
void setEnsureUpperBound(Expr *EUB) {
assert((isOpenMPWorksharingDirective(getDirectiveKind()) ||
isOpenMPTaskLoopDirective(getDirectiveKind()) ||
isOpenMPDistributeDirective(getDirectiveKind())) &&
"expected worksharing loop directive");
*std::next(child_begin(), EnsureUpperBoundOffset) = EUB;
}
void setNextLowerBound(Expr *NLB) {
assert((isOpenMPWorksharingDirective(getDirectiveKind()) ||
isOpenMPTaskLoopDirective(getDirectiveKind()) ||
isOpenMPDistributeDirective(getDirectiveKind())) &&
"expected worksharing loop directive");
*std::next(child_begin(), NextLowerBoundOffset) = NLB;
}
void setNextUpperBound(Expr *NUB) {
assert((isOpenMPWorksharingDirective(getDirectiveKind()) ||
isOpenMPTaskLoopDirective(getDirectiveKind()) ||
isOpenMPDistributeDirective(getDirectiveKind())) &&
"expected worksharing loop directive");
*std::next(child_begin(), NextUpperBoundOffset) = NUB;
}
void setNumIterations(Expr *NI) {
assert((isOpenMPWorksharingDirective(getDirectiveKind()) ||
isOpenMPTaskLoopDirective(getDirectiveKind()) ||
isOpenMPDistributeDirective(getDirectiveKind())) &&
"expected worksharing loop directive");
*std::next(child_begin(), NumIterationsOffset) = NI;
}
void setPrevLowerBoundVariable(Expr *PrevLB) {
assert(isOpenMPLoopBoundSharingDirective(getDirectiveKind()) &&
"expected loop bound sharing directive");
*std::next(child_begin(), PrevLowerBoundVariableOffset) = PrevLB;
}
void setPrevUpperBoundVariable(Expr *PrevUB) {
assert(isOpenMPLoopBoundSharingDirective(getDirectiveKind()) &&
"expected loop bound sharing directive");
*std::next(child_begin(), PrevUpperBoundVariableOffset) = PrevUB;
}
void setDistInc(Expr *DistInc) {
assert(isOpenMPLoopBoundSharingDirective(getDirectiveKind()) &&
"expected loop bound sharing directive");
*std::next(child_begin(), DistIncOffset) = DistInc;
}
void setPrevEnsureUpperBound(Expr *PrevEUB) {
assert(isOpenMPLoopBoundSharingDirective(getDirectiveKind()) &&
"expected loop bound sharing directive");
*std::next(child_begin(), PrevEnsureUpperBoundOffset) = PrevEUB;
}
void setCombinedLowerBoundVariable(Expr *CombLB) {
assert(isOpenMPLoopBoundSharingDirective(getDirectiveKind()) &&
"expected loop bound sharing directive");
*std::next(child_begin(), CombinedLowerBoundVariableOffset) = CombLB;
}
void setCombinedUpperBoundVariable(Expr *CombUB) {
assert(isOpenMPLoopBoundSharingDirective(getDirectiveKind()) &&
"expected loop bound sharing directive");
*std::next(child_begin(), CombinedUpperBoundVariableOffset) = CombUB;
}
void setCombinedEnsureUpperBound(Expr *CombEUB) {
assert(isOpenMPLoopBoundSharingDirective(getDirectiveKind()) &&
"expected loop bound sharing directive");
*std::next(child_begin(), CombinedEnsureUpperBoundOffset) = CombEUB;
}
void setCombinedInit(Expr *CombInit) {
assert(isOpenMPLoopBoundSharingDirective(getDirectiveKind()) &&
"expected loop bound sharing directive");
*std::next(child_begin(), CombinedInitOffset) = CombInit;
}
void setCombinedCond(Expr *CombCond) {
assert(isOpenMPLoopBoundSharingDirective(getDirectiveKind()) &&
"expected loop bound sharing directive");
*std::next(child_begin(), CombinedConditionOffset) = CombCond;
}
void setCombinedNextLowerBound(Expr *CombNLB) {
assert(isOpenMPLoopBoundSharingDirective(getDirectiveKind()) &&
"expected loop bound sharing directive");
*std::next(child_begin(), CombinedNextLowerBoundOffset) = CombNLB;
}
void setCombinedNextUpperBound(Expr *CombNUB) {
assert(isOpenMPLoopBoundSharingDirective(getDirectiveKind()) &&
"expected loop bound sharing directive");
*std::next(child_begin(), CombinedNextUpperBoundOffset) = CombNUB;
}
void setCounters(ArrayRef<Expr *> A);
void setPrivateCounters(ArrayRef<Expr *> A);
void setInits(ArrayRef<Expr *> A);
void setUpdates(ArrayRef<Expr *> A);
void setFinals(ArrayRef<Expr *> A);
public:
/// The expressions built to support OpenMP loops in combined/composite
/// pragmas (e.g. pragma omp distribute parallel for)
struct DistCombinedHelperExprs {
/// DistributeLowerBound - used when composing 'omp distribute' with
/// 'omp for' in a same construct.
Expr *LB;
/// DistributeUpperBound - used when composing 'omp distribute' with
/// 'omp for' in a same construct.
Expr *UB;
/// DistributeEnsureUpperBound - used when composing 'omp distribute'
/// with 'omp for' in a same construct, EUB depends on DistUB
Expr *EUB;
/// Distribute loop iteration variable init used when composing 'omp
/// distribute'
/// with 'omp for' in a same construct
Expr *Init;
/// Distribute Loop condition used when composing 'omp distribute'
/// with 'omp for' in a same construct
Expr *Cond;
/// Update of LowerBound for statically sheduled omp loops for
/// outer loop in combined constructs (e.g. 'distribute parallel for')
Expr *NLB;
/// Update of UpperBound for statically sheduled omp loops for
/// outer loop in combined constructs (e.g. 'distribute parallel for')
Expr *NUB;
};
/// \brief The expressions built for the OpenMP loop CodeGen for the
/// whole collapsed loop nest.
struct HelperExprs {
/// \brief Loop iteration variable.
Expr *IterationVarRef;
/// \brief Loop last iteration number.
Expr *LastIteration;
/// \brief Loop number of iterations.
Expr *NumIterations;
/// \brief Calculation of last iteration.
Expr *CalcLastIteration;
/// \brief Loop pre-condition.
Expr *PreCond;
/// \brief Loop condition.
Expr *Cond;
/// \brief Loop iteration variable init.
Expr *Init;
/// \brief Loop increment.
Expr *Inc;
/// \brief IsLastIteration - local flag variable passed to runtime.
Expr *IL;
/// \brief LowerBound - local variable passed to runtime.
Expr *LB;
/// \brief UpperBound - local variable passed to runtime.
Expr *UB;
/// \brief Stride - local variable passed to runtime.
Expr *ST;
/// \brief EnsureUpperBound -- expression UB = min(UB, NumIterations).
Expr *EUB;
/// \brief Update of LowerBound for statically sheduled 'omp for' loops.
Expr *NLB;
/// \brief Update of UpperBound for statically sheduled 'omp for' loops.
Expr *NUB;
/// \brief PreviousLowerBound - local variable passed to runtime in the
/// enclosing schedule or null if that does not apply.
Expr *PrevLB;
/// \brief PreviousUpperBound - local variable passed to runtime in the
/// enclosing schedule or null if that does not apply.
Expr *PrevUB;
/// \brief DistInc - increment expression for distribute loop when found
/// combined with a further loop level (e.g. in 'distribute parallel for')
/// expression IV = IV + ST
Expr *DistInc;
/// \brief PrevEUB - expression similar to EUB but to be used when loop
/// scheduling uses PrevLB and PrevUB (e.g. in 'distribute parallel for'
/// when ensuring that the UB is either the calculated UB by the runtime or
/// the end of the assigned distribute chunk)
/// expression UB = min (UB, PrevUB)
Expr *PrevEUB;
/// \brief Counters Loop counters.
SmallVector<Expr *, 4> Counters;
/// \brief PrivateCounters Loop counters.
SmallVector<Expr *, 4> PrivateCounters;
/// \brief Expressions for loop counters inits for CodeGen.
SmallVector<Expr *, 4> Inits;
/// \brief Expressions for loop counters update for CodeGen.
SmallVector<Expr *, 4> Updates;
/// \brief Final loop counter values for GodeGen.
SmallVector<Expr *, 4> Finals;
/// Init statement for all captured expressions.
Stmt *PreInits;
/// Expressions used when combining OpenMP loop pragmas
DistCombinedHelperExprs DistCombinedFields;
/// \brief Check if all the expressions are built (does not check the
/// worksharing ones).
bool builtAll() {
return IterationVarRef != nullptr && LastIteration != nullptr &&
NumIterations != nullptr && PreCond != nullptr &&
Cond != nullptr && Init != nullptr && Inc != nullptr;
}
/// \brief Initialize all the fields to null.
/// \param Size Number of elements in the counters/finals/updates arrays.
void clear(unsigned Size) {
IterationVarRef = nullptr;
LastIteration = nullptr;
CalcLastIteration = nullptr;
PreCond = nullptr;
Cond = nullptr;
Init = nullptr;
Inc = nullptr;
IL = nullptr;
LB = nullptr;
UB = nullptr;
ST = nullptr;
EUB = nullptr;
NLB = nullptr;
NUB = nullptr;
NumIterations = nullptr;
PrevLB = nullptr;
PrevUB = nullptr;
DistInc = nullptr;
PrevEUB = nullptr;
Counters.resize(Size);
PrivateCounters.resize(Size);
Inits.resize(Size);
Updates.resize(Size);
Finals.resize(Size);
for (unsigned i = 0; i < Size; ++i) {
Counters[i] = nullptr;
PrivateCounters[i] = nullptr;
Inits[i] = nullptr;
Updates[i] = nullptr;
Finals[i] = nullptr;
}
PreInits = nullptr;
DistCombinedFields.LB = nullptr;
DistCombinedFields.UB = nullptr;
DistCombinedFields.EUB = nullptr;
DistCombinedFields.Init = nullptr;
DistCombinedFields.Cond = nullptr;
DistCombinedFields.NLB = nullptr;
DistCombinedFields.NUB = nullptr;
}
};
/// \brief Get number of collapsed loops.
unsigned getCollapsedNumber() const { return CollapsedNum; }
Expr *getIterationVariable() const {
return const_cast<Expr *>(reinterpret_cast<const Expr *>(
*std::next(child_begin(), IterationVariableOffset)));
}
Expr *getLastIteration() const {
return const_cast<Expr *>(reinterpret_cast<const Expr *>(
*std::next(child_begin(), LastIterationOffset)));
}
Expr *getCalcLastIteration() const {
return const_cast<Expr *>(reinterpret_cast<const Expr *>(
*std::next(child_begin(), CalcLastIterationOffset)));
}
Expr *getPreCond() const {
return const_cast<Expr *>(reinterpret_cast<const Expr *>(
*std::next(child_begin(), PreConditionOffset)));
}
Expr *getCond() const {
return const_cast<Expr *>(
reinterpret_cast<const Expr *>(*std::next(child_begin(), CondOffset)));
}
Expr *getInit() const {
return const_cast<Expr *>(
reinterpret_cast<const Expr *>(*std::next(child_begin(), InitOffset)));
}
Expr *getInc() const {
return const_cast<Expr *>(
reinterpret_cast<const Expr *>(*std::next(child_begin(), IncOffset)));
}
const Stmt *getPreInits() const {
return *std::next(child_begin(), PreInitsOffset);
}
Stmt *getPreInits() { return *std::next(child_begin(), PreInitsOffset); }
Expr *getIsLastIterVariable() const {
assert((isOpenMPWorksharingDirective(getDirectiveKind()) ||
isOpenMPTaskLoopDirective(getDirectiveKind()) ||
isOpenMPDistributeDirective(getDirectiveKind())) &&
"expected worksharing loop directive");
return const_cast<Expr *>(reinterpret_cast<const Expr *>(
*std::next(child_begin(), IsLastIterVariableOffset)));
}
Expr *getLowerBoundVariable() const {
assert((isOpenMPWorksharingDirective(getDirectiveKind()) ||
isOpenMPTaskLoopDirective(getDirectiveKind()) ||
isOpenMPDistributeDirective(getDirectiveKind())) &&
"expected worksharing loop directive");
return const_cast<Expr *>(reinterpret_cast<const Expr *>(
*std::next(child_begin(), LowerBoundVariableOffset)));
}
Expr *getUpperBoundVariable() const {
assert((isOpenMPWorksharingDirective(getDirectiveKind()) ||
isOpenMPTaskLoopDirective(getDirectiveKind()) ||
isOpenMPDistributeDirective(getDirectiveKind())) &&
"expected worksharing loop directive");
return const_cast<Expr *>(reinterpret_cast<const Expr *>(
*std::next(child_begin(), UpperBoundVariableOffset)));
}
Expr *getStrideVariable() const {
assert((isOpenMPWorksharingDirective(getDirectiveKind()) ||
isOpenMPTaskLoopDirective(getDirectiveKind()) ||
isOpenMPDistributeDirective(getDirectiveKind())) &&
"expected worksharing loop directive");
return const_cast<Expr *>(reinterpret_cast<const Expr *>(
*std::next(child_begin(), StrideVariableOffset)));
}
Expr *getEnsureUpperBound() const {
assert((isOpenMPWorksharingDirective(getDirectiveKind()) ||
isOpenMPTaskLoopDirective(getDirectiveKind()) ||
isOpenMPDistributeDirective(getDirectiveKind())) &&
"expected worksharing loop directive");
return const_cast<Expr *>(reinterpret_cast<const Expr *>(
*std::next(child_begin(), EnsureUpperBoundOffset)));
}
Expr *getNextLowerBound() const {
assert((isOpenMPWorksharingDirective(getDirectiveKind()) ||
isOpenMPTaskLoopDirective(getDirectiveKind()) ||
isOpenMPDistributeDirective(getDirectiveKind())) &&
"expected worksharing loop directive");
return const_cast<Expr *>(reinterpret_cast<const Expr *>(
*std::next(child_begin(), NextLowerBoundOffset)));
}
Expr *getNextUpperBound() const {
assert((isOpenMPWorksharingDirective(getDirectiveKind()) ||
isOpenMPTaskLoopDirective(getDirectiveKind()) ||
isOpenMPDistributeDirective(getDirectiveKind())) &&
"expected worksharing loop directive");
return const_cast<Expr *>(reinterpret_cast<const Expr *>(
*std::next(child_begin(), NextUpperBoundOffset)));
}
Expr *getNumIterations() const {
assert((isOpenMPWorksharingDirective(getDirectiveKind()) ||
isOpenMPTaskLoopDirective(getDirectiveKind()) ||
isOpenMPDistributeDirective(getDirectiveKind())) &&
"expected worksharing loop directive");
return const_cast<Expr *>(reinterpret_cast<const Expr *>(
*std::next(child_begin(), NumIterationsOffset)));
}
Expr *getPrevLowerBoundVariable() const {
assert(isOpenMPLoopBoundSharingDirective(getDirectiveKind()) &&
"expected loop bound sharing directive");
return const_cast<Expr *>(reinterpret_cast<const Expr *>(
*std::next(child_begin(), PrevLowerBoundVariableOffset)));
}
Expr *getPrevUpperBoundVariable() const {
assert(isOpenMPLoopBoundSharingDirective(getDirectiveKind()) &&
"expected loop bound sharing directive");
return const_cast<Expr *>(reinterpret_cast<const Expr *>(
*std::next(child_begin(), PrevUpperBoundVariableOffset)));
}
Expr *getDistInc() const {
assert(isOpenMPLoopBoundSharingDirective(getDirectiveKind()) &&
"expected loop bound sharing directive");
return const_cast<Expr *>(reinterpret_cast<const Expr *>(
*std::next(child_begin(), DistIncOffset)));
}
Expr *getPrevEnsureUpperBound() const {
assert(isOpenMPLoopBoundSharingDirective(getDirectiveKind()) &&
"expected loop bound sharing directive");
return const_cast<Expr *>(reinterpret_cast<const Expr *>(
*std::next(child_begin(), PrevEnsureUpperBoundOffset)));
}
Expr *getCombinedLowerBoundVariable() const {
assert(isOpenMPLoopBoundSharingDirective(getDirectiveKind()) &&
"expected loop bound sharing directive");
return const_cast<Expr *>(reinterpret_cast<const Expr *>(
*std::next(child_begin(), CombinedLowerBoundVariableOffset)));
}
Expr *getCombinedUpperBoundVariable() const {
assert(isOpenMPLoopBoundSharingDirective(getDirectiveKind()) &&
"expected loop bound sharing directive");
return const_cast<Expr *>(reinterpret_cast<const Expr *>(
*std::next(child_begin(), CombinedUpperBoundVariableOffset)));
}
Expr *getCombinedEnsureUpperBound() const {
assert(isOpenMPLoopBoundSharingDirective(getDirectiveKind()) &&
"expected loop bound sharing directive");
return const_cast<Expr *>(reinterpret_cast<const Expr *>(
*std::next(child_begin(), CombinedEnsureUpperBoundOffset)));
}
Expr *getCombinedInit() const {
assert(isOpenMPLoopBoundSharingDirective(getDirectiveKind()) &&
"expected loop bound sharing directive");
return const_cast<Expr *>(reinterpret_cast<const Expr *>(
*std::next(child_begin(), CombinedInitOffset)));
}
Expr *getCombinedCond() const {
assert(isOpenMPLoopBoundSharingDirective(getDirectiveKind()) &&
"expected loop bound sharing directive");
return const_cast<Expr *>(reinterpret_cast<const Expr *>(
*std::next(child_begin(), CombinedConditionOffset)));
}
Expr *getCombinedNextLowerBound() const {
assert(isOpenMPLoopBoundSharingDirective(getDirectiveKind()) &&
"expected loop bound sharing directive");
return const_cast<Expr *>(reinterpret_cast<const Expr *>(
*std::next(child_begin(), CombinedNextLowerBoundOffset)));
}
Expr *getCombinedNextUpperBound() const {
assert(isOpenMPLoopBoundSharingDirective(getDirectiveKind()) &&
"expected loop bound sharing directive");
return const_cast<Expr *>(reinterpret_cast<const Expr *>(
*std::next(child_begin(), CombinedNextUpperBoundOffset)));
}
const Stmt *getBody() const {
// This relies on the loop form is already checked by Sema.
const Stmt *Body =
getInnermostCapturedStmt()->getCapturedStmt()->IgnoreContainers();
Body = cast<ForStmt>(Body)->getBody();
for (unsigned Cnt = 1; Cnt < CollapsedNum; ++Cnt) {
Body = Body->IgnoreContainers();
Body = cast<ForStmt>(Body)->getBody();
}
return Body;
}
ArrayRef<Expr *> counters() { return getCounters(); }
ArrayRef<Expr *> counters() const {
return const_cast<OMPLoopDirective *>(this)->getCounters();
}
ArrayRef<Expr *> private_counters() { return getPrivateCounters(); }
ArrayRef<Expr *> private_counters() const {
return const_cast<OMPLoopDirective *>(this)->getPrivateCounters();
}
ArrayRef<Expr *> inits() { return getInits(); }
ArrayRef<Expr *> inits() const {
return const_cast<OMPLoopDirective *>(this)->getInits();
}
ArrayRef<Expr *> updates() { return getUpdates(); }
ArrayRef<Expr *> updates() const {
return const_cast<OMPLoopDirective *>(this)->getUpdates();
}
ArrayRef<Expr *> finals() { return getFinals(); }
ArrayRef<Expr *> finals() const {
return const_cast<OMPLoopDirective *>(this)->getFinals();
}
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPSimdDirectiveClass ||
T->getStmtClass() == OMPForDirectiveClass ||
T->getStmtClass() == OMPForSimdDirectiveClass ||
T->getStmtClass() == OMPParallelForDirectiveClass ||
T->getStmtClass() == OMPParallelForSimdDirectiveClass ||
T->getStmtClass() == OMPTaskLoopDirectiveClass ||
T->getStmtClass() == OMPTaskLoopSimdDirectiveClass ||
T->getStmtClass() == OMPDistributeDirectiveClass ||
T->getStmtClass() == OMPTargetParallelForDirectiveClass ||
T->getStmtClass() == OMPDistributeParallelForDirectiveClass ||
T->getStmtClass() == OMPDistributeParallelForSimdDirectiveClass ||
T->getStmtClass() == OMPDistributeSimdDirectiveClass ||
T->getStmtClass() == OMPTargetParallelForSimdDirectiveClass ||
T->getStmtClass() == OMPTargetSimdDirectiveClass ||
T->getStmtClass() == OMPTeamsDistributeDirectiveClass ||
T->getStmtClass() == OMPTeamsDistributeSimdDirectiveClass ||
T->getStmtClass() ==
OMPTeamsDistributeParallelForSimdDirectiveClass ||
T->getStmtClass() == OMPTeamsDistributeParallelForDirectiveClass ||
T->getStmtClass() ==
OMPTargetTeamsDistributeParallelForDirectiveClass ||
T->getStmtClass() ==
OMPTargetTeamsDistributeParallelForSimdDirectiveClass ||
T->getStmtClass() == OMPTargetTeamsDistributeDirectiveClass ||
T->getStmtClass() == OMPTargetTeamsDistributeSimdDirectiveClass;
}
};
/// \brief This represents '#pragma omp simd' directive.
///
/// \code
/// #pragma omp simd private(a,b) linear(i,j:s) reduction(+:c,d)
/// \endcode
/// In this example directive '#pragma omp simd' has clauses 'private'
/// with the variables 'a' and 'b', 'linear' with variables 'i', 'j' and
/// linear step 's', 'reduction' with operator '+' and variables 'c' and 'd'.
///
class OMPSimdDirective : public OMPLoopDirective {
friend class ASTStmtReader;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
OMPSimdDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, unsigned NumClauses)
: OMPLoopDirective(this, OMPSimdDirectiveClass, OMPD_simd, StartLoc,
EndLoc, CollapsedNum, NumClauses) {}
/// \brief Build an empty directive.
///
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
explicit OMPSimdDirective(unsigned CollapsedNum, unsigned NumClauses)
: OMPLoopDirective(this, OMPSimdDirectiveClass, OMPD_simd,
SourceLocation(), SourceLocation(), CollapsedNum,
NumClauses) {}
public:
/// \brief Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param CollapsedNum Number of collapsed loops.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param Exprs Helper expressions for CodeGen.
///
static OMPSimdDirective *Create(const ASTContext &C, SourceLocation StartLoc,
SourceLocation EndLoc, unsigned CollapsedNum,
ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt,
const HelperExprs &Exprs);
/// \brief Creates an empty directive with the place
/// for \a NumClauses clauses.
///
/// \param C AST context.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
static OMPSimdDirective *CreateEmpty(const ASTContext &C, unsigned NumClauses,
unsigned CollapsedNum, EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPSimdDirectiveClass;
}
};
/// \brief This represents '#pragma omp for' directive.
///
/// \code
/// #pragma omp for private(a,b) reduction(+:c,d)
/// \endcode
/// In this example directive '#pragma omp for' has clauses 'private' with the
/// variables 'a' and 'b' and 'reduction' with operator '+' and variables 'c'
/// and 'd'.
///
class OMPForDirective : public OMPLoopDirective {
friend class ASTStmtReader;
/// \brief true if current directive has inner cancel directive.
bool HasCancel;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
OMPForDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, unsigned NumClauses)
: OMPLoopDirective(this, OMPForDirectiveClass, OMPD_for, StartLoc, EndLoc,
CollapsedNum, NumClauses),
HasCancel(false) {}
/// \brief Build an empty directive.
///
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
explicit OMPForDirective(unsigned CollapsedNum, unsigned NumClauses)
: OMPLoopDirective(this, OMPForDirectiveClass, OMPD_for, SourceLocation(),
SourceLocation(), CollapsedNum, NumClauses),
HasCancel(false) {}
/// \brief Set cancel state.
void setHasCancel(bool Has) { HasCancel = Has; }
public:
/// \brief Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param CollapsedNum Number of collapsed loops.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param Exprs Helper expressions for CodeGen.
/// \param HasCancel true if current directive has inner cancel directive.
///
static OMPForDirective *Create(const ASTContext &C, SourceLocation StartLoc,
SourceLocation EndLoc, unsigned CollapsedNum,
ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt, const HelperExprs &Exprs,
bool HasCancel);
/// \brief Creates an empty directive with the place
/// for \a NumClauses clauses.
///
/// \param C AST context.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
static OMPForDirective *CreateEmpty(const ASTContext &C, unsigned NumClauses,
unsigned CollapsedNum, EmptyShell);
/// \brief Return true if current directive has inner cancel directive.
bool hasCancel() const { return HasCancel; }
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPForDirectiveClass;
}
};
/// \brief This represents '#pragma omp for simd' directive.
///
/// \code
/// #pragma omp for simd private(a,b) linear(i,j:s) reduction(+:c,d)
/// \endcode
/// In this example directive '#pragma omp for simd' has clauses 'private'
/// with the variables 'a' and 'b', 'linear' with variables 'i', 'j' and
/// linear step 's', 'reduction' with operator '+' and variables 'c' and 'd'.
///
class OMPForSimdDirective : public OMPLoopDirective {
friend class ASTStmtReader;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
OMPForSimdDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, unsigned NumClauses)
: OMPLoopDirective(this, OMPForSimdDirectiveClass, OMPD_for_simd,
StartLoc, EndLoc, CollapsedNum, NumClauses) {}
/// \brief Build an empty directive.
///
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
explicit OMPForSimdDirective(unsigned CollapsedNum, unsigned NumClauses)
: OMPLoopDirective(this, OMPForSimdDirectiveClass, OMPD_for_simd,
SourceLocation(), SourceLocation(), CollapsedNum,
NumClauses) {}
public:
/// \brief Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param CollapsedNum Number of collapsed loops.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param Exprs Helper expressions for CodeGen.
///
static OMPForSimdDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt, const HelperExprs &Exprs);
/// \brief Creates an empty directive with the place
/// for \a NumClauses clauses.
///
/// \param C AST context.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
static OMPForSimdDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses,
unsigned CollapsedNum, EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPForSimdDirectiveClass;
}
};
/// \brief This represents '#pragma omp sections' directive.
///
/// \code
/// #pragma omp sections private(a,b) reduction(+:c,d)
/// \endcode
/// In this example directive '#pragma omp sections' has clauses 'private' with
/// the variables 'a' and 'b' and 'reduction' with operator '+' and variables
/// 'c' and 'd'.
///
class OMPSectionsDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
/// \brief true if current directive has inner cancel directive.
bool HasCancel;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param NumClauses Number of clauses.
///
OMPSectionsDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned NumClauses)
: OMPExecutableDirective(this, OMPSectionsDirectiveClass, OMPD_sections,
StartLoc, EndLoc, NumClauses, 1),
HasCancel(false) {}
/// \brief Build an empty directive.
///
/// \param NumClauses Number of clauses.
///
explicit OMPSectionsDirective(unsigned NumClauses)
: OMPExecutableDirective(this, OMPSectionsDirectiveClass, OMPD_sections,
SourceLocation(), SourceLocation(), NumClauses,
1),
HasCancel(false) {}
/// \brief Set cancel state.
void setHasCancel(bool Has) { HasCancel = Has; }
public:
/// \brief Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param HasCancel true if current directive has inner directive.
///
static OMPSectionsDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
ArrayRef<OMPClause *> Clauses, Stmt *AssociatedStmt, bool HasCancel);
/// \brief Creates an empty directive with the place for \a NumClauses
/// clauses.
///
/// \param C AST context.
/// \param NumClauses Number of clauses.
///
static OMPSectionsDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses, EmptyShell);
/// \brief Return true if current directive has inner cancel directive.
bool hasCancel() const { return HasCancel; }
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPSectionsDirectiveClass;
}
};
/// \brief This represents '#pragma omp section' directive.
///
/// \code
/// #pragma omp section
/// \endcode
///
class OMPSectionDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
/// \brief true if current directive has inner cancel directive.
bool HasCancel;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
///
OMPSectionDirective(SourceLocation StartLoc, SourceLocation EndLoc)
: OMPExecutableDirective(this, OMPSectionDirectiveClass, OMPD_section,
StartLoc, EndLoc, 0, 1),
HasCancel(false) {}
/// \brief Build an empty directive.
///
explicit OMPSectionDirective()
: OMPExecutableDirective(this, OMPSectionDirectiveClass, OMPD_section,
SourceLocation(), SourceLocation(), 0, 1),
HasCancel(false) {}
public:
/// \brief Creates directive.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param HasCancel true if current directive has inner directive.
///
static OMPSectionDirective *Create(const ASTContext &C,
SourceLocation StartLoc,
SourceLocation EndLoc,
Stmt *AssociatedStmt, bool HasCancel);
/// \brief Creates an empty directive.
///
/// \param C AST context.
///
static OMPSectionDirective *CreateEmpty(const ASTContext &C, EmptyShell);
/// \brief Set cancel state.
void setHasCancel(bool Has) { HasCancel = Has; }
/// \brief Return true if current directive has inner cancel directive.
bool hasCancel() const { return HasCancel; }
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPSectionDirectiveClass;
}
};
/// \brief This represents '#pragma omp single' directive.
///
/// \code
/// #pragma omp single private(a,b) copyprivate(c,d)
/// \endcode
/// In this example directive '#pragma omp single' has clauses 'private' with
/// the variables 'a' and 'b' and 'copyprivate' with variables 'c' and 'd'.
///
class OMPSingleDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param NumClauses Number of clauses.
///
OMPSingleDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned NumClauses)
: OMPExecutableDirective(this, OMPSingleDirectiveClass, OMPD_single,
StartLoc, EndLoc, NumClauses, 1) {}
/// \brief Build an empty directive.
///
/// \param NumClauses Number of clauses.
///
explicit OMPSingleDirective(unsigned NumClauses)
: OMPExecutableDirective(this, OMPSingleDirectiveClass, OMPD_single,
SourceLocation(), SourceLocation(), NumClauses,
1) {}
public:
/// \brief Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
///
static OMPSingleDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
ArrayRef<OMPClause *> Clauses, Stmt *AssociatedStmt);
/// \brief Creates an empty directive with the place for \a NumClauses
/// clauses.
///
/// \param C AST context.
/// \param NumClauses Number of clauses.
///
static OMPSingleDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses, EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPSingleDirectiveClass;
}
};
/// \brief This represents '#pragma omp master' directive.
///
/// \code
/// #pragma omp master
/// \endcode
///
class OMPMasterDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
///
OMPMasterDirective(SourceLocation StartLoc, SourceLocation EndLoc)
: OMPExecutableDirective(this, OMPMasterDirectiveClass, OMPD_master,
StartLoc, EndLoc, 0, 1) {}
/// \brief Build an empty directive.
///
explicit OMPMasterDirective()
: OMPExecutableDirective(this, OMPMasterDirectiveClass, OMPD_master,
SourceLocation(), SourceLocation(), 0, 1) {}
public:
/// \brief Creates directive.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param AssociatedStmt Statement, associated with the directive.
///
static OMPMasterDirective *Create(const ASTContext &C,
SourceLocation StartLoc,
SourceLocation EndLoc,
Stmt *AssociatedStmt);
/// \brief Creates an empty directive.
///
/// \param C AST context.
///
static OMPMasterDirective *CreateEmpty(const ASTContext &C, EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPMasterDirectiveClass;
}
};
/// \brief This represents '#pragma omp critical' directive.
///
/// \code
/// #pragma omp critical
/// \endcode
///
class OMPCriticalDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
/// \brief Name of the directive.
DeclarationNameInfo DirName;
/// \brief Build directive with the given start and end location.
///
/// \param Name Name of the directive.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param NumClauses Number of clauses.
///
OMPCriticalDirective(const DeclarationNameInfo &Name, SourceLocation StartLoc,
SourceLocation EndLoc, unsigned NumClauses)
: OMPExecutableDirective(this, OMPCriticalDirectiveClass, OMPD_critical,
StartLoc, EndLoc, NumClauses, 1),
DirName(Name) {}
/// \brief Build an empty directive.
///
/// \param NumClauses Number of clauses.
///
explicit OMPCriticalDirective(unsigned NumClauses)
: OMPExecutableDirective(this, OMPCriticalDirectiveClass, OMPD_critical,
SourceLocation(), SourceLocation(), NumClauses,
1),
DirName() {}
/// \brief Set name of the directive.
///
/// \param Name Name of the directive.
///
void setDirectiveName(const DeclarationNameInfo &Name) { DirName = Name; }
public:
/// \brief Creates directive.
///
/// \param C AST context.
/// \param Name Name of the directive.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
///
static OMPCriticalDirective *
Create(const ASTContext &C, const DeclarationNameInfo &Name,
SourceLocation StartLoc, SourceLocation EndLoc,
ArrayRef<OMPClause *> Clauses, Stmt *AssociatedStmt);
/// \brief Creates an empty directive.
///
/// \param C AST context.
/// \param NumClauses Number of clauses.
///
static OMPCriticalDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses, EmptyShell);
/// \brief Return name of the directive.
///
DeclarationNameInfo getDirectiveName() const { return DirName; }
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPCriticalDirectiveClass;
}
};
/// \brief This represents '#pragma omp parallel for' directive.
///
/// \code
/// #pragma omp parallel for private(a,b) reduction(+:c,d)
/// \endcode
/// In this example directive '#pragma omp parallel for' has clauses 'private'
/// with the variables 'a' and 'b' and 'reduction' with operator '+' and
/// variables 'c' and 'd'.
///
class OMPParallelForDirective : public OMPLoopDirective {
friend class ASTStmtReader;
/// \brief true if current region has inner cancel directive.
bool HasCancel;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
OMPParallelForDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, unsigned NumClauses)
: OMPLoopDirective(this, OMPParallelForDirectiveClass, OMPD_parallel_for,
StartLoc, EndLoc, CollapsedNum, NumClauses),
HasCancel(false) {}
/// \brief Build an empty directive.
///
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
explicit OMPParallelForDirective(unsigned CollapsedNum, unsigned NumClauses)
: OMPLoopDirective(this, OMPParallelForDirectiveClass, OMPD_parallel_for,
SourceLocation(), SourceLocation(), CollapsedNum,
NumClauses),
HasCancel(false) {}
/// \brief Set cancel state.
void setHasCancel(bool Has) { HasCancel = Has; }
public:
/// \brief Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param CollapsedNum Number of collapsed loops.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param Exprs Helper expressions for CodeGen.
/// \param HasCancel true if current directive has inner cancel directive.
///
static OMPParallelForDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt, const HelperExprs &Exprs, bool HasCancel);
/// \brief Creates an empty directive with the place
/// for \a NumClauses clauses.
///
/// \param C AST context.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
static OMPParallelForDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses,
unsigned CollapsedNum,
EmptyShell);
/// \brief Return true if current directive has inner cancel directive.
bool hasCancel() const { return HasCancel; }
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPParallelForDirectiveClass;
}
};
/// \brief This represents '#pragma omp parallel for simd' directive.
///
/// \code
/// #pragma omp parallel for simd private(a,b) linear(i,j:s) reduction(+:c,d)
/// \endcode
/// In this example directive '#pragma omp parallel for simd' has clauses
/// 'private' with the variables 'a' and 'b', 'linear' with variables 'i', 'j'
/// and linear step 's', 'reduction' with operator '+' and variables 'c' and
/// 'd'.
///
class OMPParallelForSimdDirective : public OMPLoopDirective {
friend class ASTStmtReader;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
OMPParallelForSimdDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, unsigned NumClauses)
: OMPLoopDirective(this, OMPParallelForSimdDirectiveClass,
OMPD_parallel_for_simd, StartLoc, EndLoc, CollapsedNum,
NumClauses) {}
/// \brief Build an empty directive.
///
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
explicit OMPParallelForSimdDirective(unsigned CollapsedNum,
unsigned NumClauses)
: OMPLoopDirective(this, OMPParallelForSimdDirectiveClass,
OMPD_parallel_for_simd, SourceLocation(),
SourceLocation(), CollapsedNum, NumClauses) {}
public:
/// \brief Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param CollapsedNum Number of collapsed loops.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param Exprs Helper expressions for CodeGen.
///
static OMPParallelForSimdDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt, const HelperExprs &Exprs);
/// \brief Creates an empty directive with the place
/// for \a NumClauses clauses.
///
/// \param C AST context.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
static OMPParallelForSimdDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses,
unsigned CollapsedNum,
EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPParallelForSimdDirectiveClass;
}
};
/// \brief This represents '#pragma omp parallel sections' directive.
///
/// \code
/// #pragma omp parallel sections private(a,b) reduction(+:c,d)
/// \endcode
/// In this example directive '#pragma omp parallel sections' has clauses
/// 'private' with the variables 'a' and 'b' and 'reduction' with operator '+'
/// and variables 'c' and 'd'.
///
class OMPParallelSectionsDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
/// \brief true if current directive has inner cancel directive.
bool HasCancel;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param NumClauses Number of clauses.
///
OMPParallelSectionsDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned NumClauses)
: OMPExecutableDirective(this, OMPParallelSectionsDirectiveClass,
OMPD_parallel_sections, StartLoc, EndLoc,
NumClauses, 1),
HasCancel(false) {}
/// \brief Build an empty directive.
///
/// \param NumClauses Number of clauses.
///
explicit OMPParallelSectionsDirective(unsigned NumClauses)
: OMPExecutableDirective(this, OMPParallelSectionsDirectiveClass,
OMPD_parallel_sections, SourceLocation(),
SourceLocation(), NumClauses, 1),
HasCancel(false) {}
/// \brief Set cancel state.
void setHasCancel(bool Has) { HasCancel = Has; }
public:
/// \brief Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param HasCancel true if current directive has inner cancel directive.
///
static OMPParallelSectionsDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
ArrayRef<OMPClause *> Clauses, Stmt *AssociatedStmt, bool HasCancel);
/// \brief Creates an empty directive with the place for \a NumClauses
/// clauses.
///
/// \param C AST context.
/// \param NumClauses Number of clauses.
///
static OMPParallelSectionsDirective *
CreateEmpty(const ASTContext &C, unsigned NumClauses, EmptyShell);
/// \brief Return true if current directive has inner cancel directive.
bool hasCancel() const { return HasCancel; }
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPParallelSectionsDirectiveClass;
}
};
/// \brief This represents '#pragma omp task' directive.
///
/// \code
/// #pragma omp task private(a,b) final(d)
/// \endcode
/// In this example directive '#pragma omp task' has clauses 'private' with the
/// variables 'a' and 'b' and 'final' with condition 'd'.
///
class OMPTaskDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
/// \brief true if this directive has inner cancel directive.
bool HasCancel;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param NumClauses Number of clauses.
///
OMPTaskDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned NumClauses)
: OMPExecutableDirective(this, OMPTaskDirectiveClass, OMPD_task, StartLoc,
EndLoc, NumClauses, 1),
HasCancel(false) {}
/// \brief Build an empty directive.
///
/// \param NumClauses Number of clauses.
///
explicit OMPTaskDirective(unsigned NumClauses)
: OMPExecutableDirective(this, OMPTaskDirectiveClass, OMPD_task,
SourceLocation(), SourceLocation(), NumClauses,
1),
HasCancel(false) {}
/// \brief Set cancel state.
void setHasCancel(bool Has) { HasCancel = Has; }
public:
/// \brief Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param HasCancel true, if current directive has inner cancel directive.
///
static OMPTaskDirective *Create(const ASTContext &C, SourceLocation StartLoc,
SourceLocation EndLoc,
ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt, bool HasCancel);
/// \brief Creates an empty directive with the place for \a NumClauses
/// clauses.
///
/// \param C AST context.
/// \param NumClauses Number of clauses.
///
static OMPTaskDirective *CreateEmpty(const ASTContext &C, unsigned NumClauses,
EmptyShell);
/// \brief Return true if current directive has inner cancel directive.
bool hasCancel() const { return HasCancel; }
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPTaskDirectiveClass;
}
};
/// \brief This represents '#pragma omp taskyield' directive.
///
/// \code
/// #pragma omp taskyield
/// \endcode
///
class OMPTaskyieldDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
///
OMPTaskyieldDirective(SourceLocation StartLoc, SourceLocation EndLoc)
: OMPExecutableDirective(this, OMPTaskyieldDirectiveClass, OMPD_taskyield,
StartLoc, EndLoc, 0, 0) {}
/// \brief Build an empty directive.
///
explicit OMPTaskyieldDirective()
: OMPExecutableDirective(this, OMPTaskyieldDirectiveClass, OMPD_taskyield,
SourceLocation(), SourceLocation(), 0, 0) {}
public:
/// \brief Creates directive.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
///
static OMPTaskyieldDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc);
/// \brief Creates an empty directive.
///
/// \param C AST context.
///
static OMPTaskyieldDirective *CreateEmpty(const ASTContext &C, EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPTaskyieldDirectiveClass;
}
};
/// \brief This represents '#pragma omp barrier' directive.
///
/// \code
/// #pragma omp barrier
/// \endcode
///
class OMPBarrierDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
///
OMPBarrierDirective(SourceLocation StartLoc, SourceLocation EndLoc)
: OMPExecutableDirective(this, OMPBarrierDirectiveClass, OMPD_barrier,
StartLoc, EndLoc, 0, 0) {}
/// \brief Build an empty directive.
///
explicit OMPBarrierDirective()
: OMPExecutableDirective(this, OMPBarrierDirectiveClass, OMPD_barrier,
SourceLocation(), SourceLocation(), 0, 0) {}
public:
/// \brief Creates directive.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
///
static OMPBarrierDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc);
/// \brief Creates an empty directive.
///
/// \param C AST context.
///
static OMPBarrierDirective *CreateEmpty(const ASTContext &C, EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPBarrierDirectiveClass;
}
};
/// \brief This represents '#pragma omp taskwait' directive.
///
/// \code
/// #pragma omp taskwait
/// \endcode
///
class OMPTaskwaitDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
///
OMPTaskwaitDirective(SourceLocation StartLoc, SourceLocation EndLoc)
: OMPExecutableDirective(this, OMPTaskwaitDirectiveClass, OMPD_taskwait,
StartLoc, EndLoc, 0, 0) {}
/// \brief Build an empty directive.
///
explicit OMPTaskwaitDirective()
: OMPExecutableDirective(this, OMPTaskwaitDirectiveClass, OMPD_taskwait,
SourceLocation(), SourceLocation(), 0, 0) {}
public:
/// \brief Creates directive.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
///
static OMPTaskwaitDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc);
/// \brief Creates an empty directive.
///
/// \param C AST context.
///
static OMPTaskwaitDirective *CreateEmpty(const ASTContext &C, EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPTaskwaitDirectiveClass;
}
};
/// This represents '#pragma omp taskgroup' directive.
///
/// \code
/// #pragma omp taskgroup
/// \endcode
///
class OMPTaskgroupDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
/// Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param NumClauses Number of clauses.
///
OMPTaskgroupDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned NumClauses)
: OMPExecutableDirective(this, OMPTaskgroupDirectiveClass, OMPD_taskgroup,
StartLoc, EndLoc, NumClauses, 2) {}
/// Build an empty directive.
/// \param NumClauses Number of clauses.
///
explicit OMPTaskgroupDirective(unsigned NumClauses)
: OMPExecutableDirective(this, OMPTaskgroupDirectiveClass, OMPD_taskgroup,
SourceLocation(), SourceLocation(), NumClauses,
2) {}
/// Sets the task_reduction return variable.
void setReductionRef(Expr *RR) {
*std::next(child_begin(), 1) = RR;
}
public:
/// Creates directive.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param ReductionRef Reference to the task_reduction return variable.
///
static OMPTaskgroupDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
ArrayRef<OMPClause *> Clauses, Stmt *AssociatedStmt,
Expr *ReductionRef);
/// Creates an empty directive.
///
/// \param C AST context.
/// \param NumClauses Number of clauses.
///
static OMPTaskgroupDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses, EmptyShell);
/// Returns reference to the task_reduction return variable.
const Expr *getReductionRef() const {
return static_cast<const Expr *>(*std::next(child_begin(), 1));
}
Expr *getReductionRef() {
return static_cast<Expr *>(*std::next(child_begin(), 1));
}
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPTaskgroupDirectiveClass;
}
};
/// \brief This represents '#pragma omp flush' directive.
///
/// \code
/// #pragma omp flush(a,b)
/// \endcode
/// In this example directive '#pragma omp flush' has 2 arguments- variables 'a'
/// and 'b'.
/// 'omp flush' directive does not have clauses but have an optional list of
/// variables to flush. This list of variables is stored within some fake clause
/// FlushClause.
class OMPFlushDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param NumClauses Number of clauses.
///
OMPFlushDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned NumClauses)
: OMPExecutableDirective(this, OMPFlushDirectiveClass, OMPD_flush,
StartLoc, EndLoc, NumClauses, 0) {}
/// \brief Build an empty directive.
///
/// \param NumClauses Number of clauses.
///
explicit OMPFlushDirective(unsigned NumClauses)
: OMPExecutableDirective(this, OMPFlushDirectiveClass, OMPD_flush,
SourceLocation(), SourceLocation(), NumClauses,
0) {}
public:
/// \brief Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param Clauses List of clauses (only single OMPFlushClause clause is
/// allowed).
///
static OMPFlushDirective *Create(const ASTContext &C, SourceLocation StartLoc,
SourceLocation EndLoc,
ArrayRef<OMPClause *> Clauses);
/// \brief Creates an empty directive with the place for \a NumClauses
/// clauses.
///
/// \param C AST context.
/// \param NumClauses Number of clauses.
///
static OMPFlushDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses, EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPFlushDirectiveClass;
}
};
/// \brief This represents '#pragma omp ordered' directive.
///
/// \code
/// #pragma omp ordered
/// \endcode
///
class OMPOrderedDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param NumClauses Number of clauses.
///
OMPOrderedDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned NumClauses)
: OMPExecutableDirective(this, OMPOrderedDirectiveClass, OMPD_ordered,
StartLoc, EndLoc, NumClauses, 1) {}
/// \brief Build an empty directive.
///
/// \param NumClauses Number of clauses.
///
explicit OMPOrderedDirective(unsigned NumClauses)
: OMPExecutableDirective(this, OMPOrderedDirectiveClass, OMPD_ordered,
SourceLocation(), SourceLocation(), NumClauses,
1) {}
public:
/// \brief Creates directive.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
///
static OMPOrderedDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
ArrayRef<OMPClause *> Clauses, Stmt *AssociatedStmt);
/// \brief Creates an empty directive.
///
/// \param C AST context.
/// \param NumClauses Number of clauses.
///
static OMPOrderedDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses, EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPOrderedDirectiveClass;
}
};
/// \brief This represents '#pragma omp atomic' directive.
///
/// \code
/// #pragma omp atomic capture
/// \endcode
/// In this example directive '#pragma omp atomic' has clause 'capture'.
///
class OMPAtomicDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
/// \brief Used for 'atomic update' or 'atomic capture' constructs. They may
/// have atomic expressions of forms
/// \code
/// x = x binop expr;
/// x = expr binop x;
/// \endcode
/// This field is true for the first form of the expression and false for the
/// second. Required for correct codegen of non-associative operations (like
/// << or >>).
bool IsXLHSInRHSPart;
/// \brief Used for 'atomic update' or 'atomic capture' constructs. They may
/// have atomic expressions of forms
/// \code
/// v = x; <update x>;
/// <update x>; v = x;
/// \endcode
/// This field is true for the first(postfix) form of the expression and false
/// otherwise.
bool IsPostfixUpdate;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param NumClauses Number of clauses.
///
OMPAtomicDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned NumClauses)
: OMPExecutableDirective(this, OMPAtomicDirectiveClass, OMPD_atomic,
StartLoc, EndLoc, NumClauses, 5),
IsXLHSInRHSPart(false), IsPostfixUpdate(false) {}
/// \brief Build an empty directive.
///
/// \param NumClauses Number of clauses.
///
explicit OMPAtomicDirective(unsigned NumClauses)
: OMPExecutableDirective(this, OMPAtomicDirectiveClass, OMPD_atomic,
SourceLocation(), SourceLocation(), NumClauses,
5),
IsXLHSInRHSPart(false), IsPostfixUpdate(false) {}
/// \brief Set 'x' part of the associated expression/statement.
void setX(Expr *X) { *std::next(child_begin()) = X; }
/// \brief Set helper expression of the form
/// 'OpaqueValueExpr(x) binop OpaqueValueExpr(expr)' or
/// 'OpaqueValueExpr(expr) binop OpaqueValueExpr(x)'.
void setUpdateExpr(Expr *UE) { *std::next(child_begin(), 2) = UE; }
/// \brief Set 'v' part of the associated expression/statement.
void setV(Expr *V) { *std::next(child_begin(), 3) = V; }
/// \brief Set 'expr' part of the associated expression/statement.
void setExpr(Expr *E) { *std::next(child_begin(), 4) = E; }
public:
/// \brief Creates directive with a list of \a Clauses and 'x', 'v' and 'expr'
/// parts of the atomic construct (see Section 2.12.6, atomic Construct, for
/// detailed description of 'x', 'v' and 'expr').
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param X 'x' part of the associated expression/statement.
/// \param V 'v' part of the associated expression/statement.
/// \param E 'expr' part of the associated expression/statement.
/// \param UE Helper expression of the form
/// 'OpaqueValueExpr(x) binop OpaqueValueExpr(expr)' or
/// 'OpaqueValueExpr(expr) binop OpaqueValueExpr(x)'.
/// \param IsXLHSInRHSPart true if \a UE has the first form and false if the
/// second.
/// \param IsPostfixUpdate true if original value of 'x' must be stored in
/// 'v', not an updated one.
static OMPAtomicDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
ArrayRef<OMPClause *> Clauses, Stmt *AssociatedStmt, Expr *X, Expr *V,
Expr *E, Expr *UE, bool IsXLHSInRHSPart, bool IsPostfixUpdate);
/// \brief Creates an empty directive with the place for \a NumClauses
/// clauses.
///
/// \param C AST context.
/// \param NumClauses Number of clauses.
///
static OMPAtomicDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses, EmptyShell);
/// \brief Get 'x' part of the associated expression/statement.
Expr *getX() { return cast_or_null<Expr>(*std::next(child_begin())); }
const Expr *getX() const {
return cast_or_null<Expr>(*std::next(child_begin()));
}
/// \brief Get helper expression of the form
/// 'OpaqueValueExpr(x) binop OpaqueValueExpr(expr)' or
/// 'OpaqueValueExpr(expr) binop OpaqueValueExpr(x)'.
Expr *getUpdateExpr() {
return cast_or_null<Expr>(*std::next(child_begin(), 2));
}
const Expr *getUpdateExpr() const {
return cast_or_null<Expr>(*std::next(child_begin(), 2));
}
/// \brief Return true if helper update expression has form
/// 'OpaqueValueExpr(x) binop OpaqueValueExpr(expr)' and false if it has form
/// 'OpaqueValueExpr(expr) binop OpaqueValueExpr(x)'.
bool isXLHSInRHSPart() const { return IsXLHSInRHSPart; }
/// \brief Return true if 'v' expression must be updated to original value of
/// 'x', false if 'v' must be updated to the new value of 'x'.
bool isPostfixUpdate() const { return IsPostfixUpdate; }
/// \brief Get 'v' part of the associated expression/statement.
Expr *getV() { return cast_or_null<Expr>(*std::next(child_begin(), 3)); }
const Expr *getV() const {
return cast_or_null<Expr>(*std::next(child_begin(), 3));
}
/// \brief Get 'expr' part of the associated expression/statement.
Expr *getExpr() { return cast_or_null<Expr>(*std::next(child_begin(), 4)); }
const Expr *getExpr() const {
return cast_or_null<Expr>(*std::next(child_begin(), 4));
}
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPAtomicDirectiveClass;
}
};
/// \brief This represents '#pragma omp target' directive.
///
/// \code
/// #pragma omp target if(a)
/// \endcode
/// In this example directive '#pragma omp target' has clause 'if' with
/// condition 'a'.
///
class OMPTargetDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param NumClauses Number of clauses.
///
OMPTargetDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned NumClauses)
: OMPExecutableDirective(this, OMPTargetDirectiveClass, OMPD_target,
StartLoc, EndLoc, NumClauses, 1) {}
/// \brief Build an empty directive.
///
/// \param NumClauses Number of clauses.
///
explicit OMPTargetDirective(unsigned NumClauses)
: OMPExecutableDirective(this, OMPTargetDirectiveClass, OMPD_target,
SourceLocation(), SourceLocation(), NumClauses,
1) {}
public:
/// \brief Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
///
static OMPTargetDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
ArrayRef<OMPClause *> Clauses, Stmt *AssociatedStmt);
/// \brief Creates an empty directive with the place for \a NumClauses
/// clauses.
///
/// \param C AST context.
/// \param NumClauses Number of clauses.
///
static OMPTargetDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses, EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPTargetDirectiveClass;
}
};
/// \brief This represents '#pragma omp target data' directive.
///
/// \code
/// #pragma omp target data device(0) if(a) map(b[:])
/// \endcode
/// In this example directive '#pragma omp target data' has clauses 'device'
/// with the value '0', 'if' with condition 'a' and 'map' with array
/// section 'b[:]'.
///
class OMPTargetDataDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param NumClauses The number of clauses.
///
OMPTargetDataDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned NumClauses)
: OMPExecutableDirective(this, OMPTargetDataDirectiveClass,
OMPD_target_data, StartLoc, EndLoc, NumClauses,
1) {}
/// \brief Build an empty directive.
///
/// \param NumClauses Number of clauses.
///
explicit OMPTargetDataDirective(unsigned NumClauses)
: OMPExecutableDirective(this, OMPTargetDataDirectiveClass,
OMPD_target_data, SourceLocation(),
SourceLocation(), NumClauses, 1) {}
public:
/// \brief Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
///
static OMPTargetDataDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
ArrayRef<OMPClause *> Clauses, Stmt *AssociatedStmt);
/// \brief Creates an empty directive with the place for \a N clauses.
///
/// \param C AST context.
/// \param N The number of clauses.
///
static OMPTargetDataDirective *CreateEmpty(const ASTContext &C, unsigned N,
EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPTargetDataDirectiveClass;
}
};
/// \brief This represents '#pragma omp target enter data' directive.
///
/// \code
/// #pragma omp target enter data device(0) if(a) map(b[:])
/// \endcode
/// In this example directive '#pragma omp target enter data' has clauses
/// 'device' with the value '0', 'if' with condition 'a' and 'map' with array
/// section 'b[:]'.
///
class OMPTargetEnterDataDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param NumClauses The number of clauses.
///
OMPTargetEnterDataDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned NumClauses)
: OMPExecutableDirective(this, OMPTargetEnterDataDirectiveClass,
OMPD_target_enter_data, StartLoc, EndLoc,
NumClauses, /*NumChildren=*/1) {}
/// \brief Build an empty directive.
///
/// \param NumClauses Number of clauses.
///
explicit OMPTargetEnterDataDirective(unsigned NumClauses)
: OMPExecutableDirective(this, OMPTargetEnterDataDirectiveClass,
OMPD_target_enter_data, SourceLocation(),
SourceLocation(), NumClauses,
/*NumChildren=*/1) {}
public:
/// \brief Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
///
static OMPTargetEnterDataDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
ArrayRef<OMPClause *> Clauses, Stmt *AssociatedStmt);
/// \brief Creates an empty directive with the place for \a N clauses.
///
/// \param C AST context.
/// \param N The number of clauses.
///
static OMPTargetEnterDataDirective *CreateEmpty(const ASTContext &C,
unsigned N, EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPTargetEnterDataDirectiveClass;
}
};
/// \brief This represents '#pragma omp target exit data' directive.
///
/// \code
/// #pragma omp target exit data device(0) if(a) map(b[:])
/// \endcode
/// In this example directive '#pragma omp target exit data' has clauses
/// 'device' with the value '0', 'if' with condition 'a' and 'map' with array
/// section 'b[:]'.
///
class OMPTargetExitDataDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param NumClauses The number of clauses.
///
OMPTargetExitDataDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned NumClauses)
: OMPExecutableDirective(this, OMPTargetExitDataDirectiveClass,
OMPD_target_exit_data, StartLoc, EndLoc,
NumClauses, /*NumChildren=*/1) {}
/// \brief Build an empty directive.
///
/// \param NumClauses Number of clauses.
///
explicit OMPTargetExitDataDirective(unsigned NumClauses)
: OMPExecutableDirective(this, OMPTargetExitDataDirectiveClass,
OMPD_target_exit_data, SourceLocation(),
SourceLocation(), NumClauses,
/*NumChildren=*/1) {}
public:
/// \brief Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
///
static OMPTargetExitDataDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
ArrayRef<OMPClause *> Clauses, Stmt *AssociatedStmt);
/// \brief Creates an empty directive with the place for \a N clauses.
///
/// \param C AST context.
/// \param N The number of clauses.
///
static OMPTargetExitDataDirective *CreateEmpty(const ASTContext &C,
unsigned N, EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPTargetExitDataDirectiveClass;
}
};
/// \brief This represents '#pragma omp target parallel' directive.
///
/// \code
/// #pragma omp target parallel if(a)
/// \endcode
/// In this example directive '#pragma omp target parallel' has clause 'if' with
/// condition 'a'.
///
class OMPTargetParallelDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param NumClauses Number of clauses.
///
OMPTargetParallelDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned NumClauses)
: OMPExecutableDirective(this, OMPTargetParallelDirectiveClass,
OMPD_target_parallel, StartLoc, EndLoc,
NumClauses, /*NumChildren=*/1) {}
/// \brief Build an empty directive.
///
/// \param NumClauses Number of clauses.
///
explicit OMPTargetParallelDirective(unsigned NumClauses)
: OMPExecutableDirective(this, OMPTargetParallelDirectiveClass,
OMPD_target_parallel, SourceLocation(),
SourceLocation(), NumClauses,
/*NumChildren=*/1) {}
public:
/// \brief Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
///
static OMPTargetParallelDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
ArrayRef<OMPClause *> Clauses, Stmt *AssociatedStmt);
/// \brief Creates an empty directive with the place for \a NumClauses
/// clauses.
///
/// \param C AST context.
/// \param NumClauses Number of clauses.
///
static OMPTargetParallelDirective *
CreateEmpty(const ASTContext &C, unsigned NumClauses, EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPTargetParallelDirectiveClass;
}
};
/// \brief This represents '#pragma omp target parallel for' directive.
///
/// \code
/// #pragma omp target parallel for private(a,b) reduction(+:c,d)
/// \endcode
/// In this example directive '#pragma omp target parallel for' has clauses
/// 'private' with the variables 'a' and 'b' and 'reduction' with operator '+'
/// and variables 'c' and 'd'.
///
class OMPTargetParallelForDirective : public OMPLoopDirective {
friend class ASTStmtReader;
/// \brief true if current region has inner cancel directive.
bool HasCancel;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
OMPTargetParallelForDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, unsigned NumClauses)
: OMPLoopDirective(this, OMPTargetParallelForDirectiveClass,
OMPD_target_parallel_for, StartLoc, EndLoc,
CollapsedNum, NumClauses),
HasCancel(false) {}
/// \brief Build an empty directive.
///
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
explicit OMPTargetParallelForDirective(unsigned CollapsedNum,
unsigned NumClauses)
: OMPLoopDirective(this, OMPTargetParallelForDirectiveClass,
OMPD_target_parallel_for, SourceLocation(),
SourceLocation(), CollapsedNum, NumClauses),
HasCancel(false) {}
/// \brief Set cancel state.
void setHasCancel(bool Has) { HasCancel = Has; }
public:
/// \brief Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param CollapsedNum Number of collapsed loops.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param Exprs Helper expressions for CodeGen.
/// \param HasCancel true if current directive has inner cancel directive.
///
static OMPTargetParallelForDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt, const HelperExprs &Exprs, bool HasCancel);
/// \brief Creates an empty directive with the place
/// for \a NumClauses clauses.
///
/// \param C AST context.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
static OMPTargetParallelForDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses,
unsigned CollapsedNum,
EmptyShell);
/// \brief Return true if current directive has inner cancel directive.
bool hasCancel() const { return HasCancel; }
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPTargetParallelForDirectiveClass;
}
};
/// \brief This represents '#pragma omp teams' directive.
///
/// \code
/// #pragma omp teams if(a)
/// \endcode
/// In this example directive '#pragma omp teams' has clause 'if' with
/// condition 'a'.
///
class OMPTeamsDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param NumClauses Number of clauses.
///
OMPTeamsDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned NumClauses)
: OMPExecutableDirective(this, OMPTeamsDirectiveClass, OMPD_teams,
StartLoc, EndLoc, NumClauses, 1) {}
/// \brief Build an empty directive.
///
/// \param NumClauses Number of clauses.
///
explicit OMPTeamsDirective(unsigned NumClauses)
: OMPExecutableDirective(this, OMPTeamsDirectiveClass, OMPD_teams,
SourceLocation(), SourceLocation(), NumClauses,
1) {}
public:
/// \brief Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
///
static OMPTeamsDirective *Create(const ASTContext &C, SourceLocation StartLoc,
SourceLocation EndLoc,
ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt);
/// \brief Creates an empty directive with the place for \a NumClauses
/// clauses.
///
/// \param C AST context.
/// \param NumClauses Number of clauses.
///
static OMPTeamsDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses, EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPTeamsDirectiveClass;
}
};
/// \brief This represents '#pragma omp cancellation point' directive.
///
/// \code
/// #pragma omp cancellation point for
/// \endcode
///
/// In this example a cancellation point is created for innermost 'for' region.
class OMPCancellationPointDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
OpenMPDirectiveKind CancelRegion;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
///
OMPCancellationPointDirective(SourceLocation StartLoc, SourceLocation EndLoc)
: OMPExecutableDirective(this, OMPCancellationPointDirectiveClass,
OMPD_cancellation_point, StartLoc, EndLoc, 0, 0),
CancelRegion(OMPD_unknown) {}
/// \brief Build an empty directive.
///
explicit OMPCancellationPointDirective()
: OMPExecutableDirective(this, OMPCancellationPointDirectiveClass,
OMPD_cancellation_point, SourceLocation(),
SourceLocation(), 0, 0),
CancelRegion(OMPD_unknown) {}
/// \brief Set cancel region for current cancellation point.
/// \param CR Cancellation region.
void setCancelRegion(OpenMPDirectiveKind CR) { CancelRegion = CR; }
public:
/// \brief Creates directive.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
///
static OMPCancellationPointDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
OpenMPDirectiveKind CancelRegion);
/// \brief Creates an empty directive.
///
/// \param C AST context.
///
static OMPCancellationPointDirective *CreateEmpty(const ASTContext &C,
EmptyShell);
/// \brief Get cancellation region for the current cancellation point.
OpenMPDirectiveKind getCancelRegion() const { return CancelRegion; }
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPCancellationPointDirectiveClass;
}
};
/// \brief This represents '#pragma omp cancel' directive.
///
/// \code
/// #pragma omp cancel for
/// \endcode
///
/// In this example a cancel is created for innermost 'for' region.
class OMPCancelDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
OpenMPDirectiveKind CancelRegion;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param NumClauses Number of clauses.
///
OMPCancelDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned NumClauses)
: OMPExecutableDirective(this, OMPCancelDirectiveClass, OMPD_cancel,
StartLoc, EndLoc, NumClauses, 0),
CancelRegion(OMPD_unknown) {}
/// \brief Build an empty directive.
///
/// \param NumClauses Number of clauses.
explicit OMPCancelDirective(unsigned NumClauses)
: OMPExecutableDirective(this, OMPCancelDirectiveClass, OMPD_cancel,
SourceLocation(), SourceLocation(), NumClauses,
0),
CancelRegion(OMPD_unknown) {}
/// \brief Set cancel region for current cancellation point.
/// \param CR Cancellation region.
void setCancelRegion(OpenMPDirectiveKind CR) { CancelRegion = CR; }
public:
/// \brief Creates directive.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param Clauses List of clauses.
///
static OMPCancelDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
ArrayRef<OMPClause *> Clauses, OpenMPDirectiveKind CancelRegion);
/// \brief Creates an empty directive.
///
/// \param C AST context.
/// \param NumClauses Number of clauses.
///
static OMPCancelDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses, EmptyShell);
/// \brief Get cancellation region for the current cancellation point.
OpenMPDirectiveKind getCancelRegion() const { return CancelRegion; }
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPCancelDirectiveClass;
}
};
/// \brief This represents '#pragma omp taskloop' directive.
///
/// \code
/// #pragma omp taskloop private(a,b) grainsize(val) num_tasks(num)
/// \endcode
/// In this example directive '#pragma omp taskloop' has clauses 'private'
/// with the variables 'a' and 'b', 'grainsize' with expression 'val' and
/// 'num_tasks' with expression 'num'.
///
class OMPTaskLoopDirective : public OMPLoopDirective {
friend class ASTStmtReader;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
OMPTaskLoopDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, unsigned NumClauses)
: OMPLoopDirective(this, OMPTaskLoopDirectiveClass, OMPD_taskloop,
StartLoc, EndLoc, CollapsedNum, NumClauses) {}
/// \brief Build an empty directive.
///
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
explicit OMPTaskLoopDirective(unsigned CollapsedNum, unsigned NumClauses)
: OMPLoopDirective(this, OMPTaskLoopDirectiveClass, OMPD_taskloop,
SourceLocation(), SourceLocation(), CollapsedNum,
NumClauses) {}
public:
/// \brief Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param CollapsedNum Number of collapsed loops.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param Exprs Helper expressions for CodeGen.
///
static OMPTaskLoopDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt, const HelperExprs &Exprs);
/// \brief Creates an empty directive with the place
/// for \a NumClauses clauses.
///
/// \param C AST context.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
static OMPTaskLoopDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses,
unsigned CollapsedNum, EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPTaskLoopDirectiveClass;
}
};
/// \brief This represents '#pragma omp taskloop simd' directive.
///
/// \code
/// #pragma omp taskloop simd private(a,b) grainsize(val) num_tasks(num)
/// \endcode
/// In this example directive '#pragma omp taskloop simd' has clauses 'private'
/// with the variables 'a' and 'b', 'grainsize' with expression 'val' and
/// 'num_tasks' with expression 'num'.
///
class OMPTaskLoopSimdDirective : public OMPLoopDirective {
friend class ASTStmtReader;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
OMPTaskLoopSimdDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, unsigned NumClauses)
: OMPLoopDirective(this, OMPTaskLoopSimdDirectiveClass,
OMPD_taskloop_simd, StartLoc, EndLoc, CollapsedNum,
NumClauses) {}
/// \brief Build an empty directive.
///
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
explicit OMPTaskLoopSimdDirective(unsigned CollapsedNum, unsigned NumClauses)
: OMPLoopDirective(this, OMPTaskLoopSimdDirectiveClass,
OMPD_taskloop_simd, SourceLocation(), SourceLocation(),
CollapsedNum, NumClauses) {}
public:
/// \brief Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param CollapsedNum Number of collapsed loops.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param Exprs Helper expressions for CodeGen.
///
static OMPTaskLoopSimdDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt, const HelperExprs &Exprs);
/// \brief Creates an empty directive with the place
/// for \a NumClauses clauses.
///
/// \param C AST context.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
static OMPTaskLoopSimdDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses,
unsigned CollapsedNum,
EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPTaskLoopSimdDirectiveClass;
}
};
/// \brief This represents '#pragma omp distribute' directive.
///
/// \code
/// #pragma omp distribute private(a,b)
/// \endcode
/// In this example directive '#pragma omp distribute' has clauses 'private'
/// with the variables 'a' and 'b'
///
class OMPDistributeDirective : public OMPLoopDirective {
friend class ASTStmtReader;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
OMPDistributeDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, unsigned NumClauses)
: OMPLoopDirective(this, OMPDistributeDirectiveClass, OMPD_distribute,
StartLoc, EndLoc, CollapsedNum, NumClauses)
{}
/// \brief Build an empty directive.
///
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
explicit OMPDistributeDirective(unsigned CollapsedNum, unsigned NumClauses)
: OMPLoopDirective(this, OMPDistributeDirectiveClass, OMPD_distribute,
SourceLocation(), SourceLocation(), CollapsedNum,
NumClauses)
{}
public:
/// \brief Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param CollapsedNum Number of collapsed loops.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param Exprs Helper expressions for CodeGen.
///
static OMPDistributeDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt, const HelperExprs &Exprs);
/// \brief Creates an empty directive with the place
/// for \a NumClauses clauses.
///
/// \param C AST context.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
static OMPDistributeDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses,
unsigned CollapsedNum, EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPDistributeDirectiveClass;
}
};
/// \brief This represents '#pragma omp target update' directive.
///
/// \code
/// #pragma omp target update to(a) from(b) device(1)
/// \endcode
/// In this example directive '#pragma omp target update' has clause 'to' with
/// argument 'a', clause 'from' with argument 'b' and clause 'device' with
/// argument '1'.
///
class OMPTargetUpdateDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param NumClauses The number of clauses.
///
OMPTargetUpdateDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned NumClauses)
: OMPExecutableDirective(this, OMPTargetUpdateDirectiveClass,
OMPD_target_update, StartLoc, EndLoc, NumClauses,
1) {}
/// \brief Build an empty directive.
///
/// \param NumClauses Number of clauses.
///
explicit OMPTargetUpdateDirective(unsigned NumClauses)
: OMPExecutableDirective(this, OMPTargetUpdateDirectiveClass,
OMPD_target_update, SourceLocation(),
SourceLocation(), NumClauses, 1) {}
public:
/// \brief Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
///
static OMPTargetUpdateDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
ArrayRef<OMPClause *> Clauses, Stmt *AssociatedStmt);
/// \brief Creates an empty directive with the place for \a NumClauses
/// clauses.
///
/// \param C AST context.
/// \param NumClauses The number of clauses.
///
static OMPTargetUpdateDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses, EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPTargetUpdateDirectiveClass;
}
};
/// \brief This represents '#pragma omp distribute parallel for' composite
/// directive.
///
/// \code
/// #pragma omp distribute parallel for private(a,b)
/// \endcode
/// In this example directive '#pragma omp distribute parallel for' has clause
/// 'private' with the variables 'a' and 'b'
///
class OMPDistributeParallelForDirective : public OMPLoopDirective {
friend class ASTStmtReader;
/// true if the construct has inner cancel directive.
bool HasCancel = false;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
OMPDistributeParallelForDirective(SourceLocation StartLoc,
SourceLocation EndLoc,
unsigned CollapsedNum, unsigned NumClauses)
: OMPLoopDirective(this, OMPDistributeParallelForDirectiveClass,
OMPD_distribute_parallel_for, StartLoc, EndLoc,
CollapsedNum, NumClauses), HasCancel(false) {}
/// \brief Build an empty directive.
///
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
explicit OMPDistributeParallelForDirective(unsigned CollapsedNum,
unsigned NumClauses)
: OMPLoopDirective(this, OMPDistributeParallelForDirectiveClass,
OMPD_distribute_parallel_for, SourceLocation(),
SourceLocation(), CollapsedNum, NumClauses),
HasCancel(false) {}
/// Set cancel state.
void setHasCancel(bool Has) { HasCancel = Has; }
public:
/// \brief Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param CollapsedNum Number of collapsed loops.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param Exprs Helper expressions for CodeGen.
/// \param HasCancel true if this directive has inner cancel directive.
///
static OMPDistributeParallelForDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt, const HelperExprs &Exprs, bool HasCancel);
/// \brief Creates an empty directive with the place
/// for \a NumClauses clauses.
///
/// \param C AST context.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
static OMPDistributeParallelForDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses,
unsigned CollapsedNum,
EmptyShell);
/// Return true if current directive has inner cancel directive.
bool hasCancel() const { return HasCancel; }
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPDistributeParallelForDirectiveClass;
}
};
/// This represents '#pragma omp distribute parallel for simd' composite
/// directive.
///
/// \code
/// #pragma omp distribute parallel for simd private(x)
/// \endcode
/// In this example directive '#pragma omp distribute parallel for simd' has
/// clause 'private' with the variables 'x'
///
class OMPDistributeParallelForSimdDirective final : public OMPLoopDirective {
friend class ASTStmtReader;
/// Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
OMPDistributeParallelForSimdDirective(SourceLocation StartLoc,
SourceLocation EndLoc,
unsigned CollapsedNum,
unsigned NumClauses)
: OMPLoopDirective(this, OMPDistributeParallelForSimdDirectiveClass,
OMPD_distribute_parallel_for_simd, StartLoc,
EndLoc, CollapsedNum, NumClauses) {}
/// Build an empty directive.
///
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
explicit OMPDistributeParallelForSimdDirective(unsigned CollapsedNum,
unsigned NumClauses)
: OMPLoopDirective(this, OMPDistributeParallelForSimdDirectiveClass,
OMPD_distribute_parallel_for_simd,
SourceLocation(), SourceLocation(), CollapsedNum,
NumClauses) {}
public:
/// Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param CollapsedNum Number of collapsed loops.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param Exprs Helper expressions for CodeGen.
///
static OMPDistributeParallelForSimdDirective *Create(
const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt, const HelperExprs &Exprs);
/// Creates an empty directive with the place for \a NumClauses clauses.
///
/// \param C AST context.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
static OMPDistributeParallelForSimdDirective *CreateEmpty(
const ASTContext &C, unsigned NumClauses, unsigned CollapsedNum,
EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPDistributeParallelForSimdDirectiveClass;
}
};
/// This represents '#pragma omp distribute simd' composite directive.
///
/// \code
/// #pragma omp distribute simd private(x)
/// \endcode
/// In this example directive '#pragma omp distribute simd' has clause
/// 'private' with the variables 'x'
///
class OMPDistributeSimdDirective final : public OMPLoopDirective {
friend class ASTStmtReader;
/// Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
OMPDistributeSimdDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, unsigned NumClauses)
: OMPLoopDirective(this, OMPDistributeSimdDirectiveClass,
OMPD_distribute_simd, StartLoc, EndLoc, CollapsedNum,
NumClauses) {}
/// Build an empty directive.
///
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
explicit OMPDistributeSimdDirective(unsigned CollapsedNum,
unsigned NumClauses)
: OMPLoopDirective(this, OMPDistributeSimdDirectiveClass,
OMPD_distribute_simd, SourceLocation(),
SourceLocation(), CollapsedNum, NumClauses) {}
public:
/// Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param CollapsedNum Number of collapsed loops.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param Exprs Helper expressions for CodeGen.
///
static OMPDistributeSimdDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt, const HelperExprs &Exprs);
/// Creates an empty directive with the place for \a NumClauses clauses.
///
/// \param C AST context.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
static OMPDistributeSimdDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses,
unsigned CollapsedNum,
EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPDistributeSimdDirectiveClass;
}
};
/// This represents '#pragma omp target parallel for simd' directive.
///
/// \code
/// #pragma omp target parallel for simd private(a) map(b) safelen(c)
/// \endcode
/// In this example directive '#pragma omp target parallel for simd' has clauses
/// 'private' with the variable 'a', 'map' with the variable 'b' and 'safelen'
/// with the variable 'c'.
///
class OMPTargetParallelForSimdDirective final : public OMPLoopDirective {
friend class ASTStmtReader;
/// Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
OMPTargetParallelForSimdDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, unsigned NumClauses)
: OMPLoopDirective(this, OMPTargetParallelForSimdDirectiveClass,
OMPD_target_parallel_for_simd, StartLoc, EndLoc,
CollapsedNum, NumClauses) {}
/// Build an empty directive.
///
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
explicit OMPTargetParallelForSimdDirective(unsigned CollapsedNum,
unsigned NumClauses)
: OMPLoopDirective(this, OMPTargetParallelForSimdDirectiveClass,
OMPD_target_parallel_for_simd, SourceLocation(),
SourceLocation(), CollapsedNum, NumClauses) {}
public:
/// Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param CollapsedNum Number of collapsed loops.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param Exprs Helper expressions for CodeGen.
///
static OMPTargetParallelForSimdDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt, const HelperExprs &Exprs);
/// Creates an empty directive with the place for \a NumClauses clauses.
///
/// \param C AST context.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
static OMPTargetParallelForSimdDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses,
unsigned CollapsedNum,
EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPTargetParallelForSimdDirectiveClass;
}
};
/// This represents '#pragma omp target simd' directive.
///
/// \code
/// #pragma omp target simd private(a) map(b) safelen(c)
/// \endcode
/// In this example directive '#pragma omp target simd' has clauses 'private'
/// with the variable 'a', 'map' with the variable 'b' and 'safelen' with
/// the variable 'c'.
///
class OMPTargetSimdDirective final : public OMPLoopDirective {
friend class ASTStmtReader;
/// Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
OMPTargetSimdDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, unsigned NumClauses)
: OMPLoopDirective(this, OMPTargetSimdDirectiveClass,
OMPD_target_simd, StartLoc, EndLoc, CollapsedNum,
NumClauses) {}
/// Build an empty directive.
///
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
explicit OMPTargetSimdDirective(unsigned CollapsedNum, unsigned NumClauses)
: OMPLoopDirective(this, OMPTargetSimdDirectiveClass, OMPD_target_simd,
SourceLocation(),SourceLocation(), CollapsedNum,
NumClauses) {}
public:
/// Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param CollapsedNum Number of collapsed loops.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param Exprs Helper expressions for CodeGen.
///
static OMPTargetSimdDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt, const HelperExprs &Exprs);
/// Creates an empty directive with the place for \a NumClauses clauses.
///
/// \param C AST context.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
static OMPTargetSimdDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses,
unsigned CollapsedNum,
EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPTargetSimdDirectiveClass;
}
};
/// This represents '#pragma omp teams distribute' directive.
///
/// \code
/// #pragma omp teams distribute private(a,b)
/// \endcode
/// In this example directive '#pragma omp teams distribute' has clauses
/// 'private' with the variables 'a' and 'b'
///
class OMPTeamsDistributeDirective final : public OMPLoopDirective {
friend class ASTStmtReader;
/// Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
OMPTeamsDistributeDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, unsigned NumClauses)
: OMPLoopDirective(this, OMPTeamsDistributeDirectiveClass,
OMPD_teams_distribute, StartLoc, EndLoc,
CollapsedNum, NumClauses) {}
/// Build an empty directive.
///
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
explicit OMPTeamsDistributeDirective(unsigned CollapsedNum,
unsigned NumClauses)
: OMPLoopDirective(this, OMPTeamsDistributeDirectiveClass,
OMPD_teams_distribute, SourceLocation(),
SourceLocation(), CollapsedNum, NumClauses) {}
public:
/// Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param CollapsedNum Number of collapsed loops.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param Exprs Helper expressions for CodeGen.
///
static OMPTeamsDistributeDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt, const HelperExprs &Exprs);
/// Creates an empty directive with the place for \a NumClauses clauses.
///
/// \param C AST context.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
static OMPTeamsDistributeDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses,
unsigned CollapsedNum,
EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPTeamsDistributeDirectiveClass;
}
};
/// This represents '#pragma omp teams distribute simd'
/// combined directive.
///
/// \code
/// #pragma omp teams distribute simd private(a,b)
/// \endcode
/// In this example directive '#pragma omp teams distribute simd'
/// has clause 'private' with the variables 'a' and 'b'
///
class OMPTeamsDistributeSimdDirective final : public OMPLoopDirective {
friend class ASTStmtReader;
/// Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
OMPTeamsDistributeSimdDirective(SourceLocation StartLoc,
SourceLocation EndLoc, unsigned CollapsedNum,
unsigned NumClauses)
: OMPLoopDirective(this, OMPTeamsDistributeSimdDirectiveClass,
OMPD_teams_distribute_simd, StartLoc, EndLoc,
CollapsedNum, NumClauses) {}
/// Build an empty directive.
///
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
explicit OMPTeamsDistributeSimdDirective(unsigned CollapsedNum,
unsigned NumClauses)
: OMPLoopDirective(this, OMPTeamsDistributeSimdDirectiveClass,
OMPD_teams_distribute_simd, SourceLocation(),
SourceLocation(), CollapsedNum, NumClauses) {}
public:
/// Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param CollapsedNum Number of collapsed loops.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param Exprs Helper expressions for CodeGen.
///
static OMPTeamsDistributeSimdDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt, const HelperExprs &Exprs);
/// Creates an empty directive with the place
/// for \a NumClauses clauses.
///
/// \param C AST context.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
static OMPTeamsDistributeSimdDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses,
unsigned CollapsedNum,
EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPTeamsDistributeSimdDirectiveClass;
}
};
/// This represents '#pragma omp teams distribute parallel for simd' composite
/// directive.
///
/// \code
/// #pragma omp teams distribute parallel for simd private(x)
/// \endcode
/// In this example directive '#pragma omp teams distribute parallel for simd'
/// has clause 'private' with the variables 'x'
///
class OMPTeamsDistributeParallelForSimdDirective final
: public OMPLoopDirective {
friend class ASTStmtReader;
/// Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
OMPTeamsDistributeParallelForSimdDirective(SourceLocation StartLoc,
SourceLocation EndLoc,
unsigned CollapsedNum,
unsigned NumClauses)
: OMPLoopDirective(this, OMPTeamsDistributeParallelForSimdDirectiveClass,
OMPD_teams_distribute_parallel_for_simd, StartLoc,
EndLoc, CollapsedNum, NumClauses) {}
/// Build an empty directive.
///
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
explicit OMPTeamsDistributeParallelForSimdDirective(unsigned CollapsedNum,
unsigned NumClauses)
: OMPLoopDirective(this, OMPTeamsDistributeParallelForSimdDirectiveClass,
OMPD_teams_distribute_parallel_for_simd,
SourceLocation(), SourceLocation(), CollapsedNum,
NumClauses) {}
public:
/// Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param CollapsedNum Number of collapsed loops.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param Exprs Helper expressions for CodeGen.
///
static OMPTeamsDistributeParallelForSimdDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt, const HelperExprs &Exprs);
/// Creates an empty directive with the place for \a NumClauses clauses.
///
/// \param C AST context.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
static OMPTeamsDistributeParallelForSimdDirective *
CreateEmpty(const ASTContext &C, unsigned NumClauses, unsigned CollapsedNum,
EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPTeamsDistributeParallelForSimdDirectiveClass;
}
};
/// This represents '#pragma omp teams distribute parallel for' composite
/// directive.
///
/// \code
/// #pragma omp teams distribute parallel for private(x)
/// \endcode
/// In this example directive '#pragma omp teams distribute parallel for'
/// has clause 'private' with the variables 'x'
///
class OMPTeamsDistributeParallelForDirective final : public OMPLoopDirective {
friend class ASTStmtReader;
/// true if the construct has inner cancel directive.
bool HasCancel = false;
/// Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
OMPTeamsDistributeParallelForDirective(SourceLocation StartLoc,
SourceLocation EndLoc,
unsigned CollapsedNum,
unsigned NumClauses)
: OMPLoopDirective(this, OMPTeamsDistributeParallelForDirectiveClass,
OMPD_teams_distribute_parallel_for, StartLoc, EndLoc,
CollapsedNum, NumClauses), HasCancel(false) {}
/// Build an empty directive.
///
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
explicit OMPTeamsDistributeParallelForDirective(unsigned CollapsedNum,
unsigned NumClauses)
: OMPLoopDirective(this, OMPTeamsDistributeParallelForDirectiveClass,
OMPD_teams_distribute_parallel_for, SourceLocation(),
SourceLocation(), CollapsedNum, NumClauses),
HasCancel(false) {}
/// Set cancel state.
void setHasCancel(bool Has) { HasCancel = Has; }
public:
/// Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param CollapsedNum Number of collapsed loops.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param Exprs Helper expressions for CodeGen.
/// \param HasCancel true if this directive has inner cancel directive.
///
static OMPTeamsDistributeParallelForDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt, const HelperExprs &Exprs, bool HasCancel);
/// Creates an empty directive with the place for \a NumClauses clauses.
///
/// \param C AST context.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
static OMPTeamsDistributeParallelForDirective *
CreateEmpty(const ASTContext &C, unsigned NumClauses, unsigned CollapsedNum,
EmptyShell);
/// Return true if current directive has inner cancel directive.
bool hasCancel() const { return HasCancel; }
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPTeamsDistributeParallelForDirectiveClass;
}
};
/// This represents '#pragma omp target teams' directive.
///
/// \code
/// #pragma omp target teams if(a>0)
/// \endcode
/// In this example directive '#pragma omp target teams' has clause 'if' with
/// condition 'a>0'.
///
class OMPTargetTeamsDirective final : public OMPExecutableDirective {
friend class ASTStmtReader;
/// Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param NumClauses Number of clauses.
///
OMPTargetTeamsDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned NumClauses)
: OMPExecutableDirective(this, OMPTargetTeamsDirectiveClass,
OMPD_target_teams, StartLoc, EndLoc, NumClauses,
1) {}
/// Build an empty directive.
///
/// \param NumClauses Number of clauses.
///
explicit OMPTargetTeamsDirective(unsigned NumClauses)
: OMPExecutableDirective(this, OMPTargetTeamsDirectiveClass,
OMPD_target_teams, SourceLocation(),
SourceLocation(), NumClauses, 1) {}
public:
/// Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
///
static OMPTargetTeamsDirective *Create(const ASTContext &C,
SourceLocation StartLoc,
SourceLocation EndLoc,
ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt);
/// Creates an empty directive with the place for \a NumClauses clauses.
///
/// \param C AST context.
/// \param NumClauses Number of clauses.
///
static OMPTargetTeamsDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses, EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPTargetTeamsDirectiveClass;
}
};
/// This represents '#pragma omp target teams distribute' combined directive.
///
/// \code
/// #pragma omp target teams distribute private(x)
/// \endcode
/// In this example directive '#pragma omp target teams distribute' has clause
/// 'private' with the variables 'x'
///
class OMPTargetTeamsDistributeDirective final : public OMPLoopDirective {
friend class ASTStmtReader;
/// Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
OMPTargetTeamsDistributeDirective(SourceLocation StartLoc,
SourceLocation EndLoc,
unsigned CollapsedNum, unsigned NumClauses)
: OMPLoopDirective(this, OMPTargetTeamsDistributeDirectiveClass,
OMPD_target_teams_distribute, StartLoc, EndLoc,
CollapsedNum, NumClauses) {}
/// Build an empty directive.
///
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
explicit OMPTargetTeamsDistributeDirective(unsigned CollapsedNum,
unsigned NumClauses)
: OMPLoopDirective(this, OMPTargetTeamsDistributeDirectiveClass,
OMPD_target_teams_distribute, SourceLocation(),
SourceLocation(), CollapsedNum, NumClauses) {}
public:
/// Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param CollapsedNum Number of collapsed loops.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param Exprs Helper expressions for CodeGen.
///
static OMPTargetTeamsDistributeDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt, const HelperExprs &Exprs);
/// Creates an empty directive with the place for \a NumClauses clauses.
///
/// \param C AST context.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
static OMPTargetTeamsDistributeDirective *
CreateEmpty(const ASTContext &C, unsigned NumClauses, unsigned CollapsedNum,
EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPTargetTeamsDistributeDirectiveClass;
}
};
/// This represents '#pragma omp target teams distribute parallel for' combined
/// directive.
///
/// \code
/// #pragma omp target teams distribute parallel for private(x)
/// \endcode
/// In this example directive '#pragma omp target teams distribute parallel
/// for' has clause 'private' with the variables 'x'
///
class OMPTargetTeamsDistributeParallelForDirective final
: public OMPLoopDirective {
friend class ASTStmtReader;
/// true if the construct has inner cancel directive.
bool HasCancel = false;
/// Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
OMPTargetTeamsDistributeParallelForDirective(SourceLocation StartLoc,
SourceLocation EndLoc,
unsigned CollapsedNum,
unsigned NumClauses)
: OMPLoopDirective(this,
OMPTargetTeamsDistributeParallelForDirectiveClass,
OMPD_target_teams_distribute_parallel_for, StartLoc,
EndLoc, CollapsedNum, NumClauses),
HasCancel(false) {}
/// Build an empty directive.
///
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
explicit OMPTargetTeamsDistributeParallelForDirective(unsigned CollapsedNum,
unsigned NumClauses)
: OMPLoopDirective(
this, OMPTargetTeamsDistributeParallelForDirectiveClass,
OMPD_target_teams_distribute_parallel_for, SourceLocation(),
SourceLocation(), CollapsedNum, NumClauses),
HasCancel(false) {}
/// Set cancel state.
void setHasCancel(bool Has) { HasCancel = Has; }
public:
/// Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param CollapsedNum Number of collapsed loops.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param Exprs Helper expressions for CodeGen.
/// \param HasCancel true if this directive has inner cancel directive.
///
static OMPTargetTeamsDistributeParallelForDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt, const HelperExprs &Exprs, bool HasCancel);
/// Creates an empty directive with the place for \a NumClauses clauses.
///
/// \param C AST context.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
static OMPTargetTeamsDistributeParallelForDirective *
CreateEmpty(const ASTContext &C, unsigned NumClauses, unsigned CollapsedNum,
EmptyShell);
/// Return true if current directive has inner cancel directive.
bool hasCancel() const { return HasCancel; }
static bool classof(const Stmt *T) {
return T->getStmtClass() ==
OMPTargetTeamsDistributeParallelForDirectiveClass;
}
};
/// This represents '#pragma omp target teams distribute parallel for simd'
/// combined directive.
///
/// \code
/// #pragma omp target teams distribute parallel for simd private(x)
/// \endcode
/// In this example directive '#pragma omp target teams distribute parallel
/// for simd' has clause 'private' with the variables 'x'
///
class OMPTargetTeamsDistributeParallelForSimdDirective final
: public OMPLoopDirective {
friend class ASTStmtReader;
/// Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
OMPTargetTeamsDistributeParallelForSimdDirective(SourceLocation StartLoc,
SourceLocation EndLoc,
unsigned CollapsedNum,
unsigned NumClauses)
: OMPLoopDirective(this,
OMPTargetTeamsDistributeParallelForSimdDirectiveClass,
OMPD_target_teams_distribute_parallel_for_simd,
StartLoc, EndLoc, CollapsedNum, NumClauses) {}
/// Build an empty directive.
///
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
explicit OMPTargetTeamsDistributeParallelForSimdDirective(
unsigned CollapsedNum, unsigned NumClauses)
: OMPLoopDirective(
this, OMPTargetTeamsDistributeParallelForSimdDirectiveClass,
OMPD_target_teams_distribute_parallel_for_simd, SourceLocation(),
SourceLocation(), CollapsedNum, NumClauses) {}
public:
/// Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param CollapsedNum Number of collapsed loops.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param Exprs Helper expressions for CodeGen.
///
static OMPTargetTeamsDistributeParallelForSimdDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt, const HelperExprs &Exprs);
/// Creates an empty directive with the place for \a NumClauses clauses.
///
/// \param C AST context.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
static OMPTargetTeamsDistributeParallelForSimdDirective *
CreateEmpty(const ASTContext &C, unsigned NumClauses, unsigned CollapsedNum,
EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() ==
OMPTargetTeamsDistributeParallelForSimdDirectiveClass;
}
};
/// This represents '#pragma omp target teams distribute simd' combined
/// directive.
///
/// \code
/// #pragma omp target teams distribute simd private(x)
/// \endcode
/// In this example directive '#pragma omp target teams distribute simd'
/// has clause 'private' with the variables 'x'
///
class OMPTargetTeamsDistributeSimdDirective final : public OMPLoopDirective {
friend class ASTStmtReader;
/// Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
OMPTargetTeamsDistributeSimdDirective(SourceLocation StartLoc,
SourceLocation EndLoc,
unsigned CollapsedNum,
unsigned NumClauses)
: OMPLoopDirective(this, OMPTargetTeamsDistributeSimdDirectiveClass,
OMPD_target_teams_distribute_simd, StartLoc, EndLoc,
CollapsedNum, NumClauses) {}
/// Build an empty directive.
///
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
explicit OMPTargetTeamsDistributeSimdDirective(unsigned CollapsedNum,
unsigned NumClauses)
: OMPLoopDirective(this, OMPTargetTeamsDistributeSimdDirectiveClass,
OMPD_target_teams_distribute_simd, SourceLocation(),
SourceLocation(), CollapsedNum, NumClauses) {}
public:
/// Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param CollapsedNum Number of collapsed loops.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param Exprs Helper expressions for CodeGen.
///
static OMPTargetTeamsDistributeSimdDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt, const HelperExprs &Exprs);
/// Creates an empty directive with the place for \a NumClauses clauses.
///
/// \param C AST context.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
static OMPTargetTeamsDistributeSimdDirective *
CreateEmpty(const ASTContext &C, unsigned NumClauses, unsigned CollapsedNum,
EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPTargetTeamsDistributeSimdDirectiveClass;
}
};
} // end namespace clang
#endif
|
runtime_error.c | // RUN: %libomp-compile-and-run 2>&1 | sort | FileCheck %s
// REQUIRES: ompt
#include <string.h>
#include <stdio.h>
#include "callback.h"
// TODO: use error directive when compiler suppors
typedef void ident_t;
extern void __kmpc_error(ident_t *, int, const char *);
int main() {
#pragma omp parallel num_threads(2)
{
if (omp_get_thread_num() == 0) {
const char *msg = "User message goes here";
printf("0: Message length=%" PRIu64 "\n", (uint64_t)strlen(msg));
__kmpc_error(NULL, ompt_warning, msg);
}
}
return 0;
}
// CHECK: {{^}}0: Message length=[[LENGTH:[0-9]+]]
// CHECK: {{^}}0: NULL_POINTER=[[NULL:.*$]]
// CHECK: {{^}}[[PRIMARY_ID:[0-9]+]]: ompt_event_implicit_task_begin
// CHECK: {{^}}[[PRIMARY_ID]]: ompt_event_runtime_error
// CHECK-SAME: severity=1
// CHECK-SAME: message=User message goes here
// CHECK-SAME: length=[[LENGTH]]
// CHECK-SAME: codeptr_ra={{0x[0-f]+}}
// Message from runtime
// CHECK: {{^}}OMP: Warning{{.*}}User message goes here
|
parallel1.c | #include <omp.h>
#include <stdio.h>
#define N 100000000
main()
{
int i, n, n1;
float a[N], b[N], c[N], d[N];
/*Some initializations */
for(i = 0; i < N; i++)
{
a[i] = b[i] = c[i] = i*1.0;
}
n = N;
omp_set_num_threads(2);
#pragma omp parallel shared (a,b,c,n) private(i)
{
#pragma omp sections nowait
{
#pragma omp section
{
for(i=0; i < n/2; i++)
d[i] = a[i] + b[i] + c[i];
}
#pragma omp section
{
for(i=n/2; i < n; i++)
d[i] = a[i] + b[i] + c[i];
}
/* end of sections */
}
n1 = omp_get_num_threads();
printf("Number of THRDS: %d\n", n1);
/* end of parallel section */
}
}
|
residual_based_implicit_time_scheme.h | // | / |
// ' / __| _` | __| _ \ __|
// . \ | ( | | ( |\__ `
// _|\_\_| \__,_|\__|\___/ ____/
// Multi-Physics
//
// License: BSD License
// Kratos default license: kratos/license.txt
//
// Main authors: Vicente Mataix Ferrandiz
//
#if !defined(KRATOS_RESIDUAL_BASED_IMPLICIT_TIME_SCHEME )
#define KRATOS_RESIDUAL_BASED_IMPLICIT_TIME_SCHEME
/* System includes */
/* External includes */
/* Project includes */
#include "solving_strategies/schemes/scheme.h"
namespace Kratos
{
///@name Kratos Globals
///@{
///@}
///@name Type Definitions
///@{
///@}
///@name Enum's
///@{
///@}
///@name Functions
///@{
///@}
///@name Kratos Classes
///@{
/**
* @class ResidualBasedImplicitTimeScheme
* @ingroup KratosCore
* @brief This is the base class for the implicit time schemes
* @details Other implicit schemes should derive from this one. With the use of this base scheme it is possible to reduce code duplication
* @tparam TSparseSpace The sparse space considered
* @tparam TDenseSpace The dense space considered
* @see Scheme
* @author Vicente Mataix Ferrandiz
*/
template<class TSparseSpace, class TDenseSpace >
class ResidualBasedImplicitTimeScheme
: public Scheme<TSparseSpace,TDenseSpace>
{
public:
///@name Type Definitions
///@{
/// Pointer definition of ResidualBasedImplicitTimeScheme
KRATOS_CLASS_POINTER_DEFINITION( ResidualBasedImplicitTimeScheme );
/// Base class definition
typedef Scheme<TSparseSpace,TDenseSpace> BaseType;
/// DoF array type definition
typedef typename BaseType::DofsArrayType DofsArrayType;
/// DoF vector type definition
typedef typename Element::DofsVectorType DofsVectorType;
/// Data type definition
typedef typename BaseType::TDataType TDataType;
/// Matrix type definition
typedef typename BaseType::TSystemMatrixType TSystemMatrixType;
/// Vector type definition
typedef typename BaseType::TSystemVectorType TSystemVectorType;
/// Local system matrix type definition
typedef typename BaseType::LocalSystemVectorType LocalSystemVectorType;
/// Local system vector type definition
typedef typename BaseType::LocalSystemMatrixType LocalSystemMatrixType;
/// Nodes containers definition
typedef ModelPart::NodesContainerType NodesArrayType;
/// Elements containers definition
typedef ModelPart::ElementsContainerType ElementsArrayType;
/// Conditions containers definition
typedef ModelPart::ConditionsContainerType ConditionsArrayType;
/// Index type definition
typedef std::size_t IndexType;
///@}
///@name Life Cycle
///@{
/**
* Constructor.
* The implicit method method
*/
explicit ResidualBasedImplicitTimeScheme()
:BaseType()
{
// Allocate auxiliary memory
const std::size_t num_threads = OpenMPUtils::GetNumThreads();
mMatrix.M.resize(num_threads);
mMatrix.D.resize(num_threads);
}
/** Copy Constructor.
*/
explicit ResidualBasedImplicitTimeScheme(ResidualBasedImplicitTimeScheme& rOther)
:BaseType(rOther)
,mMatrix(rOther.mMatrix)
{
}
/**
* Clone
*/
typename BaseType::Pointer Clone() override
{
return Kratos::make_shared<ResidualBasedImplicitTimeScheme>(*this);
}
/** Destructor.
*/
~ResidualBasedImplicitTimeScheme
() override {}
///@}
///@name Operators
///@{
///@}
///@name Operations
///@{
/**
* @brief It initializes a non-linear iteration (for the element)
* @param rModelPart The model part of the problem to solve
* @param A LHS matrix
* @param Dx Incremental update of primary variables
* @param b RHS Vector
*/
void InitializeNonLinIteration(
ModelPart& rModelPart,
TSystemMatrixType& A,
TSystemVectorType& Dx,
TSystemVectorType& b
) override
{
KRATOS_TRY;
const ProcessInfo& r_current_process_info = rModelPart.GetProcessInfo();
// Definition of the first element iterator
const auto it_elem_begin = rModelPart.ElementsBegin();
#pragma omp parallel for
for(int i=0; i<static_cast<int>(rModelPart.Elements().size()); ++i) {
auto it_elem = it_elem_begin + i;
it_elem->InitializeNonLinearIteration(r_current_process_info);
}
// Definition of the first condition iterator
const auto it_cond_begin = rModelPart.ConditionsBegin();
#pragma omp parallel for
for(int i=0; i<static_cast<int>(rModelPart.Conditions().size()); ++i) {
auto it_cond = it_cond_begin + i;
it_cond->InitializeNonLinearIteration(r_current_process_info);
}
// Definition of the first constraint iterator
const auto it_const_begin = rModelPart.MasterSlaveConstraintsBegin();
#pragma omp parallel for
for(int i=0; i<static_cast<int>(rModelPart.MasterSlaveConstraints().size()); ++i) {
auto it_const = it_const_begin + i;
it_const->InitializeNonLinearIteration(r_current_process_info);
}
KRATOS_CATCH( "" );
}
/**
* @brief It initializes a non-linear iteration (for an individual condition)
* @param pCurrentCondition The condition to compute
* @param rCurrentProcessInfo The current process info instance
*/
void InitializeNonLinearIteration(
Condition::Pointer pCurrentCondition,
ProcessInfo& rCurrentProcessInfo
) override
{
pCurrentCondition->InitializeNonLinearIteration(rCurrentProcessInfo);
}
/**
* @brief It initializes a non-linear iteration (for an individual element)
* @param pCurrentElement The element to compute
* @param rCurrentProcessInfo The current process info instance
*/
void InitializeNonLinearIteration(
Element::Pointer pCurrentElement,
ProcessInfo& rCurrentProcessInfo
) override
{
pCurrentElement->InitializeNonLinearIteration(rCurrentProcessInfo);
}
/**
* @brief This function is designed to be called in the builder and solver to introduce the selected time integration scheme.
* @details It "asks" the matrix needed to the element and performs the operations needed to introduce the selected time integration scheme. This function calculates at the same time the contribution to the LHS and to the RHS of the system
* @param rCurrentElement The element to compute
* @param LHS_Contribution The LHS matrix contribution
* @param RHS_Contribution The RHS vector contribution
* @param EquationId The ID's of the element degrees of freedom
* @param rCurrentProcessInfo The current process info instance
*/
void CalculateSystemContributions(
Element& rCurrentElement,
LocalSystemMatrixType& LHS_Contribution,
LocalSystemVectorType& RHS_Contribution,
Element::EquationIdVectorType& EquationId,
const ProcessInfo& rCurrentProcessInfo
) override
{
KRATOS_TRY;
const IndexType this_thread = OpenMPUtils::ThisThread();
//rCurrentElement.InitializeNonLinearIteration(rCurrentProcessInfo);
rCurrentElement.CalculateLocalSystem(LHS_Contribution,RHS_Contribution,rCurrentProcessInfo);
rCurrentElement.EquationIdVector(EquationId,rCurrentProcessInfo);
rCurrentElement.CalculateMassMatrix(mMatrix.M[this_thread],rCurrentProcessInfo);
rCurrentElement.CalculateDampingMatrix(mMatrix.D[this_thread],rCurrentProcessInfo);
AddDynamicsToLHS(LHS_Contribution, mMatrix.D[this_thread], mMatrix.M[this_thread], rCurrentProcessInfo);
AddDynamicsToRHS(rCurrentElement, RHS_Contribution, mMatrix.D[this_thread], mMatrix.M[this_thread], rCurrentProcessInfo);
KRATOS_CATCH("ResidualBasedImplicitTimeScheme.CalculateSystemContributions");
}
/**
* @brief This function is designed to calculate just the RHS contribution
* @param rCurrentElement The element to compute
* @param rRHSContribution The RHS vector contribution
* @param rEquationId The ID's of the element degrees of freedom
* @param rCurrentProcessInfo The current process info instance
*/
void CalculateRHSContribution(
Element& rCurrentElement,
LocalSystemVectorType& rRHSContribution,
Element::EquationIdVectorType& rEquationId,
const ProcessInfo& rCurrentProcessInfo
) override
{
KRATOS_TRY;
const IndexType this_thread = OpenMPUtils::ThisThread();
// Initializing the non linear iteration for the current element
// rCurrentElement.InitializeNonLinearIteration(rCurrentProcessInfo);
// Basic operations for the element considered
rCurrentElement.CalculateRightHandSide(rRHSContribution,rCurrentProcessInfo);
rCurrentElement.CalculateMassMatrix(mMatrix.M[this_thread], rCurrentProcessInfo);
rCurrentElement.CalculateDampingMatrix(mMatrix.D[this_thread],rCurrentProcessInfo);
rCurrentElement.EquationIdVector(rEquationId,rCurrentProcessInfo);
AddDynamicsToRHS (rCurrentElement, rRHSContribution, mMatrix.D[this_thread], mMatrix.M[this_thread], rCurrentProcessInfo);
KRATOS_CATCH("ResidualBasedImplicitTimeScheme.Calculate_RHS_Contribution");
}
/**
* @brief Functions totally analogous to the precedent but applied to the "condition" objects
* @param rCurrentCondition The condition to compute
* @param rLHSContribution The LHS matrix contribution
* @param rRHSContribution The RHS vector contribution
* @param rEquationId The ID's of the element degrees of freedom
* @param rCurrentProcessInfo The current process info instance
*/
void CalculateSystemContributions(
Condition& rCurrentCondition,
LocalSystemMatrixType& rLHSContribution,
LocalSystemVectorType& rRHSContribution,
Element::EquationIdVectorType& rEquationId,
const ProcessInfo& rCurrentProcessInfo
) override
{
KRATOS_TRY;
const IndexType this_thread = OpenMPUtils::ThisThread();
// Initializing the non linear iteration for the current condition
//rCurrentCondition.InitializeNonLinearIteration(rCurrentProcessInfo);
// Basic operations for the condition considered
rCurrentCondition.CalculateLocalSystem(rLHSContribution,rRHSContribution, rCurrentProcessInfo);
rCurrentCondition.EquationIdVector(rEquationId, rCurrentProcessInfo);
rCurrentCondition.CalculateMassMatrix(mMatrix.M[this_thread], rCurrentProcessInfo);
rCurrentCondition.CalculateDampingMatrix(mMatrix.D[this_thread], rCurrentProcessInfo);
AddDynamicsToLHS(rLHSContribution, mMatrix.D[this_thread], mMatrix.M[this_thread], rCurrentProcessInfo);
AddDynamicsToRHS(rCurrentCondition, rRHSContribution, mMatrix.D[this_thread], mMatrix.M[this_thread], rCurrentProcessInfo);
KRATOS_CATCH("ResidualBasedImplicitTimeScheme.CalculateSystemContributions");
}
/**
* @brief Functions that calculates the RHS of a "condition" object
* @param rCurrentCondition The condition to compute
* @param rRHSContribution The RHS vector contribution
* @param rEquationId The ID's of the condition degrees of freedom
* @param rCurrentProcessInfo The current process info instance
*/
void CalculateRHSContribution(
Condition& rCurrentCondition,
LocalSystemVectorType& rRHSContribution,
Element::EquationIdVectorType& rEquationId,
const ProcessInfo& rCurrentProcessInfo
) override
{
KRATOS_TRY;
const IndexType this_thread = OpenMPUtils::ThisThread();
// Initializing the non linear iteration for the current condition
//rCurrentCondition.InitializeNonLinearIteration(rCurrentProcessInfo);
// Basic operations for the condition considered
rCurrentCondition.CalculateRightHandSide(rRHSContribution, rCurrentProcessInfo);
rCurrentCondition.EquationIdVector(rEquationId, rCurrentProcessInfo);
rCurrentCondition.CalculateMassMatrix(mMatrix.M[this_thread], rCurrentProcessInfo);
rCurrentCondition.CalculateDampingMatrix(mMatrix.D[this_thread], rCurrentProcessInfo);
// Adding the dynamic contributions (static is already included)
AddDynamicsToRHS(rCurrentCondition, rRHSContribution, mMatrix.D[this_thread], mMatrix.M[this_thread], rCurrentProcessInfo);
KRATOS_CATCH("ResidualBasedImplicitTimeScheme.Calculate_RHS_Contribution");
}
/**
* @brief It initializes time step solution. Only for reasons if the time step solution is restarted
* @param rModelPart The model part of the problem to solve
* @param rA LHS matrix
* @param rDx Incremental update of primary variables
* @param rb RHS Vector
*/
void InitializeSolutionStep(
ModelPart& rModelPart,
TSystemMatrixType& rA,
TSystemVectorType& rDx,
TSystemVectorType& rb
) override
{
KRATOS_TRY;
const ProcessInfo r_current_process_info= rModelPart.GetProcessInfo();
BaseType::InitializeSolutionStep(rModelPart, rA, rDx, rb);
const double delta_time = r_current_process_info[DELTA_TIME];
KRATOS_ERROR_IF(delta_time < 1.0e-24) << "ERROR:: Detected delta_time = 0 in the Solution Scheme DELTA_TIME. PLEASE : check if the time step is created correctly for the current time step" << std::endl;
KRATOS_CATCH("ResidualBasedImplicitTimeScheme.InitializeSolutionStep");
}
/**
* @brief This function is designed to be called once to perform all the checks needed
* on the input provided.
* @details Checks can be "expensive" as the function is designed
* to catch user's errors.
* @param rModelPart The model part of the problem to solve
* @return Zero means all ok
*/
int Check(const ModelPart& rModelPart) const override
{
KRATOS_TRY;
const int err = BaseType::Check(rModelPart);
if(err!=0) return err;
return 0;
KRATOS_CATCH("ResidualBasedImplicitTimeScheme.Check");
}
///@}
///@name Access
///@{
///@}
///@name Inquiry
///@{
///@}
///@name Input and output
///@{
/// Turn back information as a string.
std::string Info() const override
{
return "ResidualBasedImplicitTimeScheme";
}
/// Print information about this object.
void PrintInfo(std::ostream& rOStream) const override
{
rOStream << Info();
}
/// Print object's data.
void PrintData(std::ostream& rOStream) const override
{
rOStream << Info();
}
///@}
///@name Friends
///@{
protected:
///@name Protected static Member Variables
///@{
///@}
///@name Protected member Variables
///@{
struct GeneralMatrices
{
std::vector< Matrix > M; /// First derivative matrix (usually mass matrix)
std::vector< Matrix > D; /// Second derivative matrix (usually damping matrix)
};
GeneralMatrices mMatrix;
///@}
///@name Protected Operators
///@{
///@}
///@name Protected Operations
///@{
/**
* @brief It adds the dynamic LHS contribution of the elements LHS = d(-RHS)/d(un0) = c0*c0*M + c0*D + K
* @param LHS_Contribution The dynamic contribution for the LHS
* @param D The damping matrix
* @param M The mass matrix
* @param rCurrentProcessInfo The current process info instance
*/
virtual void AddDynamicsToLHS(
LocalSystemMatrixType& LHS_Contribution,
LocalSystemMatrixType& D,
LocalSystemMatrixType& M,
const ProcessInfo& rCurrentProcessInfo
)
{
KRATOS_ERROR << "YOU ARE CALLING THE BASE CLASS OF AddDynamicsToLHS" << std::endl;
}
/**
* @brief It adds the dynamic RHS contribution of the elements b - M*a - D*v
* @param rCurrentElement The element to compute
* @param RHS_Contribution The dynamic contribution for the RHS
* @param D The damping matrix
* @param M The mass matrix
* @param rCurrentProcessInfo The current process info instance
*/
virtual void AddDynamicsToRHS(
Element& rCurrentElement,
LocalSystemVectorType& RHS_Contribution,
LocalSystemMatrixType& D,
LocalSystemMatrixType& M,
const ProcessInfo& rCurrentProcessInfo
)
{
KRATOS_ERROR << "YOU ARE CALLING THE BASE CLASS OF AddDynamicsToRHS" << std::endl;
}
/**
* @brief It adds the dynamic RHS contribution of the condition RHS = fext - M*an0 - D*vn0 - K*dn0
* @param rCurrentCondition The condition to compute
* @param RHS_Contribution The dynamic contribution for the RHS
* @param D The damping matrix
* @param M The mass matrix
* @param rCurrentProcessInfo The current process info instance
*/
virtual void AddDynamicsToRHS(
Condition& rCurrentCondition,
LocalSystemVectorType& RHS_Contribution,
LocalSystemMatrixType& D,
LocalSystemMatrixType& M,
const ProcessInfo& rCurrentProcessInfo
)
{
KRATOS_ERROR << "YOU ARE CALLING THE BASE CLASS OF AddDynamicsToRHS" << std::endl;
}
///@}
///@name Protected Access
///@{
///@}
///@name Protected Inquiry
///@{
///@}
///@name Protected LifeCycle
///@{
///@{
private:
///@name Static Member Variables
///@{
///@}
///@name Member Variables
///@{
///@}
///@name Private Operators
///@{
///@}
///@name Private Operations
///@{
///@}
///@name Private Access
///@{
///@}
///@}
///@name Serialization
///@{
///@name Private Inquiry
///@{
///@}
///@name Un accessible methods
///@{
///@}
}; /* Class ResidualBasedImplicitTimeScheme */
///@}
///@name Type Definitions
///@{
///@}
///@name Input and output
///@{
///@}
} /* namespace Kratos.*/
#endif /* KRATOS_RESIDUAL_BASED_IMPLICIT_TIME_SCHEME defined */
|
GB_binop__ge_int16.c | //------------------------------------------------------------------------------
// GB_binop: hard-coded functions for each built-in binary operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2021, All Rights Reserved.
// SPDX-License-Identifier: Apache-2.0
//------------------------------------------------------------------------------
// If this file is in the Generated2/ folder, do not edit it
// (it is auto-generated from Generator/*).
#include "GB.h"
#ifndef GBCOMPACT
#include "GB_emult.h"
#include "GB_control.h"
#include "GB_ek_slice.h"
#include "GB_dense.h"
#include "GB_atomics.h"
#include "GB_bitmap_assign_methods.h"
#include "GB_binop__include.h"
// C=binop(A,B) is defined by the following types and operators:
// A+B function (eWiseAdd): GB (_AaddB__ge_int16)
// A.*B function (eWiseMult): GB (_AemultB_01__ge_int16)
// A.*B function (eWiseMult): GB (_AemultB_02__ge_int16)
// A.*B function (eWiseMult): GB (_AemultB_03__ge_int16)
// A.*B function (eWiseMult): GB (_AemultB_bitmap__ge_int16)
// A*D function (colscale): GB (_AxD__ge_int16)
// D*A function (rowscale): GB (_DxB__ge_int16)
// C+=B function (dense accum): GB (_Cdense_accumB__ge_int16)
// C+=b function (dense accum): GB (_Cdense_accumb__ge_int16)
// C+=A+B function (dense ewise3): GB ((none))
// C=A+B function (dense ewise3): GB (_Cdense_ewise3_noaccum__ge_int16)
// C=scalar+B GB (_bind1st__ge_int16)
// C=scalar+B' GB (_bind1st_tran__ge_int16)
// C=A+scalar GB (_bind2nd__ge_int16)
// C=A'+scalar GB (_bind2nd_tran__ge_int16)
// C type: bool
// A type: int16_t
// B,b type: int16_t
// BinaryOp: cij = (aij >= bij)
#define GB_ATYPE \
int16_t
#define GB_BTYPE \
int16_t
#define GB_CTYPE \
bool
// true if the types of A and B are identical
#define GB_ATYPE_IS_BTYPE \
1
// true if the types of C and A are identical
#define GB_CTYPE_IS_ATYPE \
0
// true if the types of C and B are identical
#define GB_CTYPE_IS_BTYPE \
0
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA,A_iso) \
int16_t aij = GBX (Ax, pA, A_iso)
// bij = Bx [pB]
#define GB_GETB(bij,Bx,pB,B_iso) \
int16_t bij = GBX (Bx, pB, B_iso)
// declare scalar of the same type as C
#define GB_CTYPE_SCALAR(t) \
bool t
// cij = Ax [pA]
#define GB_COPY_A_TO_C(cij,Ax,pA,A_iso) \
cij = GBX (Ax, pA, A_iso)
// cij = Bx [pB]
#define GB_COPY_B_TO_C(cij,Bx,pB,B_iso) \
cij = GBX (Bx, pB, B_iso)
#define GB_CX(p) Cx [p]
// binary operator
#define GB_BINOP(z,x,y,i,j) \
z = (x >= y) ;
// true if the binop must be flipped
#define GB_BINOP_FLIP \
0
// op is second
#define GB_OP_IS_SECOND \
0
// do the numerical phases of GB_add and GB_emult
#define GB_PHASE_2_OF_2
// hard-coded loops can be vectorized
#define GB_PRAGMA_SIMD_VECTORIZE GB_PRAGMA_SIMD
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_GE || GxB_NO_INT16 || GxB_NO_GE_INT16)
//------------------------------------------------------------------------------
// C += A+B, all 3 matrices dense
//------------------------------------------------------------------------------
#if 0
// The op must be MIN, MAX, PLUS, MINUS, RMINUS, TIMES, DIV, or RDIV.
void GB ((none))
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix B,
const int nthreads
)
{
#include "GB_dense_ewise3_accum_template.c"
}
#endif
//------------------------------------------------------------------------------
// C = A+B, all 3 matrices dense
//------------------------------------------------------------------------------
GrB_Info GB (_Cdense_ewise3_noaccum__ge_int16)
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix B,
const int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_dense_ewise3_noaccum_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C += B, accumulate a sparse matrix into a dense matrix
//------------------------------------------------------------------------------
GrB_Info GB (_Cdense_accumB__ge_int16)
(
GrB_Matrix C,
const GrB_Matrix B,
const int64_t *B_ek_slicing, const int B_ntasks, const int B_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#if 0
{
#include "GB_dense_subassign_23_template.c"
}
#endif
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C += b, accumulate a scalar into a dense matrix
//------------------------------------------------------------------------------
GrB_Info GB (_Cdense_accumb__ge_int16)
(
GrB_Matrix C,
const GB_void *p_bwork,
const int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#if 0
{
// get the scalar b for C += b, of type int16_t
int16_t bwork = (*((int16_t *) p_bwork)) ;
#include "GB_dense_subassign_22_template.c"
return (GrB_SUCCESS) ;
}
#endif
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = A*D, column scale with diagonal D matrix
//------------------------------------------------------------------------------
GrB_Info GB (_AxD__ge_int16)
(
GrB_Matrix C,
const GrB_Matrix A, bool A_is_pattern,
const GrB_Matrix D, bool D_is_pattern,
const int64_t *A_ek_slicing, const int A_ntasks, const int A_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
bool *restrict Cx = (bool *) C->x ;
#include "GB_AxB_colscale_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = D*B, row scale with diagonal D matrix
//------------------------------------------------------------------------------
GrB_Info GB (_DxB__ge_int16)
(
GrB_Matrix C,
const GrB_Matrix D, bool D_is_pattern,
const GrB_Matrix B, bool B_is_pattern,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
bool *restrict Cx = (bool *) C->x ;
#include "GB_AxB_rowscale_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseAdd: C = A+B or C<M> = A+B
//------------------------------------------------------------------------------
GrB_Info GB (_AaddB__ge_int16)
(
GrB_Matrix C,
const int C_sparsity,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const bool Ch_is_Mh,
const int64_t *restrict C_to_M,
const int64_t *restrict C_to_A,
const int64_t *restrict C_to_B,
const GB_task_struct *restrict TaskList,
const int C_ntasks,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
GB_WERK_DECLARE (M_ek_slicing, int64_t) ;
GB_WERK_DECLARE (A_ek_slicing, int64_t) ;
GB_WERK_DECLARE (B_ek_slicing, int64_t) ;
#include "GB_add_template.c"
GB_FREE_WORK ;
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C = A.*B or C<M> = A.*B
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_01__ge_int16)
(
GrB_Matrix C,
const int C_sparsity,
const int ewise_method,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *restrict C_to_M,
const int64_t *restrict C_to_A,
const int64_t *restrict C_to_B,
const GB_task_struct *restrict TaskList,
const int C_ntasks,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_emult_01_meta.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C<#> = A.*B when A is sparse/hyper and B is bitmap/full
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_02__ge_int16)
(
GrB_Matrix C,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const bool flipxy,
const int64_t *restrict Cp_kfirst,
const int64_t *A_ek_slicing, const int A_ntasks, const int A_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#if GB_BINOP_FLIP
// The operator is not commutative, and does not have a flipped
// variant. For example z=atan2(y,x).
if (flipxy)
{
// use fmult(y,x)
#undef GB_FLIPPED
#define GB_FLIPPED 1
#include "GB_emult_02_template.c"
}
else
{
// use fmult(x,y)
#undef GB_FLIPPED
#define GB_FLIPPED 0
#include "GB_emult_02_template.c"
}
#else
// No need to handle the flip: the operator is either commutative, or
// has been handled by changing z=div(y,x) to z=rdiv(x,y) for example.
#undef GB_FLIPPED
#define GB_FLIPPED 0
#include "GB_emult_02_template.c"
#endif
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C<M> = A.*B, M sparse/hyper, A and B bitmap/full
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_03__ge_int16)
(
GrB_Matrix C,
const GrB_Matrix M,
const bool Mask_struct,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *restrict Cp_kfirst,
const int64_t *M_ek_slicing, const int M_ntasks, const int M_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_emult_03_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C=A.*B, C<M>=A.*B, C<!M>=A.*B where C is bitmap
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_bitmap__ge_int16)
(
GrB_Matrix C,
const int ewise_method,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *M_ek_slicing, const int M_ntasks, const int M_nthreads,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_bitmap_emult_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (x,Bx): apply a binary operator to a matrix with scalar bind1st
//------------------------------------------------------------------------------
GrB_Info GB (_bind1st__ge_int16)
(
GB_void *Cx_output, // Cx and Bx may be aliased
const GB_void *x_input,
const GB_void *Bx_input,
const int8_t *restrict Bb,
int64_t bnz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
bool *Cx = (bool *) Cx_output ;
int16_t x = (*((int16_t *) x_input)) ;
int16_t *Bx = (int16_t *) Bx_input ;
int64_t p ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < bnz ; p++)
{
if (!GBB (Bb, p)) continue ;
int16_t bij = GBX (Bx, p, false) ;
Cx [p] = (x >= bij) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (Ax,y): apply a binary operator to a matrix with scalar bind2nd
//------------------------------------------------------------------------------
GrB_Info GB (_bind2nd__ge_int16)
(
GB_void *Cx_output, // Cx and Ax may be aliased
const GB_void *Ax_input,
const GB_void *y_input,
const int8_t *restrict Ab,
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t p ;
bool *Cx = (bool *) Cx_output ;
int16_t *Ax = (int16_t *) Ax_input ;
int16_t y = (*((int16_t *) y_input)) ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
if (!GBB (Ab, p)) continue ;
int16_t aij = GBX (Ax, p, false) ;
Cx [p] = (aij >= y) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (x, A'): transpose and apply a binary operator
//------------------------------------------------------------------------------
// cij = op (x, aij), no typecasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
int16_t aij = GBX (Ax, pA, false) ; \
Cx [pC] = (x >= aij) ; \
}
GrB_Info GB (_bind1st_tran__ge_int16)
(
GrB_Matrix C,
const GB_void *x_input,
const GrB_Matrix A,
int64_t *restrict *Workspaces,
const int64_t *restrict A_slice,
int nworkspaces,
int nthreads
)
{
// GB_unop_transpose.c uses GB_ATYPE, but A is
// the 2nd input to binary operator z=f(x,y).
#undef GB_ATYPE
#define GB_ATYPE \
int16_t
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int16_t x = (*((const int16_t *) x_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
#undef GB_ATYPE
#define GB_ATYPE \
int16_t
}
//------------------------------------------------------------------------------
// C = op (A', y): transpose and apply a binary operator
//------------------------------------------------------------------------------
// cij = op (aij, y), no typecasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
int16_t aij = GBX (Ax, pA, false) ; \
Cx [pC] = (aij >= y) ; \
}
GrB_Info GB (_bind2nd_tran__ge_int16)
(
GrB_Matrix C,
const GrB_Matrix A,
const GB_void *y_input,
int64_t *restrict *Workspaces,
const int64_t *restrict A_slice,
int nworkspaces,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int16_t y = (*((const int16_t *) y_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
convolution_int8.h | // Tencent is pleased to support the open source community by making ncnn available.
//
// Copyright (C) 2022 THL A29 Limited, a Tencent company. All rights reserved.
//
// Licensed under the BSD 3-Clause License (the "License"); you may not use this file except
// in compliance with the License. You may obtain a copy of the License at
//
// https://opensource.org/licenses/BSD-3-Clause
//
// Unless required by applicable law or agreed to in writing, software distributed
// under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
// CONDITIONS OF ANY KIND, either express or implied. See the License for the
// specific language governing permissions and limitations under the License.
static void convolution_int8(const Mat& bottom_blob, Mat& top_blob, const Mat& weight_data_int8, int kernel_w, int kernel_h, int dilation_w, int dilation_h, int stride_w, int stride_h, const Option& opt)
{
int w = bottom_blob.w;
int channels = bottom_blob.c;
int outw = top_blob.w;
int outh = top_blob.h;
int outch = top_blob.c;
const int maxk = kernel_w * kernel_h;
// kernel offsets
std::vector<int> _space_ofs(maxk);
int* space_ofs = &_space_ofs[0];
{
int p1 = 0;
int p2 = 0;
int gap = w * dilation_h - kernel_w * dilation_w;
for (int i = 0; i < kernel_h; i++)
{
for (int j = 0; j < kernel_w; j++)
{
space_ofs[p1] = p2;
p1++;
p2 += dilation_w;
}
p2 += gap;
}
}
// num_output
#pragma omp parallel for num_threads(opt.num_threads)
for (int p = 0; p < outch; p++)
{
int* outptr = top_blob.channel(p);
for (int i = 0; i < outh; i++)
{
for (int j = 0; j < outw; j++)
{
int sum = 0;
// const signed char* kptr = weight_data_int8.channel(p);
const signed char* kptr = (const signed char*)weight_data_int8 + maxk * channels * p;
// channels
for (int q = 0; q < channels; q++)
{
const Mat m = bottom_blob.channel(q);
const signed char* sptr = m.row<signed char>(i * stride_h) + j * stride_w;
for (int k = 0; k < maxk; k++)
{
signed char val = sptr[space_ofs[k]];
signed char w = kptr[k];
sum += val * w;
}
kptr += maxk;
}
outptr[j] = sum;
}
outptr += outw;
}
}
}
|
sparselu.c | /**********************************************************************************************/
/* This program is part of the Barcelona OpenMP Tasks Suite */
/* Copyright (C) 2009 Barcelona Supercomputing Center - Centro Nacional de Supercomputacion */
/* Copyright (C) 2009 Universitat Politecnica de Catalunya */
/* */
/* This program is free software; you can redistribute it and/or modify */
/* it under the terms of the GNU General Public License as published by */
/* the Free Software Foundation; either version 2 of the License, or */
/* (at your option) any later version. */
/* */
/* This program is distributed in the hope that it will be useful, */
/* but WITHOUT ANY WARRANTY; without even the implied warranty of */
/* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the */
/* GNU General Public License for more details. */
/* */
/* You should have received a copy of the GNU General Public License */
/* along with this program; if not, write to the Free Software */
/* Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */
/**********************************************************************************************/
#include <stdio.h>
#include <stdint.h>
#include <stdlib.h>
#include <string.h>
#include <math.h>
#include <libgen.h>
#include "bots.h"
#include "sparselu.h"
#include "my_include.h"
/***********************************************************************
* checkmat:
**********************************************************************/
//double tmp[bots_arg_size][bots_arg_size][bots_arg_size_1*bots_arg_size_1];
int checkmat (double *M, double *N)
{
//printf("11111\n");
int i, j;
double r_err;
for (i = 0; i < bots_arg_size_1; i++)
{
for (j = 0; j < bots_arg_size_1; j++)
{
r_err = M[i*bots_arg_size_1+j] - N[i*bots_arg_size_1+j];
if (r_err < 0.0 ) r_err = -r_err;
r_err = r_err / M[i*bots_arg_size_1+j];
if(r_err > EPSILON)
{
bots_message("Checking failure: A[%d][%d]=%f B[%d][%d]=%f; Relative Error=%f\n",
i,j, M[i*bots_arg_size_1+j], i,j, N[i*bots_arg_size_1+j], r_err);
return FALSE;
}
}
}
return TRUE;
}
/***********************************************************************
* genmat:
**********************************************************************/
void genmat (double *M[])
{
int null_entry, init_val, i, j, ii, jj;
double *p;
double *prow;
double rowsum;
init_val = 1325;
/* generating the structure */
for (ii=0; ii < bots_arg_size; ii++)
{
for (jj=0; jj < bots_arg_size; jj++)
{
/* computing null entries */
null_entry=FALSE;
if ((ii<jj) && (ii%3 !=0)) null_entry = TRUE;
if ((ii>jj) && (jj%3 !=0)) null_entry = TRUE;
if (ii%2==1) null_entry = TRUE;
if (jj%2==1) null_entry = TRUE;
if (ii==jj) null_entry = FALSE;
if (ii==jj-1) null_entry = FALSE;
if (ii-1 == jj) null_entry = FALSE;
/* allocating matrix */
if (null_entry == FALSE){
// M[ii*bots_arg_size+jj] = (double *) malloc(bots_arg_size_1*bots_arg_size_1*sizeof(double));
M[ii*bots_arg_size+jj] = (double*)tmp + tmp_pos;
tmp_pos += bots_arg_size_1*bots_arg_size_1*sizeof(double);
if ((M[ii*bots_arg_size+jj] == NULL))
{
bots_message("Error: Out of memory\n");
exit(101);
}
/* initializing matrix */
/* Modify diagonal element of each row in order */
/* to ensure matrix is diagonally dominant and */
/* well conditioned. */
prow = p = M[ii*bots_arg_size+jj];
for (i = 0; i < bots_arg_size_1; i++)
{
rowsum = 0.0;
for (j = 0; j < bots_arg_size_1; j++)
{
init_val = (3125 * init_val) % 65536;
(*p) = (double)((init_val - 32768.0) / 16384.0);
rowsum += abs(*p);
p++;
}
if (ii == jj)
*(prow+i) = rowsum * (double) bots_arg_size + abs(*(prow+i));
prow += bots_arg_size_1;
}
}
else
{
M[ii*bots_arg_size+jj] = NULL;
}
}
}
}
/***********************************************************************
* print_structure:
**********************************************************************/
void print_structure(char *name, double *M[])
{
int ii, jj;
bots_message("Structure for matrix %s @ 0x%p\n",name, M);
for (ii = 0; ii < bots_arg_size; ii++) {
for (jj = 0; jj < bots_arg_size; jj++) {
if (M[ii*bots_arg_size+jj]!=NULL) {bots_message("x");}
else bots_message(" ");
}
bots_message("\n");
}
bots_message("\n");
}
/***********************************************************************
* allocate_clean_block:
**********************************************************************/
double * allocate_clean_block()
{
int i,j;
double *p, *q;
//printf("1\n");
//p = (double *) malloc(bots_arg_size_1*bots_arg_size_1*sizeof(double));
p = (double*)tmp + tmp_pos;
tmp_pos += bots_arg_size_1*bots_arg_size_1*sizeof(double);
q=p;
if (p!=NULL){
for (i = 0; i < bots_arg_size_1; i++)
for (j = 0; j < bots_arg_size_1; j++){(*p)=0.0; p++;}
}
else
{
bots_message("Error: Out of memory\n");
exit (101);
}
return (q);
}
/***********************************************************************
* lu0:
**********************************************************************/
void lu0(double *diag)
{
int i, j, k;
for (k=0; k<bots_arg_size_1; k++)
for (i=k+1; i<bots_arg_size_1; i++)
{
diag[i*bots_arg_size_1+k] = diag[i*bots_arg_size_1+k] / diag[k*bots_arg_size_1+k];
for (j=k+1; j<bots_arg_size_1; j++)
diag[i*bots_arg_size_1+j] = diag[i*bots_arg_size_1+j] - diag[i*bots_arg_size_1+k] * diag[k*bots_arg_size_1+j];
}
}
/***********************************************************************
* bdiv:
**********************************************************************/
void bdiv(double *diag, double *row)
{
int i, j, k;
for (i=0; i<bots_arg_size_1; i++) {
for (k=0; k<bots_arg_size_1; k++)
{
row[i*bots_arg_size_1+k] = row[i*bots_arg_size_1+k] / diag[k*bots_arg_size_1+k];
for (j=k+1; j<bots_arg_size_1; j++)
row[i*bots_arg_size_1+j] = row[i*bots_arg_size_1+j] - row[i*bots_arg_size_1+k]*diag[k*bots_arg_size_1+j];
}
//kai
flag5 = i;
}
}
/***********************************************************************
* bmod:
**********************************************************************/
void bmod(double *row, double *col, double *inner)
{
int i, j, k;
for (i=0; i<bots_arg_size_1; i++)
for (j=0; j<bots_arg_size_1; j++)
for (k=0; k<bots_arg_size_1; k++)
inner[i*bots_arg_size_1+j] = inner[i*bots_arg_size_1+j] - row[i*bots_arg_size_1+k]*col[k*bots_arg_size_1+j];
}
/***********************************************************************
* fwd:
**********************************************************************/
void fwd(double *diag, double *col)
{
int i, j, k;
for (j=0; j<bots_arg_size_1; j++)
for (k=0; k<bots_arg_size_1; k++)
for (i=k+1; i<bots_arg_size_1; i++)
col[i*bots_arg_size_1+j] = col[i*bots_arg_size_1+j] - diag[i*bots_arg_size_1+k]*col[k*bots_arg_size_1+j];
}
void sparselu_init (double ***pBENCH, char *pass)
{
// *pBENCH = (double **) malloc(bots_arg_size*bots_arg_size*sizeof(double *));
// printf("%s\n", pass):
tmp = malloc(bots_arg_size*bots_arg_size*sizeof(double *) + bots_arg_size * ((bots_arg_size*bots_arg_size)*bots_arg_size_1*bots_arg_size_1*sizeof(double)));
*pBENCH = (double **)tmp + tmp_pos;
tmp_pos += bots_arg_size*bots_arg_size*sizeof(double *);
genmat(*pBENCH);
crucial_data(tmp, "double", bots_arg_size*bots_arg_size + (3)*(bots_arg_size*bots_arg_size*bots_arg_size_1*bots_arg_size_1));
//kai
consistent_data(&flag1, "int", 1);
consistent_data(&flag2, "int", 1);
consistent_data(&flag3, "int", 1);
consistent_data(&flag4, "int", 1);
consistent_data(&flag5, "int", 1);
/* spec print_structure(pass, *pBENCH); */
}
void sparselu_par_call(double **BENCH)
{
//printf("1111\n");
int ii, jj, kk;
bots_message("Computing SparseLU Factorization (%dx%d matrix with %dx%d blocks) ",
bots_arg_size,bots_arg_size,bots_arg_size_1,bots_arg_size_1);
//kai
start_crash();
#pragma omp parallel
#pragma omp single nowait
for (kk=0; kk<bots_arg_size; kk++)
{
lu0(BENCH[kk*bots_arg_size+kk]);
for (jj=kk+1; jj<bots_arg_size; jj++) {
if (BENCH[kk*bots_arg_size+jj] != NULL)
#pragma omp task untied firstprivate(kk, jj) shared(BENCH)
{
fwd(BENCH[kk*bots_arg_size+kk], BENCH[kk*bots_arg_size+jj]);
}
//kai
flag2 = kk;
}
for (ii=kk+1; ii<bots_arg_size; ii++) {
if (BENCH[ii*bots_arg_size+kk] != NULL)
#pragma omp task untied firstprivate(kk, ii) shared(BENCH)
{
bdiv (BENCH[kk*bots_arg_size+kk], BENCH[ii*bots_arg_size+kk]);
}
//kai
flag3 = ii;
}
#pragma omp taskwait
// printf("1111111111111\n");
for (ii=kk+1; ii<bots_arg_size; ii++) {
if (BENCH[ii*bots_arg_size+kk] != NULL)
for (jj=kk+1; jj<bots_arg_size; jj++)
if (BENCH[kk*bots_arg_size+jj] != NULL)
#pragma omp task untied firstprivate(kk, jj, ii) shared(BENCH)
{
if (BENCH[ii*bots_arg_size+jj]==NULL) BENCH[ii*bots_arg_size+jj] = allocate_clean_block();
bmod(BENCH[ii*bots_arg_size+kk], BENCH[kk*bots_arg_size+jj], BENCH[ii*bots_arg_size+jj]);
}
//kai
flag4 = ii;
}
#pragma omp taskwait
flag1 = kk;
}
//kai
end_crash();
bots_message(" completed!\n");
}
void sparselu_seq_call(double **BENCH)
{
int ii, jj, kk;
for (kk=0; kk<bots_arg_size; kk++)
{
lu0(BENCH[kk*bots_arg_size+kk]);
for (jj=kk+1; jj<bots_arg_size; jj++)
if (BENCH[kk*bots_arg_size+jj] != NULL)
{
fwd(BENCH[kk*bots_arg_size+kk], BENCH[kk*bots_arg_size+jj]);
}
for (ii=kk+1; ii<bots_arg_size; ii++)
if (BENCH[ii*bots_arg_size+kk] != NULL)
{
bdiv (BENCH[kk*bots_arg_size+kk], BENCH[ii*bots_arg_size+kk]);
}
for (ii=kk+1; ii<bots_arg_size; ii++)
if (BENCH[ii*bots_arg_size+kk] != NULL)
for (jj=kk+1; jj<bots_arg_size; jj++)
if (BENCH[kk*bots_arg_size+jj] != NULL)
{
if (BENCH[ii*bots_arg_size+jj]==NULL) BENCH[ii*bots_arg_size+jj] = allocate_clean_block();
bmod(BENCH[ii*bots_arg_size+kk], BENCH[kk*bots_arg_size+jj], BENCH[ii*bots_arg_size+jj]);
}
}
}
void sparselu_fini (double **BENCH, char *pass)
{
/* spec print_structure(pass, BENCH); */
return;
}
/*
* changes for SPEC, original source
*
int sparselu_check(double **SEQ, double **BENCH)
{
int ii,jj,ok=1;
for (ii=0; ((ii<bots_arg_size) && ok); ii++)
{
for (jj=0; ((jj<bots_arg_size) && ok); jj++)
{
if ((SEQ[ii*bots_arg_size+jj] == NULL) && (BENCH[ii*bots_arg_size+jj] != NULL)) ok = FALSE;
if ((SEQ[ii*bots_arg_size+jj] != NULL) && (BENCH[ii*bots_arg_size+jj] == NULL)) ok = FALSE;
if ((SEQ[ii*bots_arg_size+jj] != NULL) && (BENCH[ii*bots_arg_size+jj] != NULL))
ok = checkmat(SEQ[ii*bots_arg_size+jj], BENCH[ii*bots_arg_size+jj]);
}
}
if (ok) return BOTS_RESULT_SUCCESSFUL;
else return BOTS_RESULT_UNSUCCESSFUL;
}
*/
/*
* SPEC modified check, print out values
*
*/
int sparselu_check(double **SEQ, double **BENCH)
{
int i, j, ok;
bots_message("Output size: %d\n",bots_arg_size);
for (i = 0; i < bots_arg_size; i+=50)
{
for (j = 0; j < bots_arg_size; j+=40)
{
ok = checkmat1(BENCH[i*bots_arg_size+j]);
}
}
return BOTS_RESULT_SUCCESSFUL;
}
int checkmat1 (double *N)
{
int i, j;
for (i = 0; i < bots_arg_size_1; i+=20)
{
for (j = 0; j < bots_arg_size_1; j+=20)
{
bots_message("Output Matrix: A[%d][%d]=%8.12f \n",
i,j, N[i*bots_arg_size_1+j]);
}
}
//printf("111111111\n");
return TRUE;
}
|
pzgeswp.c | /**
*
* @file
*
* PLASMA is a software package provided by:
* University of Tennessee, US,
* University of Manchester, UK.
*
* @precisions normal z -> s d c
*
**/
#include "plasma_async.h"
#include "plasma_descriptor.h"
#include "plasma_internal.h"
#include "plasma_types.h"
#include "core_blas.h"
#define A(m, n) (plasma_complex64_t*)plasma_tile_addr(A, m, n)
/******************************************************************************/
void plasma_pzgeswp(plasma_enum_t colrow,
plasma_desc_t A, int *ipiv, int incx,
plasma_sequence_t *sequence, plasma_request_t *request)
{
// Return if failed sequence.
if (sequence->status != PlasmaSuccess)
return;
if (colrow == PlasmaRowwise) {
for (int n = 0; n < A.nt; n++) {
plasma_complex64_t *a00, *a10;
a00 = A(0, n);
a10 = A(A.mt-1, n);
int ma00 = (A.mt-1)*A.mb;
int na00 = plasma_tile_nmain(A, n);
int lda10 = plasma_tile_mmain(A, A.mt-1);
int nva10 = plasma_tile_nview(A, n);
#pragma omp task depend (inout:a00[0:ma00*na00]) \
depend (inout:a10[0:lda10*nva10])
{
int nvan = plasma_tile_nview(A, n);
plasma_desc_t view = plasma_desc_view(A, 0, n*A.nb, A.m, nvan);
core_zgeswp(colrow, view, 1, A.m, ipiv, incx);
}
}
}
else {
for (int m = 0; m < A.mt; m++) {
int mvam = plasma_tile_mview(A, m);
plasma_desc_t view = plasma_desc_view(A, m*A.mb, 0, mvam, A.n);
core_zgeswp(colrow, view, 1, A.n, ipiv, incx);
}
}
}
|
ASTMatchers.h | //===- ASTMatchers.h - Structural query framework ---------------*- C++ -*-===//
//
// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
// See https://llvm.org/LICENSE.txt for license information.
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
//
//===----------------------------------------------------------------------===//
//
// This file implements matchers to be used together with the MatchFinder to
// match AST nodes.
//
// Matchers are created by generator functions, which can be combined in
// a functional in-language DSL to express queries over the C++ AST.
//
// For example, to match a class with a certain name, one would call:
// cxxRecordDecl(hasName("MyClass"))
// which returns a matcher that can be used to find all AST nodes that declare
// a class named 'MyClass'.
//
// For more complicated match expressions we're often interested in accessing
// multiple parts of the matched AST nodes once a match is found. In that case,
// call `.bind("name")` on match expressions that match the nodes you want to
// access.
//
// For example, when we're interested in child classes of a certain class, we
// would write:
// cxxRecordDecl(hasName("MyClass"), has(recordDecl().bind("child")))
// When the match is found via the MatchFinder, a user provided callback will
// be called with a BoundNodes instance that contains a mapping from the
// strings that we provided for the `.bind()` calls to the nodes that were
// matched.
// In the given example, each time our matcher finds a match we get a callback
// where "child" is bound to the RecordDecl node of the matching child
// class declaration.
//
// See ASTMatchersInternal.h for a more in-depth explanation of the
// implementation details of the matcher framework.
//
// See ASTMatchFinder.h for how to use the generated matchers to run over
// an AST.
//
//===----------------------------------------------------------------------===//
#ifndef LLVM_CLANG_ASTMATCHERS_ASTMATCHERS_H
#define LLVM_CLANG_ASTMATCHERS_ASTMATCHERS_H
#include "clang/AST/ASTContext.h"
#include "clang/AST/ASTTypeTraits.h"
#include "clang/AST/Attr.h"
#include "clang/AST/Decl.h"
#include "clang/AST/DeclCXX.h"
#include "clang/AST/DeclFriend.h"
#include "clang/AST/DeclObjC.h"
#include "clang/AST/DeclTemplate.h"
#include "clang/AST/Expr.h"
#include "clang/AST/ExprCXX.h"
#include "clang/AST/ExprObjC.h"
#include "clang/AST/LambdaCapture.h"
#include "clang/AST/NestedNameSpecifier.h"
#include "clang/AST/OpenMPClause.h"
#include "clang/AST/OperationKinds.h"
#include "clang/AST/Stmt.h"
#include "clang/AST/StmtCXX.h"
#include "clang/AST/StmtObjC.h"
#include "clang/AST/StmtOpenMP.h"
#include "clang/AST/TemplateBase.h"
#include "clang/AST/TemplateName.h"
#include "clang/AST/Type.h"
#include "clang/AST/TypeLoc.h"
#include "clang/ASTMatchers/ASTMatchersInternal.h"
#include "clang/ASTMatchers/ASTMatchersMacros.h"
#include "clang/Basic/AttrKinds.h"
#include "clang/Basic/ExceptionSpecificationType.h"
#include "clang/Basic/IdentifierTable.h"
#include "clang/Basic/LLVM.h"
#include "clang/Basic/SourceManager.h"
#include "clang/Basic/Specifiers.h"
#include "clang/Basic/TypeTraits.h"
#include "llvm/ADT/ArrayRef.h"
#include "llvm/ADT/SmallVector.h"
#include "llvm/ADT/StringRef.h"
#include "llvm/Support/Casting.h"
#include "llvm/Support/Compiler.h"
#include "llvm/Support/ErrorHandling.h"
#include "llvm/Support/Regex.h"
#include <cassert>
#include <cstddef>
#include <iterator>
#include <limits>
#include <string>
#include <utility>
#include <vector>
namespace clang {
namespace ast_matchers {
/// Maps string IDs to AST nodes matched by parts of a matcher.
///
/// The bound nodes are generated by calling \c bind("id") on the node matchers
/// of the nodes we want to access later.
///
/// The instances of BoundNodes are created by \c MatchFinder when the user's
/// callbacks are executed every time a match is found.
class BoundNodes {
public:
/// Returns the AST node bound to \c ID.
///
/// Returns NULL if there was no node bound to \c ID or if there is a node but
/// it cannot be converted to the specified type.
template <typename T>
const T *getNodeAs(StringRef ID) const {
return MyBoundNodes.getNodeAs<T>(ID);
}
/// Type of mapping from binding identifiers to bound nodes. This type
/// is an associative container with a key type of \c std::string and a value
/// type of \c clang::ast_type_traits::DynTypedNode
using IDToNodeMap = internal::BoundNodesMap::IDToNodeMap;
/// Retrieve mapping from binding identifiers to bound nodes.
const IDToNodeMap &getMap() const {
return MyBoundNodes.getMap();
}
private:
friend class internal::BoundNodesTreeBuilder;
/// Create BoundNodes from a pre-filled map of bindings.
BoundNodes(internal::BoundNodesMap &MyBoundNodes)
: MyBoundNodes(MyBoundNodes) {}
internal::BoundNodesMap MyBoundNodes;
};
/// Types of matchers for the top-level classes in the AST class
/// hierarchy.
/// @{
using DeclarationMatcher = internal::Matcher<Decl>;
using StatementMatcher = internal::Matcher<Stmt>;
using TypeMatcher = internal::Matcher<QualType>;
using TypeLocMatcher = internal::Matcher<TypeLoc>;
using NestedNameSpecifierMatcher = internal::Matcher<NestedNameSpecifier>;
using NestedNameSpecifierLocMatcher = internal::Matcher<NestedNameSpecifierLoc>;
using CXXCtorInitializerMatcher = internal::Matcher<CXXCtorInitializer>;
/// @}
/// Matches any node.
///
/// Useful when another matcher requires a child matcher, but there's no
/// additional constraint. This will often be used with an explicit conversion
/// to an \c internal::Matcher<> type such as \c TypeMatcher.
///
/// Example: \c DeclarationMatcher(anything()) matches all declarations, e.g.,
/// \code
/// "int* p" and "void f()" in
/// int* p;
/// void f();
/// \endcode
///
/// Usable as: Any Matcher
inline internal::TrueMatcher anything() { return internal::TrueMatcher(); }
/// Matches the top declaration context.
///
/// Given
/// \code
/// int X;
/// namespace NS {
/// int Y;
/// } // namespace NS
/// \endcode
/// decl(hasDeclContext(translationUnitDecl()))
/// matches "int X", but not "int Y".
extern const internal::VariadicDynCastAllOfMatcher<Decl, TranslationUnitDecl>
translationUnitDecl;
/// Matches typedef declarations.
///
/// Given
/// \code
/// typedef int X;
/// using Y = int;
/// \endcode
/// typedefDecl()
/// matches "typedef int X", but not "using Y = int"
extern const internal::VariadicDynCastAllOfMatcher<Decl, TypedefDecl>
typedefDecl;
/// Matches typedef name declarations.
///
/// Given
/// \code
/// typedef int X;
/// using Y = int;
/// \endcode
/// typedefNameDecl()
/// matches "typedef int X" and "using Y = int"
extern const internal::VariadicDynCastAllOfMatcher<Decl, TypedefNameDecl>
typedefNameDecl;
/// Matches type alias declarations.
///
/// Given
/// \code
/// typedef int X;
/// using Y = int;
/// \endcode
/// typeAliasDecl()
/// matches "using Y = int", but not "typedef int X"
extern const internal::VariadicDynCastAllOfMatcher<Decl, TypeAliasDecl>
typeAliasDecl;
/// Matches type alias template declarations.
///
/// typeAliasTemplateDecl() matches
/// \code
/// template <typename T>
/// using Y = X<T>;
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, TypeAliasTemplateDecl>
typeAliasTemplateDecl;
/// Matches AST nodes that were expanded within the main-file.
///
/// Example matches X but not Y
/// (matcher = cxxRecordDecl(isExpansionInMainFile())
/// \code
/// #include <Y.h>
/// class X {};
/// \endcode
/// Y.h:
/// \code
/// class Y {};
/// \endcode
///
/// Usable as: Matcher<Decl>, Matcher<Stmt>, Matcher<TypeLoc>
AST_POLYMORPHIC_MATCHER(isExpansionInMainFile,
AST_POLYMORPHIC_SUPPORTED_TYPES(Decl, Stmt, TypeLoc)) {
auto &SourceManager = Finder->getASTContext().getSourceManager();
return SourceManager.isInMainFile(
SourceManager.getExpansionLoc(Node.getBeginLoc()));
}
/// Matches AST nodes that were expanded within system-header-files.
///
/// Example matches Y but not X
/// (matcher = cxxRecordDecl(isExpansionInSystemHeader())
/// \code
/// #include <SystemHeader.h>
/// class X {};
/// \endcode
/// SystemHeader.h:
/// \code
/// class Y {};
/// \endcode
///
/// Usable as: Matcher<Decl>, Matcher<Stmt>, Matcher<TypeLoc>
AST_POLYMORPHIC_MATCHER(isExpansionInSystemHeader,
AST_POLYMORPHIC_SUPPORTED_TYPES(Decl, Stmt, TypeLoc)) {
auto &SourceManager = Finder->getASTContext().getSourceManager();
auto ExpansionLoc = SourceManager.getExpansionLoc(Node.getBeginLoc());
if (ExpansionLoc.isInvalid()) {
return false;
}
return SourceManager.isInSystemHeader(ExpansionLoc);
}
/// Matches AST nodes that were expanded within files whose name is
/// partially matching a given regex.
///
/// Example matches Y but not X
/// (matcher = cxxRecordDecl(isExpansionInFileMatching("AST.*"))
/// \code
/// #include "ASTMatcher.h"
/// class X {};
/// \endcode
/// ASTMatcher.h:
/// \code
/// class Y {};
/// \endcode
///
/// Usable as: Matcher<Decl>, Matcher<Stmt>, Matcher<TypeLoc>
AST_POLYMORPHIC_MATCHER_P(isExpansionInFileMatching,
AST_POLYMORPHIC_SUPPORTED_TYPES(Decl, Stmt, TypeLoc),
std::string, RegExp) {
auto &SourceManager = Finder->getASTContext().getSourceManager();
auto ExpansionLoc = SourceManager.getExpansionLoc(Node.getBeginLoc());
if (ExpansionLoc.isInvalid()) {
return false;
}
auto FileEntry =
SourceManager.getFileEntryForID(SourceManager.getFileID(ExpansionLoc));
if (!FileEntry) {
return false;
}
auto Filename = FileEntry->getName();
llvm::Regex RE(RegExp);
return RE.match(Filename);
}
/// Matches declarations.
///
/// Examples matches \c X, \c C, and the friend declaration inside \c C;
/// \code
/// void X();
/// class C {
/// friend X;
/// };
/// \endcode
extern const internal::VariadicAllOfMatcher<Decl> decl;
/// Matches a declaration of a linkage specification.
///
/// Given
/// \code
/// extern "C" {}
/// \endcode
/// linkageSpecDecl()
/// matches "extern "C" {}"
extern const internal::VariadicDynCastAllOfMatcher<Decl, LinkageSpecDecl>
linkageSpecDecl;
/// Matches a declaration of anything that could have a name.
///
/// Example matches \c X, \c S, the anonymous union type, \c i, and \c U;
/// \code
/// typedef int X;
/// struct S {
/// union {
/// int i;
/// } U;
/// };
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, NamedDecl> namedDecl;
/// Matches a declaration of label.
///
/// Given
/// \code
/// goto FOO;
/// FOO: bar();
/// \endcode
/// labelDecl()
/// matches 'FOO:'
extern const internal::VariadicDynCastAllOfMatcher<Decl, LabelDecl> labelDecl;
/// Matches a declaration of a namespace.
///
/// Given
/// \code
/// namespace {}
/// namespace test {}
/// \endcode
/// namespaceDecl()
/// matches "namespace {}" and "namespace test {}"
extern const internal::VariadicDynCastAllOfMatcher<Decl, NamespaceDecl>
namespaceDecl;
/// Matches a declaration of a namespace alias.
///
/// Given
/// \code
/// namespace test {}
/// namespace alias = ::test;
/// \endcode
/// namespaceAliasDecl()
/// matches "namespace alias" but not "namespace test"
extern const internal::VariadicDynCastAllOfMatcher<Decl, NamespaceAliasDecl>
namespaceAliasDecl;
/// Matches class, struct, and union declarations.
///
/// Example matches \c X, \c Z, \c U, and \c S
/// \code
/// class X;
/// template<class T> class Z {};
/// struct S {};
/// union U {};
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, RecordDecl> recordDecl;
/// Matches C++ class declarations.
///
/// Example matches \c X, \c Z
/// \code
/// class X;
/// template<class T> class Z {};
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, CXXRecordDecl>
cxxRecordDecl;
/// Matches C++ class template declarations.
///
/// Example matches \c Z
/// \code
/// template<class T> class Z {};
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, ClassTemplateDecl>
classTemplateDecl;
/// Matches C++ class template specializations.
///
/// Given
/// \code
/// template<typename T> class A {};
/// template<> class A<double> {};
/// A<int> a;
/// \endcode
/// classTemplateSpecializationDecl()
/// matches the specializations \c A<int> and \c A<double>
extern const internal::VariadicDynCastAllOfMatcher<
Decl, ClassTemplateSpecializationDecl>
classTemplateSpecializationDecl;
/// Matches C++ class template partial specializations.
///
/// Given
/// \code
/// template<class T1, class T2, int I>
/// class A {};
///
/// template<class T, int I>
/// class A<T, T*, I> {};
///
/// template<>
/// class A<int, int, 1> {};
/// \endcode
/// classTemplatePartialSpecializationDecl()
/// matches the specialization \c A<T,T*,I> but not \c A<int,int,1>
extern const internal::VariadicDynCastAllOfMatcher<
Decl, ClassTemplatePartialSpecializationDecl>
classTemplatePartialSpecializationDecl;
/// Matches declarator declarations (field, variable, function
/// and non-type template parameter declarations).
///
/// Given
/// \code
/// class X { int y; };
/// \endcode
/// declaratorDecl()
/// matches \c int y.
extern const internal::VariadicDynCastAllOfMatcher<Decl, DeclaratorDecl>
declaratorDecl;
/// Matches parameter variable declarations.
///
/// Given
/// \code
/// void f(int x);
/// \endcode
/// parmVarDecl()
/// matches \c int x.
extern const internal::VariadicDynCastAllOfMatcher<Decl, ParmVarDecl>
parmVarDecl;
/// Matches C++ access specifier declarations.
///
/// Given
/// \code
/// class C {
/// public:
/// int a;
/// };
/// \endcode
/// accessSpecDecl()
/// matches 'public:'
extern const internal::VariadicDynCastAllOfMatcher<Decl, AccessSpecDecl>
accessSpecDecl;
/// Matches constructor initializers.
///
/// Examples matches \c i(42).
/// \code
/// class C {
/// C() : i(42) {}
/// int i;
/// };
/// \endcode
extern const internal::VariadicAllOfMatcher<CXXCtorInitializer>
cxxCtorInitializer;
/// Matches template arguments.
///
/// Given
/// \code
/// template <typename T> struct C {};
/// C<int> c;
/// \endcode
/// templateArgument()
/// matches 'int' in C<int>.
extern const internal::VariadicAllOfMatcher<TemplateArgument> templateArgument;
/// Matches template name.
///
/// Given
/// \code
/// template <typename T> class X { };
/// X<int> xi;
/// \endcode
/// templateName()
/// matches 'X' in X<int>.
extern const internal::VariadicAllOfMatcher<TemplateName> templateName;
/// Matches non-type template parameter declarations.
///
/// Given
/// \code
/// template <typename T, int N> struct C {};
/// \endcode
/// nonTypeTemplateParmDecl()
/// matches 'N', but not 'T'.
extern const internal::VariadicDynCastAllOfMatcher<Decl,
NonTypeTemplateParmDecl>
nonTypeTemplateParmDecl;
/// Matches template type parameter declarations.
///
/// Given
/// \code
/// template <typename T, int N> struct C {};
/// \endcode
/// templateTypeParmDecl()
/// matches 'T', but not 'N'.
extern const internal::VariadicDynCastAllOfMatcher<Decl, TemplateTypeParmDecl>
templateTypeParmDecl;
/// Matches public C++ declarations.
///
/// Given
/// \code
/// class C {
/// public: int a;
/// protected: int b;
/// private: int c;
/// };
/// \endcode
/// fieldDecl(isPublic())
/// matches 'int a;'
AST_MATCHER(Decl, isPublic) {
return Node.getAccess() == AS_public;
}
/// Matches protected C++ declarations.
///
/// Given
/// \code
/// class C {
/// public: int a;
/// protected: int b;
/// private: int c;
/// };
/// \endcode
/// fieldDecl(isProtected())
/// matches 'int b;'
AST_MATCHER(Decl, isProtected) {
return Node.getAccess() == AS_protected;
}
/// Matches private C++ declarations.
///
/// Given
/// \code
/// class C {
/// public: int a;
/// protected: int b;
/// private: int c;
/// };
/// \endcode
/// fieldDecl(isPrivate())
/// matches 'int c;'
AST_MATCHER(Decl, isPrivate) {
return Node.getAccess() == AS_private;
}
/// Matches non-static data members that are bit-fields.
///
/// Given
/// \code
/// class C {
/// int a : 2;
/// int b;
/// };
/// \endcode
/// fieldDecl(isBitField())
/// matches 'int a;' but not 'int b;'.
AST_MATCHER(FieldDecl, isBitField) {
return Node.isBitField();
}
/// Matches non-static data members that are bit-fields of the specified
/// bit width.
///
/// Given
/// \code
/// class C {
/// int a : 2;
/// int b : 4;
/// int c : 2;
/// };
/// \endcode
/// fieldDecl(hasBitWidth(2))
/// matches 'int a;' and 'int c;' but not 'int b;'.
AST_MATCHER_P(FieldDecl, hasBitWidth, unsigned, Width) {
return Node.isBitField() &&
Node.getBitWidthValue(Finder->getASTContext()) == Width;
}
/// Matches non-static data members that have an in-class initializer.
///
/// Given
/// \code
/// class C {
/// int a = 2;
/// int b = 3;
/// int c;
/// };
/// \endcode
/// fieldDecl(hasInClassInitializer(integerLiteral(equals(2))))
/// matches 'int a;' but not 'int b;'.
/// fieldDecl(hasInClassInitializer(anything()))
/// matches 'int a;' and 'int b;' but not 'int c;'.
AST_MATCHER_P(FieldDecl, hasInClassInitializer, internal::Matcher<Expr>,
InnerMatcher) {
const Expr *Initializer = Node.getInClassInitializer();
return (Initializer != nullptr &&
InnerMatcher.matches(*Initializer, Finder, Builder));
}
/// Determines whether the function is "main", which is the entry point
/// into an executable program.
AST_MATCHER(FunctionDecl, isMain) {
return Node.isMain();
}
/// Matches the specialized template of a specialization declaration.
///
/// Given
/// \code
/// template<typename T> class A {}; #1
/// template<> class A<int> {}; #2
/// \endcode
/// classTemplateSpecializationDecl(hasSpecializedTemplate(classTemplateDecl()))
/// matches '#2' with classTemplateDecl() matching the class template
/// declaration of 'A' at #1.
AST_MATCHER_P(ClassTemplateSpecializationDecl, hasSpecializedTemplate,
internal::Matcher<ClassTemplateDecl>, InnerMatcher) {
const ClassTemplateDecl* Decl = Node.getSpecializedTemplate();
return (Decl != nullptr &&
InnerMatcher.matches(*Decl, Finder, Builder));
}
/// Matches a declaration that has been implicitly added
/// by the compiler (eg. implicit default/copy constructors).
AST_MATCHER(Decl, isImplicit) {
return Node.isImplicit();
}
/// Matches classTemplateSpecializations, templateSpecializationType and
/// functionDecl that have at least one TemplateArgument matching the given
/// InnerMatcher.
///
/// Given
/// \code
/// template<typename T> class A {};
/// template<> class A<double> {};
/// A<int> a;
///
/// template<typename T> f() {};
/// void func() { f<int>(); };
/// \endcode
///
/// \endcode
/// classTemplateSpecializationDecl(hasAnyTemplateArgument(
/// refersToType(asString("int"))))
/// matches the specialization \c A<int>
///
/// functionDecl(hasAnyTemplateArgument(refersToType(asString("int"))))
/// matches the specialization \c f<int>
AST_POLYMORPHIC_MATCHER_P(
hasAnyTemplateArgument,
AST_POLYMORPHIC_SUPPORTED_TYPES(ClassTemplateSpecializationDecl,
TemplateSpecializationType,
FunctionDecl),
internal::Matcher<TemplateArgument>, InnerMatcher) {
ArrayRef<TemplateArgument> List =
internal::getTemplateSpecializationArgs(Node);
return matchesFirstInRange(InnerMatcher, List.begin(), List.end(), Finder,
Builder);
}
/// Causes all nested matchers to be matched with the specified traversal kind.
///
/// Given
/// \code
/// void foo()
/// {
/// int i = 3.0;
/// }
/// \endcode
/// The matcher
/// \code
/// traverse(ast_type_traits::TK_IgnoreImplicitCastsAndParentheses,
/// varDecl(hasInitializer(floatLiteral().bind("init")))
/// )
/// \endcode
/// matches the variable declaration with "init" bound to the "3.0".
template <typename T>
internal::Matcher<T> traverse(ast_type_traits::TraversalKind TK,
const internal::Matcher<T> &InnerMatcher) {
return internal::DynTypedMatcher::constructRestrictedWrapper(
new internal::TraversalMatcher<T>(TK, InnerMatcher),
InnerMatcher.getID().first)
.template unconditionalConvertTo<T>();
}
template <typename T>
internal::BindableMatcher<T>
traverse(ast_type_traits::TraversalKind TK,
const internal::BindableMatcher<T> &InnerMatcher) {
return internal::BindableMatcher<T>(
internal::DynTypedMatcher::constructRestrictedWrapper(
new internal::TraversalMatcher<T>(TK, InnerMatcher),
InnerMatcher.getID().first)
.template unconditionalConvertTo<T>());
}
template <typename... T>
internal::TraversalWrapper<internal::VariadicOperatorMatcher<T...>>
traverse(ast_type_traits::TraversalKind TK,
const internal::VariadicOperatorMatcher<T...> &InnerMatcher) {
return internal::TraversalWrapper<internal::VariadicOperatorMatcher<T...>>(
TK, InnerMatcher);
}
template <template <typename ToArg, typename FromArg> class ArgumentAdapterT,
typename T, typename ToTypes>
internal::TraversalWrapper<
internal::ArgumentAdaptingMatcherFuncAdaptor<ArgumentAdapterT, T, ToTypes>>
traverse(ast_type_traits::TraversalKind TK,
const internal::ArgumentAdaptingMatcherFuncAdaptor<
ArgumentAdapterT, T, ToTypes> &InnerMatcher) {
return internal::TraversalWrapper<
internal::ArgumentAdaptingMatcherFuncAdaptor<ArgumentAdapterT, T,
ToTypes>>(TK, InnerMatcher);
}
template <template <typename T, typename P1> class MatcherT, typename P1,
typename ReturnTypesF>
internal::TraversalWrapper<
internal::PolymorphicMatcherWithParam1<MatcherT, P1, ReturnTypesF>>
traverse(
ast_type_traits::TraversalKind TK,
const internal::PolymorphicMatcherWithParam1<MatcherT, P1, ReturnTypesF>
&InnerMatcher) {
return internal::TraversalWrapper<
internal::PolymorphicMatcherWithParam1<MatcherT, P1, ReturnTypesF>>(
TK, InnerMatcher);
}
template <template <typename T, typename P1, typename P2> class MatcherT,
typename P1, typename P2, typename ReturnTypesF>
internal::TraversalWrapper<
internal::PolymorphicMatcherWithParam2<MatcherT, P1, P2, ReturnTypesF>>
traverse(
ast_type_traits::TraversalKind TK,
const internal::PolymorphicMatcherWithParam2<MatcherT, P1, P2, ReturnTypesF>
&InnerMatcher) {
return internal::TraversalWrapper<
internal::PolymorphicMatcherWithParam2<MatcherT, P1, P2, ReturnTypesF>>(
TK, InnerMatcher);
}
/// Matches expressions that match InnerMatcher after any implicit AST
/// nodes are stripped off.
///
/// Parentheses and explicit casts are not discarded.
/// Given
/// \code
/// class C {};
/// C a = C();
/// C b;
/// C c = b;
/// \endcode
/// The matchers
/// \code
/// varDecl(hasInitializer(ignoringImplicit(cxxConstructExpr())))
/// \endcode
/// would match the declarations for a, b, and c.
/// While
/// \code
/// varDecl(hasInitializer(cxxConstructExpr()))
/// \endcode
/// only match the declarations for b and c.
AST_MATCHER_P(Expr, ignoringImplicit, internal::Matcher<Expr>,
InnerMatcher) {
return InnerMatcher.matches(*Node.IgnoreImplicit(), Finder, Builder);
}
/// Matches expressions that match InnerMatcher after any implicit casts
/// are stripped off.
///
/// Parentheses and explicit casts are not discarded.
/// Given
/// \code
/// int arr[5];
/// int a = 0;
/// char b = 0;
/// const int c = a;
/// int *d = arr;
/// long e = (long) 0l;
/// \endcode
/// The matchers
/// \code
/// varDecl(hasInitializer(ignoringImpCasts(integerLiteral())))
/// varDecl(hasInitializer(ignoringImpCasts(declRefExpr())))
/// \endcode
/// would match the declarations for a, b, c, and d, but not e.
/// While
/// \code
/// varDecl(hasInitializer(integerLiteral()))
/// varDecl(hasInitializer(declRefExpr()))
/// \endcode
/// only match the declarations for b, c, and d.
AST_MATCHER_P(Expr, ignoringImpCasts,
internal::Matcher<Expr>, InnerMatcher) {
return InnerMatcher.matches(*Node.IgnoreImpCasts(), Finder, Builder);
}
/// Matches expressions that match InnerMatcher after parentheses and
/// casts are stripped off.
///
/// Implicit and non-C Style casts are also discarded.
/// Given
/// \code
/// int a = 0;
/// char b = (0);
/// void* c = reinterpret_cast<char*>(0);
/// char d = char(0);
/// \endcode
/// The matcher
/// varDecl(hasInitializer(ignoringParenCasts(integerLiteral())))
/// would match the declarations for a, b, c, and d.
/// while
/// varDecl(hasInitializer(integerLiteral()))
/// only match the declaration for a.
AST_MATCHER_P(Expr, ignoringParenCasts, internal::Matcher<Expr>, InnerMatcher) {
return InnerMatcher.matches(*Node.IgnoreParenCasts(), Finder, Builder);
}
/// Matches expressions that match InnerMatcher after implicit casts and
/// parentheses are stripped off.
///
/// Explicit casts are not discarded.
/// Given
/// \code
/// int arr[5];
/// int a = 0;
/// char b = (0);
/// const int c = a;
/// int *d = (arr);
/// long e = ((long) 0l);
/// \endcode
/// The matchers
/// varDecl(hasInitializer(ignoringParenImpCasts(integerLiteral())))
/// varDecl(hasInitializer(ignoringParenImpCasts(declRefExpr())))
/// would match the declarations for a, b, c, and d, but not e.
/// while
/// varDecl(hasInitializer(integerLiteral()))
/// varDecl(hasInitializer(declRefExpr()))
/// would only match the declaration for a.
AST_MATCHER_P(Expr, ignoringParenImpCasts,
internal::Matcher<Expr>, InnerMatcher) {
return InnerMatcher.matches(*Node.IgnoreParenImpCasts(), Finder, Builder);
}
/// Matches types that match InnerMatcher after any parens are stripped.
///
/// Given
/// \code
/// void (*fp)(void);
/// \endcode
/// The matcher
/// \code
/// varDecl(hasType(pointerType(pointee(ignoringParens(functionType())))))
/// \endcode
/// would match the declaration for fp.
AST_MATCHER_P_OVERLOAD(QualType, ignoringParens, internal::Matcher<QualType>,
InnerMatcher, 0) {
return InnerMatcher.matches(Node.IgnoreParens(), Finder, Builder);
}
/// Overload \c ignoringParens for \c Expr.
///
/// Given
/// \code
/// const char* str = ("my-string");
/// \endcode
/// The matcher
/// \code
/// implicitCastExpr(hasSourceExpression(ignoringParens(stringLiteral())))
/// \endcode
/// would match the implicit cast resulting from the assignment.
AST_MATCHER_P_OVERLOAD(Expr, ignoringParens, internal::Matcher<Expr>,
InnerMatcher, 1) {
const Expr *E = Node.IgnoreParens();
return InnerMatcher.matches(*E, Finder, Builder);
}
/// Matches expressions that are instantiation-dependent even if it is
/// neither type- nor value-dependent.
///
/// In the following example, the expression sizeof(sizeof(T() + T()))
/// is instantiation-dependent (since it involves a template parameter T),
/// but is neither type- nor value-dependent, since the type of the inner
/// sizeof is known (std::size_t) and therefore the size of the outer
/// sizeof is known.
/// \code
/// template<typename T>
/// void f(T x, T y) { sizeof(sizeof(T() + T()); }
/// \endcode
/// expr(isInstantiationDependent()) matches sizeof(sizeof(T() + T())
AST_MATCHER(Expr, isInstantiationDependent) {
return Node.isInstantiationDependent();
}
/// Matches expressions that are type-dependent because the template type
/// is not yet instantiated.
///
/// For example, the expressions "x" and "x + y" are type-dependent in
/// the following code, but "y" is not type-dependent:
/// \code
/// template<typename T>
/// void add(T x, int y) {
/// x + y;
/// }
/// \endcode
/// expr(isTypeDependent()) matches x + y
AST_MATCHER(Expr, isTypeDependent) { return Node.isTypeDependent(); }
/// Matches expression that are value-dependent because they contain a
/// non-type template parameter.
///
/// For example, the array bound of "Chars" in the following example is
/// value-dependent.
/// \code
/// template<int Size> int f() { return Size; }
/// \endcode
/// expr(isValueDependent()) matches return Size
AST_MATCHER(Expr, isValueDependent) { return Node.isValueDependent(); }
/// Matches classTemplateSpecializations, templateSpecializationType and
/// functionDecl where the n'th TemplateArgument matches the given InnerMatcher.
///
/// Given
/// \code
/// template<typename T, typename U> class A {};
/// A<bool, int> b;
/// A<int, bool> c;
///
/// template<typename T> void f() {}
/// void func() { f<int>(); };
/// \endcode
/// classTemplateSpecializationDecl(hasTemplateArgument(
/// 1, refersToType(asString("int"))))
/// matches the specialization \c A<bool, int>
///
/// functionDecl(hasTemplateArgument(0, refersToType(asString("int"))))
/// matches the specialization \c f<int>
AST_POLYMORPHIC_MATCHER_P2(
hasTemplateArgument,
AST_POLYMORPHIC_SUPPORTED_TYPES(ClassTemplateSpecializationDecl,
TemplateSpecializationType,
FunctionDecl),
unsigned, N, internal::Matcher<TemplateArgument>, InnerMatcher) {
ArrayRef<TemplateArgument> List =
internal::getTemplateSpecializationArgs(Node);
if (List.size() <= N)
return false;
return InnerMatcher.matches(List[N], Finder, Builder);
}
/// Matches if the number of template arguments equals \p N.
///
/// Given
/// \code
/// template<typename T> struct C {};
/// C<int> c;
/// \endcode
/// classTemplateSpecializationDecl(templateArgumentCountIs(1))
/// matches C<int>.
AST_POLYMORPHIC_MATCHER_P(
templateArgumentCountIs,
AST_POLYMORPHIC_SUPPORTED_TYPES(ClassTemplateSpecializationDecl,
TemplateSpecializationType),
unsigned, N) {
return internal::getTemplateSpecializationArgs(Node).size() == N;
}
/// Matches a TemplateArgument that refers to a certain type.
///
/// Given
/// \code
/// struct X {};
/// template<typename T> struct A {};
/// A<X> a;
/// \endcode
/// classTemplateSpecializationDecl(hasAnyTemplateArgument(
/// refersToType(class(hasName("X")))))
/// matches the specialization \c A<X>
AST_MATCHER_P(TemplateArgument, refersToType,
internal::Matcher<QualType>, InnerMatcher) {
if (Node.getKind() != TemplateArgument::Type)
return false;
return InnerMatcher.matches(Node.getAsType(), Finder, Builder);
}
/// Matches a TemplateArgument that refers to a certain template.
///
/// Given
/// \code
/// template<template <typename> class S> class X {};
/// template<typename T> class Y {};
/// X<Y> xi;
/// \endcode
/// classTemplateSpecializationDecl(hasAnyTemplateArgument(
/// refersToTemplate(templateName())))
/// matches the specialization \c X<Y>
AST_MATCHER_P(TemplateArgument, refersToTemplate,
internal::Matcher<TemplateName>, InnerMatcher) {
if (Node.getKind() != TemplateArgument::Template)
return false;
return InnerMatcher.matches(Node.getAsTemplate(), Finder, Builder);
}
/// Matches a canonical TemplateArgument that refers to a certain
/// declaration.
///
/// Given
/// \code
/// struct B { int next; };
/// template<int(B::*next_ptr)> struct A {};
/// A<&B::next> a;
/// \endcode
/// classTemplateSpecializationDecl(hasAnyTemplateArgument(
/// refersToDeclaration(fieldDecl(hasName("next")))))
/// matches the specialization \c A<&B::next> with \c fieldDecl(...) matching
/// \c B::next
AST_MATCHER_P(TemplateArgument, refersToDeclaration,
internal::Matcher<Decl>, InnerMatcher) {
if (Node.getKind() == TemplateArgument::Declaration)
return InnerMatcher.matches(*Node.getAsDecl(), Finder, Builder);
return false;
}
/// Matches a sugar TemplateArgument that refers to a certain expression.
///
/// Given
/// \code
/// struct B { int next; };
/// template<int(B::*next_ptr)> struct A {};
/// A<&B::next> a;
/// \endcode
/// templateSpecializationType(hasAnyTemplateArgument(
/// isExpr(hasDescendant(declRefExpr(to(fieldDecl(hasName("next"))))))))
/// matches the specialization \c A<&B::next> with \c fieldDecl(...) matching
/// \c B::next
AST_MATCHER_P(TemplateArgument, isExpr, internal::Matcher<Expr>, InnerMatcher) {
if (Node.getKind() == TemplateArgument::Expression)
return InnerMatcher.matches(*Node.getAsExpr(), Finder, Builder);
return false;
}
/// Matches a TemplateArgument that is an integral value.
///
/// Given
/// \code
/// template<int T> struct C {};
/// C<42> c;
/// \endcode
/// classTemplateSpecializationDecl(
/// hasAnyTemplateArgument(isIntegral()))
/// matches the implicit instantiation of C in C<42>
/// with isIntegral() matching 42.
AST_MATCHER(TemplateArgument, isIntegral) {
return Node.getKind() == TemplateArgument::Integral;
}
/// Matches a TemplateArgument that referes to an integral type.
///
/// Given
/// \code
/// template<int T> struct C {};
/// C<42> c;
/// \endcode
/// classTemplateSpecializationDecl(
/// hasAnyTemplateArgument(refersToIntegralType(asString("int"))))
/// matches the implicit instantiation of C in C<42>.
AST_MATCHER_P(TemplateArgument, refersToIntegralType,
internal::Matcher<QualType>, InnerMatcher) {
if (Node.getKind() != TemplateArgument::Integral)
return false;
return InnerMatcher.matches(Node.getIntegralType(), Finder, Builder);
}
/// Matches a TemplateArgument of integral type with a given value.
///
/// Note that 'Value' is a string as the template argument's value is
/// an arbitrary precision integer. 'Value' must be euqal to the canonical
/// representation of that integral value in base 10.
///
/// Given
/// \code
/// template<int T> struct C {};
/// C<42> c;
/// \endcode
/// classTemplateSpecializationDecl(
/// hasAnyTemplateArgument(equalsIntegralValue("42")))
/// matches the implicit instantiation of C in C<42>.
AST_MATCHER_P(TemplateArgument, equalsIntegralValue,
std::string, Value) {
if (Node.getKind() != TemplateArgument::Integral)
return false;
return Node.getAsIntegral().toString(10) == Value;
}
/// Matches an Objective-C autorelease pool statement.
///
/// Given
/// \code
/// @autoreleasepool {
/// int x = 0;
/// }
/// \endcode
/// autoreleasePoolStmt(stmt()) matches the declaration of "x"
/// inside the autorelease pool.
extern const internal::VariadicDynCastAllOfMatcher<Stmt,
ObjCAutoreleasePoolStmt> autoreleasePoolStmt;
/// Matches any value declaration.
///
/// Example matches A, B, C and F
/// \code
/// enum X { A, B, C };
/// void F();
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, ValueDecl> valueDecl;
/// Matches C++ constructor declarations.
///
/// Example matches Foo::Foo() and Foo::Foo(int)
/// \code
/// class Foo {
/// public:
/// Foo();
/// Foo(int);
/// int DoSomething();
/// };
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, CXXConstructorDecl>
cxxConstructorDecl;
/// Matches explicit C++ destructor declarations.
///
/// Example matches Foo::~Foo()
/// \code
/// class Foo {
/// public:
/// virtual ~Foo();
/// };
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, CXXDestructorDecl>
cxxDestructorDecl;
/// Matches enum declarations.
///
/// Example matches X
/// \code
/// enum X {
/// A, B, C
/// };
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, EnumDecl> enumDecl;
/// Matches enum constants.
///
/// Example matches A, B, C
/// \code
/// enum X {
/// A, B, C
/// };
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, EnumConstantDecl>
enumConstantDecl;
/// Matches method declarations.
///
/// Example matches y
/// \code
/// class X { void y(); };
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, CXXMethodDecl>
cxxMethodDecl;
/// Matches conversion operator declarations.
///
/// Example matches the operator.
/// \code
/// class X { operator int() const; };
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, CXXConversionDecl>
cxxConversionDecl;
/// Matches user-defined and implicitly generated deduction guide.
///
/// Example matches the deduction guide.
/// \code
/// template<typename T>
/// class X { X(int) };
/// X(int) -> X<int>;
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, CXXDeductionGuideDecl>
cxxDeductionGuideDecl;
/// Matches variable declarations.
///
/// Note: this does not match declarations of member variables, which are
/// "field" declarations in Clang parlance.
///
/// Example matches a
/// \code
/// int a;
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, VarDecl> varDecl;
/// Matches field declarations.
///
/// Given
/// \code
/// class X { int m; };
/// \endcode
/// fieldDecl()
/// matches 'm'.
extern const internal::VariadicDynCastAllOfMatcher<Decl, FieldDecl> fieldDecl;
/// Matches indirect field declarations.
///
/// Given
/// \code
/// struct X { struct { int a; }; };
/// \endcode
/// indirectFieldDecl()
/// matches 'a'.
extern const internal::VariadicDynCastAllOfMatcher<Decl, IndirectFieldDecl>
indirectFieldDecl;
/// Matches function declarations.
///
/// Example matches f
/// \code
/// void f();
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, FunctionDecl>
functionDecl;
/// Matches C++ function template declarations.
///
/// Example matches f
/// \code
/// template<class T> void f(T t) {}
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, FunctionTemplateDecl>
functionTemplateDecl;
/// Matches friend declarations.
///
/// Given
/// \code
/// class X { friend void foo(); };
/// \endcode
/// friendDecl()
/// matches 'friend void foo()'.
extern const internal::VariadicDynCastAllOfMatcher<Decl, FriendDecl> friendDecl;
/// Matches statements.
///
/// Given
/// \code
/// { ++a; }
/// \endcode
/// stmt()
/// matches both the compound statement '{ ++a; }' and '++a'.
extern const internal::VariadicAllOfMatcher<Stmt> stmt;
/// Matches declaration statements.
///
/// Given
/// \code
/// int a;
/// \endcode
/// declStmt()
/// matches 'int a'.
extern const internal::VariadicDynCastAllOfMatcher<Stmt, DeclStmt> declStmt;
/// Matches member expressions.
///
/// Given
/// \code
/// class Y {
/// void x() { this->x(); x(); Y y; y.x(); a; this->b; Y::b; }
/// int a; static int b;
/// };
/// \endcode
/// memberExpr()
/// matches this->x, x, y.x, a, this->b
extern const internal::VariadicDynCastAllOfMatcher<Stmt, MemberExpr> memberExpr;
/// Matches unresolved member expressions.
///
/// Given
/// \code
/// struct X {
/// template <class T> void f();
/// void g();
/// };
/// template <class T> void h() { X x; x.f<T>(); x.g(); }
/// \endcode
/// unresolvedMemberExpr()
/// matches x.f<T>
extern const internal::VariadicDynCastAllOfMatcher<Stmt, UnresolvedMemberExpr>
unresolvedMemberExpr;
/// Matches member expressions where the actual member referenced could not be
/// resolved because the base expression or the member name was dependent.
///
/// Given
/// \code
/// template <class T> void f() { T t; t.g(); }
/// \endcode
/// cxxDependentScopeMemberExpr()
/// matches t.g
extern const internal::VariadicDynCastAllOfMatcher<Stmt,
CXXDependentScopeMemberExpr>
cxxDependentScopeMemberExpr;
/// Matches call expressions.
///
/// Example matches x.y() and y()
/// \code
/// X x;
/// x.y();
/// y();
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CallExpr> callExpr;
/// Matches call expressions which were resolved using ADL.
///
/// Example matches y(x) but not y(42) or NS::y(x).
/// \code
/// namespace NS {
/// struct X {};
/// void y(X);
/// }
///
/// void y(...);
///
/// void test() {
/// NS::X x;
/// y(x); // Matches
/// NS::y(x); // Doesn't match
/// y(42); // Doesn't match
/// using NS::y;
/// y(x); // Found by both unqualified lookup and ADL, doesn't match
// }
/// \endcode
AST_MATCHER(CallExpr, usesADL) { return Node.usesADL(); }
/// Matches lambda expressions.
///
/// Example matches [&](){return 5;}
/// \code
/// [&](){return 5;}
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, LambdaExpr> lambdaExpr;
/// Matches member call expressions.
///
/// Example matches x.y()
/// \code
/// X x;
/// x.y();
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CXXMemberCallExpr>
cxxMemberCallExpr;
/// Matches ObjectiveC Message invocation expressions.
///
/// The innermost message send invokes the "alloc" class method on the
/// NSString class, while the outermost message send invokes the
/// "initWithString" instance method on the object returned from
/// NSString's "alloc". This matcher should match both message sends.
/// \code
/// [[NSString alloc] initWithString:@"Hello"]
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, ObjCMessageExpr>
objcMessageExpr;
/// Matches Objective-C interface declarations.
///
/// Example matches Foo
/// \code
/// @interface Foo
/// @end
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, ObjCInterfaceDecl>
objcInterfaceDecl;
/// Matches Objective-C implementation declarations.
///
/// Example matches Foo
/// \code
/// @implementation Foo
/// @end
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, ObjCImplementationDecl>
objcImplementationDecl;
/// Matches Objective-C protocol declarations.
///
/// Example matches FooDelegate
/// \code
/// @protocol FooDelegate
/// @end
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, ObjCProtocolDecl>
objcProtocolDecl;
/// Matches Objective-C category declarations.
///
/// Example matches Foo (Additions)
/// \code
/// @interface Foo (Additions)
/// @end
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, ObjCCategoryDecl>
objcCategoryDecl;
/// Matches Objective-C category definitions.
///
/// Example matches Foo (Additions)
/// \code
/// @implementation Foo (Additions)
/// @end
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, ObjCCategoryImplDecl>
objcCategoryImplDecl;
/// Matches Objective-C method declarations.
///
/// Example matches both declaration and definition of -[Foo method]
/// \code
/// @interface Foo
/// - (void)method;
/// @end
///
/// @implementation Foo
/// - (void)method {}
/// @end
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, ObjCMethodDecl>
objcMethodDecl;
/// Matches block declarations.
///
/// Example matches the declaration of the nameless block printing an input
/// integer.
///
/// \code
/// myFunc(^(int p) {
/// printf("%d", p);
/// })
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, BlockDecl>
blockDecl;
/// Matches Objective-C instance variable declarations.
///
/// Example matches _enabled
/// \code
/// @implementation Foo {
/// BOOL _enabled;
/// }
/// @end
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, ObjCIvarDecl>
objcIvarDecl;
/// Matches Objective-C property declarations.
///
/// Example matches enabled
/// \code
/// @interface Foo
/// @property BOOL enabled;
/// @end
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, ObjCPropertyDecl>
objcPropertyDecl;
/// Matches Objective-C \@throw statements.
///
/// Example matches \@throw
/// \code
/// @throw obj;
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, ObjCAtThrowStmt>
objcThrowStmt;
/// Matches Objective-C @try statements.
///
/// Example matches @try
/// \code
/// @try {}
/// @catch (...) {}
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, ObjCAtTryStmt>
objcTryStmt;
/// Matches Objective-C @catch statements.
///
/// Example matches @catch
/// \code
/// @try {}
/// @catch (...) {}
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, ObjCAtCatchStmt>
objcCatchStmt;
/// Matches Objective-C @finally statements.
///
/// Example matches @finally
/// \code
/// @try {}
/// @finally {}
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, ObjCAtFinallyStmt>
objcFinallyStmt;
/// Matches expressions that introduce cleanups to be run at the end
/// of the sub-expression's evaluation.
///
/// Example matches std::string()
/// \code
/// const std::string str = std::string();
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, ExprWithCleanups>
exprWithCleanups;
/// Matches init list expressions.
///
/// Given
/// \code
/// int a[] = { 1, 2 };
/// struct B { int x, y; };
/// B b = { 5, 6 };
/// \endcode
/// initListExpr()
/// matches "{ 1, 2 }" and "{ 5, 6 }"
extern const internal::VariadicDynCastAllOfMatcher<Stmt, InitListExpr>
initListExpr;
/// Matches the syntactic form of init list expressions
/// (if expression have it).
AST_MATCHER_P(InitListExpr, hasSyntacticForm,
internal::Matcher<Expr>, InnerMatcher) {
const Expr *SyntForm = Node.getSyntacticForm();
return (SyntForm != nullptr &&
InnerMatcher.matches(*SyntForm, Finder, Builder));
}
/// Matches C++ initializer list expressions.
///
/// Given
/// \code
/// std::vector<int> a({ 1, 2, 3 });
/// std::vector<int> b = { 4, 5 };
/// int c[] = { 6, 7 };
/// std::pair<int, int> d = { 8, 9 };
/// \endcode
/// cxxStdInitializerListExpr()
/// matches "{ 1, 2, 3 }" and "{ 4, 5 }"
extern const internal::VariadicDynCastAllOfMatcher<Stmt,
CXXStdInitializerListExpr>
cxxStdInitializerListExpr;
/// Matches implicit initializers of init list expressions.
///
/// Given
/// \code
/// point ptarray[10] = { [2].y = 1.0, [2].x = 2.0, [0].x = 1.0 };
/// \endcode
/// implicitValueInitExpr()
/// matches "[0].y" (implicitly)
extern const internal::VariadicDynCastAllOfMatcher<Stmt, ImplicitValueInitExpr>
implicitValueInitExpr;
/// Matches paren list expressions.
/// ParenListExprs don't have a predefined type and are used for late parsing.
/// In the final AST, they can be met in template declarations.
///
/// Given
/// \code
/// template<typename T> class X {
/// void f() {
/// X x(*this);
/// int a = 0, b = 1; int i = (a, b);
/// }
/// };
/// \endcode
/// parenListExpr() matches "*this" but NOT matches (a, b) because (a, b)
/// has a predefined type and is a ParenExpr, not a ParenListExpr.
extern const internal::VariadicDynCastAllOfMatcher<Stmt, ParenListExpr>
parenListExpr;
/// Matches substitutions of non-type template parameters.
///
/// Given
/// \code
/// template <int N>
/// struct A { static const int n = N; };
/// struct B : public A<42> {};
/// \endcode
/// substNonTypeTemplateParmExpr()
/// matches "N" in the right-hand side of "static const int n = N;"
extern const internal::VariadicDynCastAllOfMatcher<Stmt,
SubstNonTypeTemplateParmExpr>
substNonTypeTemplateParmExpr;
/// Matches using declarations.
///
/// Given
/// \code
/// namespace X { int x; }
/// using X::x;
/// \endcode
/// usingDecl()
/// matches \code using X::x \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, UsingDecl> usingDecl;
/// Matches using namespace declarations.
///
/// Given
/// \code
/// namespace X { int x; }
/// using namespace X;
/// \endcode
/// usingDirectiveDecl()
/// matches \code using namespace X \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, UsingDirectiveDecl>
usingDirectiveDecl;
/// Matches reference to a name that can be looked up during parsing
/// but could not be resolved to a specific declaration.
///
/// Given
/// \code
/// template<typename T>
/// T foo() { T a; return a; }
/// template<typename T>
/// void bar() {
/// foo<T>();
/// }
/// \endcode
/// unresolvedLookupExpr()
/// matches \code foo<T>() \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, UnresolvedLookupExpr>
unresolvedLookupExpr;
/// Matches unresolved using value declarations.
///
/// Given
/// \code
/// template<typename X>
/// class C : private X {
/// using X::x;
/// };
/// \endcode
/// unresolvedUsingValueDecl()
/// matches \code using X::x \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl,
UnresolvedUsingValueDecl>
unresolvedUsingValueDecl;
/// Matches unresolved using value declarations that involve the
/// typename.
///
/// Given
/// \code
/// template <typename T>
/// struct Base { typedef T Foo; };
///
/// template<typename T>
/// struct S : private Base<T> {
/// using typename Base<T>::Foo;
/// };
/// \endcode
/// unresolvedUsingTypenameDecl()
/// matches \code using Base<T>::Foo \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl,
UnresolvedUsingTypenameDecl>
unresolvedUsingTypenameDecl;
/// Matches a constant expression wrapper.
///
/// Example matches the constant in the case statement:
/// (matcher = constantExpr())
/// \code
/// switch (a) {
/// case 37: break;
/// }
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, ConstantExpr>
constantExpr;
/// Matches parentheses used in expressions.
///
/// Example matches (foo() + 1)
/// \code
/// int foo() { return 1; }
/// int a = (foo() + 1);
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, ParenExpr> parenExpr;
/// Matches constructor call expressions (including implicit ones).
///
/// Example matches string(ptr, n) and ptr within arguments of f
/// (matcher = cxxConstructExpr())
/// \code
/// void f(const string &a, const string &b);
/// char *ptr;
/// int n;
/// f(string(ptr, n), ptr);
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CXXConstructExpr>
cxxConstructExpr;
/// Matches unresolved constructor call expressions.
///
/// Example matches T(t) in return statement of f
/// (matcher = cxxUnresolvedConstructExpr())
/// \code
/// template <typename T>
/// void f(const T& t) { return T(t); }
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt,
CXXUnresolvedConstructExpr>
cxxUnresolvedConstructExpr;
/// Matches implicit and explicit this expressions.
///
/// Example matches the implicit this expression in "return i".
/// (matcher = cxxThisExpr())
/// \code
/// struct foo {
/// int i;
/// int f() { return i; }
/// };
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CXXThisExpr>
cxxThisExpr;
/// Matches nodes where temporaries are created.
///
/// Example matches FunctionTakesString(GetStringByValue())
/// (matcher = cxxBindTemporaryExpr())
/// \code
/// FunctionTakesString(GetStringByValue());
/// FunctionTakesStringByPointer(GetStringPointer());
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CXXBindTemporaryExpr>
cxxBindTemporaryExpr;
/// Matches nodes where temporaries are materialized.
///
/// Example: Given
/// \code
/// struct T {void func();};
/// T f();
/// void g(T);
/// \endcode
/// materializeTemporaryExpr() matches 'f()' in these statements
/// \code
/// T u(f());
/// g(f());
/// f().func();
/// \endcode
/// but does not match
/// \code
/// f();
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt,
MaterializeTemporaryExpr>
materializeTemporaryExpr;
/// Matches new expressions.
///
/// Given
/// \code
/// new X;
/// \endcode
/// cxxNewExpr()
/// matches 'new X'.
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CXXNewExpr> cxxNewExpr;
/// Matches delete expressions.
///
/// Given
/// \code
/// delete X;
/// \endcode
/// cxxDeleteExpr()
/// matches 'delete X'.
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CXXDeleteExpr>
cxxDeleteExpr;
/// Matches array subscript expressions.
///
/// Given
/// \code
/// int i = a[1];
/// \endcode
/// arraySubscriptExpr()
/// matches "a[1]"
extern const internal::VariadicDynCastAllOfMatcher<Stmt, ArraySubscriptExpr>
arraySubscriptExpr;
/// Matches the value of a default argument at the call site.
///
/// Example matches the CXXDefaultArgExpr placeholder inserted for the
/// default value of the second parameter in the call expression f(42)
/// (matcher = cxxDefaultArgExpr())
/// \code
/// void f(int x, int y = 0);
/// f(42);
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CXXDefaultArgExpr>
cxxDefaultArgExpr;
/// Matches overloaded operator calls.
///
/// Note that if an operator isn't overloaded, it won't match. Instead, use
/// binaryOperator matcher.
/// Currently it does not match operators such as new delete.
/// FIXME: figure out why these do not match?
///
/// Example matches both operator<<((o << b), c) and operator<<(o, b)
/// (matcher = cxxOperatorCallExpr())
/// \code
/// ostream &operator<< (ostream &out, int i) { };
/// ostream &o; int b = 1, c = 1;
/// o << b << c;
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CXXOperatorCallExpr>
cxxOperatorCallExpr;
/// Matches expressions.
///
/// Example matches x()
/// \code
/// void f() { x(); }
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, Expr> expr;
/// Matches expressions that refer to declarations.
///
/// Example matches x in if (x)
/// \code
/// bool x;
/// if (x) {}
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, DeclRefExpr>
declRefExpr;
/// Matches a reference to an ObjCIvar.
///
/// Example: matches "a" in "init" method:
/// \code
/// @implementation A {
/// NSString *a;
/// }
/// - (void) init {
/// a = @"hello";
/// }
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, ObjCIvarRefExpr>
objcIvarRefExpr;
/// Matches a reference to a block.
///
/// Example: matches "^{}":
/// \code
/// void f() { ^{}(); }
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, BlockExpr> blockExpr;
/// Matches if statements.
///
/// Example matches 'if (x) {}'
/// \code
/// if (x) {}
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, IfStmt> ifStmt;
/// Matches for statements.
///
/// Example matches 'for (;;) {}'
/// \code
/// for (;;) {}
/// int i[] = {1, 2, 3}; for (auto a : i);
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, ForStmt> forStmt;
/// Matches the increment statement of a for loop.
///
/// Example:
/// forStmt(hasIncrement(unaryOperator(hasOperatorName("++"))))
/// matches '++x' in
/// \code
/// for (x; x < N; ++x) { }
/// \endcode
AST_MATCHER_P(ForStmt, hasIncrement, internal::Matcher<Stmt>,
InnerMatcher) {
const Stmt *const Increment = Node.getInc();
return (Increment != nullptr &&
InnerMatcher.matches(*Increment, Finder, Builder));
}
/// Matches the initialization statement of a for loop.
///
/// Example:
/// forStmt(hasLoopInit(declStmt()))
/// matches 'int x = 0' in
/// \code
/// for (int x = 0; x < N; ++x) { }
/// \endcode
AST_MATCHER_P(ForStmt, hasLoopInit, internal::Matcher<Stmt>,
InnerMatcher) {
const Stmt *const Init = Node.getInit();
return (Init != nullptr && InnerMatcher.matches(*Init, Finder, Builder));
}
/// Matches range-based for statements.
///
/// cxxForRangeStmt() matches 'for (auto a : i)'
/// \code
/// int i[] = {1, 2, 3}; for (auto a : i);
/// for(int j = 0; j < 5; ++j);
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CXXForRangeStmt>
cxxForRangeStmt;
/// Matches the initialization statement of a for loop.
///
/// Example:
/// forStmt(hasLoopVariable(anything()))
/// matches 'int x' in
/// \code
/// for (int x : a) { }
/// \endcode
AST_MATCHER_P(CXXForRangeStmt, hasLoopVariable, internal::Matcher<VarDecl>,
InnerMatcher) {
const VarDecl *const Var = Node.getLoopVariable();
return (Var != nullptr && InnerMatcher.matches(*Var, Finder, Builder));
}
/// Matches the range initialization statement of a for loop.
///
/// Example:
/// forStmt(hasRangeInit(anything()))
/// matches 'a' in
/// \code
/// for (int x : a) { }
/// \endcode
AST_MATCHER_P(CXXForRangeStmt, hasRangeInit, internal::Matcher<Expr>,
InnerMatcher) {
const Expr *const Init = Node.getRangeInit();
return (Init != nullptr && InnerMatcher.matches(*Init, Finder, Builder));
}
/// Matches while statements.
///
/// Given
/// \code
/// while (true) {}
/// \endcode
/// whileStmt()
/// matches 'while (true) {}'.
extern const internal::VariadicDynCastAllOfMatcher<Stmt, WhileStmt> whileStmt;
/// Matches do statements.
///
/// Given
/// \code
/// do {} while (true);
/// \endcode
/// doStmt()
/// matches 'do {} while(true)'
extern const internal::VariadicDynCastAllOfMatcher<Stmt, DoStmt> doStmt;
/// Matches break statements.
///
/// Given
/// \code
/// while (true) { break; }
/// \endcode
/// breakStmt()
/// matches 'break'
extern const internal::VariadicDynCastAllOfMatcher<Stmt, BreakStmt> breakStmt;
/// Matches continue statements.
///
/// Given
/// \code
/// while (true) { continue; }
/// \endcode
/// continueStmt()
/// matches 'continue'
extern const internal::VariadicDynCastAllOfMatcher<Stmt, ContinueStmt>
continueStmt;
/// Matches return statements.
///
/// Given
/// \code
/// return 1;
/// \endcode
/// returnStmt()
/// matches 'return 1'
extern const internal::VariadicDynCastAllOfMatcher<Stmt, ReturnStmt> returnStmt;
/// Matches goto statements.
///
/// Given
/// \code
/// goto FOO;
/// FOO: bar();
/// \endcode
/// gotoStmt()
/// matches 'goto FOO'
extern const internal::VariadicDynCastAllOfMatcher<Stmt, GotoStmt> gotoStmt;
/// Matches label statements.
///
/// Given
/// \code
/// goto FOO;
/// FOO: bar();
/// \endcode
/// labelStmt()
/// matches 'FOO:'
extern const internal::VariadicDynCastAllOfMatcher<Stmt, LabelStmt> labelStmt;
/// Matches address of label statements (GNU extension).
///
/// Given
/// \code
/// FOO: bar();
/// void *ptr = &&FOO;
/// goto *bar;
/// \endcode
/// addrLabelExpr()
/// matches '&&FOO'
extern const internal::VariadicDynCastAllOfMatcher<Stmt, AddrLabelExpr>
addrLabelExpr;
/// Matches switch statements.
///
/// Given
/// \code
/// switch(a) { case 42: break; default: break; }
/// \endcode
/// switchStmt()
/// matches 'switch(a)'.
extern const internal::VariadicDynCastAllOfMatcher<Stmt, SwitchStmt> switchStmt;
/// Matches case and default statements inside switch statements.
///
/// Given
/// \code
/// switch(a) { case 42: break; default: break; }
/// \endcode
/// switchCase()
/// matches 'case 42:' and 'default:'.
extern const internal::VariadicDynCastAllOfMatcher<Stmt, SwitchCase> switchCase;
/// Matches case statements inside switch statements.
///
/// Given
/// \code
/// switch(a) { case 42: break; default: break; }
/// \endcode
/// caseStmt()
/// matches 'case 42:'.
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CaseStmt> caseStmt;
/// Matches default statements inside switch statements.
///
/// Given
/// \code
/// switch(a) { case 42: break; default: break; }
/// \endcode
/// defaultStmt()
/// matches 'default:'.
extern const internal::VariadicDynCastAllOfMatcher<Stmt, DefaultStmt>
defaultStmt;
/// Matches compound statements.
///
/// Example matches '{}' and '{{}}' in 'for (;;) {{}}'
/// \code
/// for (;;) {{}}
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CompoundStmt>
compoundStmt;
/// Matches catch statements.
///
/// \code
/// try {} catch(int i) {}
/// \endcode
/// cxxCatchStmt()
/// matches 'catch(int i)'
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CXXCatchStmt>
cxxCatchStmt;
/// Matches try statements.
///
/// \code
/// try {} catch(int i) {}
/// \endcode
/// cxxTryStmt()
/// matches 'try {}'
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CXXTryStmt> cxxTryStmt;
/// Matches throw expressions.
///
/// \code
/// try { throw 5; } catch(int i) {}
/// \endcode
/// cxxThrowExpr()
/// matches 'throw 5'
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CXXThrowExpr>
cxxThrowExpr;
/// Matches null statements.
///
/// \code
/// foo();;
/// \endcode
/// nullStmt()
/// matches the second ';'
extern const internal::VariadicDynCastAllOfMatcher<Stmt, NullStmt> nullStmt;
/// Matches asm statements.
///
/// \code
/// int i = 100;
/// __asm("mov al, 2");
/// \endcode
/// asmStmt()
/// matches '__asm("mov al, 2")'
extern const internal::VariadicDynCastAllOfMatcher<Stmt, AsmStmt> asmStmt;
/// Matches bool literals.
///
/// Example matches true
/// \code
/// true
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CXXBoolLiteralExpr>
cxxBoolLiteral;
/// Matches string literals (also matches wide string literals).
///
/// Example matches "abcd", L"abcd"
/// \code
/// char *s = "abcd";
/// wchar_t *ws = L"abcd";
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, StringLiteral>
stringLiteral;
/// Matches character literals (also matches wchar_t).
///
/// Not matching Hex-encoded chars (e.g. 0x1234, which is a IntegerLiteral),
/// though.
///
/// Example matches 'a', L'a'
/// \code
/// char ch = 'a';
/// wchar_t chw = L'a';
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CharacterLiteral>
characterLiteral;
/// Matches integer literals of all sizes / encodings, e.g.
/// 1, 1L, 0x1 and 1U.
///
/// Does not match character-encoded integers such as L'a'.
extern const internal::VariadicDynCastAllOfMatcher<Stmt, IntegerLiteral>
integerLiteral;
/// Matches float literals of all sizes / encodings, e.g.
/// 1.0, 1.0f, 1.0L and 1e10.
///
/// Does not match implicit conversions such as
/// \code
/// float a = 10;
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, FloatingLiteral>
floatLiteral;
/// Matches imaginary literals, which are based on integer and floating
/// point literals e.g.: 1i, 1.0i
extern const internal::VariadicDynCastAllOfMatcher<Stmt, ImaginaryLiteral>
imaginaryLiteral;
/// Matches user defined literal operator call.
///
/// Example match: "foo"_suffix
extern const internal::VariadicDynCastAllOfMatcher<Stmt, UserDefinedLiteral>
userDefinedLiteral;
/// Matches compound (i.e. non-scalar) literals
///
/// Example match: {1}, (1, 2)
/// \code
/// int array[4] = {1};
/// vector int myvec = (vector int)(1, 2);
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CompoundLiteralExpr>
compoundLiteralExpr;
/// Matches nullptr literal.
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CXXNullPtrLiteralExpr>
cxxNullPtrLiteralExpr;
/// Matches GNU __builtin_choose_expr.
extern const internal::VariadicDynCastAllOfMatcher<Stmt, ChooseExpr>
chooseExpr;
/// Matches GNU __null expression.
extern const internal::VariadicDynCastAllOfMatcher<Stmt, GNUNullExpr>
gnuNullExpr;
/// Matches atomic builtins.
/// Example matches __atomic_load_n(ptr, 1)
/// \code
/// void foo() { int *ptr; __atomic_load_n(ptr, 1); }
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, AtomicExpr> atomicExpr;
/// Matches statement expression (GNU extension).
///
/// Example match: ({ int X = 4; X; })
/// \code
/// int C = ({ int X = 4; X; });
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, StmtExpr> stmtExpr;
/// Matches binary operator expressions.
///
/// Example matches a || b
/// \code
/// !(a || b)
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, BinaryOperator>
binaryOperator;
/// Matches unary operator expressions.
///
/// Example matches !a
/// \code
/// !a || b
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, UnaryOperator>
unaryOperator;
/// Matches conditional operator expressions.
///
/// Example matches a ? b : c
/// \code
/// (a ? b : c) + 42
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, ConditionalOperator>
conditionalOperator;
/// Matches binary conditional operator expressions (GNU extension).
///
/// Example matches a ?: b
/// \code
/// (a ?: b) + 42;
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt,
BinaryConditionalOperator>
binaryConditionalOperator;
/// Matches opaque value expressions. They are used as helpers
/// to reference another expressions and can be met
/// in BinaryConditionalOperators, for example.
///
/// Example matches 'a'
/// \code
/// (a ?: c) + 42;
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, OpaqueValueExpr>
opaqueValueExpr;
/// Matches a C++ static_assert declaration.
///
/// Example:
/// staticAssertExpr()
/// matches
/// static_assert(sizeof(S) == sizeof(int))
/// in
/// \code
/// struct S {
/// int x;
/// };
/// static_assert(sizeof(S) == sizeof(int));
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, StaticAssertDecl>
staticAssertDecl;
/// Matches a reinterpret_cast expression.
///
/// Either the source expression or the destination type can be matched
/// using has(), but hasDestinationType() is more specific and can be
/// more readable.
///
/// Example matches reinterpret_cast<char*>(&p) in
/// \code
/// void* p = reinterpret_cast<char*>(&p);
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CXXReinterpretCastExpr>
cxxReinterpretCastExpr;
/// Matches a C++ static_cast expression.
///
/// \see hasDestinationType
/// \see reinterpretCast
///
/// Example:
/// cxxStaticCastExpr()
/// matches
/// static_cast<long>(8)
/// in
/// \code
/// long eight(static_cast<long>(8));
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CXXStaticCastExpr>
cxxStaticCastExpr;
/// Matches a dynamic_cast expression.
///
/// Example:
/// cxxDynamicCastExpr()
/// matches
/// dynamic_cast<D*>(&b);
/// in
/// \code
/// struct B { virtual ~B() {} }; struct D : B {};
/// B b;
/// D* p = dynamic_cast<D*>(&b);
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CXXDynamicCastExpr>
cxxDynamicCastExpr;
/// Matches a const_cast expression.
///
/// Example: Matches const_cast<int*>(&r) in
/// \code
/// int n = 42;
/// const int &r(n);
/// int* p = const_cast<int*>(&r);
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CXXConstCastExpr>
cxxConstCastExpr;
/// Matches a C-style cast expression.
///
/// Example: Matches (int) 2.2f in
/// \code
/// int i = (int) 2.2f;
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CStyleCastExpr>
cStyleCastExpr;
/// Matches explicit cast expressions.
///
/// Matches any cast expression written in user code, whether it be a
/// C-style cast, a functional-style cast, or a keyword cast.
///
/// Does not match implicit conversions.
///
/// Note: the name "explicitCast" is chosen to match Clang's terminology, as
/// Clang uses the term "cast" to apply to implicit conversions as well as to
/// actual cast expressions.
///
/// \see hasDestinationType.
///
/// Example: matches all five of the casts in
/// \code
/// int((int)(reinterpret_cast<int>(static_cast<int>(const_cast<int>(42)))))
/// \endcode
/// but does not match the implicit conversion in
/// \code
/// long ell = 42;
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, ExplicitCastExpr>
explicitCastExpr;
/// Matches the implicit cast nodes of Clang's AST.
///
/// This matches many different places, including function call return value
/// eliding, as well as any type conversions.
extern const internal::VariadicDynCastAllOfMatcher<Stmt, ImplicitCastExpr>
implicitCastExpr;
/// Matches any cast nodes of Clang's AST.
///
/// Example: castExpr() matches each of the following:
/// \code
/// (int) 3;
/// const_cast<Expr *>(SubExpr);
/// char c = 0;
/// \endcode
/// but does not match
/// \code
/// int i = (0);
/// int k = 0;
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CastExpr> castExpr;
/// Matches functional cast expressions
///
/// Example: Matches Foo(bar);
/// \code
/// Foo f = bar;
/// Foo g = (Foo) bar;
/// Foo h = Foo(bar);
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CXXFunctionalCastExpr>
cxxFunctionalCastExpr;
/// Matches functional cast expressions having N != 1 arguments
///
/// Example: Matches Foo(bar, bar)
/// \code
/// Foo h = Foo(bar, bar);
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CXXTemporaryObjectExpr>
cxxTemporaryObjectExpr;
/// Matches predefined identifier expressions [C99 6.4.2.2].
///
/// Example: Matches __func__
/// \code
/// printf("%s", __func__);
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, PredefinedExpr>
predefinedExpr;
/// Matches C99 designated initializer expressions [C99 6.7.8].
///
/// Example: Matches { [2].y = 1.0, [0].x = 1.0 }
/// \code
/// point ptarray[10] = { [2].y = 1.0, [0].x = 1.0 };
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, DesignatedInitExpr>
designatedInitExpr;
/// Matches designated initializer expressions that contain
/// a specific number of designators.
///
/// Example: Given
/// \code
/// point ptarray[10] = { [2].y = 1.0, [0].x = 1.0 };
/// point ptarray2[10] = { [2].y = 1.0, [2].x = 0.0, [0].x = 1.0 };
/// \endcode
/// designatorCountIs(2)
/// matches '{ [2].y = 1.0, [0].x = 1.0 }',
/// but not '{ [2].y = 1.0, [2].x = 0.0, [0].x = 1.0 }'.
AST_MATCHER_P(DesignatedInitExpr, designatorCountIs, unsigned, N) {
return Node.size() == N;
}
/// Matches \c QualTypes in the clang AST.
extern const internal::VariadicAllOfMatcher<QualType> qualType;
/// Matches \c Types in the clang AST.
extern const internal::VariadicAllOfMatcher<Type> type;
/// Matches \c TypeLocs in the clang AST.
extern const internal::VariadicAllOfMatcher<TypeLoc> typeLoc;
/// Matches if any of the given matchers matches.
///
/// Unlike \c anyOf, \c eachOf will generate a match result for each
/// matching submatcher.
///
/// For example, in:
/// \code
/// class A { int a; int b; };
/// \endcode
/// The matcher:
/// \code
/// cxxRecordDecl(eachOf(has(fieldDecl(hasName("a")).bind("v")),
/// has(fieldDecl(hasName("b")).bind("v"))))
/// \endcode
/// will generate two results binding "v", the first of which binds
/// the field declaration of \c a, the second the field declaration of
/// \c b.
///
/// Usable as: Any Matcher
extern const internal::VariadicOperatorMatcherFunc<
2, std::numeric_limits<unsigned>::max()>
eachOf;
/// Matches if any of the given matchers matches.
///
/// Usable as: Any Matcher
extern const internal::VariadicOperatorMatcherFunc<
2, std::numeric_limits<unsigned>::max()>
anyOf;
/// Matches if all given matchers match.
///
/// Usable as: Any Matcher
extern const internal::VariadicOperatorMatcherFunc<
2, std::numeric_limits<unsigned>::max()>
allOf;
/// Matches any node regardless of the submatchers.
///
/// However, \c optionally will generate a result binding for each matching
/// submatcher.
///
/// Useful when additional information which may or may not present about a
/// main matching node is desired.
///
/// For example, in:
/// \code
/// class Foo {
/// int bar;
/// }
/// \endcode
/// The matcher:
/// \code
/// cxxRecordDecl(
/// optionally(has(
/// fieldDecl(hasName("bar")).bind("var")
/// ))).bind("record")
/// \endcode
/// will produce a result binding for both "record" and "var".
/// The matcher will produce a "record" binding for even if there is no data
/// member named "bar" in that class.
///
/// Usable as: Any Matcher
extern const internal::VariadicOperatorMatcherFunc<
1, std::numeric_limits<unsigned>::max()>
optionally;
/// Matches sizeof (C99), alignof (C++11) and vec_step (OpenCL)
///
/// Given
/// \code
/// Foo x = bar;
/// int y = sizeof(x) + alignof(x);
/// \endcode
/// unaryExprOrTypeTraitExpr()
/// matches \c sizeof(x) and \c alignof(x)
extern const internal::VariadicDynCastAllOfMatcher<Stmt,
UnaryExprOrTypeTraitExpr>
unaryExprOrTypeTraitExpr;
/// Matches unary expressions that have a specific type of argument.
///
/// Given
/// \code
/// int a, c; float b; int s = sizeof(a) + sizeof(b) + alignof(c);
/// \endcode
/// unaryExprOrTypeTraitExpr(hasArgumentOfType(asString("int"))
/// matches \c sizeof(a) and \c alignof(c)
AST_MATCHER_P(UnaryExprOrTypeTraitExpr, hasArgumentOfType,
internal::Matcher<QualType>, InnerMatcher) {
const QualType ArgumentType = Node.getTypeOfArgument();
return InnerMatcher.matches(ArgumentType, Finder, Builder);
}
/// Matches unary expressions of a certain kind.
///
/// Given
/// \code
/// int x;
/// int s = sizeof(x) + alignof(x)
/// \endcode
/// unaryExprOrTypeTraitExpr(ofKind(UETT_SizeOf))
/// matches \c sizeof(x)
///
/// If the matcher is use from clang-query, UnaryExprOrTypeTrait parameter
/// should be passed as a quoted string. e.g., ofKind("UETT_SizeOf").
AST_MATCHER_P(UnaryExprOrTypeTraitExpr, ofKind, UnaryExprOrTypeTrait, Kind) {
return Node.getKind() == Kind;
}
/// Same as unaryExprOrTypeTraitExpr, but only matching
/// alignof.
inline internal::Matcher<Stmt> alignOfExpr(
const internal::Matcher<UnaryExprOrTypeTraitExpr> &InnerMatcher) {
return stmt(unaryExprOrTypeTraitExpr(
allOf(anyOf(ofKind(UETT_AlignOf), ofKind(UETT_PreferredAlignOf)),
InnerMatcher)));
}
/// Same as unaryExprOrTypeTraitExpr, but only matching
/// sizeof.
inline internal::Matcher<Stmt> sizeOfExpr(
const internal::Matcher<UnaryExprOrTypeTraitExpr> &InnerMatcher) {
return stmt(unaryExprOrTypeTraitExpr(
allOf(ofKind(UETT_SizeOf), InnerMatcher)));
}
/// Matches NamedDecl nodes that have the specified name.
///
/// Supports specifying enclosing namespaces or classes by prefixing the name
/// with '<enclosing>::'.
/// Does not match typedefs of an underlying type with the given name.
///
/// Example matches X (Name == "X")
/// \code
/// class X;
/// \endcode
///
/// Example matches X (Name is one of "::a::b::X", "a::b::X", "b::X", "X")
/// \code
/// namespace a { namespace b { class X; } }
/// \endcode
inline internal::Matcher<NamedDecl> hasName(const std::string &Name) {
return internal::Matcher<NamedDecl>(new internal::HasNameMatcher({Name}));
}
/// Matches NamedDecl nodes that have any of the specified names.
///
/// This matcher is only provided as a performance optimization of hasName.
/// \code
/// hasAnyName(a, b, c)
/// \endcode
/// is equivalent to, but faster than
/// \code
/// anyOf(hasName(a), hasName(b), hasName(c))
/// \endcode
extern const internal::VariadicFunction<internal::Matcher<NamedDecl>, StringRef,
internal::hasAnyNameFunc>
hasAnyName;
/// Matches NamedDecl nodes whose fully qualified names contain
/// a substring matched by the given RegExp.
///
/// Supports specifying enclosing namespaces or classes by
/// prefixing the name with '<enclosing>::'. Does not match typedefs
/// of an underlying type with the given name.
///
/// Example matches X (regexp == "::X")
/// \code
/// class X;
/// \endcode
///
/// Example matches X (regexp is one of "::X", "^foo::.*X", among others)
/// \code
/// namespace foo { namespace bar { class X; } }
/// \endcode
AST_MATCHER_P(NamedDecl, matchesName, std::string, RegExp) {
assert(!RegExp.empty());
std::string FullNameString = "::" + Node.getQualifiedNameAsString();
llvm::Regex RE(RegExp);
return RE.match(FullNameString);
}
/// Matches overloaded operator names.
///
/// Matches overloaded operator names specified in strings without the
/// "operator" prefix: e.g. "<<".
///
/// Given:
/// \code
/// class A { int operator*(); };
/// const A &operator<<(const A &a, const A &b);
/// A a;
/// a << a; // <-- This matches
/// \endcode
///
/// \c cxxOperatorCallExpr(hasOverloadedOperatorName("<<"))) matches the
/// specified line and
/// \c cxxRecordDecl(hasMethod(hasOverloadedOperatorName("*")))
/// matches the declaration of \c A.
///
/// Usable as: Matcher<CXXOperatorCallExpr>, Matcher<FunctionDecl>
inline internal::PolymorphicMatcherWithParam1<
internal::HasOverloadedOperatorNameMatcher, StringRef,
AST_POLYMORPHIC_SUPPORTED_TYPES(CXXOperatorCallExpr, FunctionDecl)>
hasOverloadedOperatorName(StringRef Name) {
return internal::PolymorphicMatcherWithParam1<
internal::HasOverloadedOperatorNameMatcher, StringRef,
AST_POLYMORPHIC_SUPPORTED_TYPES(CXXOperatorCallExpr, FunctionDecl)>(Name);
}
/// Matches C++ classes that are directly or indirectly derived from a class
/// matching \c Base, or Objective-C classes that directly or indirectly
/// subclass a class matching \c Base.
///
/// Note that a class is not considered to be derived from itself.
///
/// Example matches Y, Z, C (Base == hasName("X"))
/// \code
/// class X;
/// class Y : public X {}; // directly derived
/// class Z : public Y {}; // indirectly derived
/// typedef X A;
/// typedef A B;
/// class C : public B {}; // derived from a typedef of X
/// \endcode
///
/// In the following example, Bar matches isDerivedFrom(hasName("X")):
/// \code
/// class Foo;
/// typedef Foo X;
/// class Bar : public Foo {}; // derived from a type that X is a typedef of
/// \endcode
///
/// In the following example, Bar matches isDerivedFrom(hasName("NSObject"))
/// \code
/// @interface NSObject @end
/// @interface Bar : NSObject @end
/// \endcode
///
/// Usable as: Matcher<CXXRecordDecl>, Matcher<ObjCInterfaceDecl>
AST_POLYMORPHIC_MATCHER_P(
isDerivedFrom,
AST_POLYMORPHIC_SUPPORTED_TYPES(CXXRecordDecl, ObjCInterfaceDecl),
internal::Matcher<NamedDecl>, Base) {
// Check if the node is a C++ struct/union/class.
if (const auto *RD = dyn_cast<CXXRecordDecl>(&Node))
return Finder->classIsDerivedFrom(RD, Base, Builder, /*Directly=*/false);
// The node must be an Objective-C class.
const auto *InterfaceDecl = cast<ObjCInterfaceDecl>(&Node);
return Finder->objcClassIsDerivedFrom(InterfaceDecl, Base, Builder,
/*Directly=*/false);
}
/// Overloaded method as shortcut for \c isDerivedFrom(hasName(...)).
AST_POLYMORPHIC_MATCHER_P_OVERLOAD(
isDerivedFrom,
AST_POLYMORPHIC_SUPPORTED_TYPES(CXXRecordDecl, ObjCInterfaceDecl),
std::string, BaseName, 1) {
if (BaseName.empty())
return false;
const auto M = isDerivedFrom(hasName(BaseName));
if (const auto *RD = dyn_cast<CXXRecordDecl>(&Node))
return Matcher<CXXRecordDecl>(M).matches(*RD, Finder, Builder);
const auto *InterfaceDecl = cast<ObjCInterfaceDecl>(&Node);
return Matcher<ObjCInterfaceDecl>(M).matches(*InterfaceDecl, Finder, Builder);
}
/// Similar to \c isDerivedFrom(), but also matches classes that directly
/// match \c Base.
AST_POLYMORPHIC_MATCHER_P_OVERLOAD(
isSameOrDerivedFrom,
AST_POLYMORPHIC_SUPPORTED_TYPES(CXXRecordDecl, ObjCInterfaceDecl),
internal::Matcher<NamedDecl>, Base, 0) {
const auto M = anyOf(Base, isDerivedFrom(Base));
if (const auto *RD = dyn_cast<CXXRecordDecl>(&Node))
return Matcher<CXXRecordDecl>(M).matches(*RD, Finder, Builder);
const auto *InterfaceDecl = cast<ObjCInterfaceDecl>(&Node);
return Matcher<ObjCInterfaceDecl>(M).matches(*InterfaceDecl, Finder, Builder);
}
/// Overloaded method as shortcut for
/// \c isSameOrDerivedFrom(hasName(...)).
AST_POLYMORPHIC_MATCHER_P_OVERLOAD(
isSameOrDerivedFrom,
AST_POLYMORPHIC_SUPPORTED_TYPES(CXXRecordDecl, ObjCInterfaceDecl),
std::string, BaseName, 1) {
if (BaseName.empty())
return false;
const auto M = isSameOrDerivedFrom(hasName(BaseName));
if (const auto *RD = dyn_cast<CXXRecordDecl>(&Node))
return Matcher<CXXRecordDecl>(M).matches(*RD, Finder, Builder);
const auto *InterfaceDecl = cast<ObjCInterfaceDecl>(&Node);
return Matcher<ObjCInterfaceDecl>(M).matches(*InterfaceDecl, Finder, Builder);
}
/// Matches C++ or Objective-C classes that are directly derived from a class
/// matching \c Base.
///
/// Note that a class is not considered to be derived from itself.
///
/// Example matches Y, C (Base == hasName("X"))
/// \code
/// class X;
/// class Y : public X {}; // directly derived
/// class Z : public Y {}; // indirectly derived
/// typedef X A;
/// typedef A B;
/// class C : public B {}; // derived from a typedef of X
/// \endcode
///
/// In the following example, Bar matches isDerivedFrom(hasName("X")):
/// \code
/// class Foo;
/// typedef Foo X;
/// class Bar : public Foo {}; // derived from a type that X is a typedef of
/// \endcode
AST_POLYMORPHIC_MATCHER_P_OVERLOAD(
isDirectlyDerivedFrom,
AST_POLYMORPHIC_SUPPORTED_TYPES(CXXRecordDecl, ObjCInterfaceDecl),
internal::Matcher<NamedDecl>, Base, 0) {
// Check if the node is a C++ struct/union/class.
if (const auto *RD = dyn_cast<CXXRecordDecl>(&Node))
return Finder->classIsDerivedFrom(RD, Base, Builder, /*Directly=*/true);
// The node must be an Objective-C class.
const auto *InterfaceDecl = cast<ObjCInterfaceDecl>(&Node);
return Finder->objcClassIsDerivedFrom(InterfaceDecl, Base, Builder,
/*Directly=*/true);
}
/// Overloaded method as shortcut for \c isDirectlyDerivedFrom(hasName(...)).
AST_POLYMORPHIC_MATCHER_P_OVERLOAD(
isDirectlyDerivedFrom,
AST_POLYMORPHIC_SUPPORTED_TYPES(CXXRecordDecl, ObjCInterfaceDecl),
std::string, BaseName, 1) {
if (BaseName.empty())
return false;
const auto M = isDirectlyDerivedFrom(hasName(BaseName));
if (const auto *RD = dyn_cast<CXXRecordDecl>(&Node))
return Matcher<CXXRecordDecl>(M).matches(*RD, Finder, Builder);
const auto *InterfaceDecl = cast<ObjCInterfaceDecl>(&Node);
return Matcher<ObjCInterfaceDecl>(M).matches(*InterfaceDecl, Finder, Builder);
}
/// Matches the first method of a class or struct that satisfies \c
/// InnerMatcher.
///
/// Given:
/// \code
/// class A { void func(); };
/// class B { void member(); };
/// \endcode
///
/// \c cxxRecordDecl(hasMethod(hasName("func"))) matches the declaration of
/// \c A but not \c B.
AST_MATCHER_P(CXXRecordDecl, hasMethod, internal::Matcher<CXXMethodDecl>,
InnerMatcher) {
return matchesFirstInPointerRange(InnerMatcher, Node.method_begin(),
Node.method_end(), Finder, Builder);
}
/// Matches the generated class of lambda expressions.
///
/// Given:
/// \code
/// auto x = []{};
/// \endcode
///
/// \c cxxRecordDecl(isLambda()) matches the implicit class declaration of
/// \c decltype(x)
AST_MATCHER(CXXRecordDecl, isLambda) {
return Node.isLambda();
}
/// Matches AST nodes that have child AST nodes that match the
/// provided matcher.
///
/// Example matches X, Y
/// (matcher = cxxRecordDecl(has(cxxRecordDecl(hasName("X")))
/// \code
/// class X {}; // Matches X, because X::X is a class of name X inside X.
/// class Y { class X {}; };
/// class Z { class Y { class X {}; }; }; // Does not match Z.
/// \endcode
///
/// ChildT must be an AST base type.
///
/// Usable as: Any Matcher
/// Note that has is direct matcher, so it also matches things like implicit
/// casts and paren casts. If you are matching with expr then you should
/// probably consider using ignoringParenImpCasts like:
/// has(ignoringParenImpCasts(expr())).
extern const internal::ArgumentAdaptingMatcherFunc<internal::HasMatcher> has;
/// Matches AST nodes that have descendant AST nodes that match the
/// provided matcher.
///
/// Example matches X, Y, Z
/// (matcher = cxxRecordDecl(hasDescendant(cxxRecordDecl(hasName("X")))))
/// \code
/// class X {}; // Matches X, because X::X is a class of name X inside X.
/// class Y { class X {}; };
/// class Z { class Y { class X {}; }; };
/// \endcode
///
/// DescendantT must be an AST base type.
///
/// Usable as: Any Matcher
extern const internal::ArgumentAdaptingMatcherFunc<
internal::HasDescendantMatcher>
hasDescendant;
/// Matches AST nodes that have child AST nodes that match the
/// provided matcher.
///
/// Example matches X, Y, Y::X, Z::Y, Z::Y::X
/// (matcher = cxxRecordDecl(forEach(cxxRecordDecl(hasName("X")))
/// \code
/// class X {};
/// class Y { class X {}; }; // Matches Y, because Y::X is a class of name X
/// // inside Y.
/// class Z { class Y { class X {}; }; }; // Does not match Z.
/// \endcode
///
/// ChildT must be an AST base type.
///
/// As opposed to 'has', 'forEach' will cause a match for each result that
/// matches instead of only on the first one.
///
/// Usable as: Any Matcher
extern const internal::ArgumentAdaptingMatcherFunc<internal::ForEachMatcher>
forEach;
/// Matches AST nodes that have descendant AST nodes that match the
/// provided matcher.
///
/// Example matches X, A, A::X, B, B::C, B::C::X
/// (matcher = cxxRecordDecl(forEachDescendant(cxxRecordDecl(hasName("X")))))
/// \code
/// class X {};
/// class A { class X {}; }; // Matches A, because A::X is a class of name
/// // X inside A.
/// class B { class C { class X {}; }; };
/// \endcode
///
/// DescendantT must be an AST base type.
///
/// As opposed to 'hasDescendant', 'forEachDescendant' will cause a match for
/// each result that matches instead of only on the first one.
///
/// Note: Recursively combined ForEachDescendant can cause many matches:
/// cxxRecordDecl(forEachDescendant(cxxRecordDecl(
/// forEachDescendant(cxxRecordDecl())
/// )))
/// will match 10 times (plus injected class name matches) on:
/// \code
/// class A { class B { class C { class D { class E {}; }; }; }; };
/// \endcode
///
/// Usable as: Any Matcher
extern const internal::ArgumentAdaptingMatcherFunc<
internal::ForEachDescendantMatcher>
forEachDescendant;
/// Matches if the node or any descendant matches.
///
/// Generates results for each match.
///
/// For example, in:
/// \code
/// class A { class B {}; class C {}; };
/// \endcode
/// The matcher:
/// \code
/// cxxRecordDecl(hasName("::A"),
/// findAll(cxxRecordDecl(isDefinition()).bind("m")))
/// \endcode
/// will generate results for \c A, \c B and \c C.
///
/// Usable as: Any Matcher
template <typename T>
internal::Matcher<T> findAll(const internal::Matcher<T> &Matcher) {
return eachOf(Matcher, forEachDescendant(Matcher));
}
/// Matches AST nodes that have a parent that matches the provided
/// matcher.
///
/// Given
/// \code
/// void f() { for (;;) { int x = 42; if (true) { int x = 43; } } }
/// \endcode
/// \c compoundStmt(hasParent(ifStmt())) matches "{ int x = 43; }".
///
/// Usable as: Any Matcher
extern const internal::ArgumentAdaptingMatcherFunc<
internal::HasParentMatcher,
internal::TypeList<Decl, NestedNameSpecifierLoc, Stmt, TypeLoc>,
internal::TypeList<Decl, NestedNameSpecifierLoc, Stmt, TypeLoc>>
hasParent;
/// Matches AST nodes that have an ancestor that matches the provided
/// matcher.
///
/// Given
/// \code
/// void f() { if (true) { int x = 42; } }
/// void g() { for (;;) { int x = 43; } }
/// \endcode
/// \c expr(integerLiteral(hasAncestor(ifStmt()))) matches \c 42, but not 43.
///
/// Usable as: Any Matcher
extern const internal::ArgumentAdaptingMatcherFunc<
internal::HasAncestorMatcher,
internal::TypeList<Decl, NestedNameSpecifierLoc, Stmt, TypeLoc>,
internal::TypeList<Decl, NestedNameSpecifierLoc, Stmt, TypeLoc>>
hasAncestor;
/// Matches if the provided matcher does not match.
///
/// Example matches Y (matcher = cxxRecordDecl(unless(hasName("X"))))
/// \code
/// class X {};
/// class Y {};
/// \endcode
///
/// Usable as: Any Matcher
extern const internal::VariadicOperatorMatcherFunc<1, 1> unless;
/// Matches a node if the declaration associated with that node
/// matches the given matcher.
///
/// The associated declaration is:
/// - for type nodes, the declaration of the underlying type
/// - for CallExpr, the declaration of the callee
/// - for MemberExpr, the declaration of the referenced member
/// - for CXXConstructExpr, the declaration of the constructor
/// - for CXXNewExpr, the declaration of the operator new
/// - for ObjCIvarExpr, the declaration of the ivar
///
/// For type nodes, hasDeclaration will generally match the declaration of the
/// sugared type. Given
/// \code
/// class X {};
/// typedef X Y;
/// Y y;
/// \endcode
/// in varDecl(hasType(hasDeclaration(decl()))) the decl will match the
/// typedefDecl. A common use case is to match the underlying, desugared type.
/// This can be achieved by using the hasUnqualifiedDesugaredType matcher:
/// \code
/// varDecl(hasType(hasUnqualifiedDesugaredType(
/// recordType(hasDeclaration(decl())))))
/// \endcode
/// In this matcher, the decl will match the CXXRecordDecl of class X.
///
/// Usable as: Matcher<AddrLabelExpr>, Matcher<CallExpr>,
/// Matcher<CXXConstructExpr>, Matcher<CXXNewExpr>, Matcher<DeclRefExpr>,
/// Matcher<EnumType>, Matcher<InjectedClassNameType>, Matcher<LabelStmt>,
/// Matcher<MemberExpr>, Matcher<QualType>, Matcher<RecordType>,
/// Matcher<TagType>, Matcher<TemplateSpecializationType>,
/// Matcher<TemplateTypeParmType>, Matcher<TypedefType>,
/// Matcher<UnresolvedUsingType>
inline internal::PolymorphicMatcherWithParam1<
internal::HasDeclarationMatcher, internal::Matcher<Decl>,
void(internal::HasDeclarationSupportedTypes)>
hasDeclaration(const internal::Matcher<Decl> &InnerMatcher) {
return internal::PolymorphicMatcherWithParam1<
internal::HasDeclarationMatcher, internal::Matcher<Decl>,
void(internal::HasDeclarationSupportedTypes)>(InnerMatcher);
}
/// Matches a \c NamedDecl whose underlying declaration matches the given
/// matcher.
///
/// Given
/// \code
/// namespace N { template<class T> void f(T t); }
/// template <class T> void g() { using N::f; f(T()); }
/// \endcode
/// \c unresolvedLookupExpr(hasAnyDeclaration(
/// namedDecl(hasUnderlyingDecl(hasName("::N::f")))))
/// matches the use of \c f in \c g() .
AST_MATCHER_P(NamedDecl, hasUnderlyingDecl, internal::Matcher<NamedDecl>,
InnerMatcher) {
const NamedDecl *UnderlyingDecl = Node.getUnderlyingDecl();
return UnderlyingDecl != nullptr &&
InnerMatcher.matches(*UnderlyingDecl, Finder, Builder);
}
/// Matches on the implicit object argument of a member call expression, after
/// stripping off any parentheses or implicit casts.
///
/// Given
/// \code
/// class Y { public: void m(); };
/// Y g();
/// class X : public Y {};
/// void z(Y y, X x) { y.m(); (g()).m(); x.m(); }
/// \endcode
/// cxxMemberCallExpr(on(hasType(cxxRecordDecl(hasName("Y")))))
/// matches `y.m()` and `(g()).m()`.
/// cxxMemberCallExpr(on(hasType(cxxRecordDecl(hasName("X")))))
/// matches `x.m()`.
/// cxxMemberCallExpr(on(callExpr()))
/// matches `(g()).m()`.
///
/// FIXME: Overload to allow directly matching types?
AST_MATCHER_P(CXXMemberCallExpr, on, internal::Matcher<Expr>,
InnerMatcher) {
const Expr *ExprNode = Node.getImplicitObjectArgument()
->IgnoreParenImpCasts();
return (ExprNode != nullptr &&
InnerMatcher.matches(*ExprNode, Finder, Builder));
}
/// Matches on the receiver of an ObjectiveC Message expression.
///
/// Example
/// matcher = objCMessageExpr(hasReceiverType(asString("UIWebView *")));
/// matches the [webView ...] message invocation.
/// \code
/// NSString *webViewJavaScript = ...
/// UIWebView *webView = ...
/// [webView stringByEvaluatingJavaScriptFromString:webViewJavascript];
/// \endcode
AST_MATCHER_P(ObjCMessageExpr, hasReceiverType, internal::Matcher<QualType>,
InnerMatcher) {
const QualType TypeDecl = Node.getReceiverType();
return InnerMatcher.matches(TypeDecl, Finder, Builder);
}
/// Returns true when the Objective-C method declaration is a class method.
///
/// Example
/// matcher = objcMethodDecl(isClassMethod())
/// matches
/// \code
/// @interface I + (void)foo; @end
/// \endcode
/// but not
/// \code
/// @interface I - (void)bar; @end
/// \endcode
AST_MATCHER(ObjCMethodDecl, isClassMethod) {
return Node.isClassMethod();
}
/// Returns true when the Objective-C method declaration is an instance method.
///
/// Example
/// matcher = objcMethodDecl(isInstanceMethod())
/// matches
/// \code
/// @interface I - (void)bar; @end
/// \endcode
/// but not
/// \code
/// @interface I + (void)foo; @end
/// \endcode
AST_MATCHER(ObjCMethodDecl, isInstanceMethod) {
return Node.isInstanceMethod();
}
/// Returns true when the Objective-C message is sent to a class.
///
/// Example
/// matcher = objcMessageExpr(isClassMessage())
/// matches
/// \code
/// [NSString stringWithFormat:@"format"];
/// \endcode
/// but not
/// \code
/// NSString *x = @"hello";
/// [x containsString:@"h"];
/// \endcode
AST_MATCHER(ObjCMessageExpr, isClassMessage) {
return Node.isClassMessage();
}
/// Returns true when the Objective-C message is sent to an instance.
///
/// Example
/// matcher = objcMessageExpr(isInstanceMessage())
/// matches
/// \code
/// NSString *x = @"hello";
/// [x containsString:@"h"];
/// \endcode
/// but not
/// \code
/// [NSString stringWithFormat:@"format"];
/// \endcode
AST_MATCHER(ObjCMessageExpr, isInstanceMessage) {
return Node.isInstanceMessage();
}
/// Matches if the Objective-C message is sent to an instance,
/// and the inner matcher matches on that instance.
///
/// For example the method call in
/// \code
/// NSString *x = @"hello";
/// [x containsString:@"h"];
/// \endcode
/// is matched by
/// objcMessageExpr(hasReceiver(declRefExpr(to(varDecl(hasName("x"))))))
AST_MATCHER_P(ObjCMessageExpr, hasReceiver, internal::Matcher<Expr>,
InnerMatcher) {
const Expr *ReceiverNode = Node.getInstanceReceiver();
return (ReceiverNode != nullptr &&
InnerMatcher.matches(*ReceiverNode->IgnoreParenImpCasts(), Finder,
Builder));
}
/// Matches when BaseName == Selector.getAsString()
///
/// matcher = objCMessageExpr(hasSelector("loadHTMLString:baseURL:"));
/// matches the outer message expr in the code below, but NOT the message
/// invocation for self.bodyView.
/// \code
/// [self.bodyView loadHTMLString:html baseURL:NULL];
/// \endcode
AST_MATCHER_P(ObjCMessageExpr, hasSelector, std::string, BaseName) {
Selector Sel = Node.getSelector();
return BaseName.compare(Sel.getAsString()) == 0;
}
/// Matches when at least one of the supplied string equals to the
/// Selector.getAsString()
///
/// matcher = objCMessageExpr(hasSelector("methodA:", "methodB:"));
/// matches both of the expressions below:
/// \code
/// [myObj methodA:argA];
/// [myObj methodB:argB];
/// \endcode
extern const internal::VariadicFunction<internal::Matcher<ObjCMessageExpr>,
StringRef,
internal::hasAnySelectorFunc>
hasAnySelector;
/// Matches ObjC selectors whose name contains
/// a substring matched by the given RegExp.
/// matcher = objCMessageExpr(matchesSelector("loadHTMLString\:baseURL?"));
/// matches the outer message expr in the code below, but NOT the message
/// invocation for self.bodyView.
/// \code
/// [self.bodyView loadHTMLString:html baseURL:NULL];
/// \endcode
AST_MATCHER_P(ObjCMessageExpr, matchesSelector, std::string, RegExp) {
assert(!RegExp.empty());
std::string SelectorString = Node.getSelector().getAsString();
llvm::Regex RE(RegExp);
return RE.match(SelectorString);
}
/// Matches when the selector is the empty selector
///
/// Matches only when the selector of the objCMessageExpr is NULL. This may
/// represent an error condition in the tree!
AST_MATCHER(ObjCMessageExpr, hasNullSelector) {
return Node.getSelector().isNull();
}
/// Matches when the selector is a Unary Selector
///
/// matcher = objCMessageExpr(matchesSelector(hasUnarySelector());
/// matches self.bodyView in the code below, but NOT the outer message
/// invocation of "loadHTMLString:baseURL:".
/// \code
/// [self.bodyView loadHTMLString:html baseURL:NULL];
/// \endcode
AST_MATCHER(ObjCMessageExpr, hasUnarySelector) {
return Node.getSelector().isUnarySelector();
}
/// Matches when the selector is a keyword selector
///
/// objCMessageExpr(hasKeywordSelector()) matches the generated setFrame
/// message expression in
///
/// \code
/// UIWebView *webView = ...;
/// CGRect bodyFrame = webView.frame;
/// bodyFrame.size.height = self.bodyContentHeight;
/// webView.frame = bodyFrame;
/// // ^---- matches here
/// \endcode
AST_MATCHER(ObjCMessageExpr, hasKeywordSelector) {
return Node.getSelector().isKeywordSelector();
}
/// Matches when the selector has the specified number of arguments
///
/// matcher = objCMessageExpr(numSelectorArgs(0));
/// matches self.bodyView in the code below
///
/// matcher = objCMessageExpr(numSelectorArgs(2));
/// matches the invocation of "loadHTMLString:baseURL:" but not that
/// of self.bodyView
/// \code
/// [self.bodyView loadHTMLString:html baseURL:NULL];
/// \endcode
AST_MATCHER_P(ObjCMessageExpr, numSelectorArgs, unsigned, N) {
return Node.getSelector().getNumArgs() == N;
}
/// Matches if the call expression's callee expression matches.
///
/// Given
/// \code
/// class Y { void x() { this->x(); x(); Y y; y.x(); } };
/// void f() { f(); }
/// \endcode
/// callExpr(callee(expr()))
/// matches this->x(), x(), y.x(), f()
/// with callee(...)
/// matching this->x, x, y.x, f respectively
///
/// Note: Callee cannot take the more general internal::Matcher<Expr>
/// because this introduces ambiguous overloads with calls to Callee taking a
/// internal::Matcher<Decl>, as the matcher hierarchy is purely
/// implemented in terms of implicit casts.
AST_MATCHER_P(CallExpr, callee, internal::Matcher<Stmt>,
InnerMatcher) {
const Expr *ExprNode = Node.getCallee();
return (ExprNode != nullptr &&
InnerMatcher.matches(*ExprNode, Finder, Builder));
}
/// Matches if the call expression's callee's declaration matches the
/// given matcher.
///
/// Example matches y.x() (matcher = callExpr(callee(
/// cxxMethodDecl(hasName("x")))))
/// \code
/// class Y { public: void x(); };
/// void z() { Y y; y.x(); }
/// \endcode
AST_MATCHER_P_OVERLOAD(CallExpr, callee, internal::Matcher<Decl>, InnerMatcher,
1) {
return callExpr(hasDeclaration(InnerMatcher)).matches(Node, Finder, Builder);
}
/// Matches if the expression's or declaration's type matches a type
/// matcher.
///
/// Example matches x (matcher = expr(hasType(cxxRecordDecl(hasName("X")))))
/// and z (matcher = varDecl(hasType(cxxRecordDecl(hasName("X")))))
/// and U (matcher = typedefDecl(hasType(asString("int")))
/// and friend class X (matcher = friendDecl(hasType("X"))
/// \code
/// class X {};
/// void y(X &x) { x; X z; }
/// typedef int U;
/// class Y { friend class X; };
/// \endcode
AST_POLYMORPHIC_MATCHER_P_OVERLOAD(
hasType,
AST_POLYMORPHIC_SUPPORTED_TYPES(Expr, FriendDecl, TypedefNameDecl,
ValueDecl),
internal::Matcher<QualType>, InnerMatcher, 0) {
QualType QT = internal::getUnderlyingType(Node);
if (!QT.isNull())
return InnerMatcher.matches(QT, Finder, Builder);
return false;
}
/// Overloaded to match the declaration of the expression's or value
/// declaration's type.
///
/// In case of a value declaration (for example a variable declaration),
/// this resolves one layer of indirection. For example, in the value
/// declaration "X x;", cxxRecordDecl(hasName("X")) matches the declaration of
/// X, while varDecl(hasType(cxxRecordDecl(hasName("X")))) matches the
/// declaration of x.
///
/// Example matches x (matcher = expr(hasType(cxxRecordDecl(hasName("X")))))
/// and z (matcher = varDecl(hasType(cxxRecordDecl(hasName("X")))))
/// and friend class X (matcher = friendDecl(hasType("X"))
/// \code
/// class X {};
/// void y(X &x) { x; X z; }
/// class Y { friend class X; };
/// \endcode
///
/// Usable as: Matcher<Expr>, Matcher<ValueDecl>
AST_POLYMORPHIC_MATCHER_P_OVERLOAD(
hasType, AST_POLYMORPHIC_SUPPORTED_TYPES(Expr, FriendDecl, ValueDecl),
internal::Matcher<Decl>, InnerMatcher, 1) {
QualType QT = internal::getUnderlyingType(Node);
if (!QT.isNull())
return qualType(hasDeclaration(InnerMatcher)).matches(QT, Finder, Builder);
return false;
}
/// Matches if the type location of the declarator decl's type matches
/// the inner matcher.
///
/// Given
/// \code
/// int x;
/// \endcode
/// declaratorDecl(hasTypeLoc(loc(asString("int"))))
/// matches int x
AST_MATCHER_P(DeclaratorDecl, hasTypeLoc, internal::Matcher<TypeLoc>, Inner) {
if (!Node.getTypeSourceInfo())
// This happens for example for implicit destructors.
return false;
return Inner.matches(Node.getTypeSourceInfo()->getTypeLoc(), Finder, Builder);
}
/// Matches if the matched type is represented by the given string.
///
/// Given
/// \code
/// class Y { public: void x(); };
/// void z() { Y* y; y->x(); }
/// \endcode
/// cxxMemberCallExpr(on(hasType(asString("class Y *"))))
/// matches y->x()
AST_MATCHER_P(QualType, asString, std::string, Name) {
return Name == Node.getAsString();
}
/// Matches if the matched type is a pointer type and the pointee type
/// matches the specified matcher.
///
/// Example matches y->x()
/// (matcher = cxxMemberCallExpr(on(hasType(pointsTo
/// cxxRecordDecl(hasName("Y")))))))
/// \code
/// class Y { public: void x(); };
/// void z() { Y *y; y->x(); }
/// \endcode
AST_MATCHER_P(
QualType, pointsTo, internal::Matcher<QualType>,
InnerMatcher) {
return (!Node.isNull() && Node->isAnyPointerType() &&
InnerMatcher.matches(Node->getPointeeType(), Finder, Builder));
}
/// Overloaded to match the pointee type's declaration.
AST_MATCHER_P_OVERLOAD(QualType, pointsTo, internal::Matcher<Decl>,
InnerMatcher, 1) {
return pointsTo(qualType(hasDeclaration(InnerMatcher)))
.matches(Node, Finder, Builder);
}
/// Matches if the matched type matches the unqualified desugared
/// type of the matched node.
///
/// For example, in:
/// \code
/// class A {};
/// using B = A;
/// \endcode
/// The matcher type(hasUnqualifiedDesugaredType(recordType())) matches
/// both B and A.
AST_MATCHER_P(Type, hasUnqualifiedDesugaredType, internal::Matcher<Type>,
InnerMatcher) {
return InnerMatcher.matches(*Node.getUnqualifiedDesugaredType(), Finder,
Builder);
}
/// Matches if the matched type is a reference type and the referenced
/// type matches the specified matcher.
///
/// Example matches X &x and const X &y
/// (matcher = varDecl(hasType(references(cxxRecordDecl(hasName("X"))))))
/// \code
/// class X {
/// void a(X b) {
/// X &x = b;
/// const X &y = b;
/// }
/// };
/// \endcode
AST_MATCHER_P(QualType, references, internal::Matcher<QualType>,
InnerMatcher) {
return (!Node.isNull() && Node->isReferenceType() &&
InnerMatcher.matches(Node->getPointeeType(), Finder, Builder));
}
/// Matches QualTypes whose canonical type matches InnerMatcher.
///
/// Given:
/// \code
/// typedef int &int_ref;
/// int a;
/// int_ref b = a;
/// \endcode
///
/// \c varDecl(hasType(qualType(referenceType()))))) will not match the
/// declaration of b but \c
/// varDecl(hasType(qualType(hasCanonicalType(referenceType())))))) does.
AST_MATCHER_P(QualType, hasCanonicalType, internal::Matcher<QualType>,
InnerMatcher) {
if (Node.isNull())
return false;
return InnerMatcher.matches(Node.getCanonicalType(), Finder, Builder);
}
/// Overloaded to match the referenced type's declaration.
AST_MATCHER_P_OVERLOAD(QualType, references, internal::Matcher<Decl>,
InnerMatcher, 1) {
return references(qualType(hasDeclaration(InnerMatcher)))
.matches(Node, Finder, Builder);
}
/// Matches on the implicit object argument of a member call expression. Unlike
/// `on`, matches the argument directly without stripping away anything.
///
/// Given
/// \code
/// class Y { public: void m(); };
/// Y g();
/// class X : public Y { void g(); };
/// void z(Y y, X x) { y.m(); x.m(); x.g(); (g()).m(); }
/// \endcode
/// cxxMemberCallExpr(onImplicitObjectArgument(hasType(
/// cxxRecordDecl(hasName("Y")))))
/// matches `y.m()`, `x.m()` and (g()).m(), but not `x.g()`.
/// cxxMemberCallExpr(on(callExpr()))
/// does not match `(g()).m()`, because the parens are not ignored.
///
/// FIXME: Overload to allow directly matching types?
AST_MATCHER_P(CXXMemberCallExpr, onImplicitObjectArgument,
internal::Matcher<Expr>, InnerMatcher) {
const Expr *ExprNode = Node.getImplicitObjectArgument();
return (ExprNode != nullptr &&
InnerMatcher.matches(*ExprNode, Finder, Builder));
}
/// Matches if the type of the expression's implicit object argument either
/// matches the InnerMatcher, or is a pointer to a type that matches the
/// InnerMatcher.
///
/// Given
/// \code
/// class Y { public: void m(); };
/// class X : public Y { void g(); };
/// void z() { Y y; y.m(); Y *p; p->m(); X x; x.m(); x.g(); }
/// \endcode
/// cxxMemberCallExpr(thisPointerType(hasDeclaration(
/// cxxRecordDecl(hasName("Y")))))
/// matches `y.m()`, `p->m()` and `x.m()`.
/// cxxMemberCallExpr(thisPointerType(hasDeclaration(
/// cxxRecordDecl(hasName("X")))))
/// matches `x.g()`.
AST_MATCHER_P_OVERLOAD(CXXMemberCallExpr, thisPointerType,
internal::Matcher<QualType>, InnerMatcher, 0) {
return onImplicitObjectArgument(
anyOf(hasType(InnerMatcher), hasType(pointsTo(InnerMatcher))))
.matches(Node, Finder, Builder);
}
/// Overloaded to match the type's declaration.
AST_MATCHER_P_OVERLOAD(CXXMemberCallExpr, thisPointerType,
internal::Matcher<Decl>, InnerMatcher, 1) {
return onImplicitObjectArgument(
anyOf(hasType(InnerMatcher), hasType(pointsTo(InnerMatcher))))
.matches(Node, Finder, Builder);
}
/// Matches a DeclRefExpr that refers to a declaration that matches the
/// specified matcher.
///
/// Example matches x in if(x)
/// (matcher = declRefExpr(to(varDecl(hasName("x")))))
/// \code
/// bool x;
/// if (x) {}
/// \endcode
AST_MATCHER_P(DeclRefExpr, to, internal::Matcher<Decl>,
InnerMatcher) {
const Decl *DeclNode = Node.getDecl();
return (DeclNode != nullptr &&
InnerMatcher.matches(*DeclNode, Finder, Builder));
}
/// Matches a \c DeclRefExpr that refers to a declaration through a
/// specific using shadow declaration.
///
/// Given
/// \code
/// namespace a { void f() {} }
/// using a::f;
/// void g() {
/// f(); // Matches this ..
/// a::f(); // .. but not this.
/// }
/// \endcode
/// declRefExpr(throughUsingDecl(anything()))
/// matches \c f()
AST_MATCHER_P(DeclRefExpr, throughUsingDecl,
internal::Matcher<UsingShadowDecl>, InnerMatcher) {
const NamedDecl *FoundDecl = Node.getFoundDecl();
if (const UsingShadowDecl *UsingDecl = dyn_cast<UsingShadowDecl>(FoundDecl))
return InnerMatcher.matches(*UsingDecl, Finder, Builder);
return false;
}
/// Matches an \c OverloadExpr if any of the declarations in the set of
/// overloads matches the given matcher.
///
/// Given
/// \code
/// template <typename T> void foo(T);
/// template <typename T> void bar(T);
/// template <typename T> void baz(T t) {
/// foo(t);
/// bar(t);
/// }
/// \endcode
/// unresolvedLookupExpr(hasAnyDeclaration(
/// functionTemplateDecl(hasName("foo"))))
/// matches \c foo in \c foo(t); but not \c bar in \c bar(t);
AST_MATCHER_P(OverloadExpr, hasAnyDeclaration, internal::Matcher<Decl>,
InnerMatcher) {
return matchesFirstInPointerRange(InnerMatcher, Node.decls_begin(),
Node.decls_end(), Finder, Builder);
}
/// Matches the Decl of a DeclStmt which has a single declaration.
///
/// Given
/// \code
/// int a, b;
/// int c;
/// \endcode
/// declStmt(hasSingleDecl(anything()))
/// matches 'int c;' but not 'int a, b;'.
AST_MATCHER_P(DeclStmt, hasSingleDecl, internal::Matcher<Decl>, InnerMatcher) {
if (Node.isSingleDecl()) {
const Decl *FoundDecl = Node.getSingleDecl();
return InnerMatcher.matches(*FoundDecl, Finder, Builder);
}
return false;
}
/// Matches a variable declaration that has an initializer expression
/// that matches the given matcher.
///
/// Example matches x (matcher = varDecl(hasInitializer(callExpr())))
/// \code
/// bool y() { return true; }
/// bool x = y();
/// \endcode
AST_MATCHER_P(
VarDecl, hasInitializer, internal::Matcher<Expr>,
InnerMatcher) {
const Expr *Initializer = Node.getAnyInitializer();
return (Initializer != nullptr &&
InnerMatcher.matches(*Initializer, Finder, Builder));
}
/// \brief Matches a static variable with local scope.
///
/// Example matches y (matcher = varDecl(isStaticLocal()))
/// \code
/// void f() {
/// int x;
/// static int y;
/// }
/// static int z;
/// \endcode
AST_MATCHER(VarDecl, isStaticLocal) {
return Node.isStaticLocal();
}
/// Matches a variable declaration that has function scope and is a
/// non-static local variable.
///
/// Example matches x (matcher = varDecl(hasLocalStorage())
/// \code
/// void f() {
/// int x;
/// static int y;
/// }
/// int z;
/// \endcode
AST_MATCHER(VarDecl, hasLocalStorage) {
return Node.hasLocalStorage();
}
/// Matches a variable declaration that does not have local storage.
///
/// Example matches y and z (matcher = varDecl(hasGlobalStorage())
/// \code
/// void f() {
/// int x;
/// static int y;
/// }
/// int z;
/// \endcode
AST_MATCHER(VarDecl, hasGlobalStorage) {
return Node.hasGlobalStorage();
}
/// Matches a variable declaration that has automatic storage duration.
///
/// Example matches x, but not y, z, or a.
/// (matcher = varDecl(hasAutomaticStorageDuration())
/// \code
/// void f() {
/// int x;
/// static int y;
/// thread_local int z;
/// }
/// int a;
/// \endcode
AST_MATCHER(VarDecl, hasAutomaticStorageDuration) {
return Node.getStorageDuration() == SD_Automatic;
}
/// Matches a variable declaration that has static storage duration.
/// It includes the variable declared at namespace scope and those declared
/// with "static" and "extern" storage class specifiers.
///
/// \code
/// void f() {
/// int x;
/// static int y;
/// thread_local int z;
/// }
/// int a;
/// static int b;
/// extern int c;
/// varDecl(hasStaticStorageDuration())
/// matches the function declaration y, a, b and c.
/// \endcode
AST_MATCHER(VarDecl, hasStaticStorageDuration) {
return Node.getStorageDuration() == SD_Static;
}
/// Matches a variable declaration that has thread storage duration.
///
/// Example matches z, but not x, z, or a.
/// (matcher = varDecl(hasThreadStorageDuration())
/// \code
/// void f() {
/// int x;
/// static int y;
/// thread_local int z;
/// }
/// int a;
/// \endcode
AST_MATCHER(VarDecl, hasThreadStorageDuration) {
return Node.getStorageDuration() == SD_Thread;
}
/// Matches a variable declaration that is an exception variable from
/// a C++ catch block, or an Objective-C \@catch statement.
///
/// Example matches x (matcher = varDecl(isExceptionVariable())
/// \code
/// void f(int y) {
/// try {
/// } catch (int x) {
/// }
/// }
/// \endcode
AST_MATCHER(VarDecl, isExceptionVariable) {
return Node.isExceptionVariable();
}
/// Checks that a call expression or a constructor call expression has
/// a specific number of arguments (including absent default arguments).
///
/// Example matches f(0, 0) (matcher = callExpr(argumentCountIs(2)))
/// \code
/// void f(int x, int y);
/// f(0, 0);
/// \endcode
AST_POLYMORPHIC_MATCHER_P(argumentCountIs,
AST_POLYMORPHIC_SUPPORTED_TYPES(CallExpr,
CXXConstructExpr,
ObjCMessageExpr),
unsigned, N) {
return Node.getNumArgs() == N;
}
/// Matches the n'th argument of a call expression or a constructor
/// call expression.
///
/// Example matches y in x(y)
/// (matcher = callExpr(hasArgument(0, declRefExpr())))
/// \code
/// void x(int) { int y; x(y); }
/// \endcode
AST_POLYMORPHIC_MATCHER_P2(hasArgument,
AST_POLYMORPHIC_SUPPORTED_TYPES(CallExpr,
CXXConstructExpr,
ObjCMessageExpr),
unsigned, N, internal::Matcher<Expr>, InnerMatcher) {
return (N < Node.getNumArgs() &&
InnerMatcher.matches(
*Node.getArg(N)->IgnoreParenImpCasts(), Finder, Builder));
}
/// Matches the n'th item of an initializer list expression.
///
/// Example matches y.
/// (matcher = initListExpr(hasInit(0, expr())))
/// \code
/// int x{y}.
/// \endcode
AST_MATCHER_P2(InitListExpr, hasInit, unsigned, N,
ast_matchers::internal::Matcher<Expr>, InnerMatcher) {
return N < Node.getNumInits() &&
InnerMatcher.matches(*Node.getInit(N), Finder, Builder);
}
/// Matches declaration statements that contain a specific number of
/// declarations.
///
/// Example: Given
/// \code
/// int a, b;
/// int c;
/// int d = 2, e;
/// \endcode
/// declCountIs(2)
/// matches 'int a, b;' and 'int d = 2, e;', but not 'int c;'.
AST_MATCHER_P(DeclStmt, declCountIs, unsigned, N) {
return std::distance(Node.decl_begin(), Node.decl_end()) == (ptrdiff_t)N;
}
/// Matches the n'th declaration of a declaration statement.
///
/// Note that this does not work for global declarations because the AST
/// breaks up multiple-declaration DeclStmt's into multiple single-declaration
/// DeclStmt's.
/// Example: Given non-global declarations
/// \code
/// int a, b = 0;
/// int c;
/// int d = 2, e;
/// \endcode
/// declStmt(containsDeclaration(
/// 0, varDecl(hasInitializer(anything()))))
/// matches only 'int d = 2, e;', and
/// declStmt(containsDeclaration(1, varDecl()))
/// \code
/// matches 'int a, b = 0' as well as 'int d = 2, e;'
/// but 'int c;' is not matched.
/// \endcode
AST_MATCHER_P2(DeclStmt, containsDeclaration, unsigned, N,
internal::Matcher<Decl>, InnerMatcher) {
const unsigned NumDecls = std::distance(Node.decl_begin(), Node.decl_end());
if (N >= NumDecls)
return false;
DeclStmt::const_decl_iterator Iterator = Node.decl_begin();
std::advance(Iterator, N);
return InnerMatcher.matches(**Iterator, Finder, Builder);
}
/// Matches a C++ catch statement that has a catch-all handler.
///
/// Given
/// \code
/// try {
/// // ...
/// } catch (int) {
/// // ...
/// } catch (...) {
/// // ...
/// }
/// \endcode
/// cxxCatchStmt(isCatchAll()) matches catch(...) but not catch(int).
AST_MATCHER(CXXCatchStmt, isCatchAll) {
return Node.getExceptionDecl() == nullptr;
}
/// Matches a constructor initializer.
///
/// Given
/// \code
/// struct Foo {
/// Foo() : foo_(1) { }
/// int foo_;
/// };
/// \endcode
/// cxxRecordDecl(has(cxxConstructorDecl(
/// hasAnyConstructorInitializer(anything())
/// )))
/// record matches Foo, hasAnyConstructorInitializer matches foo_(1)
AST_MATCHER_P(CXXConstructorDecl, hasAnyConstructorInitializer,
internal::Matcher<CXXCtorInitializer>, InnerMatcher) {
return matchesFirstInPointerRange(InnerMatcher, Node.init_begin(),
Node.init_end(), Finder, Builder);
}
/// Matches the field declaration of a constructor initializer.
///
/// Given
/// \code
/// struct Foo {
/// Foo() : foo_(1) { }
/// int foo_;
/// };
/// \endcode
/// cxxRecordDecl(has(cxxConstructorDecl(hasAnyConstructorInitializer(
/// forField(hasName("foo_"))))))
/// matches Foo
/// with forField matching foo_
AST_MATCHER_P(CXXCtorInitializer, forField,
internal::Matcher<FieldDecl>, InnerMatcher) {
const FieldDecl *NodeAsDecl = Node.getAnyMember();
return (NodeAsDecl != nullptr &&
InnerMatcher.matches(*NodeAsDecl, Finder, Builder));
}
/// Matches the initializer expression of a constructor initializer.
///
/// Given
/// \code
/// struct Foo {
/// Foo() : foo_(1) { }
/// int foo_;
/// };
/// \endcode
/// cxxRecordDecl(has(cxxConstructorDecl(hasAnyConstructorInitializer(
/// withInitializer(integerLiteral(equals(1)))))))
/// matches Foo
/// with withInitializer matching (1)
AST_MATCHER_P(CXXCtorInitializer, withInitializer,
internal::Matcher<Expr>, InnerMatcher) {
const Expr* NodeAsExpr = Node.getInit();
return (NodeAsExpr != nullptr &&
InnerMatcher.matches(*NodeAsExpr, Finder, Builder));
}
/// Matches a constructor initializer if it is explicitly written in
/// code (as opposed to implicitly added by the compiler).
///
/// Given
/// \code
/// struct Foo {
/// Foo() { }
/// Foo(int) : foo_("A") { }
/// string foo_;
/// };
/// \endcode
/// cxxConstructorDecl(hasAnyConstructorInitializer(isWritten()))
/// will match Foo(int), but not Foo()
AST_MATCHER(CXXCtorInitializer, isWritten) {
return Node.isWritten();
}
/// Matches a constructor initializer if it is initializing a base, as
/// opposed to a member.
///
/// Given
/// \code
/// struct B {};
/// struct D : B {
/// int I;
/// D(int i) : I(i) {}
/// };
/// struct E : B {
/// E() : B() {}
/// };
/// \endcode
/// cxxConstructorDecl(hasAnyConstructorInitializer(isBaseInitializer()))
/// will match E(), but not match D(int).
AST_MATCHER(CXXCtorInitializer, isBaseInitializer) {
return Node.isBaseInitializer();
}
/// Matches a constructor initializer if it is initializing a member, as
/// opposed to a base.
///
/// Given
/// \code
/// struct B {};
/// struct D : B {
/// int I;
/// D(int i) : I(i) {}
/// };
/// struct E : B {
/// E() : B() {}
/// };
/// \endcode
/// cxxConstructorDecl(hasAnyConstructorInitializer(isMemberInitializer()))
/// will match D(int), but not match E().
AST_MATCHER(CXXCtorInitializer, isMemberInitializer) {
return Node.isMemberInitializer();
}
/// Matches any argument of a call expression or a constructor call
/// expression, or an ObjC-message-send expression.
///
/// Given
/// \code
/// void x(int, int, int) { int y; x(1, y, 42); }
/// \endcode
/// callExpr(hasAnyArgument(declRefExpr()))
/// matches x(1, y, 42)
/// with hasAnyArgument(...)
/// matching y
///
/// For ObjectiveC, given
/// \code
/// @interface I - (void) f:(int) y; @end
/// void foo(I *i) { [i f:12]; }
/// \endcode
/// objcMessageExpr(hasAnyArgument(integerLiteral(equals(12))))
/// matches [i f:12]
AST_POLYMORPHIC_MATCHER_P(hasAnyArgument,
AST_POLYMORPHIC_SUPPORTED_TYPES(
CallExpr, CXXConstructExpr,
CXXUnresolvedConstructExpr, ObjCMessageExpr),
internal::Matcher<Expr>, InnerMatcher) {
for (const Expr *Arg : Node.arguments()) {
BoundNodesTreeBuilder Result(*Builder);
if (InnerMatcher.matches(*Arg, Finder, &Result)) {
*Builder = std::move(Result);
return true;
}
}
return false;
}
/// Matches any capture of a lambda expression.
///
/// Given
/// \code
/// void foo() {
/// int x;
/// auto f = [x](){};
/// }
/// \endcode
/// lambdaExpr(hasAnyCapture(anything()))
/// matches [x](){};
AST_MATCHER_P_OVERLOAD(LambdaExpr, hasAnyCapture, internal::Matcher<VarDecl>,
InnerMatcher, 0) {
for (const LambdaCapture &Capture : Node.captures()) {
if (Capture.capturesVariable()) {
BoundNodesTreeBuilder Result(*Builder);
if (InnerMatcher.matches(*Capture.getCapturedVar(), Finder, &Result)) {
*Builder = std::move(Result);
return true;
}
}
}
return false;
}
/// Matches any capture of 'this' in a lambda expression.
///
/// Given
/// \code
/// struct foo {
/// void bar() {
/// auto f = [this](){};
/// }
/// }
/// \endcode
/// lambdaExpr(hasAnyCapture(cxxThisExpr()))
/// matches [this](){};
AST_MATCHER_P_OVERLOAD(LambdaExpr, hasAnyCapture,
internal::Matcher<CXXThisExpr>, InnerMatcher, 1) {
return llvm::any_of(Node.captures(), [](const LambdaCapture &LC) {
return LC.capturesThis();
});
}
/// Matches a constructor call expression which uses list initialization.
AST_MATCHER(CXXConstructExpr, isListInitialization) {
return Node.isListInitialization();
}
/// Matches a constructor call expression which requires
/// zero initialization.
///
/// Given
/// \code
/// void foo() {
/// struct point { double x; double y; };
/// point pt[2] = { { 1.0, 2.0 } };
/// }
/// \endcode
/// initListExpr(has(cxxConstructExpr(requiresZeroInitialization()))
/// will match the implicit array filler for pt[1].
AST_MATCHER(CXXConstructExpr, requiresZeroInitialization) {
return Node.requiresZeroInitialization();
}
/// Matches the n'th parameter of a function or an ObjC method
/// declaration or a block.
///
/// Given
/// \code
/// class X { void f(int x) {} };
/// \endcode
/// cxxMethodDecl(hasParameter(0, hasType(varDecl())))
/// matches f(int x) {}
/// with hasParameter(...)
/// matching int x
///
/// For ObjectiveC, given
/// \code
/// @interface I - (void) f:(int) y; @end
/// \endcode
//
/// the matcher objcMethodDecl(hasParameter(0, hasName("y")))
/// matches the declaration of method f with hasParameter
/// matching y.
AST_POLYMORPHIC_MATCHER_P2(hasParameter,
AST_POLYMORPHIC_SUPPORTED_TYPES(FunctionDecl,
ObjCMethodDecl,
BlockDecl),
unsigned, N, internal::Matcher<ParmVarDecl>,
InnerMatcher) {
return (N < Node.parameters().size()
&& InnerMatcher.matches(*Node.parameters()[N], Finder, Builder));
}
/// Matches all arguments and their respective ParmVarDecl.
///
/// Given
/// \code
/// void f(int i);
/// int y;
/// f(y);
/// \endcode
/// callExpr(
/// forEachArgumentWithParam(
/// declRefExpr(to(varDecl(hasName("y")))),
/// parmVarDecl(hasType(isInteger()))
/// ))
/// matches f(y);
/// with declRefExpr(...)
/// matching int y
/// and parmVarDecl(...)
/// matching int i
AST_POLYMORPHIC_MATCHER_P2(forEachArgumentWithParam,
AST_POLYMORPHIC_SUPPORTED_TYPES(CallExpr,
CXXConstructExpr),
internal::Matcher<Expr>, ArgMatcher,
internal::Matcher<ParmVarDecl>, ParamMatcher) {
BoundNodesTreeBuilder Result;
// The first argument of an overloaded member operator is the implicit object
// argument of the method which should not be matched against a parameter, so
// we skip over it here.
BoundNodesTreeBuilder Matches;
unsigned ArgIndex = cxxOperatorCallExpr(callee(cxxMethodDecl()))
.matches(Node, Finder, &Matches)
? 1
: 0;
int ParamIndex = 0;
bool Matched = false;
for (; ArgIndex < Node.getNumArgs(); ++ArgIndex) {
BoundNodesTreeBuilder ArgMatches(*Builder);
if (ArgMatcher.matches(*(Node.getArg(ArgIndex)->IgnoreParenCasts()),
Finder, &ArgMatches)) {
BoundNodesTreeBuilder ParamMatches(ArgMatches);
if (expr(anyOf(cxxConstructExpr(hasDeclaration(cxxConstructorDecl(
hasParameter(ParamIndex, ParamMatcher)))),
callExpr(callee(functionDecl(
hasParameter(ParamIndex, ParamMatcher))))))
.matches(Node, Finder, &ParamMatches)) {
Result.addMatch(ParamMatches);
Matched = true;
}
}
++ParamIndex;
}
*Builder = std::move(Result);
return Matched;
}
/// Matches any parameter of a function or an ObjC method declaration or a
/// block.
///
/// Does not match the 'this' parameter of a method.
///
/// Given
/// \code
/// class X { void f(int x, int y, int z) {} };
/// \endcode
/// cxxMethodDecl(hasAnyParameter(hasName("y")))
/// matches f(int x, int y, int z) {}
/// with hasAnyParameter(...)
/// matching int y
///
/// For ObjectiveC, given
/// \code
/// @interface I - (void) f:(int) y; @end
/// \endcode
//
/// the matcher objcMethodDecl(hasAnyParameter(hasName("y")))
/// matches the declaration of method f with hasParameter
/// matching y.
///
/// For blocks, given
/// \code
/// b = ^(int y) { printf("%d", y) };
/// \endcode
///
/// the matcher blockDecl(hasAnyParameter(hasName("y")))
/// matches the declaration of the block b with hasParameter
/// matching y.
AST_POLYMORPHIC_MATCHER_P(hasAnyParameter,
AST_POLYMORPHIC_SUPPORTED_TYPES(FunctionDecl,
ObjCMethodDecl,
BlockDecl),
internal::Matcher<ParmVarDecl>,
InnerMatcher) {
return matchesFirstInPointerRange(InnerMatcher, Node.param_begin(),
Node.param_end(), Finder, Builder);
}
/// Matches \c FunctionDecls and \c FunctionProtoTypes that have a
/// specific parameter count.
///
/// Given
/// \code
/// void f(int i) {}
/// void g(int i, int j) {}
/// void h(int i, int j);
/// void j(int i);
/// void k(int x, int y, int z, ...);
/// \endcode
/// functionDecl(parameterCountIs(2))
/// matches \c g and \c h
/// functionProtoType(parameterCountIs(2))
/// matches \c g and \c h
/// functionProtoType(parameterCountIs(3))
/// matches \c k
AST_POLYMORPHIC_MATCHER_P(parameterCountIs,
AST_POLYMORPHIC_SUPPORTED_TYPES(FunctionDecl,
FunctionProtoType),
unsigned, N) {
return Node.getNumParams() == N;
}
/// Matches \c FunctionDecls that have a noreturn attribute.
///
/// Given
/// \code
/// void nope();
/// [[noreturn]] void a();
/// __attribute__((noreturn)) void b();
/// struct c { [[noreturn]] c(); };
/// \endcode
/// functionDecl(isNoReturn())
/// matches all of those except
/// \code
/// void nope();
/// \endcode
AST_MATCHER(FunctionDecl, isNoReturn) { return Node.isNoReturn(); }
/// Matches the return type of a function declaration.
///
/// Given:
/// \code
/// class X { int f() { return 1; } };
/// \endcode
/// cxxMethodDecl(returns(asString("int")))
/// matches int f() { return 1; }
AST_MATCHER_P(FunctionDecl, returns,
internal::Matcher<QualType>, InnerMatcher) {
return InnerMatcher.matches(Node.getReturnType(), Finder, Builder);
}
/// Matches extern "C" function or variable declarations.
///
/// Given:
/// \code
/// extern "C" void f() {}
/// extern "C" { void g() {} }
/// void h() {}
/// extern "C" int x = 1;
/// extern "C" int y = 2;
/// int z = 3;
/// \endcode
/// functionDecl(isExternC())
/// matches the declaration of f and g, but not the declaration of h.
/// varDecl(isExternC())
/// matches the declaration of x and y, but not the declaration of z.
AST_POLYMORPHIC_MATCHER(isExternC, AST_POLYMORPHIC_SUPPORTED_TYPES(FunctionDecl,
VarDecl)) {
return Node.isExternC();
}
/// Matches variable/function declarations that have "static" storage
/// class specifier ("static" keyword) written in the source.
///
/// Given:
/// \code
/// static void f() {}
/// static int i = 0;
/// extern int j;
/// int k;
/// \endcode
/// functionDecl(isStaticStorageClass())
/// matches the function declaration f.
/// varDecl(isStaticStorageClass())
/// matches the variable declaration i.
AST_POLYMORPHIC_MATCHER(isStaticStorageClass,
AST_POLYMORPHIC_SUPPORTED_TYPES(FunctionDecl,
VarDecl)) {
return Node.getStorageClass() == SC_Static;
}
/// Matches deleted function declarations.
///
/// Given:
/// \code
/// void Func();
/// void DeletedFunc() = delete;
/// \endcode
/// functionDecl(isDeleted())
/// matches the declaration of DeletedFunc, but not Func.
AST_MATCHER(FunctionDecl, isDeleted) {
return Node.isDeleted();
}
/// Matches defaulted function declarations.
///
/// Given:
/// \code
/// class A { ~A(); };
/// class B { ~B() = default; };
/// \endcode
/// functionDecl(isDefaulted())
/// matches the declaration of ~B, but not ~A.
AST_MATCHER(FunctionDecl, isDefaulted) {
return Node.isDefaulted();
}
/// Matches functions that have a dynamic exception specification.
///
/// Given:
/// \code
/// void f();
/// void g() noexcept;
/// void h() noexcept(true);
/// void i() noexcept(false);
/// void j() throw();
/// void k() throw(int);
/// void l() throw(...);
/// \endcode
/// functionDecl(hasDynamicExceptionSpec()) and
/// functionProtoType(hasDynamicExceptionSpec())
/// match the declarations of j, k, and l, but not f, g, h, or i.
AST_POLYMORPHIC_MATCHER(hasDynamicExceptionSpec,
AST_POLYMORPHIC_SUPPORTED_TYPES(FunctionDecl,
FunctionProtoType)) {
if (const FunctionProtoType *FnTy = internal::getFunctionProtoType(Node))
return FnTy->hasDynamicExceptionSpec();
return false;
}
/// Matches functions that have a non-throwing exception specification.
///
/// Given:
/// \code
/// void f();
/// void g() noexcept;
/// void h() throw();
/// void i() throw(int);
/// void j() noexcept(false);
/// \endcode
/// functionDecl(isNoThrow()) and functionProtoType(isNoThrow())
/// match the declarations of g, and h, but not f, i or j.
AST_POLYMORPHIC_MATCHER(isNoThrow,
AST_POLYMORPHIC_SUPPORTED_TYPES(FunctionDecl,
FunctionProtoType)) {
const FunctionProtoType *FnTy = internal::getFunctionProtoType(Node);
// If the function does not have a prototype, then it is assumed to be a
// throwing function (as it would if the function did not have any exception
// specification).
if (!FnTy)
return false;
// Assume the best for any unresolved exception specification.
if (isUnresolvedExceptionSpec(FnTy->getExceptionSpecType()))
return true;
return FnTy->isNothrow();
}
/// Matches constexpr variable and function declarations,
/// and if constexpr.
///
/// Given:
/// \code
/// constexpr int foo = 42;
/// constexpr int bar();
/// void baz() { if constexpr(1 > 0) {} }
/// \endcode
/// varDecl(isConstexpr())
/// matches the declaration of foo.
/// functionDecl(isConstexpr())
/// matches the declaration of bar.
/// ifStmt(isConstexpr())
/// matches the if statement in baz.
AST_POLYMORPHIC_MATCHER(isConstexpr,
AST_POLYMORPHIC_SUPPORTED_TYPES(VarDecl,
FunctionDecl,
IfStmt)) {
return Node.isConstexpr();
}
/// Matches selection statements with initializer.
///
/// Given:
/// \code
/// void foo() {
/// if (int i = foobar(); i > 0) {}
/// switch (int i = foobar(); i) {}
/// for (auto& a = get_range(); auto& x : a) {}
/// }
/// void bar() {
/// if (foobar() > 0) {}
/// switch (foobar()) {}
/// for (auto& x : get_range()) {}
/// }
/// \endcode
/// ifStmt(hasInitStatement(anything()))
/// matches the if statement in foo but not in bar.
/// switchStmt(hasInitStatement(anything()))
/// matches the switch statement in foo but not in bar.
/// cxxForRangeStmt(hasInitStatement(anything()))
/// matches the range for statement in foo but not in bar.
AST_POLYMORPHIC_MATCHER_P(hasInitStatement,
AST_POLYMORPHIC_SUPPORTED_TYPES(IfStmt, SwitchStmt,
CXXForRangeStmt),
internal::Matcher<Stmt>, InnerMatcher) {
const Stmt *Init = Node.getInit();
return Init != nullptr && InnerMatcher.matches(*Init, Finder, Builder);
}
/// Matches the condition expression of an if statement, for loop,
/// switch statement or conditional operator.
///
/// Example matches true (matcher = hasCondition(cxxBoolLiteral(equals(true))))
/// \code
/// if (true) {}
/// \endcode
AST_POLYMORPHIC_MATCHER_P(
hasCondition,
AST_POLYMORPHIC_SUPPORTED_TYPES(IfStmt, ForStmt, WhileStmt, DoStmt,
SwitchStmt, AbstractConditionalOperator),
internal::Matcher<Expr>, InnerMatcher) {
const Expr *const Condition = Node.getCond();
return (Condition != nullptr &&
InnerMatcher.matches(*Condition, Finder, Builder));
}
/// Matches the then-statement of an if statement.
///
/// Examples matches the if statement
/// (matcher = ifStmt(hasThen(cxxBoolLiteral(equals(true)))))
/// \code
/// if (false) true; else false;
/// \endcode
AST_MATCHER_P(IfStmt, hasThen, internal::Matcher<Stmt>, InnerMatcher) {
const Stmt *const Then = Node.getThen();
return (Then != nullptr && InnerMatcher.matches(*Then, Finder, Builder));
}
/// Matches the else-statement of an if statement.
///
/// Examples matches the if statement
/// (matcher = ifStmt(hasElse(cxxBoolLiteral(equals(true)))))
/// \code
/// if (false) false; else true;
/// \endcode
AST_MATCHER_P(IfStmt, hasElse, internal::Matcher<Stmt>, InnerMatcher) {
const Stmt *const Else = Node.getElse();
return (Else != nullptr && InnerMatcher.matches(*Else, Finder, Builder));
}
/// Matches if a node equals a previously bound node.
///
/// Matches a node if it equals the node previously bound to \p ID.
///
/// Given
/// \code
/// class X { int a; int b; };
/// \endcode
/// cxxRecordDecl(
/// has(fieldDecl(hasName("a"), hasType(type().bind("t")))),
/// has(fieldDecl(hasName("b"), hasType(type(equalsBoundNode("t"))))))
/// matches the class \c X, as \c a and \c b have the same type.
///
/// Note that when multiple matches are involved via \c forEach* matchers,
/// \c equalsBoundNodes acts as a filter.
/// For example:
/// compoundStmt(
/// forEachDescendant(varDecl().bind("d")),
/// forEachDescendant(declRefExpr(to(decl(equalsBoundNode("d"))))))
/// will trigger a match for each combination of variable declaration
/// and reference to that variable declaration within a compound statement.
AST_POLYMORPHIC_MATCHER_P(equalsBoundNode,
AST_POLYMORPHIC_SUPPORTED_TYPES(Stmt, Decl, Type,
QualType),
std::string, ID) {
// FIXME: Figure out whether it makes sense to allow this
// on any other node types.
// For *Loc it probably does not make sense, as those seem
// unique. For NestedNameSepcifier it might make sense, as
// those also have pointer identity, but I'm not sure whether
// they're ever reused.
internal::NotEqualsBoundNodePredicate Predicate;
Predicate.ID = ID;
Predicate.Node = ast_type_traits::DynTypedNode::create(Node);
return Builder->removeBindings(Predicate);
}
/// Matches the condition variable statement in an if statement.
///
/// Given
/// \code
/// if (A* a = GetAPointer()) {}
/// \endcode
/// hasConditionVariableStatement(...)
/// matches 'A* a = GetAPointer()'.
AST_MATCHER_P(IfStmt, hasConditionVariableStatement,
internal::Matcher<DeclStmt>, InnerMatcher) {
const DeclStmt* const DeclarationStatement =
Node.getConditionVariableDeclStmt();
return DeclarationStatement != nullptr &&
InnerMatcher.matches(*DeclarationStatement, Finder, Builder);
}
/// Matches the index expression of an array subscript expression.
///
/// Given
/// \code
/// int i[5];
/// void f() { i[1] = 42; }
/// \endcode
/// arraySubscriptExpression(hasIndex(integerLiteral()))
/// matches \c i[1] with the \c integerLiteral() matching \c 1
AST_MATCHER_P(ArraySubscriptExpr, hasIndex,
internal::Matcher<Expr>, InnerMatcher) {
if (const Expr* Expression = Node.getIdx())
return InnerMatcher.matches(*Expression, Finder, Builder);
return false;
}
/// Matches the base expression of an array subscript expression.
///
/// Given
/// \code
/// int i[5];
/// void f() { i[1] = 42; }
/// \endcode
/// arraySubscriptExpression(hasBase(implicitCastExpr(
/// hasSourceExpression(declRefExpr()))))
/// matches \c i[1] with the \c declRefExpr() matching \c i
AST_MATCHER_P(ArraySubscriptExpr, hasBase,
internal::Matcher<Expr>, InnerMatcher) {
if (const Expr* Expression = Node.getBase())
return InnerMatcher.matches(*Expression, Finder, Builder);
return false;
}
/// Matches a 'for', 'while', 'do while' statement or a function
/// definition that has a given body.
///
/// Given
/// \code
/// for (;;) {}
/// \endcode
/// hasBody(compoundStmt())
/// matches 'for (;;) {}'
/// with compoundStmt()
/// matching '{}'
AST_POLYMORPHIC_MATCHER_P(hasBody,
AST_POLYMORPHIC_SUPPORTED_TYPES(DoStmt, ForStmt,
WhileStmt,
CXXForRangeStmt,
FunctionDecl),
internal::Matcher<Stmt>, InnerMatcher) {
const Stmt *const Statement = internal::GetBodyMatcher<NodeType>::get(Node);
return (Statement != nullptr &&
InnerMatcher.matches(*Statement, Finder, Builder));
}
/// Matches compound statements where at least one substatement matches
/// a given matcher. Also matches StmtExprs that have CompoundStmt as children.
///
/// Given
/// \code
/// { {}; 1+2; }
/// \endcode
/// hasAnySubstatement(compoundStmt())
/// matches '{ {}; 1+2; }'
/// with compoundStmt()
/// matching '{}'
AST_POLYMORPHIC_MATCHER_P(hasAnySubstatement,
AST_POLYMORPHIC_SUPPORTED_TYPES(CompoundStmt,
StmtExpr),
internal::Matcher<Stmt>, InnerMatcher) {
const CompoundStmt *CS = CompoundStmtMatcher<NodeType>::get(Node);
return CS && matchesFirstInPointerRange(InnerMatcher, CS->body_begin(),
CS->body_end(), Finder, Builder);
}
/// Checks that a compound statement contains a specific number of
/// child statements.
///
/// Example: Given
/// \code
/// { for (;;) {} }
/// \endcode
/// compoundStmt(statementCountIs(0)))
/// matches '{}'
/// but does not match the outer compound statement.
AST_MATCHER_P(CompoundStmt, statementCountIs, unsigned, N) {
return Node.size() == N;
}
/// Matches literals that are equal to the given value of type ValueT.
///
/// Given
/// \code
/// f('\0', false, 3.14, 42);
/// \endcode
/// characterLiteral(equals(0))
/// matches '\0'
/// cxxBoolLiteral(equals(false)) and cxxBoolLiteral(equals(0))
/// match false
/// floatLiteral(equals(3.14)) and floatLiteral(equals(314e-2))
/// match 3.14
/// integerLiteral(equals(42))
/// matches 42
///
/// Note that you cannot directly match a negative numeric literal because the
/// minus sign is not part of the literal: It is a unary operator whose operand
/// is the positive numeric literal. Instead, you must use a unaryOperator()
/// matcher to match the minus sign:
///
/// unaryOperator(hasOperatorName("-"),
/// hasUnaryOperand(integerLiteral(equals(13))))
///
/// Usable as: Matcher<CharacterLiteral>, Matcher<CXXBoolLiteralExpr>,
/// Matcher<FloatingLiteral>, Matcher<IntegerLiteral>
template <typename ValueT>
internal::PolymorphicMatcherWithParam1<internal::ValueEqualsMatcher, ValueT>
equals(const ValueT &Value) {
return internal::PolymorphicMatcherWithParam1<
internal::ValueEqualsMatcher,
ValueT>(Value);
}
AST_POLYMORPHIC_MATCHER_P_OVERLOAD(equals,
AST_POLYMORPHIC_SUPPORTED_TYPES(CharacterLiteral,
CXXBoolLiteralExpr,
IntegerLiteral),
bool, Value, 0) {
return internal::ValueEqualsMatcher<NodeType, ParamT>(Value)
.matchesNode(Node);
}
AST_POLYMORPHIC_MATCHER_P_OVERLOAD(equals,
AST_POLYMORPHIC_SUPPORTED_TYPES(CharacterLiteral,
CXXBoolLiteralExpr,
IntegerLiteral),
unsigned, Value, 1) {
return internal::ValueEqualsMatcher<NodeType, ParamT>(Value)
.matchesNode(Node);
}
AST_POLYMORPHIC_MATCHER_P_OVERLOAD(equals,
AST_POLYMORPHIC_SUPPORTED_TYPES(CharacterLiteral,
CXXBoolLiteralExpr,
FloatingLiteral,
IntegerLiteral),
double, Value, 2) {
return internal::ValueEqualsMatcher<NodeType, ParamT>(Value)
.matchesNode(Node);
}
/// Matches the operator Name of operator expressions (binary or
/// unary).
///
/// Example matches a || b (matcher = binaryOperator(hasOperatorName("||")))
/// \code
/// !(a || b)
/// \endcode
AST_POLYMORPHIC_MATCHER_P(hasOperatorName,
AST_POLYMORPHIC_SUPPORTED_TYPES(BinaryOperator,
UnaryOperator),
std::string, Name) {
return Name == Node.getOpcodeStr(Node.getOpcode());
}
/// Matches all kinds of assignment operators.
///
/// Example 1: matches a += b (matcher = binaryOperator(isAssignmentOperator()))
/// \code
/// if (a == b)
/// a += b;
/// \endcode
///
/// Example 2: matches s1 = s2
/// (matcher = cxxOperatorCallExpr(isAssignmentOperator()))
/// \code
/// struct S { S& operator=(const S&); };
/// void x() { S s1, s2; s1 = s2; })
/// \endcode
AST_POLYMORPHIC_MATCHER(isAssignmentOperator,
AST_POLYMORPHIC_SUPPORTED_TYPES(BinaryOperator,
CXXOperatorCallExpr)) {
return Node.isAssignmentOp();
}
/// Matches the left hand side of binary operator expressions.
///
/// Example matches a (matcher = binaryOperator(hasLHS()))
/// \code
/// a || b
/// \endcode
AST_POLYMORPHIC_MATCHER_P(hasLHS,
AST_POLYMORPHIC_SUPPORTED_TYPES(BinaryOperator,
ArraySubscriptExpr),
internal::Matcher<Expr>, InnerMatcher) {
const Expr *LeftHandSide = Node.getLHS();
return (LeftHandSide != nullptr &&
InnerMatcher.matches(*LeftHandSide, Finder, Builder));
}
/// Matches the right hand side of binary operator expressions.
///
/// Example matches b (matcher = binaryOperator(hasRHS()))
/// \code
/// a || b
/// \endcode
AST_POLYMORPHIC_MATCHER_P(hasRHS,
AST_POLYMORPHIC_SUPPORTED_TYPES(BinaryOperator,
ArraySubscriptExpr),
internal::Matcher<Expr>, InnerMatcher) {
const Expr *RightHandSide = Node.getRHS();
return (RightHandSide != nullptr &&
InnerMatcher.matches(*RightHandSide, Finder, Builder));
}
/// Matches if either the left hand side or the right hand side of a
/// binary operator matches.
inline internal::Matcher<BinaryOperator> hasEitherOperand(
const internal::Matcher<Expr> &InnerMatcher) {
return anyOf(hasLHS(InnerMatcher), hasRHS(InnerMatcher));
}
/// Matches if the operand of a unary operator matches.
///
/// Example matches true (matcher = hasUnaryOperand(
/// cxxBoolLiteral(equals(true))))
/// \code
/// !true
/// \endcode
AST_MATCHER_P(UnaryOperator, hasUnaryOperand,
internal::Matcher<Expr>, InnerMatcher) {
const Expr * const Operand = Node.getSubExpr();
return (Operand != nullptr &&
InnerMatcher.matches(*Operand, Finder, Builder));
}
/// Matches if the cast's source expression
/// or opaque value's source expression matches the given matcher.
///
/// Example 1: matches "a string"
/// (matcher = castExpr(hasSourceExpression(cxxConstructExpr())))
/// \code
/// class URL { URL(string); };
/// URL url = "a string";
/// \endcode
///
/// Example 2: matches 'b' (matcher =
/// opaqueValueExpr(hasSourceExpression(implicitCastExpr(declRefExpr())))
/// \code
/// int a = b ?: 1;
/// \endcode
AST_POLYMORPHIC_MATCHER_P(hasSourceExpression,
AST_POLYMORPHIC_SUPPORTED_TYPES(CastExpr,
OpaqueValueExpr),
internal::Matcher<Expr>, InnerMatcher) {
const Expr *const SubExpression =
internal::GetSourceExpressionMatcher<NodeType>::get(Node);
return (SubExpression != nullptr &&
InnerMatcher.matches(*SubExpression, Finder, Builder));
}
/// Matches casts that has a given cast kind.
///
/// Example: matches the implicit cast around \c 0
/// (matcher = castExpr(hasCastKind(CK_NullToPointer)))
/// \code
/// int *p = 0;
/// \endcode
///
/// If the matcher is use from clang-query, CastKind parameter
/// should be passed as a quoted string. e.g., ofKind("CK_NullToPointer").
AST_MATCHER_P(CastExpr, hasCastKind, CastKind, Kind) {
return Node.getCastKind() == Kind;
}
/// Matches casts whose destination type matches a given matcher.
///
/// (Note: Clang's AST refers to other conversions as "casts" too, and calls
/// actual casts "explicit" casts.)
AST_MATCHER_P(ExplicitCastExpr, hasDestinationType,
internal::Matcher<QualType>, InnerMatcher) {
const QualType NodeType = Node.getTypeAsWritten();
return InnerMatcher.matches(NodeType, Finder, Builder);
}
/// Matches implicit casts whose destination type matches a given
/// matcher.
///
/// FIXME: Unit test this matcher
AST_MATCHER_P(ImplicitCastExpr, hasImplicitDestinationType,
internal::Matcher<QualType>, InnerMatcher) {
return InnerMatcher.matches(Node.getType(), Finder, Builder);
}
/// Matches RecordDecl object that are spelled with "struct."
///
/// Example matches S, but not C or U.
/// \code
/// struct S {};
/// class C {};
/// union U {};
/// \endcode
AST_MATCHER(RecordDecl, isStruct) {
return Node.isStruct();
}
/// Matches RecordDecl object that are spelled with "union."
///
/// Example matches U, but not C or S.
/// \code
/// struct S {};
/// class C {};
/// union U {};
/// \endcode
AST_MATCHER(RecordDecl, isUnion) {
return Node.isUnion();
}
/// Matches RecordDecl object that are spelled with "class."
///
/// Example matches C, but not S or U.
/// \code
/// struct S {};
/// class C {};
/// union U {};
/// \endcode
AST_MATCHER(RecordDecl, isClass) {
return Node.isClass();
}
/// Matches the true branch expression of a conditional operator.
///
/// Example 1 (conditional ternary operator): matches a
/// \code
/// condition ? a : b
/// \endcode
///
/// Example 2 (conditional binary operator): matches opaqueValueExpr(condition)
/// \code
/// condition ?: b
/// \endcode
AST_MATCHER_P(AbstractConditionalOperator, hasTrueExpression,
internal::Matcher<Expr>, InnerMatcher) {
const Expr *Expression = Node.getTrueExpr();
return (Expression != nullptr &&
InnerMatcher.matches(*Expression, Finder, Builder));
}
/// Matches the false branch expression of a conditional operator
/// (binary or ternary).
///
/// Example matches b
/// \code
/// condition ? a : b
/// condition ?: b
/// \endcode
AST_MATCHER_P(AbstractConditionalOperator, hasFalseExpression,
internal::Matcher<Expr>, InnerMatcher) {
const Expr *Expression = Node.getFalseExpr();
return (Expression != nullptr &&
InnerMatcher.matches(*Expression, Finder, Builder));
}
/// Matches if a declaration has a body attached.
///
/// Example matches A, va, fa
/// \code
/// class A {};
/// class B; // Doesn't match, as it has no body.
/// int va;
/// extern int vb; // Doesn't match, as it doesn't define the variable.
/// void fa() {}
/// void fb(); // Doesn't match, as it has no body.
/// @interface X
/// - (void)ma; // Doesn't match, interface is declaration.
/// @end
/// @implementation X
/// - (void)ma {}
/// @end
/// \endcode
///
/// Usable as: Matcher<TagDecl>, Matcher<VarDecl>, Matcher<FunctionDecl>,
/// Matcher<ObjCMethodDecl>
AST_POLYMORPHIC_MATCHER(isDefinition,
AST_POLYMORPHIC_SUPPORTED_TYPES(TagDecl, VarDecl,
ObjCMethodDecl,
FunctionDecl)) {
return Node.isThisDeclarationADefinition();
}
/// Matches if a function declaration is variadic.
///
/// Example matches f, but not g or h. The function i will not match, even when
/// compiled in C mode.
/// \code
/// void f(...);
/// void g(int);
/// template <typename... Ts> void h(Ts...);
/// void i();
/// \endcode
AST_MATCHER(FunctionDecl, isVariadic) {
return Node.isVariadic();
}
/// Matches the class declaration that the given method declaration
/// belongs to.
///
/// FIXME: Generalize this for other kinds of declarations.
/// FIXME: What other kind of declarations would we need to generalize
/// this to?
///
/// Example matches A() in the last line
/// (matcher = cxxConstructExpr(hasDeclaration(cxxMethodDecl(
/// ofClass(hasName("A"))))))
/// \code
/// class A {
/// public:
/// A();
/// };
/// A a = A();
/// \endcode
AST_MATCHER_P(CXXMethodDecl, ofClass,
internal::Matcher<CXXRecordDecl>, InnerMatcher) {
const CXXRecordDecl *Parent = Node.getParent();
return (Parent != nullptr &&
InnerMatcher.matches(*Parent, Finder, Builder));
}
/// Matches each method overridden by the given method. This matcher may
/// produce multiple matches.
///
/// Given
/// \code
/// class A { virtual void f(); };
/// class B : public A { void f(); };
/// class C : public B { void f(); };
/// \endcode
/// cxxMethodDecl(ofClass(hasName("C")),
/// forEachOverridden(cxxMethodDecl().bind("b"))).bind("d")
/// matches once, with "b" binding "A::f" and "d" binding "C::f" (Note
/// that B::f is not overridden by C::f).
///
/// The check can produce multiple matches in case of multiple inheritance, e.g.
/// \code
/// class A1 { virtual void f(); };
/// class A2 { virtual void f(); };
/// class C : public A1, public A2 { void f(); };
/// \endcode
/// cxxMethodDecl(ofClass(hasName("C")),
/// forEachOverridden(cxxMethodDecl().bind("b"))).bind("d")
/// matches twice, once with "b" binding "A1::f" and "d" binding "C::f", and
/// once with "b" binding "A2::f" and "d" binding "C::f".
AST_MATCHER_P(CXXMethodDecl, forEachOverridden,
internal::Matcher<CXXMethodDecl>, InnerMatcher) {
BoundNodesTreeBuilder Result;
bool Matched = false;
for (const auto *Overridden : Node.overridden_methods()) {
BoundNodesTreeBuilder OverriddenBuilder(*Builder);
const bool OverriddenMatched =
InnerMatcher.matches(*Overridden, Finder, &OverriddenBuilder);
if (OverriddenMatched) {
Matched = true;
Result.addMatch(OverriddenBuilder);
}
}
*Builder = std::move(Result);
return Matched;
}
/// Matches if the given method declaration is virtual.
///
/// Given
/// \code
/// class A {
/// public:
/// virtual void x();
/// };
/// \endcode
/// matches A::x
AST_MATCHER(CXXMethodDecl, isVirtual) {
return Node.isVirtual();
}
/// Matches if the given method declaration has an explicit "virtual".
///
/// Given
/// \code
/// class A {
/// public:
/// virtual void x();
/// };
/// class B : public A {
/// public:
/// void x();
/// };
/// \endcode
/// matches A::x but not B::x
AST_MATCHER(CXXMethodDecl, isVirtualAsWritten) {
return Node.isVirtualAsWritten();
}
/// Matches if the given method or class declaration is final.
///
/// Given:
/// \code
/// class A final {};
///
/// struct B {
/// virtual void f();
/// };
///
/// struct C : B {
/// void f() final;
/// };
/// \endcode
/// matches A and C::f, but not B, C, or B::f
AST_POLYMORPHIC_MATCHER(isFinal,
AST_POLYMORPHIC_SUPPORTED_TYPES(CXXRecordDecl,
CXXMethodDecl)) {
return Node.template hasAttr<FinalAttr>();
}
/// Matches if the given method declaration is pure.
///
/// Given
/// \code
/// class A {
/// public:
/// virtual void x() = 0;
/// };
/// \endcode
/// matches A::x
AST_MATCHER(CXXMethodDecl, isPure) {
return Node.isPure();
}
/// Matches if the given method declaration is const.
///
/// Given
/// \code
/// struct A {
/// void foo() const;
/// void bar();
/// };
/// \endcode
///
/// cxxMethodDecl(isConst()) matches A::foo() but not A::bar()
AST_MATCHER(CXXMethodDecl, isConst) {
return Node.isConst();
}
/// Matches if the given method declaration declares a copy assignment
/// operator.
///
/// Given
/// \code
/// struct A {
/// A &operator=(const A &);
/// A &operator=(A &&);
/// };
/// \endcode
///
/// cxxMethodDecl(isCopyAssignmentOperator()) matches the first method but not
/// the second one.
AST_MATCHER(CXXMethodDecl, isCopyAssignmentOperator) {
return Node.isCopyAssignmentOperator();
}
/// Matches if the given method declaration declares a move assignment
/// operator.
///
/// Given
/// \code
/// struct A {
/// A &operator=(const A &);
/// A &operator=(A &&);
/// };
/// \endcode
///
/// cxxMethodDecl(isMoveAssignmentOperator()) matches the second method but not
/// the first one.
AST_MATCHER(CXXMethodDecl, isMoveAssignmentOperator) {
return Node.isMoveAssignmentOperator();
}
/// Matches if the given method declaration overrides another method.
///
/// Given
/// \code
/// class A {
/// public:
/// virtual void x();
/// };
/// class B : public A {
/// public:
/// virtual void x();
/// };
/// \endcode
/// matches B::x
AST_MATCHER(CXXMethodDecl, isOverride) {
return Node.size_overridden_methods() > 0 || Node.hasAttr<OverrideAttr>();
}
/// Matches method declarations that are user-provided.
///
/// Given
/// \code
/// struct S {
/// S(); // #1
/// S(const S &) = default; // #2
/// S(S &&) = delete; // #3
/// };
/// \endcode
/// cxxConstructorDecl(isUserProvided()) will match #1, but not #2 or #3.
AST_MATCHER(CXXMethodDecl, isUserProvided) {
return Node.isUserProvided();
}
/// Matches member expressions that are called with '->' as opposed
/// to '.'.
///
/// Member calls on the implicit this pointer match as called with '->'.
///
/// Given
/// \code
/// class Y {
/// void x() { this->x(); x(); Y y; y.x(); a; this->b; Y::b; }
/// template <class T> void f() { this->f<T>(); f<T>(); }
/// int a;
/// static int b;
/// };
/// template <class T>
/// class Z {
/// void x() { this->m; }
/// };
/// \endcode
/// memberExpr(isArrow())
/// matches this->x, x, y.x, a, this->b
/// cxxDependentScopeMemberExpr(isArrow())
/// matches this->m
/// unresolvedMemberExpr(isArrow())
/// matches this->f<T>, f<T>
AST_POLYMORPHIC_MATCHER(
isArrow, AST_POLYMORPHIC_SUPPORTED_TYPES(MemberExpr, UnresolvedMemberExpr,
CXXDependentScopeMemberExpr)) {
return Node.isArrow();
}
/// Matches QualType nodes that are of integer type.
///
/// Given
/// \code
/// void a(int);
/// void b(long);
/// void c(double);
/// \endcode
/// functionDecl(hasAnyParameter(hasType(isInteger())))
/// matches "a(int)", "b(long)", but not "c(double)".
AST_MATCHER(QualType, isInteger) {
return Node->isIntegerType();
}
/// Matches QualType nodes that are of unsigned integer type.
///
/// Given
/// \code
/// void a(int);
/// void b(unsigned long);
/// void c(double);
/// \endcode
/// functionDecl(hasAnyParameter(hasType(isUnsignedInteger())))
/// matches "b(unsigned long)", but not "a(int)" and "c(double)".
AST_MATCHER(QualType, isUnsignedInteger) {
return Node->isUnsignedIntegerType();
}
/// Matches QualType nodes that are of signed integer type.
///
/// Given
/// \code
/// void a(int);
/// void b(unsigned long);
/// void c(double);
/// \endcode
/// functionDecl(hasAnyParameter(hasType(isSignedInteger())))
/// matches "a(int)", but not "b(unsigned long)" and "c(double)".
AST_MATCHER(QualType, isSignedInteger) {
return Node->isSignedIntegerType();
}
/// Matches QualType nodes that are of character type.
///
/// Given
/// \code
/// void a(char);
/// void b(wchar_t);
/// void c(double);
/// \endcode
/// functionDecl(hasAnyParameter(hasType(isAnyCharacter())))
/// matches "a(char)", "b(wchar_t)", but not "c(double)".
AST_MATCHER(QualType, isAnyCharacter) {
return Node->isAnyCharacterType();
}
/// Matches QualType nodes that are of any pointer type; this includes
/// the Objective-C object pointer type, which is different despite being
/// syntactically similar.
///
/// Given
/// \code
/// int *i = nullptr;
///
/// @interface Foo
/// @end
/// Foo *f;
///
/// int j;
/// \endcode
/// varDecl(hasType(isAnyPointer()))
/// matches "int *i" and "Foo *f", but not "int j".
AST_MATCHER(QualType, isAnyPointer) {
return Node->isAnyPointerType();
}
/// Matches QualType nodes that are const-qualified, i.e., that
/// include "top-level" const.
///
/// Given
/// \code
/// void a(int);
/// void b(int const);
/// void c(const int);
/// void d(const int*);
/// void e(int const) {};
/// \endcode
/// functionDecl(hasAnyParameter(hasType(isConstQualified())))
/// matches "void b(int const)", "void c(const int)" and
/// "void e(int const) {}". It does not match d as there
/// is no top-level const on the parameter type "const int *".
AST_MATCHER(QualType, isConstQualified) {
return Node.isConstQualified();
}
/// Matches QualType nodes that are volatile-qualified, i.e., that
/// include "top-level" volatile.
///
/// Given
/// \code
/// void a(int);
/// void b(int volatile);
/// void c(volatile int);
/// void d(volatile int*);
/// void e(int volatile) {};
/// \endcode
/// functionDecl(hasAnyParameter(hasType(isVolatileQualified())))
/// matches "void b(int volatile)", "void c(volatile int)" and
/// "void e(int volatile) {}". It does not match d as there
/// is no top-level volatile on the parameter type "volatile int *".
AST_MATCHER(QualType, isVolatileQualified) {
return Node.isVolatileQualified();
}
/// Matches QualType nodes that have local CV-qualifiers attached to
/// the node, not hidden within a typedef.
///
/// Given
/// \code
/// typedef const int const_int;
/// const_int i;
/// int *const j;
/// int *volatile k;
/// int m;
/// \endcode
/// \c varDecl(hasType(hasLocalQualifiers())) matches only \c j and \c k.
/// \c i is const-qualified but the qualifier is not local.
AST_MATCHER(QualType, hasLocalQualifiers) {
return Node.hasLocalQualifiers();
}
/// Matches a member expression where the member is matched by a
/// given matcher.
///
/// Given
/// \code
/// struct { int first, second; } first, second;
/// int i(second.first);
/// int j(first.second);
/// \endcode
/// memberExpr(member(hasName("first")))
/// matches second.first
/// but not first.second (because the member name there is "second").
AST_MATCHER_P(MemberExpr, member,
internal::Matcher<ValueDecl>, InnerMatcher) {
return InnerMatcher.matches(*Node.getMemberDecl(), Finder, Builder);
}
/// Matches a member expression where the object expression is matched by a
/// given matcher. Implicit object expressions are included; that is, it matches
/// use of implicit `this`.
///
/// Given
/// \code
/// struct X {
/// int m;
/// int f(X x) { x.m; return m; }
/// };
/// \endcode
/// memberExpr(hasObjectExpression(hasType(cxxRecordDecl(hasName("X")))))
/// matches `x.m`, but not `m`; however,
/// memberExpr(hasObjectExpression(hasType(pointsTo(
// cxxRecordDecl(hasName("X"))))))
/// matches `m` (aka. `this->m`), but not `x.m`.
AST_POLYMORPHIC_MATCHER_P(
hasObjectExpression,
AST_POLYMORPHIC_SUPPORTED_TYPES(MemberExpr, UnresolvedMemberExpr,
CXXDependentScopeMemberExpr),
internal::Matcher<Expr>, InnerMatcher) {
if (const auto *E = dyn_cast<UnresolvedMemberExpr>(&Node))
if (E->isImplicitAccess())
return false;
if (const auto *E = dyn_cast<CXXDependentScopeMemberExpr>(&Node))
if (E->isImplicitAccess())
return false;
return InnerMatcher.matches(*Node.getBase(), Finder, Builder);
}
/// Matches any using shadow declaration.
///
/// Given
/// \code
/// namespace X { void b(); }
/// using X::b;
/// \endcode
/// usingDecl(hasAnyUsingShadowDecl(hasName("b"))))
/// matches \code using X::b \endcode
AST_MATCHER_P(UsingDecl, hasAnyUsingShadowDecl,
internal::Matcher<UsingShadowDecl>, InnerMatcher) {
return matchesFirstInPointerRange(InnerMatcher, Node.shadow_begin(),
Node.shadow_end(), Finder, Builder);
}
/// Matches a using shadow declaration where the target declaration is
/// matched by the given matcher.
///
/// Given
/// \code
/// namespace X { int a; void b(); }
/// using X::a;
/// using X::b;
/// \endcode
/// usingDecl(hasAnyUsingShadowDecl(hasTargetDecl(functionDecl())))
/// matches \code using X::b \endcode
/// but not \code using X::a \endcode
AST_MATCHER_P(UsingShadowDecl, hasTargetDecl,
internal::Matcher<NamedDecl>, InnerMatcher) {
return InnerMatcher.matches(*Node.getTargetDecl(), Finder, Builder);
}
/// Matches template instantiations of function, class, or static
/// member variable template instantiations.
///
/// Given
/// \code
/// template <typename T> class X {}; class A {}; X<A> x;
/// \endcode
/// or
/// \code
/// template <typename T> class X {}; class A {}; template class X<A>;
/// \endcode
/// or
/// \code
/// template <typename T> class X {}; class A {}; extern template class X<A>;
/// \endcode
/// cxxRecordDecl(hasName("::X"), isTemplateInstantiation())
/// matches the template instantiation of X<A>.
///
/// But given
/// \code
/// template <typename T> class X {}; class A {};
/// template <> class X<A> {}; X<A> x;
/// \endcode
/// cxxRecordDecl(hasName("::X"), isTemplateInstantiation())
/// does not match, as X<A> is an explicit template specialization.
///
/// Usable as: Matcher<FunctionDecl>, Matcher<VarDecl>, Matcher<CXXRecordDecl>
AST_POLYMORPHIC_MATCHER(isTemplateInstantiation,
AST_POLYMORPHIC_SUPPORTED_TYPES(FunctionDecl, VarDecl,
CXXRecordDecl)) {
return (Node.getTemplateSpecializationKind() == TSK_ImplicitInstantiation ||
Node.getTemplateSpecializationKind() ==
TSK_ExplicitInstantiationDefinition ||
Node.getTemplateSpecializationKind() ==
TSK_ExplicitInstantiationDeclaration);
}
/// Matches declarations that are template instantiations or are inside
/// template instantiations.
///
/// Given
/// \code
/// template<typename T> void A(T t) { T i; }
/// A(0);
/// A(0U);
/// \endcode
/// functionDecl(isInstantiated())
/// matches 'A(int) {...};' and 'A(unsigned) {...}'.
AST_MATCHER_FUNCTION(internal::Matcher<Decl>, isInstantiated) {
auto IsInstantiation = decl(anyOf(cxxRecordDecl(isTemplateInstantiation()),
functionDecl(isTemplateInstantiation())));
return decl(anyOf(IsInstantiation, hasAncestor(IsInstantiation)));
}
/// Matches statements inside of a template instantiation.
///
/// Given
/// \code
/// int j;
/// template<typename T> void A(T t) { T i; j += 42;}
/// A(0);
/// A(0U);
/// \endcode
/// declStmt(isInTemplateInstantiation())
/// matches 'int i;' and 'unsigned i'.
/// unless(stmt(isInTemplateInstantiation()))
/// will NOT match j += 42; as it's shared between the template definition and
/// instantiation.
AST_MATCHER_FUNCTION(internal::Matcher<Stmt>, isInTemplateInstantiation) {
return stmt(
hasAncestor(decl(anyOf(cxxRecordDecl(isTemplateInstantiation()),
functionDecl(isTemplateInstantiation())))));
}
/// Matches explicit template specializations of function, class, or
/// static member variable template instantiations.
///
/// Given
/// \code
/// template<typename T> void A(T t) { }
/// template<> void A(int N) { }
/// \endcode
/// functionDecl(isExplicitTemplateSpecialization())
/// matches the specialization A<int>().
///
/// Usable as: Matcher<FunctionDecl>, Matcher<VarDecl>, Matcher<CXXRecordDecl>
AST_POLYMORPHIC_MATCHER(isExplicitTemplateSpecialization,
AST_POLYMORPHIC_SUPPORTED_TYPES(FunctionDecl, VarDecl,
CXXRecordDecl)) {
return (Node.getTemplateSpecializationKind() == TSK_ExplicitSpecialization);
}
/// Matches \c TypeLocs for which the given inner
/// QualType-matcher matches.
AST_MATCHER_FUNCTION_P_OVERLOAD(internal::BindableMatcher<TypeLoc>, loc,
internal::Matcher<QualType>, InnerMatcher, 0) {
return internal::BindableMatcher<TypeLoc>(
new internal::TypeLocTypeMatcher(InnerMatcher));
}
/// Matches type \c bool.
///
/// Given
/// \code
/// struct S { bool func(); };
/// \endcode
/// functionDecl(returns(booleanType()))
/// matches "bool func();"
AST_MATCHER(Type, booleanType) {
return Node.isBooleanType();
}
/// Matches type \c void.
///
/// Given
/// \code
/// struct S { void func(); };
/// \endcode
/// functionDecl(returns(voidType()))
/// matches "void func();"
AST_MATCHER(Type, voidType) {
return Node.isVoidType();
}
template <typename NodeType>
using AstTypeMatcher = internal::VariadicDynCastAllOfMatcher<Type, NodeType>;
/// Matches builtin Types.
///
/// Given
/// \code
/// struct A {};
/// A a;
/// int b;
/// float c;
/// bool d;
/// \endcode
/// builtinType()
/// matches "int b", "float c" and "bool d"
extern const AstTypeMatcher<BuiltinType> builtinType;
/// Matches all kinds of arrays.
///
/// Given
/// \code
/// int a[] = { 2, 3 };
/// int b[4];
/// void f() { int c[a[0]]; }
/// \endcode
/// arrayType()
/// matches "int a[]", "int b[4]" and "int c[a[0]]";
extern const AstTypeMatcher<ArrayType> arrayType;
/// Matches C99 complex types.
///
/// Given
/// \code
/// _Complex float f;
/// \endcode
/// complexType()
/// matches "_Complex float f"
extern const AstTypeMatcher<ComplexType> complexType;
/// Matches any real floating-point type (float, double, long double).
///
/// Given
/// \code
/// int i;
/// float f;
/// \endcode
/// realFloatingPointType()
/// matches "float f" but not "int i"
AST_MATCHER(Type, realFloatingPointType) {
return Node.isRealFloatingType();
}
/// Matches arrays and C99 complex types that have a specific element
/// type.
///
/// Given
/// \code
/// struct A {};
/// A a[7];
/// int b[7];
/// \endcode
/// arrayType(hasElementType(builtinType()))
/// matches "int b[7]"
///
/// Usable as: Matcher<ArrayType>, Matcher<ComplexType>
AST_TYPELOC_TRAVERSE_MATCHER_DECL(hasElementType, getElement,
AST_POLYMORPHIC_SUPPORTED_TYPES(ArrayType,
ComplexType));
/// Matches C arrays with a specified constant size.
///
/// Given
/// \code
/// void() {
/// int a[2];
/// int b[] = { 2, 3 };
/// int c[b[0]];
/// }
/// \endcode
/// constantArrayType()
/// matches "int a[2]"
extern const AstTypeMatcher<ConstantArrayType> constantArrayType;
/// Matches nodes that have the specified size.
///
/// Given
/// \code
/// int a[42];
/// int b[2 * 21];
/// int c[41], d[43];
/// char *s = "abcd";
/// wchar_t *ws = L"abcd";
/// char *w = "a";
/// \endcode
/// constantArrayType(hasSize(42))
/// matches "int a[42]" and "int b[2 * 21]"
/// stringLiteral(hasSize(4))
/// matches "abcd", L"abcd"
AST_POLYMORPHIC_MATCHER_P(hasSize,
AST_POLYMORPHIC_SUPPORTED_TYPES(ConstantArrayType,
StringLiteral),
unsigned, N) {
return internal::HasSizeMatcher<NodeType>::hasSize(Node, N);
}
/// Matches C++ arrays whose size is a value-dependent expression.
///
/// Given
/// \code
/// template<typename T, int Size>
/// class array {
/// T data[Size];
/// };
/// \endcode
/// dependentSizedArrayType
/// matches "T data[Size]"
extern const AstTypeMatcher<DependentSizedArrayType> dependentSizedArrayType;
/// Matches C arrays with unspecified size.
///
/// Given
/// \code
/// int a[] = { 2, 3 };
/// int b[42];
/// void f(int c[]) { int d[a[0]]; };
/// \endcode
/// incompleteArrayType()
/// matches "int a[]" and "int c[]"
extern const AstTypeMatcher<IncompleteArrayType> incompleteArrayType;
/// Matches C arrays with a specified size that is not an
/// integer-constant-expression.
///
/// Given
/// \code
/// void f() {
/// int a[] = { 2, 3 }
/// int b[42];
/// int c[a[0]];
/// }
/// \endcode
/// variableArrayType()
/// matches "int c[a[0]]"
extern const AstTypeMatcher<VariableArrayType> variableArrayType;
/// Matches \c VariableArrayType nodes that have a specific size
/// expression.
///
/// Given
/// \code
/// void f(int b) {
/// int a[b];
/// }
/// \endcode
/// variableArrayType(hasSizeExpr(ignoringImpCasts(declRefExpr(to(
/// varDecl(hasName("b")))))))
/// matches "int a[b]"
AST_MATCHER_P(VariableArrayType, hasSizeExpr,
internal::Matcher<Expr>, InnerMatcher) {
return InnerMatcher.matches(*Node.getSizeExpr(), Finder, Builder);
}
/// Matches atomic types.
///
/// Given
/// \code
/// _Atomic(int) i;
/// \endcode
/// atomicType()
/// matches "_Atomic(int) i"
extern const AstTypeMatcher<AtomicType> atomicType;
/// Matches atomic types with a specific value type.
///
/// Given
/// \code
/// _Atomic(int) i;
/// _Atomic(float) f;
/// \endcode
/// atomicType(hasValueType(isInteger()))
/// matches "_Atomic(int) i"
///
/// Usable as: Matcher<AtomicType>
AST_TYPELOC_TRAVERSE_MATCHER_DECL(hasValueType, getValue,
AST_POLYMORPHIC_SUPPORTED_TYPES(AtomicType));
/// Matches types nodes representing C++11 auto types.
///
/// Given:
/// \code
/// auto n = 4;
/// int v[] = { 2, 3 }
/// for (auto i : v) { }
/// \endcode
/// autoType()
/// matches "auto n" and "auto i"
extern const AstTypeMatcher<AutoType> autoType;
/// Matches types nodes representing C++11 decltype(<expr>) types.
///
/// Given:
/// \code
/// short i = 1;
/// int j = 42;
/// decltype(i + j) result = i + j;
/// \endcode
/// decltypeType()
/// matches "decltype(i + j)"
extern const AstTypeMatcher<DecltypeType> decltypeType;
/// Matches \c AutoType nodes where the deduced type is a specific type.
///
/// Note: There is no \c TypeLoc for the deduced type and thus no
/// \c getDeducedLoc() matcher.
///
/// Given
/// \code
/// auto a = 1;
/// auto b = 2.0;
/// \endcode
/// autoType(hasDeducedType(isInteger()))
/// matches "auto a"
///
/// Usable as: Matcher<AutoType>
AST_TYPE_TRAVERSE_MATCHER(hasDeducedType, getDeducedType,
AST_POLYMORPHIC_SUPPORTED_TYPES(AutoType));
/// Matches \c DecltypeType nodes to find out the underlying type.
///
/// Given
/// \code
/// decltype(1) a = 1;
/// decltype(2.0) b = 2.0;
/// \endcode
/// decltypeType(hasUnderlyingType(isInteger()))
/// matches the type of "a"
///
/// Usable as: Matcher<DecltypeType>
AST_TYPE_TRAVERSE_MATCHER(hasUnderlyingType, getUnderlyingType,
AST_POLYMORPHIC_SUPPORTED_TYPES(DecltypeType));
/// Matches \c FunctionType nodes.
///
/// Given
/// \code
/// int (*f)(int);
/// void g();
/// \endcode
/// functionType()
/// matches "int (*f)(int)" and the type of "g".
extern const AstTypeMatcher<FunctionType> functionType;
/// Matches \c FunctionProtoType nodes.
///
/// Given
/// \code
/// int (*f)(int);
/// void g();
/// \endcode
/// functionProtoType()
/// matches "int (*f)(int)" and the type of "g" in C++ mode.
/// In C mode, "g" is not matched because it does not contain a prototype.
extern const AstTypeMatcher<FunctionProtoType> functionProtoType;
/// Matches \c ParenType nodes.
///
/// Given
/// \code
/// int (*ptr_to_array)[4];
/// int *array_of_ptrs[4];
/// \endcode
///
/// \c varDecl(hasType(pointsTo(parenType()))) matches \c ptr_to_array but not
/// \c array_of_ptrs.
extern const AstTypeMatcher<ParenType> parenType;
/// Matches \c ParenType nodes where the inner type is a specific type.
///
/// Given
/// \code
/// int (*ptr_to_array)[4];
/// int (*ptr_to_func)(int);
/// \endcode
///
/// \c varDecl(hasType(pointsTo(parenType(innerType(functionType()))))) matches
/// \c ptr_to_func but not \c ptr_to_array.
///
/// Usable as: Matcher<ParenType>
AST_TYPE_TRAVERSE_MATCHER(innerType, getInnerType,
AST_POLYMORPHIC_SUPPORTED_TYPES(ParenType));
/// Matches block pointer types, i.e. types syntactically represented as
/// "void (^)(int)".
///
/// The \c pointee is always required to be a \c FunctionType.
extern const AstTypeMatcher<BlockPointerType> blockPointerType;
/// Matches member pointer types.
/// Given
/// \code
/// struct A { int i; }
/// A::* ptr = A::i;
/// \endcode
/// memberPointerType()
/// matches "A::* ptr"
extern const AstTypeMatcher<MemberPointerType> memberPointerType;
/// Matches pointer types, but does not match Objective-C object pointer
/// types.
///
/// Given
/// \code
/// int *a;
/// int &b = *a;
/// int c = 5;
///
/// @interface Foo
/// @end
/// Foo *f;
/// \endcode
/// pointerType()
/// matches "int *a", but does not match "Foo *f".
extern const AstTypeMatcher<PointerType> pointerType;
/// Matches an Objective-C object pointer type, which is different from
/// a pointer type, despite being syntactically similar.
///
/// Given
/// \code
/// int *a;
///
/// @interface Foo
/// @end
/// Foo *f;
/// \endcode
/// pointerType()
/// matches "Foo *f", but does not match "int *a".
extern const AstTypeMatcher<ObjCObjectPointerType> objcObjectPointerType;
/// Matches both lvalue and rvalue reference types.
///
/// Given
/// \code
/// int *a;
/// int &b = *a;
/// int &&c = 1;
/// auto &d = b;
/// auto &&e = c;
/// auto &&f = 2;
/// int g = 5;
/// \endcode
///
/// \c referenceType() matches the types of \c b, \c c, \c d, \c e, and \c f.
extern const AstTypeMatcher<ReferenceType> referenceType;
/// Matches lvalue reference types.
///
/// Given:
/// \code
/// int *a;
/// int &b = *a;
/// int &&c = 1;
/// auto &d = b;
/// auto &&e = c;
/// auto &&f = 2;
/// int g = 5;
/// \endcode
///
/// \c lValueReferenceType() matches the types of \c b, \c d, and \c e. \c e is
/// matched since the type is deduced as int& by reference collapsing rules.
extern const AstTypeMatcher<LValueReferenceType> lValueReferenceType;
/// Matches rvalue reference types.
///
/// Given:
/// \code
/// int *a;
/// int &b = *a;
/// int &&c = 1;
/// auto &d = b;
/// auto &&e = c;
/// auto &&f = 2;
/// int g = 5;
/// \endcode
///
/// \c rValueReferenceType() matches the types of \c c and \c f. \c e is not
/// matched as it is deduced to int& by reference collapsing rules.
extern const AstTypeMatcher<RValueReferenceType> rValueReferenceType;
/// Narrows PointerType (and similar) matchers to those where the
/// \c pointee matches a given matcher.
///
/// Given
/// \code
/// int *a;
/// int const *b;
/// float const *f;
/// \endcode
/// pointerType(pointee(isConstQualified(), isInteger()))
/// matches "int const *b"
///
/// Usable as: Matcher<BlockPointerType>, Matcher<MemberPointerType>,
/// Matcher<PointerType>, Matcher<ReferenceType>
AST_TYPELOC_TRAVERSE_MATCHER_DECL(
pointee, getPointee,
AST_POLYMORPHIC_SUPPORTED_TYPES(BlockPointerType, MemberPointerType,
PointerType, ReferenceType));
/// Matches typedef types.
///
/// Given
/// \code
/// typedef int X;
/// \endcode
/// typedefType()
/// matches "typedef int X"
extern const AstTypeMatcher<TypedefType> typedefType;
/// Matches enum types.
///
/// Given
/// \code
/// enum C { Green };
/// enum class S { Red };
///
/// C c;
/// S s;
/// \endcode
//
/// \c enumType() matches the type of the variable declarations of both \c c and
/// \c s.
extern const AstTypeMatcher<EnumType> enumType;
/// Matches template specialization types.
///
/// Given
/// \code
/// template <typename T>
/// class C { };
///
/// template class C<int>; // A
/// C<char> var; // B
/// \endcode
///
/// \c templateSpecializationType() matches the type of the explicit
/// instantiation in \c A and the type of the variable declaration in \c B.
extern const AstTypeMatcher<TemplateSpecializationType>
templateSpecializationType;
/// Matches types nodes representing unary type transformations.
///
/// Given:
/// \code
/// typedef __underlying_type(T) type;
/// \endcode
/// unaryTransformType()
/// matches "__underlying_type(T)"
extern const AstTypeMatcher<UnaryTransformType> unaryTransformType;
/// Matches record types (e.g. structs, classes).
///
/// Given
/// \code
/// class C {};
/// struct S {};
///
/// C c;
/// S s;
/// \endcode
///
/// \c recordType() matches the type of the variable declarations of both \c c
/// and \c s.
extern const AstTypeMatcher<RecordType> recordType;
/// Matches tag types (record and enum types).
///
/// Given
/// \code
/// enum E {};
/// class C {};
///
/// E e;
/// C c;
/// \endcode
///
/// \c tagType() matches the type of the variable declarations of both \c e
/// and \c c.
extern const AstTypeMatcher<TagType> tagType;
/// Matches types specified with an elaborated type keyword or with a
/// qualified name.
///
/// Given
/// \code
/// namespace N {
/// namespace M {
/// class D {};
/// }
/// }
/// class C {};
///
/// class C c;
/// N::M::D d;
/// \endcode
///
/// \c elaboratedType() matches the type of the variable declarations of both
/// \c c and \c d.
extern const AstTypeMatcher<ElaboratedType> elaboratedType;
/// Matches ElaboratedTypes whose qualifier, a NestedNameSpecifier,
/// matches \c InnerMatcher if the qualifier exists.
///
/// Given
/// \code
/// namespace N {
/// namespace M {
/// class D {};
/// }
/// }
/// N::M::D d;
/// \endcode
///
/// \c elaboratedType(hasQualifier(hasPrefix(specifiesNamespace(hasName("N"))))
/// matches the type of the variable declaration of \c d.
AST_MATCHER_P(ElaboratedType, hasQualifier,
internal::Matcher<NestedNameSpecifier>, InnerMatcher) {
if (const NestedNameSpecifier *Qualifier = Node.getQualifier())
return InnerMatcher.matches(*Qualifier, Finder, Builder);
return false;
}
/// Matches ElaboratedTypes whose named type matches \c InnerMatcher.
///
/// Given
/// \code
/// namespace N {
/// namespace M {
/// class D {};
/// }
/// }
/// N::M::D d;
/// \endcode
///
/// \c elaboratedType(namesType(recordType(
/// hasDeclaration(namedDecl(hasName("D")))))) matches the type of the variable
/// declaration of \c d.
AST_MATCHER_P(ElaboratedType, namesType, internal::Matcher<QualType>,
InnerMatcher) {
return InnerMatcher.matches(Node.getNamedType(), Finder, Builder);
}
/// Matches types that represent the result of substituting a type for a
/// template type parameter.
///
/// Given
/// \code
/// template <typename T>
/// void F(T t) {
/// int i = 1 + t;
/// }
/// \endcode
///
/// \c substTemplateTypeParmType() matches the type of 't' but not '1'
extern const AstTypeMatcher<SubstTemplateTypeParmType>
substTemplateTypeParmType;
/// Matches template type parameter substitutions that have a replacement
/// type that matches the provided matcher.
///
/// Given
/// \code
/// template <typename T>
/// double F(T t);
/// int i;
/// double j = F(i);
/// \endcode
///
/// \c substTemplateTypeParmType(hasReplacementType(type())) matches int
AST_TYPE_TRAVERSE_MATCHER(
hasReplacementType, getReplacementType,
AST_POLYMORPHIC_SUPPORTED_TYPES(SubstTemplateTypeParmType));
/// Matches template type parameter types.
///
/// Example matches T, but not int.
/// (matcher = templateTypeParmType())
/// \code
/// template <typename T> void f(int i);
/// \endcode
extern const AstTypeMatcher<TemplateTypeParmType> templateTypeParmType;
/// Matches injected class name types.
///
/// Example matches S s, but not S<T> s.
/// (matcher = parmVarDecl(hasType(injectedClassNameType())))
/// \code
/// template <typename T> struct S {
/// void f(S s);
/// void g(S<T> s);
/// };
/// \endcode
extern const AstTypeMatcher<InjectedClassNameType> injectedClassNameType;
/// Matches decayed type
/// Example matches i[] in declaration of f.
/// (matcher = valueDecl(hasType(decayedType(hasDecayedType(pointerType())))))
/// Example matches i[1].
/// (matcher = expr(hasType(decayedType(hasDecayedType(pointerType())))))
/// \code
/// void f(int i[]) {
/// i[1] = 0;
/// }
/// \endcode
extern const AstTypeMatcher<DecayedType> decayedType;
/// Matches the decayed type, whos decayed type matches \c InnerMatcher
AST_MATCHER_P(DecayedType, hasDecayedType, internal::Matcher<QualType>,
InnerType) {
return InnerType.matches(Node.getDecayedType(), Finder, Builder);
}
/// Matches declarations whose declaration context, interpreted as a
/// Decl, matches \c InnerMatcher.
///
/// Given
/// \code
/// namespace N {
/// namespace M {
/// class D {};
/// }
/// }
/// \endcode
///
/// \c cxxRcordDecl(hasDeclContext(namedDecl(hasName("M")))) matches the
/// declaration of \c class \c D.
AST_MATCHER_P(Decl, hasDeclContext, internal::Matcher<Decl>, InnerMatcher) {
const DeclContext *DC = Node.getDeclContext();
if (!DC) return false;
return InnerMatcher.matches(*Decl::castFromDeclContext(DC), Finder, Builder);
}
/// Matches nested name specifiers.
///
/// Given
/// \code
/// namespace ns {
/// struct A { static void f(); };
/// void A::f() {}
/// void g() { A::f(); }
/// }
/// ns::A a;
/// \endcode
/// nestedNameSpecifier()
/// matches "ns::" and both "A::"
extern const internal::VariadicAllOfMatcher<NestedNameSpecifier>
nestedNameSpecifier;
/// Same as \c nestedNameSpecifier but matches \c NestedNameSpecifierLoc.
extern const internal::VariadicAllOfMatcher<NestedNameSpecifierLoc>
nestedNameSpecifierLoc;
/// Matches \c NestedNameSpecifierLocs for which the given inner
/// NestedNameSpecifier-matcher matches.
AST_MATCHER_FUNCTION_P_OVERLOAD(
internal::BindableMatcher<NestedNameSpecifierLoc>, loc,
internal::Matcher<NestedNameSpecifier>, InnerMatcher, 1) {
return internal::BindableMatcher<NestedNameSpecifierLoc>(
new internal::LocMatcher<NestedNameSpecifierLoc, NestedNameSpecifier>(
InnerMatcher));
}
/// Matches nested name specifiers that specify a type matching the
/// given \c QualType matcher without qualifiers.
///
/// Given
/// \code
/// struct A { struct B { struct C {}; }; };
/// A::B::C c;
/// \endcode
/// nestedNameSpecifier(specifiesType(
/// hasDeclaration(cxxRecordDecl(hasName("A")))
/// ))
/// matches "A::"
AST_MATCHER_P(NestedNameSpecifier, specifiesType,
internal::Matcher<QualType>, InnerMatcher) {
if (!Node.getAsType())
return false;
return InnerMatcher.matches(QualType(Node.getAsType(), 0), Finder, Builder);
}
/// Matches nested name specifier locs that specify a type matching the
/// given \c TypeLoc.
///
/// Given
/// \code
/// struct A { struct B { struct C {}; }; };
/// A::B::C c;
/// \endcode
/// nestedNameSpecifierLoc(specifiesTypeLoc(loc(type(
/// hasDeclaration(cxxRecordDecl(hasName("A")))))))
/// matches "A::"
AST_MATCHER_P(NestedNameSpecifierLoc, specifiesTypeLoc,
internal::Matcher<TypeLoc>, InnerMatcher) {
return Node && Node.getNestedNameSpecifier()->getAsType() &&
InnerMatcher.matches(Node.getTypeLoc(), Finder, Builder);
}
/// Matches on the prefix of a \c NestedNameSpecifier.
///
/// Given
/// \code
/// struct A { struct B { struct C {}; }; };
/// A::B::C c;
/// \endcode
/// nestedNameSpecifier(hasPrefix(specifiesType(asString("struct A")))) and
/// matches "A::"
AST_MATCHER_P_OVERLOAD(NestedNameSpecifier, hasPrefix,
internal::Matcher<NestedNameSpecifier>, InnerMatcher,
0) {
const NestedNameSpecifier *NextNode = Node.getPrefix();
if (!NextNode)
return false;
return InnerMatcher.matches(*NextNode, Finder, Builder);
}
/// Matches on the prefix of a \c NestedNameSpecifierLoc.
///
/// Given
/// \code
/// struct A { struct B { struct C {}; }; };
/// A::B::C c;
/// \endcode
/// nestedNameSpecifierLoc(hasPrefix(loc(specifiesType(asString("struct A")))))
/// matches "A::"
AST_MATCHER_P_OVERLOAD(NestedNameSpecifierLoc, hasPrefix,
internal::Matcher<NestedNameSpecifierLoc>, InnerMatcher,
1) {
NestedNameSpecifierLoc NextNode = Node.getPrefix();
if (!NextNode)
return false;
return InnerMatcher.matches(NextNode, Finder, Builder);
}
/// Matches nested name specifiers that specify a namespace matching the
/// given namespace matcher.
///
/// Given
/// \code
/// namespace ns { struct A {}; }
/// ns::A a;
/// \endcode
/// nestedNameSpecifier(specifiesNamespace(hasName("ns")))
/// matches "ns::"
AST_MATCHER_P(NestedNameSpecifier, specifiesNamespace,
internal::Matcher<NamespaceDecl>, InnerMatcher) {
if (!Node.getAsNamespace())
return false;
return InnerMatcher.matches(*Node.getAsNamespace(), Finder, Builder);
}
/// Overloads for the \c equalsNode matcher.
/// FIXME: Implement for other node types.
/// @{
/// Matches if a node equals another node.
///
/// \c Decl has pointer identity in the AST.
AST_MATCHER_P_OVERLOAD(Decl, equalsNode, const Decl*, Other, 0) {
return &Node == Other;
}
/// Matches if a node equals another node.
///
/// \c Stmt has pointer identity in the AST.
AST_MATCHER_P_OVERLOAD(Stmt, equalsNode, const Stmt*, Other, 1) {
return &Node == Other;
}
/// Matches if a node equals another node.
///
/// \c Type has pointer identity in the AST.
AST_MATCHER_P_OVERLOAD(Type, equalsNode, const Type*, Other, 2) {
return &Node == Other;
}
/// @}
/// Matches each case or default statement belonging to the given switch
/// statement. This matcher may produce multiple matches.
///
/// Given
/// \code
/// switch (1) { case 1: case 2: default: switch (2) { case 3: case 4: ; } }
/// \endcode
/// switchStmt(forEachSwitchCase(caseStmt().bind("c"))).bind("s")
/// matches four times, with "c" binding each of "case 1:", "case 2:",
/// "case 3:" and "case 4:", and "s" respectively binding "switch (1)",
/// "switch (1)", "switch (2)" and "switch (2)".
AST_MATCHER_P(SwitchStmt, forEachSwitchCase, internal::Matcher<SwitchCase>,
InnerMatcher) {
BoundNodesTreeBuilder Result;
// FIXME: getSwitchCaseList() does not necessarily guarantee a stable
// iteration order. We should use the more general iterating matchers once
// they are capable of expressing this matcher (for example, it should ignore
// case statements belonging to nested switch statements).
bool Matched = false;
for (const SwitchCase *SC = Node.getSwitchCaseList(); SC;
SC = SC->getNextSwitchCase()) {
BoundNodesTreeBuilder CaseBuilder(*Builder);
bool CaseMatched = InnerMatcher.matches(*SC, Finder, &CaseBuilder);
if (CaseMatched) {
Matched = true;
Result.addMatch(CaseBuilder);
}
}
*Builder = std::move(Result);
return Matched;
}
/// Matches each constructor initializer in a constructor definition.
///
/// Given
/// \code
/// class A { A() : i(42), j(42) {} int i; int j; };
/// \endcode
/// cxxConstructorDecl(forEachConstructorInitializer(
/// forField(decl().bind("x"))
/// ))
/// will trigger two matches, binding for 'i' and 'j' respectively.
AST_MATCHER_P(CXXConstructorDecl, forEachConstructorInitializer,
internal::Matcher<CXXCtorInitializer>, InnerMatcher) {
BoundNodesTreeBuilder Result;
bool Matched = false;
for (const auto *I : Node.inits()) {
BoundNodesTreeBuilder InitBuilder(*Builder);
if (InnerMatcher.matches(*I, Finder, &InitBuilder)) {
Matched = true;
Result.addMatch(InitBuilder);
}
}
*Builder = std::move(Result);
return Matched;
}
/// Matches constructor declarations that are copy constructors.
///
/// Given
/// \code
/// struct S {
/// S(); // #1
/// S(const S &); // #2
/// S(S &&); // #3
/// };
/// \endcode
/// cxxConstructorDecl(isCopyConstructor()) will match #2, but not #1 or #3.
AST_MATCHER(CXXConstructorDecl, isCopyConstructor) {
return Node.isCopyConstructor();
}
/// Matches constructor declarations that are move constructors.
///
/// Given
/// \code
/// struct S {
/// S(); // #1
/// S(const S &); // #2
/// S(S &&); // #3
/// };
/// \endcode
/// cxxConstructorDecl(isMoveConstructor()) will match #3, but not #1 or #2.
AST_MATCHER(CXXConstructorDecl, isMoveConstructor) {
return Node.isMoveConstructor();
}
/// Matches constructor declarations that are default constructors.
///
/// Given
/// \code
/// struct S {
/// S(); // #1
/// S(const S &); // #2
/// S(S &&); // #3
/// };
/// \endcode
/// cxxConstructorDecl(isDefaultConstructor()) will match #1, but not #2 or #3.
AST_MATCHER(CXXConstructorDecl, isDefaultConstructor) {
return Node.isDefaultConstructor();
}
/// Matches constructors that delegate to another constructor.
///
/// Given
/// \code
/// struct S {
/// S(); // #1
/// S(int) {} // #2
/// S(S &&) : S() {} // #3
/// };
/// S::S() : S(0) {} // #4
/// \endcode
/// cxxConstructorDecl(isDelegatingConstructor()) will match #3 and #4, but not
/// #1 or #2.
AST_MATCHER(CXXConstructorDecl, isDelegatingConstructor) {
return Node.isDelegatingConstructor();
}
/// Matches constructor, conversion function, and deduction guide declarations
/// that have an explicit specifier if this explicit specifier is resolved to
/// true.
///
/// Given
/// \code
/// template<bool b>
/// struct S {
/// S(int); // #1
/// explicit S(double); // #2
/// operator int(); // #3
/// explicit operator bool(); // #4
/// explicit(false) S(bool) // # 7
/// explicit(true) S(char) // # 8
/// explicit(b) S(S) // # 9
/// };
/// S(int) -> S<true> // #5
/// explicit S(double) -> S<false> // #6
/// \endcode
/// cxxConstructorDecl(isExplicit()) will match #2 and #8, but not #1, #7 or #9.
/// cxxConversionDecl(isExplicit()) will match #4, but not #3.
/// cxxDeductionGuideDecl(isExplicit()) will match #6, but not #5.
AST_POLYMORPHIC_MATCHER(isExplicit, AST_POLYMORPHIC_SUPPORTED_TYPES(
CXXConstructorDecl, CXXConversionDecl,
CXXDeductionGuideDecl)) {
return Node.isExplicit();
}
/// Matches the expression in an explicit specifier if present in the given
/// declaration.
///
/// Given
/// \code
/// template<bool b>
/// struct S {
/// S(int); // #1
/// explicit S(double); // #2
/// operator int(); // #3
/// explicit operator bool(); // #4
/// explicit(false) S(bool) // # 7
/// explicit(true) S(char) // # 8
/// explicit(b) S(S) // # 9
/// };
/// S(int) -> S<true> // #5
/// explicit S(double) -> S<false> // #6
/// \endcode
/// cxxConstructorDecl(hasExplicitSpecifier(constantExpr())) will match #7, #8 and #9, but not #1 or #2.
/// cxxConversionDecl(hasExplicitSpecifier(constantExpr())) will not match #3 or #4.
/// cxxDeductionGuideDecl(hasExplicitSpecifier(constantExpr())) will not match #5 or #6.
AST_MATCHER_P(FunctionDecl, hasExplicitSpecifier, internal::Matcher<Expr>,
InnerMatcher) {
ExplicitSpecifier ES = ExplicitSpecifier::getFromDecl(&Node);
if (!ES.getExpr())
return false;
return InnerMatcher.matches(*ES.getExpr(), Finder, Builder);
}
/// Matches function and namespace declarations that are marked with
/// the inline keyword.
///
/// Given
/// \code
/// inline void f();
/// void g();
/// namespace n {
/// inline namespace m {}
/// }
/// \endcode
/// functionDecl(isInline()) will match ::f().
/// namespaceDecl(isInline()) will match n::m.
AST_POLYMORPHIC_MATCHER(isInline,
AST_POLYMORPHIC_SUPPORTED_TYPES(NamespaceDecl,
FunctionDecl)) {
// This is required because the spelling of the function used to determine
// whether inline is specified or not differs between the polymorphic types.
if (const auto *FD = dyn_cast<FunctionDecl>(&Node))
return FD->isInlineSpecified();
else if (const auto *NSD = dyn_cast<NamespaceDecl>(&Node))
return NSD->isInline();
llvm_unreachable("Not a valid polymorphic type");
}
/// Matches anonymous namespace declarations.
///
/// Given
/// \code
/// namespace n {
/// namespace {} // #1
/// }
/// \endcode
/// namespaceDecl(isAnonymous()) will match #1 but not ::n.
AST_MATCHER(NamespaceDecl, isAnonymous) {
return Node.isAnonymousNamespace();
}
/// Matches declarations in the namespace `std`, but not in nested namespaces.
///
/// Given
/// \code
/// class vector {};
/// namespace foo {
/// class vector {};
/// namespace std {
/// class vector {};
/// }
/// }
/// namespace std {
/// inline namespace __1 {
/// class vector {}; // #1
/// namespace experimental {
/// class vector {};
/// }
/// }
/// }
/// \endcode
/// cxxRecordDecl(hasName("vector"), isInStdNamespace()) will match only #1.
AST_MATCHER(Decl, isInStdNamespace) { return Node.isInStdNamespace(); }
/// If the given case statement does not use the GNU case range
/// extension, matches the constant given in the statement.
///
/// Given
/// \code
/// switch (1) { case 1: case 1+1: case 3 ... 4: ; }
/// \endcode
/// caseStmt(hasCaseConstant(integerLiteral()))
/// matches "case 1:"
AST_MATCHER_P(CaseStmt, hasCaseConstant, internal::Matcher<Expr>,
InnerMatcher) {
if (Node.getRHS())
return false;
return InnerMatcher.matches(*Node.getLHS(), Finder, Builder);
}
/// Matches declaration that has a given attribute.
///
/// Given
/// \code
/// __attribute__((device)) void f() { ... }
/// \endcode
/// decl(hasAttr(clang::attr::CUDADevice)) matches the function declaration of
/// f. If the matcher is used from clang-query, attr::Kind parameter should be
/// passed as a quoted string. e.g., hasAttr("attr::CUDADevice").
AST_MATCHER_P(Decl, hasAttr, attr::Kind, AttrKind) {
for (const auto *Attr : Node.attrs()) {
if (Attr->getKind() == AttrKind)
return true;
}
return false;
}
/// Matches the return value expression of a return statement
///
/// Given
/// \code
/// return a + b;
/// \endcode
/// hasReturnValue(binaryOperator())
/// matches 'return a + b'
/// with binaryOperator()
/// matching 'a + b'
AST_MATCHER_P(ReturnStmt, hasReturnValue, internal::Matcher<Expr>,
InnerMatcher) {
if (const auto *RetValue = Node.getRetValue())
return InnerMatcher.matches(*RetValue, Finder, Builder);
return false;
}
/// Matches CUDA kernel call expression.
///
/// Example matches,
/// \code
/// kernel<<<i,j>>>();
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CUDAKernelCallExpr>
cudaKernelCallExpr;
/// Matches expressions that resolve to a null pointer constant, such as
/// GNU's __null, C++11's nullptr, or C's NULL macro.
///
/// Given:
/// \code
/// void *v1 = NULL;
/// void *v2 = nullptr;
/// void *v3 = __null; // GNU extension
/// char *cp = (char *)0;
/// int *ip = 0;
/// int i = 0;
/// \endcode
/// expr(nullPointerConstant())
/// matches the initializer for v1, v2, v3, cp, and ip. Does not match the
/// initializer for i.
AST_MATCHER(Expr, nullPointerConstant) {
return Node.isNullPointerConstant(Finder->getASTContext(),
Expr::NPC_ValueDependentIsNull);
}
/// Matches declaration of the function the statement belongs to
///
/// Given:
/// \code
/// F& operator=(const F& o) {
/// std::copy_if(o.begin(), o.end(), begin(), [](V v) { return v > 0; });
/// return *this;
/// }
/// \endcode
/// returnStmt(forFunction(hasName("operator=")))
/// matches 'return *this'
/// but does not match 'return v > 0'
AST_MATCHER_P(Stmt, forFunction, internal::Matcher<FunctionDecl>,
InnerMatcher) {
const auto &Parents = Finder->getASTContext().getParents(Node);
llvm::SmallVector<ast_type_traits::DynTypedNode, 8> Stack(Parents.begin(),
Parents.end());
while(!Stack.empty()) {
const auto &CurNode = Stack.back();
Stack.pop_back();
if(const auto *FuncDeclNode = CurNode.get<FunctionDecl>()) {
if(InnerMatcher.matches(*FuncDeclNode, Finder, Builder)) {
return true;
}
} else if(const auto *LambdaExprNode = CurNode.get<LambdaExpr>()) {
if(InnerMatcher.matches(*LambdaExprNode->getCallOperator(),
Finder, Builder)) {
return true;
}
} else {
for(const auto &Parent: Finder->getASTContext().getParents(CurNode))
Stack.push_back(Parent);
}
}
return false;
}
/// Matches a declaration that has external formal linkage.
///
/// Example matches only z (matcher = varDecl(hasExternalFormalLinkage()))
/// \code
/// void f() {
/// int x;
/// static int y;
/// }
/// int z;
/// \endcode
///
/// Example matches f() because it has external formal linkage despite being
/// unique to the translation unit as though it has internal likage
/// (matcher = functionDecl(hasExternalFormalLinkage()))
///
/// \code
/// namespace {
/// void f() {}
/// }
/// \endcode
AST_MATCHER(NamedDecl, hasExternalFormalLinkage) {
return Node.hasExternalFormalLinkage();
}
/// Matches a declaration that has default arguments.
///
/// Example matches y (matcher = parmVarDecl(hasDefaultArgument()))
/// \code
/// void x(int val) {}
/// void y(int val = 0) {}
/// \endcode
///
/// Deprecated. Use hasInitializer() instead to be able to
/// match on the contents of the default argument. For example:
///
/// \code
/// void x(int val = 7) {}
/// void y(int val = 42) {}
/// \endcode
/// parmVarDecl(hasInitializer(integerLiteral(equals(42))))
/// matches the parameter of y
///
/// A matcher such as
/// parmVarDecl(hasInitializer(anything()))
/// is equivalent to parmVarDecl(hasDefaultArgument()).
AST_MATCHER(ParmVarDecl, hasDefaultArgument) {
return Node.hasDefaultArg();
}
/// Matches array new expressions.
///
/// Given:
/// \code
/// MyClass *p1 = new MyClass[10];
/// \endcode
/// cxxNewExpr(isArray())
/// matches the expression 'new MyClass[10]'.
AST_MATCHER(CXXNewExpr, isArray) {
return Node.isArray();
}
/// Matches array new expressions with a given array size.
///
/// Given:
/// \code
/// MyClass *p1 = new MyClass[10];
/// \endcode
/// cxxNewExpr(hasArraySize(integerLiteral(equals(10))))
/// matches the expression 'new MyClass[10]'.
AST_MATCHER_P(CXXNewExpr, hasArraySize, internal::Matcher<Expr>, InnerMatcher) {
return Node.isArray() && *Node.getArraySize() &&
InnerMatcher.matches(**Node.getArraySize(), Finder, Builder);
}
/// Matches a class declaration that is defined.
///
/// Example matches x (matcher = cxxRecordDecl(hasDefinition()))
/// \code
/// class x {};
/// class y;
/// \endcode
AST_MATCHER(CXXRecordDecl, hasDefinition) {
return Node.hasDefinition();
}
/// Matches C++11 scoped enum declaration.
///
/// Example matches Y (matcher = enumDecl(isScoped()))
/// \code
/// enum X {};
/// enum class Y {};
/// \endcode
AST_MATCHER(EnumDecl, isScoped) {
return Node.isScoped();
}
/// Matches a function declared with a trailing return type.
///
/// Example matches Y (matcher = functionDecl(hasTrailingReturn()))
/// \code
/// int X() {}
/// auto Y() -> int {}
/// \endcode
AST_MATCHER(FunctionDecl, hasTrailingReturn) {
if (const auto *F = Node.getType()->getAs<FunctionProtoType>())
return F->hasTrailingReturn();
return false;
}
/// Matches expressions that match InnerMatcher that are possibly wrapped in an
/// elidable constructor and other corresponding bookkeeping nodes.
///
/// In C++17, elidable copy constructors are no longer being generated in the
/// AST as it is not permitted by the standard. They are, however, part of the
/// AST in C++14 and earlier. So, a matcher must abstract over these differences
/// to work in all language modes. This matcher skips elidable constructor-call
/// AST nodes, `ExprWithCleanups` nodes wrapping elidable constructor-calls and
/// various implicit nodes inside the constructor calls, all of which will not
/// appear in the C++17 AST.
///
/// Given
///
/// \code
/// struct H {};
/// H G();
/// void f() {
/// H D = G();
/// }
/// \endcode
///
/// ``varDecl(hasInitializer(ignoringElidableConstructorCall(callExpr())))``
/// matches ``H D = G()`` in C++11 through C++17 (and beyond).
AST_MATCHER_P(Expr, ignoringElidableConstructorCall,
ast_matchers::internal::Matcher<Expr>, InnerMatcher) {
// E tracks the node that we are examining.
const Expr *E = &Node;
// If present, remove an outer `ExprWithCleanups` corresponding to the
// underlying `CXXConstructExpr`. This check won't cover all cases of added
// `ExprWithCleanups` corresponding to `CXXConstructExpr` nodes (because the
// EWC is placed on the outermost node of the expression, which this may not
// be), but, it still improves the coverage of this matcher.
if (const auto *CleanupsExpr = dyn_cast<ExprWithCleanups>(&Node))
E = CleanupsExpr->getSubExpr();
if (const auto *CtorExpr = dyn_cast<CXXConstructExpr>(E)) {
if (CtorExpr->isElidable()) {
if (const auto *MaterializeTemp =
dyn_cast<MaterializeTemporaryExpr>(CtorExpr->getArg(0))) {
return InnerMatcher.matches(*MaterializeTemp->getSubExpr(), Finder,
Builder);
}
}
}
return InnerMatcher.matches(Node, Finder, Builder);
}
//----------------------------------------------------------------------------//
// OpenMP handling.
//----------------------------------------------------------------------------//
/// Matches any ``#pragma omp`` executable directive.
///
/// Given
///
/// \code
/// #pragma omp parallel
/// #pragma omp parallel default(none)
/// #pragma omp taskyield
/// \endcode
///
/// ``ompExecutableDirective()`` matches ``omp parallel``,
/// ``omp parallel default(none)`` and ``omp taskyield``.
extern const internal::VariadicDynCastAllOfMatcher<Stmt, OMPExecutableDirective>
ompExecutableDirective;
/// Matches standalone OpenMP directives,
/// i.e., directives that can't have a structured block.
///
/// Given
///
/// \code
/// #pragma omp parallel
/// {}
/// #pragma omp taskyield
/// \endcode
///
/// ``ompExecutableDirective(isStandaloneDirective()))`` matches
/// ``omp taskyield``.
AST_MATCHER(OMPExecutableDirective, isStandaloneDirective) {
return Node.isStandaloneDirective();
}
/// Matches the Stmt AST node that is marked as being the structured-block
/// of an OpenMP executable directive.
///
/// Given
///
/// \code
/// #pragma omp parallel
/// {}
/// \endcode
///
/// ``stmt(isOMPStructuredBlock()))`` matches ``{}``.
AST_MATCHER(Stmt, isOMPStructuredBlock) { return Node.isOMPStructuredBlock(); }
/// Matches the structured-block of the OpenMP executable directive
///
/// Prerequisite: the executable directive must not be standalone directive.
/// If it is, it will never match.
///
/// Given
///
/// \code
/// #pragma omp parallel
/// ;
/// #pragma omp parallel
/// {}
/// \endcode
///
/// ``ompExecutableDirective(hasStructuredBlock(nullStmt()))`` will match ``;``
AST_MATCHER_P(OMPExecutableDirective, hasStructuredBlock,
internal::Matcher<Stmt>, InnerMatcher) {
if (Node.isStandaloneDirective())
return false; // Standalone directives have no structured blocks.
return InnerMatcher.matches(*Node.getStructuredBlock(), Finder, Builder);
}
/// Matches any clause in an OpenMP directive.
///
/// Given
///
/// \code
/// #pragma omp parallel
/// #pragma omp parallel default(none)
/// \endcode
///
/// ``ompExecutableDirective(hasAnyClause(anything()))`` matches
/// ``omp parallel default(none)``.
AST_MATCHER_P(OMPExecutableDirective, hasAnyClause,
internal::Matcher<OMPClause>, InnerMatcher) {
ArrayRef<OMPClause *> Clauses = Node.clauses();
return matchesFirstInPointerRange(InnerMatcher, Clauses.begin(),
Clauses.end(), Finder, Builder);
}
/// Matches OpenMP ``default`` clause.
///
/// Given
///
/// \code
/// #pragma omp parallel default(none)
/// #pragma omp parallel default(shared)
/// #pragma omp parallel
/// \endcode
///
/// ``ompDefaultClause()`` matches ``default(none)`` and ``default(shared)``.
extern const internal::VariadicDynCastAllOfMatcher<OMPClause, OMPDefaultClause>
ompDefaultClause;
/// Matches if the OpenMP ``default`` clause has ``none`` kind specified.
///
/// Given
///
/// \code
/// #pragma omp parallel
/// #pragma omp parallel default(none)
/// #pragma omp parallel default(shared)
/// \endcode
///
/// ``ompDefaultClause(isNoneKind())`` matches only ``default(none)``.
AST_MATCHER(OMPDefaultClause, isNoneKind) {
return Node.getDefaultKind() == OMPC_DEFAULT_none;
}
/// Matches if the OpenMP ``default`` clause has ``shared`` kind specified.
///
/// Given
///
/// \code
/// #pragma omp parallel
/// #pragma omp parallel default(none)
/// #pragma omp parallel default(shared)
/// \endcode
///
/// ``ompDefaultClause(isSharedKind())`` matches only ``default(shared)``.
AST_MATCHER(OMPDefaultClause, isSharedKind) {
return Node.getDefaultKind() == OMPC_DEFAULT_shared;
}
/// Matches if the OpenMP directive is allowed to contain the specified OpenMP
/// clause kind.
///
/// Given
///
/// \code
/// #pragma omp parallel
/// #pragma omp parallel for
/// #pragma omp for
/// \endcode
///
/// `ompExecutableDirective(isAllowedToContainClause(OMPC_default))`` matches
/// ``omp parallel`` and ``omp parallel for``.
///
/// If the matcher is use from clang-query, ``OpenMPClauseKind`` parameter
/// should be passed as a quoted string. e.g.,
/// ``isAllowedToContainClauseKind("OMPC_default").``
AST_MATCHER_P(OMPExecutableDirective, isAllowedToContainClauseKind,
OpenMPClauseKind, CKind) {
return isAllowedClauseForDirective(
Node.getDirectiveKind(), CKind,
Finder->getASTContext().getLangOpts().OpenMP);
}
//----------------------------------------------------------------------------//
// End OpenMP handling.
//----------------------------------------------------------------------------//
} // namespace ast_matchers
} // namespace clang
#endif // LLVM_CLANG_ASTMATCHERS_ASTMATCHERS_H
|
infgraph.h |
class VV
{
public:
vector<int> head;
vector<int> next;
vector<int> data;
vector<int> vsize;
void clear()
{
head.clear();
next.clear();
data.clear();
vsize.clear();
}
// trick for not change code
void push_back(vector<int> x){
ASSERT(x.size()==0);
addVector();
}
void addVector()
{
head.push_back(-1);
vsize.push_back(0);
}
int size(int t){
return vsize[t];
}
//vv[a].push_back(b)
void addElement( int a, int b)
{
//a.push_back(b);
vsize[a]++;
data.push_back(b);
next.push_back(head[a]);
head[a]=next.size()-1;
}
//loop
//for(int t:vv[a])
//for (int x=vv.head[a]; x!=-1; x=vv.next[x])
//{
//t=vv.data[x]
//}
};
class InfGraph:public Graph
{
public:
vector<vector<int>> hyperG;
//VV hyperG;
vector<vector<int>> hyperGT;
InfGraph(string folder, string graph_file):Graph(folder, graph_file){
hyperG.clear();
for(int i=0; i<n; i++)
hyperG.push_back(vector<int>());
for(int i=0; i<12; i++)
sfmt_init_gen_rand(&sfmtSeed, i+1234);
}
enum ProbModel {TR, WC, TR001};
ProbModel probModel;
double BuildHypergraphR(int64 R){
hyperId=R;
double tau=0;
//for(int i=0; i<n; i++)
//hyperG[i].clear();
hyperG.clear();
for(int i=0; i<n; i++)
hyperG.push_back(vector<int>());
hyperGT.clear();
while((int)hyperGT.size() <= R)
hyperGT.push_back( vector<int>() );
for(int i=0; i<R; i++){
tau+=BuildHypergraphNode(sfmt_genrand_uint32(&sfmtSeed)%n, i, true);
}
int totAddedElement=0;
for(int i=0; i<R; i++){
for(int t:hyperGT[i])
{
hyperG[t].push_back(i);
//hyperG.addElement(t, i);
totAddedElement++;
}
}
ASSERT(hyperId == R);
return tau;
}
int BuildHypergraphNode(int uStart, int hyperiiid, bool addHyperEdge){
int n_visit_edge=1;
if(addHyperEdge)
{
ASSERT((int)hyperGT.size() > hyperiiid);
hyperGT[hyperiiid].push_back(uStart);
}
int n_visit_mark=0;
//for(int i=0; i<12; i++) ASSERT((int)visit[i].size()==n);
//for(int i=0; i<12; i++) ASSERT((int)visit_mark[i].size()==n);
//hyperiiid ++;
q.clear();
q.push_back(uStart);
ASSERT(n_visit_mark < n);
visit_mark[n_visit_mark++]=uStart;
visit[uStart]=true;
while(!q.empty()) {
int expand=q.front();
q.pop_front();
if(influModel==IC){
int i=expand;
for(int j=0; j<(int)gT[i].size(); j++){
//int u=expand;
int v=gT[i][j];
n_visit_edge++;
double randDouble=double(sfmt_genrand_uint32(&sfmtSeed))/double(RAND_MAX)/2;
if(randDouble > probT[i][j])
continue;
if(visit[v])
continue;
if(!visit[v])
{
ASSERT(n_visit_mark < n);
visit_mark[n_visit_mark++]=v;
visit[v]=true;
}
q.push_back(v);
//#pragma omp critical
//if(0)
if(addHyperEdge)
{
//hyperG[v].push_back(hyperiiid);
ASSERT((int)hyperGT.size() > hyperiiid);
hyperGT[hyperiiid].push_back(v);
}
}
}
else if(influModel==LT){
if(gT[expand].size()==0)
continue;
ASSERT(gT[expand].size()>0);
n_visit_edge+=gT[expand].size();
double randDouble=double(sfmt_genrand_uint32(&sfmtSeed))/double(RAND_MAX)/2;
for(int i=0; i<(int)gT[expand].size(); i++){
ASSERT( i< (int)probT[expand].size());
randDouble -= probT[expand][i];
if(randDouble>0)
continue;
//int u=expand;
int v=gT[expand][i];
if(visit[v])
break;
if(!visit[v])
{
visit_mark[n_visit_mark++]=v;
visit[v]=true;
}
q.push_back(v);
if(addHyperEdge)
{
ASSERT((int)hyperGT.size() > hyperiiid);
hyperGT[hyperiiid].push_back(v);
}
break;
}
}
else
ASSERT(false);
}
for(int i=0; i<n_visit_mark; i++)
visit[visit_mark[i]]=false;
return n_visit_edge;
}
//return the number of edges visited
int64 hyperId = 0;
deque<int> q;
sfmt_t sfmtSeed;
set<int> seedSet;
void BuildSeedSet() {
vector< int > degree;
vector< int> visit_local(hyperGT.size());
//sort(ALL(degree));
//reverse(ALL(degree));
seedSet.clear();
for(int i=0; i<n; i++)
{
degree.push_back( hyperG[i].size() );
//degree.push_back( hyperG.size(i) );
}
ASSERT(k > 0);
ASSERT(k < (int)degree.size());
for(int i=0; i<k; i++){
auto t=max_element(degree.begin(), degree.end());
int id=t-degree.begin();
seedSet.insert(id);
degree[id]=0;
for(int t:hyperG[id]){
if(!visit_local[t]){
visit_local[t]=true;
for(int item:hyperGT[t]){
degree[item]--;
}
}
}
}
}
double InfluenceHyperGraph(){
set<int> s;
for(auto t:seedSet){
for(auto tt:hyperG[t]){
//for(int index=hyperG.head[t]; index!=-1; index=hyperG.next[index]){
//int tt=hyperG.data[index];
s.insert(tt);
}
}
double inf=(double)n*s.size()/hyperId;
return inf;
}
};
|
DRB067-restrictpointer1-orig-no.c | /*
Copyright (C) 1991-2018 Free Software Foundation, Inc.
This file is part of the GNU C Library.
The GNU C Library is free software; you can redistribute it andor
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
The GNU C Library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with the GNU C Library; if not, see
<http:www.gnu.org/licenses/>.
*/
/*
This header is separate from features.h so that the compiler can
include it implicitly at the start of every compilation. It must
not itself include <features.h> or any other header that includes
<features.h> because the implicit include comes before any feature
test macros that may be defined in a source file before it first
explicitly includes a system header. GCC knows the name of this
header in order to preinclude it.
*/
/*
glibc's intent is to support the IEC 559 math functionality, real
and complex. If the GCC (4.9 and later) predefined macros
specifying compiler intent are available, use them to determine
whether the overall intent is to support these features; otherwise,
presume an older compiler has intent to support these features and
define these macros by default.
*/
/*
wchar_t uses Unicode 10.0.0. Version 10.0 of the Unicode Standard is
synchronized with ISOIEC 10646:2017, fifth edition, plus
the following additions from Amendment 1 to the fifth edition:
- 56 emoji characters
- 285 hentaigana
- 3 additional Zanabazar Square characters
*/
/*
Copyright (c) 2017, Lawrence Livermore National Security, LLC.
Produced at the Lawrence Livermore National Laboratory
Written by Chunhua Liao, Pei-Hung Lin, Joshua Asplund,
Markus Schordan, and Ian Karlin
(email: liao6@llnl.gov, lin32@llnl.gov, asplund1@llnl.gov,
schordan1@llnl.gov, karlin1@llnl.gov)
LLNL-CODE-732144
All rights reserved.
This file is part of DataRaceBench. For details, see
https:github.comLLNL/dataracebench. Please also see the LICENSE file
for our additional BSD notice.
Redistribution and use in source and binary forms, with
or without modification, are permitted provided that the following
conditions are met:
* Redistributions of source code must retain the above copyright
notice, this list of conditions and the disclaimer below.
* Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the disclaimer (as noted below)
in the documentation and/or other materials provided with the
distribution.
* Neither the name of the LLNS/LLNL nor the names of its contributors
may be used to endorse or promote products derived from this
software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND
CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES,
INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL LAWRENCE LIVERMORE NATIONAL
SECURITY, LLC, THE U.S. DEPARTMENT OF ENERGY OR CONTRIBUTORS BE
LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY,
OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING
IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF
THE POSSIBILITY OF SUCH DAMAGE.
*/
/*
restrict pointers: no aliasing
Array initialization using assignments.
C99 is needed to compile this code
e.g. gcc -std=c99 -c Stress-1.c
*/
#include <stdlib.h>
typedef double real8;
void foo(real8 * restrict newSxx, real8 * restrict newSyy, int length)
{
int i;
#pragma cetus private(i)
#pragma loop name foo#0
#pragma cetus parallel
#pragma omp parallel for private(i)
for (i=0; i<=(length-1); i+=1)
{
newSxx[i]=0.0;
newSyy[i]=0.0;
}
return ;
}
void print(real8 * restrict newSxx, real8 * restrict newSyy, int length)
{
int i;
#pragma cetus private(i)
#pragma loop name print#0
for (i=0; i<=(length-1); i+=1)
{
printf("%lf %lf\n", newSxx[i], newSyy[i]);
}
return ;
}
int main()
{
int length = 1000;
real8 * newSxx = malloc(length*sizeof (real8));
real8 * newSyy = malloc(length*sizeof (real8));
int _ret_val_0;
foo(newSxx, newSyy, length);
print(newSxx, newSyy, length);
free(newSxx);
free(newSyy);
_ret_val_0=0;
return _ret_val_0;
}
|
stribog_fmt_plug.c | /*
* GOST R 34.11-2012 cracker patch for JtR. Hacked together during
* the Hash Runner 2015 contest by Dhiru Kholia and Aleksey Cherepanov.
*
* Based on https://www.streebog.net/ and https://github.com/sjinks/php-stribog
* code. See "LICENSE.gost" for licensing details of the original code.
*/
#include "arch.h"
#if __SSE4_1__
#if FMT_EXTERNS_H
extern struct fmt_main fmt_stribog_256;
extern struct fmt_main fmt_stribog_512;
#elif FMT_REGISTERS_H
john_register_one(&fmt_stribog_256);
john_register_one(&fmt_stribog_512);
#else
#include <string.h>
#include <assert.h>
#include <errno.h>
#include "arch.h"
#include "misc.h"
#include "common.h"
#include "formats.h"
#include "params.h"
#include "options.h"
#include "gost3411-2012-sse41.h"
#ifdef _OPENMP
#include <omp.h>
#ifndef OMP_SCALE
#define OMP_SCALE 512 // XXX
#endif
#endif
#include "memdbg.h"
#define FORMAT_LABEL "stribog"
#define FORMAT_NAME ""
#define ALGORITHM_NAME "GOST R 34.11-2012 128/128 SSE4.1 1x"
#define BENCHMARK_COMMENT ""
#define BENCHMARK_LENGTH -1
#define PLAINTEXT_LENGTH 64 - 1
#define CIPHERTEXT256_LENGTH 64
#define CIPHERTEXT512_LENGTH 64
#define BINARY_SIZE_256 32
#define BINARY_SIZE_512 64
#define SALT_SIZE 0
#define SALT_ALIGN 1
#define BINARY_ALIGN sizeof(ARCH_WORD_32)
#define MIN_KEYS_PER_CRYPT 1
#define MAX_KEYS_PER_CRYPT 1
static struct fmt_tests stribog_256_tests[] = {
{"$stribog256$bbe19c8d2025d99f943a932a0b365a822aa36a4c479d22cc02c8973e219a533f", ""},
/* {"3f539a213e97c802cc229d474c6aa32a825a360b2a933a949fd925208d9ce1bb", ""}, */
/* 9d151eefd8590b89daa6ba6cb74af9275dd051026bb149a452fd84e5e57b5500 */
{"$stribog256$00557be5e584fd52a449b16b0251d05d27f94ab76cbaa6da890b59d8ef1e159d", "012345678901234567890123456789012345678901234567890123456789012"},
{NULL}
};
static struct fmt_tests stribog_512_tests[] = {
/* 8e945da209aa869f0455928529bcae4679e9873ab707b55315f56ceb98bef0a7362f715528356ee83cda5f2aac4c6ad2ba3a715c1bcd81cb8e9f90bf4c1c1a8a */
{"$stribog512$8a1a1c4cbf909f8ecb81cd1b5c713abad26a4cac2a5fda3ce86e352855712f36a7f0be98eb6cf51553b507b73a87e97946aebc29859255049f86aa09a25d948e", ""},
/* 1b54d01a4af5b9d5cc3d86d68d285462b19abc2475222f35c085122be4ba1ffa00ad30f8767b3a82384c6574f024c311e2a481332b08ef7f41797891c1646f48 */
{"$stribog512$486f64c1917879417fef082b3381a4e211c324f074654c38823a7b76f830ad00fa1fbae42b1285c0352f227524bc9ab16254288dd6863dccd5b9f54a1ad0541b", "012345678901234567890123456789012345678901234567890123456789012"},
{NULL}
};
#define make_full_static_buf(type, var, len) static type (var)[(len)]
#define make_dynamic_static_buf(type, var, len) \
static type *var; \
if (!var) \
var = mem_alloc_tiny((len), MEM_ALIGN_WORD)
#if 1
#define make_static_buf make_dynamic_static_buf
#else
#define make_static_buf make_full_static_buf
#endif
static char (*saved_key)[PLAINTEXT_LENGTH + 1];
static ARCH_WORD_32 (*crypt_out)[BINARY_SIZE_512 / sizeof(ARCH_WORD_32)];
static void init(struct fmt_main *self)
{
#ifdef _OPENMP
int omp_t = omp_get_max_threads();
self->params.min_keys_per_crypt *= omp_t;
omp_t *= OMP_SCALE;
self->params.max_keys_per_crypt *= omp_t;
#endif
if (!saved_key) {
saved_key = mem_calloc_align(self->params.max_keys_per_crypt, sizeof(*saved_key), MEM_ALIGN_SIMD);
}
if (!crypt_out)
crypt_out = mem_calloc(self->params.max_keys_per_crypt, sizeof(*crypt_out));
}
static void done(void)
{
MEM_FREE(crypt_out);
MEM_FREE(saved_key);
}
#define TAG256 "$stribog256$"
#define TAG256_LENGTH strlen(TAG256)
#define TAG512 "$stribog512$"
#define TAG512_LENGTH strlen(TAG512)
#define TAG_LENGTH TAG256_LENGTH
#define FORMAT_TAG TAG256
#define CIPHERTEXT_LENGTH 64
static char *split_256(char *ciphertext, int index, struct fmt_main *self)
{
make_static_buf(char, out, TAG_LENGTH + CIPHERTEXT_LENGTH + 1);
if (!strncmp(ciphertext, FORMAT_TAG, TAG_LENGTH))
ciphertext += TAG_LENGTH;
memcpy(out, FORMAT_TAG, TAG_LENGTH);
memcpy(out + TAG_LENGTH, ciphertext, CIPHERTEXT_LENGTH + 1);
strlwr(out + TAG_LENGTH);
return out;
}
static int valid_256(char *ciphertext, struct fmt_main *self)
{
char *p = ciphertext;
if (!strncmp(p, FORMAT_TAG, TAG_LENGTH))
p += TAG_LENGTH;
/* else */
/* return 0; */
if (strlen(p) != CIPHERTEXT_LENGTH)
return 0;
while(*p)
if(atoi16[ARCH_INDEX(*p++)]==0x7f)
return 0;
return 1;
}
static void *get_binary_256(char *ciphertext)
{
static unsigned char *out;
char *p = ciphertext;
int i;
if (!out) out = mem_alloc_tiny(BINARY_SIZE_256, MEM_ALIGN_WORD);
if (!strncmp(ciphertext, FORMAT_TAG, TAG_LENGTH))
p = ciphertext + TAG_LENGTH;
for (i = 0; i < BINARY_SIZE_256; i++) {
out[BINARY_SIZE_256 - i - 1] = (atoi16[ARCH_INDEX(*p)] << 4) | atoi16[ARCH_INDEX(p[1])];
p += 2;
}
return out;
}
#undef TAG_LENGTH
#undef FORMAT_TAG
#undef CIPHERTEXT_LENGTH
#define TAG_LENGTH TAG512_LENGTH
#define FORMAT_TAG TAG512
#define CIPHERTEXT_LENGTH 128
static char *split_512(char *ciphertext, int index, struct fmt_main *self)
{
make_static_buf(char, out, TAG_LENGTH + CIPHERTEXT_LENGTH + 1);
if (!strncmp(ciphertext, FORMAT_TAG, TAG_LENGTH))
ciphertext += TAG_LENGTH;
memcpy(out, FORMAT_TAG, TAG_LENGTH);
memcpy(out + TAG_LENGTH, ciphertext, CIPHERTEXT_LENGTH + 1);
strlwr(out + TAG_LENGTH);
return out;
}
static int valid_512(char *ciphertext, struct fmt_main *self)
{
char *p = ciphertext;
if (!strncmp(p, FORMAT_TAG, TAG_LENGTH))
p += TAG_LENGTH;
/* else */
/* return 0; */
if (strlen(p) != CIPHERTEXT_LENGTH)
return 0;
while(*p)
if(atoi16[ARCH_INDEX(*p++)]==0x7f)
return 0;
return 1;
}
static void *get_binary_512(char *ciphertext)
{
static unsigned char *out;
char *p = ciphertext;
int i;
if (!out) out = mem_alloc_tiny(BINARY_SIZE_512, MEM_ALIGN_WORD);
if (!strncmp(ciphertext, FORMAT_TAG, TAG_LENGTH))
p = ciphertext + TAG_LENGTH;
for (i = 0; i < BINARY_SIZE_512; i++) {
out[BINARY_SIZE_512 - i - 1] = (atoi16[ARCH_INDEX(*p)] << 4) | atoi16[ARCH_INDEX(p[1])];
p += 2;
}
return out;
}
#undef TAG_LENGTH
#undef FORMAT_TAG
#undef CIPHERTEXT_LENGTH
/* static int valid_256(char *ciphertext, struct fmt_main *self) */
/* { */
/* return valid(ciphertext, self, 64); */
/* } */
/* static int valid_512(char *ciphertext, struct fmt_main *self) */
/* { */
/* return valid(ciphertext, self, 128); */
/* } */
static int get_hash_0(int index) { return crypt_out[index][0] & PH_MASK_0; }
static int get_hash_1(int index) { return crypt_out[index][0] & PH_MASK_1; }
static int get_hash_2(int index) { return crypt_out[index][0] & PH_MASK_2; }
static int get_hash_3(int index) { return crypt_out[index][0] & PH_MASK_3; }
static int get_hash_4(int index) { return crypt_out[index][0] & PH_MASK_4; }
static int get_hash_5(int index) { return crypt_out[index][0] & PH_MASK_5; }
static int get_hash_6(int index) { return crypt_out[index][0] & PH_MASK_6; }
static void stribog256_init(void* context)
{
size_t offset = (((size_t)context + 15) & ~0x0F) - (size_t)context;
void *ctx = (char*)context + offset;
GOST34112012Init(ctx, 256);
}
static void stribog512_init(void* context)
{
size_t offset = (((size_t)context + 15) & ~0x0F) - (size_t)context;
void *ctx = (char*)context + offset;
GOST34112012Init(ctx, 512);
}
static void stribog_update(void* context, const unsigned char* buf, unsigned int count)
{
size_t offset = (((size_t)context + 15) & ~0x0F) - (size_t)context;
void *ctx = (char*)context + offset;
offset = (((size_t)buf + 15) & ~0x0F) - (size_t)buf;
if (!offset) {
GOST34112012Update(ctx, buf, count);
}
else {
ALIGN(16) unsigned char tmp[15];
assert(offset < 16);
memcpy(tmp, buf, offset);
GOST34112012Update(ctx, tmp, offset);
GOST34112012Update(ctx, buf + offset, count - offset);
}
}
static void stribog_final(unsigned char* digest, void* context)
{
size_t offset = (((size_t)context + 15) & ~0x0F) - (size_t)context;
void *ctx = (char*)context + offset;
GOST34112012Final(ctx, digest);
}
static int crypt_256(int *pcount, struct db_salt *salt)
{
const int count = *pcount;
int index = 0;
#ifdef _OPENMP
#pragma omp parallel for
for (index = 0; index < count; index++)
#endif
{
/* GOST34112012Context ctx;
GOST34112012Init(&ctx, 256);
GOST34112012Update(&ctx, (const unsigned char*)saved_key[index], strlen(saved_key[index]));
GOST34112012Final(&ctx, (unsigned char*)crypt_out[index]); */
GOST34112012Context ctx[2]; // alignment stuff
stribog256_init((void *)ctx);
stribog_update(&ctx, (const unsigned char*)saved_key[index], strlen(saved_key[index]));
stribog_final((unsigned char*)crypt_out[index], &ctx);
}
return count;
}
static int crypt_512(int *pcount, struct db_salt *salt)
{
const int count = *pcount;
int index = 0;
#ifdef _OPENMP
#pragma omp parallel for
for (index = 0; index < count; index++)
#endif
{
/* GOST34112012Context ctx;
GOST34112012Init(&ctx, 512);
GOST34112012Update(&ctx, (const unsigned char*)saved_key[index], strlen(saved_key[index]));
GOST34112012Final(&ctx, (unsigned char*)crypt_out[index]); */
GOST34112012Context ctx[2]; // alignment stuff
stribog512_init((void *)ctx);
stribog_update(&ctx, (const unsigned char*)saved_key[index], strlen(saved_key[index]));
stribog_final((unsigned char*)crypt_out[index], &ctx);
}
return count;
}
static int cmp_all(void *binary, int count)
{
int index = 0;
#ifdef _OPENMP
for (; index < count; index++)
#endif
if (!memcmp(binary, crypt_out[index], ARCH_SIZE))
return 1;
return 0;
}
static int cmp_one_256(void *binary, int index)
{
return !memcmp(binary, crypt_out[index], BINARY_SIZE_256);
}
static int cmp_one_512(void *binary, int index)
{
return !memcmp(binary, crypt_out[index], BINARY_SIZE_512);
}
static int cmp_exact(char *source, int index)
{
return 1;
}
static void stribog_set_key(char *key, int index)
{
int saved_len = strlen(key);
if (saved_len > PLAINTEXT_LENGTH)
saved_len = PLAINTEXT_LENGTH;
memcpy(saved_key[index], key, saved_len);
saved_key[index][saved_len] = 0;
}
static char *get_key(int index)
{
return saved_key[index];
}
struct fmt_main fmt_stribog_256 = {
{
"Stribog-256",
FORMAT_NAME,
ALGORITHM_NAME,
BENCHMARK_COMMENT,
BENCHMARK_LENGTH,
0,
PLAINTEXT_LENGTH,
BINARY_SIZE_256,
BINARY_ALIGN,
SALT_SIZE,
SALT_ALIGN,
MIN_KEYS_PER_CRYPT,
MAX_KEYS_PER_CRYPT,
FMT_CASE | FMT_8_BIT | FMT_SPLIT_UNIFIES_CASE | FMT_OMP,
{ NULL },
stribog_256_tests
}, {
init,
done,
fmt_default_reset,
fmt_default_prepare,
valid_256,
split_256,
get_binary_256,
fmt_default_salt,
{ NULL },
fmt_default_source,
{
fmt_default_binary_hash_0,
fmt_default_binary_hash_1,
fmt_default_binary_hash_2,
fmt_default_binary_hash_3,
fmt_default_binary_hash_4,
fmt_default_binary_hash_5,
fmt_default_binary_hash_6
},
fmt_default_salt_hash,
NULL,
fmt_default_set_salt,
stribog_set_key,
get_key,
fmt_default_clear_keys,
crypt_256,
{
get_hash_0,
get_hash_1,
get_hash_2,
get_hash_3,
get_hash_4,
get_hash_5,
get_hash_6
},
cmp_all,
cmp_one_256,
cmp_exact
}
};
struct fmt_main fmt_stribog_512 = {
{
"Stribog-512",
FORMAT_NAME,
ALGORITHM_NAME,
BENCHMARK_COMMENT,
BENCHMARK_LENGTH,
0,
PLAINTEXT_LENGTH,
BINARY_SIZE_512,
BINARY_ALIGN,
SALT_SIZE,
SALT_ALIGN,
MIN_KEYS_PER_CRYPT,
MAX_KEYS_PER_CRYPT,
FMT_CASE | FMT_8_BIT | FMT_SPLIT_UNIFIES_CASE | FMT_OMP,
{ NULL },
stribog_512_tests
}, {
init,
done,
fmt_default_reset,
fmt_default_prepare,
valid_512,
split_512,
get_binary_512,
fmt_default_salt,
{ NULL },
fmt_default_source,
{
fmt_default_binary_hash_0,
fmt_default_binary_hash_1,
fmt_default_binary_hash_2,
fmt_default_binary_hash_3,
fmt_default_binary_hash_4,
fmt_default_binary_hash_5,
fmt_default_binary_hash_6
},
fmt_default_salt_hash,
NULL,
fmt_default_set_salt,
stribog_set_key,
get_key,
fmt_default_clear_keys,
crypt_512,
{
get_hash_0,
get_hash_1,
get_hash_2,
get_hash_3,
get_hash_4,
get_hash_5,
get_hash_6
},
cmp_all,
cmp_one_512,
cmp_exact
}
};
#endif /* plugin stanza */
#else
#if !defined(FMT_EXTERNS_H) && !defined(FMT_REGISTERS_H)
#ifdef __GNUC__
#warning Stribog-256 and Stribog-512 formats require SSE 4.1, formats disabled
#elif _MSC_VER
#pragma message(": warning Stribog-256 and Stribog-512 formats require SSE 4.1, formats disabled:")
#endif
#endif
#endif /* __SSE4_1__ */
|
broadcast_reduce-inl.h | /*
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you under the Apache License, Version 2.0 (the
* "License"); you may not use this file except in compliance
* with the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing,
* software distributed under the License is distributed on an
* "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
* KIND, either express or implied. See the License for the
* specific language governing permissions and limitations
* under the License.
*/
/*!
* Copyright (c) 2015-2017 by Contributors
* \file broadcast_reduce-inl.h
* \brief CPU-specific Function definition of broadcast and reduce operators
*/
#ifndef MXNET_OPERATOR_TENSOR_BROADCAST_REDUCE_INL_H_
#define MXNET_OPERATOR_TENSOR_BROADCAST_REDUCE_INL_H_
#include <mxnet/operator_util.h>
#include <algorithm>
#include <vector>
#include <string>
#include <utility>
#include "../mshadow_op.h"
#include "../operator_common.h"
namespace mxnet {
namespace op {
namespace broadcast {
using namespace mshadow;
const int MAX_DIM = 5;
template<int ndim>
MSHADOW_XINLINE Shape<ndim> calc_stride(const Shape<ndim>& shape) {
Shape<ndim> stride;
index_t cumprod = 1;
#pragma unroll
for (int i = ndim - 1; i >= 0; --i) {
stride[i] = (shape[i] > 1) ? cumprod : 0;
cumprod *= shape[i];
}
return stride;
}
template<int ndim>
MSHADOW_XINLINE void unravel_dot(const int idx, const Shape<ndim>& shape,
const Shape<ndim>& stridej, const Shape<ndim>& stridek, int* j, int* k) {
*j = 0;
*k = 0;
#pragma unroll
for (int i = ndim-1, idx_t = idx; i >=0; --i) {
const int tmp = idx_t / shape[i];
const int coord = idx_t - tmp*shape[i];
*j += coord*stridej[i];
*k += coord*stridek[i];
idx_t = tmp;
}
}
template<int ndim>
MSHADOW_XINLINE Shape<ndim> unravel(const int idx, const Shape<ndim>& shape) {
Shape<ndim> ret;
#pragma unroll
for (int i = ndim-1, j = idx; i >=0; --i) {
int tmp = j / shape[i];
ret[i] = j - tmp*shape[i];
j = tmp;
}
return ret;
}
template<int ndim>
MSHADOW_XINLINE int ravel(const Shape<ndim>& coord, const Shape<ndim>& shape) {
int ret = 0;
#pragma unroll
for (int i = 0; i < ndim; ++i) {
ret = ret * shape[i] + (shape[i] > 1) * coord[i];
}
return ret;
}
template<int ndim>
MSHADOW_XINLINE int diff(const Shape<ndim>& small, const Shape<ndim>& big, Shape<ndim>* dims,
Shape<ndim>* stride) {
int mdim = 0;
#pragma unroll
for (int i = 0; i < ndim; ++i) {
mdim += small[i] != big[i];
(*dims)[i] = (*stride)[i] = 1;
}
#pragma unroll
for (int i = ndim-1, j = mdim, s = 1; i >= 0; --i) {
if (small[i] != big[i]) {
--j;
(*stride)[j] = s;
(*dims)[j] = big[i];
}
s *= big[i];
}
return mdim;
}
template<int ndim>
MSHADOW_XINLINE int unravel_dot(const int idx, const Shape<ndim>& shape,
const Shape<ndim>& stride) {
int ret = 0;
#pragma unroll
for (int i = ndim-1, j = idx; i >=0; --i) {
int tmp = j / shape[i];
ret += (j - tmp*shape[i])*stride[i];
j = tmp;
}
return ret;
}
template<int ndim>
MSHADOW_XINLINE int dot(const Shape<ndim>& coord, const Shape<ndim>& stride) {
int ret = 0;
#pragma unroll
for (int i = 0; i < ndim; ++i)
ret += coord[i] * stride[i];
return ret;
}
template<typename DType>
MSHADOW_XINLINE void assign(DType* dst, const bool addto, const DType src) {
if (addto) {
*dst += src;
} else {
*dst = src;
}
}
template<int ndim, typename DType, typename OP>
MSHADOW_XINLINE void binary_broadcast_assign(const int idx, const bool addto,
const DType* __restrict lhs,
const DType* __restrict rhs, DType* out,
const Shape<ndim>& lshape, const Shape<ndim>& rshape,
const Shape<ndim>& oshape) {
const Shape<ndim> coord = unravel(idx, oshape);
const int j = ravel(coord, lshape);
const int k = ravel(coord, rshape);
assign(&out[idx], addto, OP::Map(lhs[j], rhs[k]));
}
template<typename Reducer, int ndim, typename DType, typename OP>
MSHADOW_XINLINE void seq_reduce_assign(const int idx, const int M, const bool addto,
const DType* __restrict big, DType *small,
const Shape<ndim>& bshape, const Shape<ndim>& sshape,
const Shape<ndim>& rshape, const Shape<ndim>& rstride) {
Shape<ndim> coord = unravel(idx, sshape);
int j = ravel(coord, bshape);
DType val, residual;
Reducer::SetInitValue(val, residual);
for (int k = 0; k < M; ++k) {
coord = unravel(k, rshape);
Reducer::Reduce(val, OP::Map(big[j + dot(coord, rstride)]), residual);
}
Reducer::Finalize(val, residual);
assign(&small[idx], addto, val);
}
#ifdef __HIPCC__
#include "broadcast_reduce-inl.cuh"
#else
template<int ndim, typename DType, typename OP>
void binary_broadcast_compute(const int N, const bool addto, const DType *lhs,
const DType *rhs, DType *out, const Shape<ndim> lshape,
const Shape<ndim> rshape, const Shape<ndim> oshape) {
for (int idx = 0; idx < N; ++idx) {
binary_broadcast_assign<ndim, DType, OP>(idx, addto, lhs, rhs, out, lshape, rshape, oshape);
}
}
template<int ndim, typename DType, typename OP>
void BinaryBroadcastComputeImpl(Stream<cpu> *s, const OpReqType req,
const TBlob& lhs, const TBlob& rhs, const TBlob& out) {
if (req == kNullOp) return;
int N = out.shape_.Size();
binary_broadcast_compute<ndim, DType, OP>(N, req == kAddTo, lhs.dptr<DType>(), rhs.dptr<DType>(),
out.dptr<DType>(), lhs.shape_.get<ndim>(), rhs.shape_.get<ndim>(),
out.shape_.get<ndim>());
}
template<typename Reducer, int ndim, typename DType, typename OP>
void seq_reduce_compute(const int N, const int M, const bool addto,
const DType *big, DType *small, const Shape<ndim> bshape,
const Shape<ndim> sshape, const Shape<ndim> rshape,
const Shape<ndim> rstride) {
#pragma omp parallel for num_threads(engine::OpenMP::Get()->GetRecommendedOMPThreadCount())
for (int idx = 0; idx < N; ++idx) {
seq_reduce_assign<Reducer, ndim, DType, OP>(idx, M, addto, big, small, bshape, sshape, rshape,
rstride);
}
}
template <typename Reducer, int ndim, typename DType, typename OP>
void seq_reduce_compute_extra_mem(const int N, const int M, const bool addto,
const DType* big, DType* small,
const Shape<ndim> bshape,
const Shape<ndim> sshape,
const Shape<ndim> rshape,
const Shape<ndim> rstride,
const index_t* ws_dptr) {
#pragma omp parallel for num_threads(engine::OpenMP::Get()->GetRecommendedOMPThreadCount())
for (int idx = 0; idx < N; ++idx) {
Shape<ndim> coord = unravel(idx, sshape);
int j = ravel(coord, bshape);
DType val, residual;
Reducer::SetInitValue(val, residual);
for (int k = 0; k < M; ++k) {
Reducer::Reduce(val, OP::Map(big[j + ws_dptr[k]]), residual);
}
assign(&small[idx], addto, val);
}
}
template <typename Reducer, int ndim, typename DType, typename OP>
void Reduce(Stream<cpu>* s, const TBlob& small, const OpReqType req,
const Tensor<cpu, 1, char>& workspace, const TBlob& big) {
if (req == kNullOp) return;
Shape<ndim> rshape, rstride;
diff(small.shape_.get<ndim>(), big.shape_.get<ndim>(), &rshape, &rstride);
int N = small.shape_.Size(), M = rshape.Size();
seq_reduce_compute<Reducer, ndim, DType, OP>(
N, M, req == kAddTo, big.dptr<DType>(), small.dptr<DType>(),
big.shape_.get<ndim>(), small.shape_.get<ndim>(), rshape, rstride);
}
template <typename Reducer, int ndim, typename DType, typename OP>
void ReduceWithExtraMem(Stream<cpu>* s, const TBlob& small, const OpReqType req,
const Tensor<cpu, 1, char>& workspace, const TBlob& big) {
using namespace mxnet_op;
if (req == kNullOp) return;
Shape<ndim> rshape, rstride;
diff(small.shape_.get<ndim>(), big.shape_.get<ndim>(), &rshape, &rstride);
index_t* ws_dptr = reinterpret_cast<index_t*>(workspace.dptr_);
int N = small.shape_.Size(), M = rshape.Size();
#pragma omp parallel for num_threads(engine::OpenMP::Get()->GetRecommendedOMPThreadCount())
for (int k = 0; k < M; k++) {
Shape<ndim> coord = unravel(k, rshape);
ws_dptr[k] = dot(coord, rstride);
}
seq_reduce_compute_extra_mem<Reducer, ndim, DType, OP>(
N, M, req == kAddTo, big.dptr<DType>(), small.dptr<DType>(), big.shape_.get<ndim>(),
small.shape_.get<ndim>(), rshape, rstride, ws_dptr);
}
template<int ndim, typename DType>
size_t ReduceWorkspaceSize(Stream<cpu> *s, const TShape& small, const OpReqType req,
const TShape& big) {
return 0;
}
template<int ndim, typename DType>
size_t ReduceWorkspaceSize(Stream<cpu> *s, const TShape& small, const OpReqType req,
const TShape& big, const TShape& lhs, const TShape& rhs) {
return 0;
}
template<typename Reducer, int ndim, typename DType, typename OP1, typename OP2>
MSHADOW_XINLINE void seq_reduce_assign(const int idx, const int M, const bool addto,
const DType* __restrict big, const DType* __restrict lhs,
const DType* __restrict rhs, DType *small,
const Shape<ndim>& big_shape, const Shape<ndim>& lhs_shape0,
const Shape<ndim>& rhs_shape0,
const Shape<ndim>& small_shape, const Shape<ndim>& rshape,
const Shape<ndim>& lhs_shape, const Shape<ndim>& rhs_shape,
const Shape<ndim>& rstride, const Shape<ndim>& lhs_stride,
const Shape<ndim>& rhs_stride) {
Shape<ndim> coord = unravel(idx, small_shape);
const int idx_big0 = ravel(coord, big_shape);
const int idx_lhs0 = ravel(coord, lhs_shape0);
const int idx_rhs0 = ravel(coord, rhs_shape0);
DType val, residual;
Reducer::SetInitValue(val, residual);
for (int k = 0; k < M; ++k) {
Shape<ndim> coord_big = unravel(k, rshape);
int idx_big = idx_big0 + dot(coord_big, rstride);
Shape<ndim> coord_lhs = unravel(k, lhs_shape);
int idx_lhs = idx_lhs0 + dot(coord_lhs, lhs_stride);
Shape<ndim> coord_rhs = unravel(k, rhs_shape);
int idx_rhs = idx_rhs0 + dot(coord_rhs, rhs_stride);
Reducer::Reduce(val, OP1::Map(big[idx_big], OP2::Map(lhs[idx_lhs], rhs[idx_rhs])), residual);
}
Reducer::Finalize(val, residual);
assign(&small[idx], addto, val);
}
template<typename Reducer, int ndim, typename DType, typename OP1, typename OP2>
void seq_reduce_compute(const int N, const int M, const bool addto,
const DType *big, const DType *lhs, const DType *rhs, DType *small,
const Shape<ndim> big_shape, const Shape<ndim> small_shape,
const Shape<ndim> rshape, const Shape<ndim> rstride,
const Shape<ndim> lhs_shape, const Shape<ndim> lhs_stride,
const Shape<ndim> rhs_shape, const Shape<ndim> rhs_stride,
const Shape<ndim>& lhs_shape0, const Shape<ndim>& rhs_shape0) {
#pragma omp parallel for num_threads(engine::OpenMP::Get()->GetRecommendedOMPThreadCount())
for (int idx = 0; idx < N; ++idx) {
seq_reduce_assign<Reducer, ndim, DType, OP1, OP2>(idx, M, addto, big, lhs, rhs, small,
big_shape, lhs_shape0, rhs_shape0, small_shape, rshape, lhs_shape, rhs_shape, rstride,
lhs_stride, rhs_stride);
}
}
template<typename Reducer, int ndim, typename DType, typename OP1, typename OP2>
void Reduce(Stream<cpu> *s, const TBlob& small, const OpReqType req,
const Tensor<cpu, 1, char>& workspace, const TBlob& big, const TBlob& lhs,
const TBlob& rhs) {
if (req == kNullOp) return;
Shape<ndim> rshape, rstride;
diff(small.shape_.get<ndim>(), big.shape_.get<ndim>(), &rshape, &rstride);
int N = small.shape_.Size();
int M = rshape.Size();
Shape<ndim> lhs_shape, lhs_stride;
diff(small.shape_.get<ndim>(), lhs.shape_.get<ndim>(), &lhs_shape, &lhs_stride);
Shape<ndim> rhs_shape, rhs_stride;
diff(small.shape_.get<ndim>(), rhs.shape_.get<ndim>(), &rhs_shape, &rhs_stride);
seq_reduce_compute<Reducer, ndim, DType, OP1, OP2>(
N, M, req == kAddTo,
big.dptr<DType>(), lhs.dptr<DType>(), rhs.dptr<DType>(), small.dptr<DType>(),
big.shape_.get<ndim>(), small.shape_.get<ndim>(),
rshape, rstride,
lhs_shape, lhs_stride,
rhs_shape, rhs_stride,
lhs.shape_.get<ndim>(), rhs.shape_.get<ndim>());
}
#endif
} // namespace broadcast
} // namespace op
} // namespace mxnet
#endif // MXNET_OPERATOR_TENSOR_BROADCAST_REDUCE_INL_H_
|
3d7pt.c | /*
* Order-1, 3D 7 point stencil
* Adapted from PLUTO and Pochoir test bench
*
* Tareq Malas
*/
#include <stdio.h>
#include <stdlib.h>
#include <sys/time.h>
#ifdef LIKWID_PERFMON
#include <likwid.h>
#endif
#include "print_utils.h"
#define TESTS 2
#define MAX(a,b) ((a) > (b) ? a : b)
#define MIN(a,b) ((a) < (b) ? a : b)
/* Subtract the `struct timeval' values X and Y,
* storing the result in RESULT.
*
* Return 1 if the difference is negative, otherwise 0.
*/
int timeval_subtract(struct timeval *result, struct timeval *x, struct timeval *y)
{
/* Perform the carry for the later subtraction by updating y. */
if (x->tv_usec < y->tv_usec)
{
int nsec = (y->tv_usec - x->tv_usec) / 1000000 + 1;
y->tv_usec -= 1000000 * nsec;
y->tv_sec += nsec;
}
if (x->tv_usec - y->tv_usec > 1000000)
{
int nsec = (x->tv_usec - y->tv_usec) / 1000000;
y->tv_usec += 1000000 * nsec;
y->tv_sec -= nsec;
}
/* Compute the time remaining to wait.
* tv_usec is certainly positive.
*/
result->tv_sec = x->tv_sec - y->tv_sec;
result->tv_usec = x->tv_usec - y->tv_usec;
/* Return 1 if result is negative. */
return x->tv_sec < y->tv_sec;
}
int main(int argc, char *argv[])
{
int t, i, j, k, test;
int Nx, Ny, Nz, Nt;
if (argc > 3) {
Nx = atoi(argv[1])+2;
Ny = atoi(argv[2])+2;
Nz = atoi(argv[3])+2;
}
if (argc > 4)
Nt = atoi(argv[4]);
double ****A = (double ****) malloc(sizeof(double***)*2);
A[0] = (double ***) malloc(sizeof(double**)*Nz);
A[1] = (double ***) malloc(sizeof(double**)*Nz);
for(i=0; i<Nz; i++){
A[0][i] = (double**) malloc(sizeof(double*)*Ny);
A[1][i] = (double**) malloc(sizeof(double*)*Ny);
for(j=0;j<Ny;j++){
A[0][i][j] = (double*) malloc(sizeof(double)*Nx);
A[1][i][j] = (double*) malloc(sizeof(double)*Nx);
}
}
// tile size information, including extra element to decide the list length
int *tile_size = (int*) malloc(sizeof(int));
tile_size[0] = -1;
// The list is modified here before source-to-source transformations
tile_size = (int*) realloc((void *)tile_size, sizeof(int)*5);
tile_size[0] = 32;
tile_size[1] = 32;
tile_size[2] = 8;
tile_size[3] = 1024;
tile_size[4] = -1;
// for timekeeping
int ts_return = -1;
struct timeval start, end, result;
double tdiff = 0.0, min_tdiff=1.e100;
const int BASE = 1024;
const double alpha = 0.0876;
const double beta = 0.0765;
// initialize variables
//
srand(42);
for (i = 1; i < Nz; i++) {
for (j = 1; j < Ny; j++) {
for (k = 1; k < Nx; k++) {
A[0][i][j][k] = 1.0 * (rand() % BASE);
}
}
}
#ifdef LIKWID_PERFMON
LIKWID_MARKER_INIT;
#pragma omp parallel
{
LIKWID_MARKER_THREADINIT;
#pragma omp barrier
LIKWID_MARKER_START("calc");
}
#endif
int num_threads = 1;
#if defined(_OPENMP)
num_threads = omp_get_max_threads();
#endif
for(test=0; test<TESTS; test++){
gettimeofday(&start, 0);
// serial execution - Addition: 6 && Multiplication: 2
#pragma scop
for (t = 0; t < Nt-1; t++) {
for (i = 1; i < Nz-1; i++) {
for (j = 1; j < Ny-1; j++) {
for (k = 1; k < Nx-1; k++) {
A[(t+1)%2][i][j][k] = alpha * (A[t%2][i][j][k])
+ beta * (A[t%2][i - 1][j][k] + A[t%2][i][j - 1][k] + A[t%2][i][j][k - 1] +
A[t%2][i + 1][j][k] + A[t%2][i][j + 1][k] + A[t%2][i][j][k + 1]);
}
}
}
}
#pragma endscop
gettimeofday(&end, 0);
ts_return = timeval_subtract(&result, &end, &start);
tdiff = (double) (result.tv_sec + result.tv_usec * 1.0e-6);
min_tdiff = min(min_tdiff, tdiff);
printf("Rank 0 TEST# %d time: %f\n", test, tdiff);
}
PRINT_RESULTS(1, "constant")
#ifdef LIKWID_PERFMON
#pragma omp parallel
{
LIKWID_MARKER_STOP("calc");
}
LIKWID_MARKER_CLOSE;
#endif
// Free allocated arrays (Causing performance degradation
/* for(i=0; i<Nz; i++){
for(j=0;j<Ny;j++){
free(A[0][i][j]);
free(A[1][i][j]);
}
free(A[0][i]);
free(A[1][i]);
}
free(A[0]);
free(A[1]);
*/
return 0;
}
|
blas_dh.c | /*BHEADER**********************************************************************
* Copyright (c) 2008, Lawrence Livermore National Security, LLC.
* Produced at the Lawrence Livermore National Laboratory.
* This file is part of HYPRE. See file COPYRIGHT for details.
*
* HYPRE is free software; you can redistribute it and/or modify it under the
* terms of the GNU Lesser General Public License (as published by the Free
* Software Foundation) version 2.1 dated February 1999.
*
* $Revision$
***********************************************************************EHEADER*/
#include "_hypre_Euclid.h"
/* #include "blas_dh.h" */
#undef __FUNC__
#define __FUNC__ "matvec_euclid_seq"
void matvec_euclid_seq(HYPRE_Int n, HYPRE_Int *rp, HYPRE_Int *cval, HYPRE_Real *aval, HYPRE_Real *x, HYPRE_Real *y)
{
START_FUNC_DH
HYPRE_Int i, j;
HYPRE_Int from, to, col;
HYPRE_Real sum;
if (np_dh > 1) SET_V_ERROR("only for sequential case!\n");
#ifdef USING_OPENMP_DH
#pragma omp parallel private(j, col, sum, from, to) \
default(shared) \
firstprivate(n, rp, cval, aval, x, y)
#endif
{
#ifdef USING_OPENMP_DH
#pragma omp for schedule(static)
#endif
for (i=0; i<n; ++i) {
sum = 0.0;
from = rp[i];
to = rp[i+1];
for (j=from; j<to; ++j) {
col = cval[j];
sum += (aval[j]*x[col]);
}
y[i] = sum;
}
}
END_FUNC_DH
}
#undef __FUNC__
#define __FUNC__ "Axpy"
void Axpy(HYPRE_Int n, HYPRE_Real alpha, HYPRE_Real *x, HYPRE_Real *y)
{
START_FUNC_DH
HYPRE_Int i;
#ifdef USING_OPENMP_DH
#pragma omp parallel for schedule(static) firstprivate(alpha, x, y) \
private(i)
#endif
for (i=0; i<n; ++i) {
y[i] = alpha*x[i] + y[i];
}
END_FUNC_DH
}
#undef __FUNC__
#define __FUNC__ "CopyVec"
void CopyVec(HYPRE_Int n, HYPRE_Real *xIN, HYPRE_Real *yOUT)
{
START_FUNC_DH
HYPRE_Int i;
#ifdef USING_OPENMP_DH
#pragma omp parallel for schedule(static) firstprivate(yOUT, xIN) \
private(i)
#endif
for (i=0; i<n; ++i) {
yOUT[i] = xIN[i];
}
END_FUNC_DH
}
#undef __FUNC__
#define __FUNC__ "ScaleVec"
void ScaleVec(HYPRE_Int n, HYPRE_Real alpha, HYPRE_Real *x)
{
START_FUNC_DH
HYPRE_Int i;
#ifdef USING_OPENMP_DH
#pragma omp parallel for schedule(static) firstprivate(alpha, x) \
private(i)
#endif
for (i=0; i<n; ++i) {
x[i] *= alpha;
}
END_FUNC_DH
}
#undef __FUNC__
#define __FUNC__ "InnerProd"
HYPRE_Real InnerProd(HYPRE_Int n, HYPRE_Real *x, HYPRE_Real *y)
{
START_FUNC_DH
HYPRE_Real result, local_result = 0.0;
HYPRE_Int i;
#ifdef USING_OPENMP_DH
#pragma omp parallel for schedule(static) firstprivate(x, y) \
private(i) \
reduction(+:local_result)
#endif
for (i=0; i<n; ++i) {
local_result += x[i] * y[i];
}
if (np_dh > 1) {
hypre_MPI_Allreduce(&local_result, &result, 1, hypre_MPI_DOUBLE, hypre_MPI_SUM, comm_dh);
} else {
result = local_result;
}
END_FUNC_VAL(result)
}
#undef __FUNC__
#define __FUNC__ "Norm2"
HYPRE_Real Norm2(HYPRE_Int n, HYPRE_Real *x)
{
START_FUNC_DH
HYPRE_Real result, local_result = 0.0;
HYPRE_Int i;
#ifdef USING_OPENMP_DH
#pragma omp parallel for schedule(static) firstprivate(x) \
private(i) \
reduction(+:local_result)
#endif
for (i=0; i<n; ++i) {
local_result += (x[i]*x[i]);
}
if (np_dh > 1) {
hypre_MPI_Allreduce(&local_result, &result, 1, hypre_MPI_DOUBLE, hypre_MPI_SUM, comm_dh);
} else {
result = local_result;
}
result = sqrt(result);
END_FUNC_VAL(result)
}
|
GB_binop__rminus_fp32.c |
//------------------------------------------------------------------------------
// GB_binop: hard-coded functions for each built-in binary operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2021, All Rights Reserved.
// SPDX-License-Identifier: Apache-2.0
//------------------------------------------------------------------------------
// If this file is in the Generated2/ folder, do not edit it
// (it is auto-generated from Generator/*).
#include "GB.h"
#ifndef GBCOMPACT
#include "GB_emult.h"
#include "GB_control.h"
#include "GB_ek_slice.h"
#include "GB_dense.h"
#include "GB_atomics.h"
#include "GB_bitmap_assign_methods.h"
#include "GB_binop__include.h"
// C=binop(A,B) is defined by the following types and operators:
// A+B function (eWiseAdd): GB (_AaddB__rminus_fp32)
// A.*B function (eWiseMult): GB (_AemultB_08__rminus_fp32)
// A.*B function (eWiseMult): GB (_AemultB_02__rminus_fp32)
// A.*B function (eWiseMult): GB (_AemultB_04__rminus_fp32)
// A.*B function (eWiseMult): GB (_AemultB_bitmap__rminus_fp32)
// A*D function (colscale): GB (_AxD__rminus_fp32)
// D*A function (rowscale): GB (_DxB__rminus_fp32)
// C+=B function (dense accum): GB (_Cdense_accumB__rminus_fp32)
// C+=b function (dense accum): GB (_Cdense_accumb__rminus_fp32)
// C+=A+B function (dense ewise3): GB (_Cdense_ewise3_accum__rminus_fp32)
// C=A+B function (dense ewise3): GB (_Cdense_ewise3_noaccum__rminus_fp32)
// C=scalar+B GB (_bind1st__rminus_fp32)
// C=scalar+B' GB (_bind1st_tran__rminus_fp32)
// C=A+scalar GB (_bind2nd__rminus_fp32)
// C=A'+scalar GB (_bind2nd_tran__rminus_fp32)
// C type: float
// A type: float
// A pattern? 0
// B type: float
// B pattern? 0
// BinaryOp: cij = (bij - aij)
#define GB_ATYPE \
float
#define GB_BTYPE \
float
#define GB_CTYPE \
float
// true if the types of A and B are identical
#define GB_ATYPE_IS_BTYPE \
1
// true if the types of C and A are identical
#define GB_CTYPE_IS_ATYPE \
1
// true if the types of C and B are identical
#define GB_CTYPE_IS_BTYPE \
1
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA,A_iso) \
float aij = GBX (Ax, pA, A_iso)
// true if values of A are not used
#define GB_A_IS_PATTERN \
0 \
// bij = Bx [pB]
#define GB_GETB(bij,Bx,pB,B_iso) \
float bij = GBX (Bx, pB, B_iso)
// true if values of B are not used
#define GB_B_IS_PATTERN \
0 \
// declare scalar of the same type as C
#define GB_CTYPE_SCALAR(t) \
float t
// cij = Ax [pA]
#define GB_COPY_A_TO_C(cij,Ax,pA,A_iso) \
cij = GBX (Ax, pA, A_iso)
// cij = Bx [pB]
#define GB_COPY_B_TO_C(cij,Bx,pB,B_iso) \
cij = GBX (Bx, pB, B_iso)
#define GB_CX(p) Cx [p]
// binary operator
#define GB_BINOP(z,x,y,i,j) \
z = (y - x) ;
// true if the binop must be flipped
#define GB_BINOP_FLIP \
0
// op is second
#define GB_OP_IS_SECOND \
0
// do the numerical phases of GB_add and GB_emult
#define GB_PHASE_2_OF_2
// hard-coded loops can be vectorized
#define GB_PRAGMA_SIMD_VECTORIZE GB_PRAGMA_SIMD
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_RMINUS || GxB_NO_FP32 || GxB_NO_RMINUS_FP32)
//------------------------------------------------------------------------------
// C += A+B, all 3 matrices dense
//------------------------------------------------------------------------------
// The op must be MIN, MAX, PLUS, MINUS, RMINUS, TIMES, DIV, or RDIV.
void GB (_Cdense_ewise3_accum__rminus_fp32)
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix B,
const int nthreads
)
{
#include "GB_dense_ewise3_accum_template.c"
}
//------------------------------------------------------------------------------
// C = A+B, all 3 matrices dense
//------------------------------------------------------------------------------
void GB (_Cdense_ewise3_noaccum__rminus_fp32)
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix B,
const int nthreads
)
{
#include "GB_dense_ewise3_noaccum_template.c"
}
//------------------------------------------------------------------------------
// C += B, accumulate a sparse matrix into a dense matrix
//------------------------------------------------------------------------------
GrB_Info GB (_Cdense_accumB__rminus_fp32)
(
GrB_Matrix C,
const GrB_Matrix B,
const int64_t *B_ek_slicing, const int B_ntasks, const int B_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
{
#include "GB_dense_subassign_23_template.c"
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C += b, accumulate a scalar into a dense matrix
//------------------------------------------------------------------------------
GrB_Info GB (_Cdense_accumb__rminus_fp32)
(
GrB_Matrix C,
const GB_void *p_bwork,
const int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
{
// get the scalar b for C += b, of type float
float bwork = (*((float *) p_bwork)) ;
#include "GB_dense_subassign_22_template.c"
return (GrB_SUCCESS) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = A*D, column scale with diagonal D matrix
//------------------------------------------------------------------------------
GrB_Info GB (_AxD__rminus_fp32)
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix D,
const int64_t *A_ek_slicing, const int A_ntasks, const int A_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
float *restrict Cx = (float *) C->x ;
#include "GB_AxB_colscale_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = D*B, row scale with diagonal D matrix
//------------------------------------------------------------------------------
GrB_Info GB (_DxB__rminus_fp32)
(
GrB_Matrix C,
const GrB_Matrix D,
const GrB_Matrix B,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
float *restrict Cx = (float *) C->x ;
#include "GB_AxB_rowscale_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseAdd: C=A+B, C<M>=A+B, C<!M>=A+B
//------------------------------------------------------------------------------
GrB_Info GB (_AaddB__rminus_fp32)
(
GrB_Matrix C,
const int C_sparsity,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const bool is_eWiseUnion,
const GB_void *alpha_scalar_in,
const GB_void *beta_scalar_in,
const bool Ch_is_Mh,
const int64_t *restrict C_to_M,
const int64_t *restrict C_to_A,
const int64_t *restrict C_to_B,
const GB_task_struct *restrict TaskList,
const int C_ntasks,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
GB_WERK_DECLARE (M_ek_slicing, int64_t) ;
GB_WERK_DECLARE (A_ek_slicing, int64_t) ;
GB_WERK_DECLARE (B_ek_slicing, int64_t) ;
float alpha_scalar ;
float beta_scalar ;
if (is_eWiseUnion)
{
alpha_scalar = (*((float *) alpha_scalar_in)) ;
beta_scalar = (*((float *) beta_scalar_in )) ;
}
#include "GB_add_template.c"
GB_FREE_WORKSPACE ;
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C=A.*B, C<M>=A.*B, or C<M!>=A.*B where C is sparse/hyper
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_08__rminus_fp32)
(
GrB_Matrix C,
const int C_sparsity,
const int ewise_method,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *restrict C_to_M,
const int64_t *restrict C_to_A,
const int64_t *restrict C_to_B,
const GB_task_struct *restrict TaskList,
const int C_ntasks,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_emult_08_meta.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C<#> = A.*B when A is sparse/hyper and B is bitmap/full
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_02__rminus_fp32)
(
GrB_Matrix C,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const bool flipxy,
const int64_t *restrict Cp_kfirst,
const int64_t *A_ek_slicing, const int A_ntasks, const int A_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#if GB_BINOP_FLIP
// The operator is not commutative, and does not have a flipped
// variant. For example z=atan2(y,x).
if (flipxy)
{
// use fmult(y,x)
#undef GB_FLIPPED
#define GB_FLIPPED 1
#include "GB_emult_02_template.c"
}
else
{
// use fmult(x,y)
#undef GB_FLIPPED
#define GB_FLIPPED 0
#include "GB_emult_02_template.c"
}
#else
// No need to handle the flip: the operator is either commutative, or
// has been handled by changing z=div(y,x) to z=rdiv(x,y) for example.
#undef GB_FLIPPED
#define GB_FLIPPED 0
#include "GB_emult_02_template.c"
#endif
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C<M> = A.*B, M sparse/hyper, A and B bitmap/full
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_04__rminus_fp32)
(
GrB_Matrix C,
const GrB_Matrix M,
const bool Mask_struct,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *restrict Cp_kfirst,
const int64_t *M_ek_slicing, const int M_ntasks, const int M_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_emult_04_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C=A.*B, C<M>=A.*B, C<!M>=A.*B where C is bitmap
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_bitmap__rminus_fp32)
(
GrB_Matrix C,
const int ewise_method,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *M_ek_slicing, const int M_ntasks, const int M_nthreads,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_bitmap_emult_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (x,Bx): apply a binary operator to a matrix with scalar bind1st
//------------------------------------------------------------------------------
GrB_Info GB (_bind1st__rminus_fp32)
(
GB_void *Cx_output, // Cx and Bx may be aliased
const GB_void *x_input,
const GB_void *Bx_input,
const int8_t *restrict Bb,
int64_t bnz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
float *Cx = (float *) Cx_output ;
float x = (*((float *) x_input)) ;
float *Bx = (float *) Bx_input ;
int64_t p ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < bnz ; p++)
{
if (!GBB (Bb, p)) continue ;
float bij = GBX (Bx, p, false) ;
Cx [p] = (bij - x) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (Ax,y): apply a binary operator to a matrix with scalar bind2nd
//------------------------------------------------------------------------------
GrB_Info GB (_bind2nd__rminus_fp32)
(
GB_void *Cx_output, // Cx and Ax may be aliased
const GB_void *Ax_input,
const GB_void *y_input,
const int8_t *restrict Ab,
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t p ;
float *Cx = (float *) Cx_output ;
float *Ax = (float *) Ax_input ;
float y = (*((float *) y_input)) ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
if (!GBB (Ab, p)) continue ;
float aij = GBX (Ax, p, false) ;
Cx [p] = (y - aij) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (x, A'): transpose and apply a binary operator
//------------------------------------------------------------------------------
// cij = op (x, aij), no typecasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
float aij = GBX (Ax, pA, false) ; \
Cx [pC] = (aij - x) ; \
}
GrB_Info GB (_bind1st_tran__rminus_fp32)
(
GrB_Matrix C,
const GB_void *x_input,
const GrB_Matrix A,
int64_t *restrict *Workspaces,
const int64_t *restrict A_slice,
int nworkspaces,
int nthreads
)
{
// GB_unop_transpose.c uses GB_ATYPE, but A is
// the 2nd input to binary operator z=f(x,y).
#undef GB_ATYPE
#define GB_ATYPE \
float
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
float x = (*((const float *) x_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
#undef GB_ATYPE
#define GB_ATYPE \
float
}
//------------------------------------------------------------------------------
// C = op (A', y): transpose and apply a binary operator
//------------------------------------------------------------------------------
// cij = op (aij, y), no typecasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
float aij = GBX (Ax, pA, false) ; \
Cx [pC] = (y - aij) ; \
}
GrB_Info GB (_bind2nd_tran__rminus_fp32)
(
GrB_Matrix C,
const GrB_Matrix A,
const GB_void *y_input,
int64_t *restrict *Workspaces,
const int64_t *restrict A_slice,
int nworkspaces,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
float y = (*((const float *) y_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
StmtOpenMP.h | //===- StmtOpenMP.h - Classes for OpenMP directives ------------*- C++ -*-===//
//
// The LLVM Compiler Infrastructure
//
// This file is distributed under the University of Illinois Open Source
// License. See LICENSE.TXT for details.
//
//===----------------------------------------------------------------------===//
/// \file
/// \brief This file defines OpenMP AST classes for executable directives and
/// clauses.
///
//===----------------------------------------------------------------------===//
#ifndef LLVM_CLANG_AST_STMTOPENMP_H
#define LLVM_CLANG_AST_STMTOPENMP_H
#include "clang/AST/Expr.h"
#include "clang/AST/OpenMPClause.h"
#include "clang/AST/Stmt.h"
#include "clang/Basic/OpenMPKinds.h"
#include "clang/Basic/SourceLocation.h"
namespace clang {
//===----------------------------------------------------------------------===//
// AST classes for directives.
//===----------------------------------------------------------------------===//
/// \brief This is a basic class for representing single OpenMP executable
/// directive.
///
class OMPExecutableDirective : public Stmt {
friend class ASTStmtReader;
/// \brief Kind of the directive.
OpenMPDirectiveKind Kind;
/// \brief Starting location of the directive (directive keyword).
SourceLocation StartLoc;
/// \brief Ending location of the directive.
SourceLocation EndLoc;
/// \brief Numbers of clauses.
const unsigned NumClauses;
/// \brief Number of child expressions/stmts.
const unsigned NumChildren;
/// \brief Offset from this to the start of clauses.
/// There are NumClauses pointers to clauses, they are followed by
/// NumChildren pointers to child stmts/exprs (if the directive type
/// requires an associated stmt, then it has to be the first of them).
const unsigned ClausesOffset;
/// \brief Get the clauses storage.
MutableArrayRef<OMPClause *> getClauses() {
OMPClause **ClauseStorage = reinterpret_cast<OMPClause **>(
reinterpret_cast<char *>(this) + ClausesOffset);
return MutableArrayRef<OMPClause *>(ClauseStorage, NumClauses);
}
protected:
/// \brief Build instance of directive of class \a K.
///
/// \param SC Statement class.
/// \param K Kind of OpenMP directive.
/// \param StartLoc Starting location of the directive (directive keyword).
/// \param EndLoc Ending location of the directive.
///
template <typename T>
OMPExecutableDirective(const T *, StmtClass SC, OpenMPDirectiveKind K,
SourceLocation StartLoc, SourceLocation EndLoc,
unsigned NumClauses, unsigned NumChildren)
: Stmt(SC), Kind(K), StartLoc(std::move(StartLoc)),
EndLoc(std::move(EndLoc)), NumClauses(NumClauses),
NumChildren(NumChildren),
ClausesOffset(llvm::alignTo(sizeof(T), alignof(OMPClause *))) {}
/// \brief Sets the list of variables for this clause.
///
/// \param Clauses The list of clauses for the directive.
///
void setClauses(ArrayRef<OMPClause *> Clauses);
/// \brief Set the associated statement for the directive.
///
/// /param S Associated statement.
///
void setAssociatedStmt(Stmt *S) {
assert(hasAssociatedStmt() && "no associated statement.");
*child_begin() = S;
}
public:
/// \brief Iterates over a filtered subrange of clauses applied to a
/// directive.
///
/// This iterator visits only clauses of type SpecificClause.
template <typename SpecificClause>
class specific_clause_iterator
: public llvm::iterator_adaptor_base<
specific_clause_iterator<SpecificClause>,
ArrayRef<OMPClause *>::const_iterator, std::forward_iterator_tag,
const SpecificClause *, ptrdiff_t, const SpecificClause *,
const SpecificClause *> {
ArrayRef<OMPClause *>::const_iterator End;
void SkipToNextClause() {
while (this->I != End && !isa<SpecificClause>(*this->I))
++this->I;
}
public:
explicit specific_clause_iterator(ArrayRef<OMPClause *> Clauses)
: specific_clause_iterator::iterator_adaptor_base(Clauses.begin()),
End(Clauses.end()) {
SkipToNextClause();
}
const SpecificClause *operator*() const {
return cast<SpecificClause>(*this->I);
}
const SpecificClause *operator->() const { return **this; }
specific_clause_iterator &operator++() {
++this->I;
SkipToNextClause();
return *this;
}
};
template <typename SpecificClause>
static llvm::iterator_range<specific_clause_iterator<SpecificClause>>
getClausesOfKind(ArrayRef<OMPClause *> Clauses) {
return {specific_clause_iterator<SpecificClause>(Clauses),
specific_clause_iterator<SpecificClause>(
llvm::makeArrayRef(Clauses.end(), 0))};
}
template <typename SpecificClause>
llvm::iterator_range<specific_clause_iterator<SpecificClause>>
getClausesOfKind() const {
return getClausesOfKind<SpecificClause>(clauses());
}
/// Gets a single clause of the specified kind associated with the
/// current directive iff there is only one clause of this kind (and assertion
/// is fired if there is more than one clause is associated with the
/// directive). Returns nullptr if no clause of this kind is associated with
/// the directive.
template <typename SpecificClause>
const SpecificClause *getSingleClause() const {
auto Clauses = getClausesOfKind<SpecificClause>();
if (Clauses.begin() != Clauses.end()) {
assert(std::next(Clauses.begin()) == Clauses.end() &&
"There are at least 2 clauses of the specified kind");
return *Clauses.begin();
}
return nullptr;
}
/// Returns true if the current directive has one or more clauses of a
/// specific kind.
template <typename SpecificClause>
bool hasClausesOfKind() const {
auto Clauses = getClausesOfKind<SpecificClause>();
return Clauses.begin() != Clauses.end();
}
/// \brief Returns starting location of directive kind.
SourceLocation getLocStart() const { return StartLoc; }
/// \brief Returns ending location of directive.
SourceLocation getLocEnd() const { return EndLoc; }
/// \brief Set starting location of directive kind.
///
/// \param Loc New starting location of directive.
///
void setLocStart(SourceLocation Loc) { StartLoc = Loc; }
/// \brief Set ending location of directive.
///
/// \param Loc New ending location of directive.
///
void setLocEnd(SourceLocation Loc) { EndLoc = Loc; }
/// \brief Get number of clauses.
unsigned getNumClauses() const { return NumClauses; }
/// \brief Returns specified clause.
///
/// \param i Number of clause.
///
OMPClause *getClause(unsigned i) const { return clauses()[i]; }
/// \brief Returns true if directive has associated statement.
bool hasAssociatedStmt() const { return NumChildren > 0; }
/// \brief Returns statement associated with the directive.
Stmt *getAssociatedStmt() const {
assert(hasAssociatedStmt() && "no associated statement.");
return const_cast<Stmt *>(*child_begin());
}
OpenMPDirectiveKind getDirectiveKind() const { return Kind; }
static bool classof(const Stmt *S) {
return S->getStmtClass() >= firstOMPExecutableDirectiveConstant &&
S->getStmtClass() <= lastOMPExecutableDirectiveConstant;
}
child_range children() {
if (!hasAssociatedStmt())
return child_range(child_iterator(), child_iterator());
Stmt **ChildStorage = reinterpret_cast<Stmt **>(getClauses().end());
return child_range(ChildStorage, ChildStorage + NumChildren);
}
ArrayRef<OMPClause *> clauses() { return getClauses(); }
ArrayRef<OMPClause *> clauses() const {
return const_cast<OMPExecutableDirective *>(this)->getClauses();
}
};
/// \brief This represents '#pragma omp parallel' directive.
///
/// \code
/// #pragma omp parallel private(a,b) reduction(+: c,d)
/// \endcode
/// In this example directive '#pragma omp parallel' has clauses 'private'
/// with the variables 'a' and 'b' and 'reduction' with operator '+' and
/// variables 'c' and 'd'.
///
class OMPParallelDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
/// \brief true if the construct has inner cancel directive.
bool HasCancel;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive (directive keyword).
/// \param EndLoc Ending Location of the directive.
///
OMPParallelDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned NumClauses)
: OMPExecutableDirective(this, OMPParallelDirectiveClass, OMPD_parallel,
StartLoc, EndLoc, NumClauses, 1),
HasCancel(false) {}
/// \brief Build an empty directive.
///
/// \param NumClauses Number of clauses.
///
explicit OMPParallelDirective(unsigned NumClauses)
: OMPExecutableDirective(this, OMPParallelDirectiveClass, OMPD_parallel,
SourceLocation(), SourceLocation(), NumClauses,
1),
HasCancel(false) {}
/// \brief Set cancel state.
void setHasCancel(bool Has) { HasCancel = Has; }
public:
/// \brief Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement associated with the directive.
/// \param HasCancel true if this directive has inner cancel directive.
///
static OMPParallelDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
ArrayRef<OMPClause *> Clauses, Stmt *AssociatedStmt, bool HasCancel);
/// \brief Creates an empty directive with the place for \a N clauses.
///
/// \param C AST context.
/// \param NumClauses Number of clauses.
///
static OMPParallelDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses, EmptyShell);
/// \brief Return true if current directive has inner cancel directive.
bool hasCancel() const { return HasCancel; }
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPParallelDirectiveClass;
}
};
/// \brief This is a common base class for loop directives ('omp simd', 'omp
/// for', 'omp for simd' etc.). It is responsible for the loop code generation.
///
class OMPLoopDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
/// \brief Number of collapsed loops as specified by 'collapse' clause.
unsigned CollapsedNum;
/// \brief Offsets to the stored exprs.
/// This enumeration contains offsets to all the pointers to children
/// expressions stored in OMPLoopDirective.
/// The first 9 children are nesessary for all the loop directives, and
/// the next 10 are specific to the worksharing ones.
/// After the fixed children, three arrays of length CollapsedNum are
/// allocated: loop counters, their updates and final values.
/// PrevLowerBound and PrevUpperBound are used to communicate blocking
/// information in composite constructs which require loop blocking
///
enum {
AssociatedStmtOffset = 0,
IterationVariableOffset = 1,
LastIterationOffset = 2,
CalcLastIterationOffset = 3,
PreConditionOffset = 4,
CondOffset = 5,
InitOffset = 6,
IncOffset = 7,
PreInitsOffset = 8,
// The '...End' enumerators do not correspond to child expressions - they
// specify the offset to the end (and start of the following counters/
// updates/finals arrays).
DefaultEnd = 9,
// The following 7 exprs are used by worksharing loops only.
IsLastIterVariableOffset = 9,
LowerBoundVariableOffset = 10,
UpperBoundVariableOffset = 11,
StrideVariableOffset = 12,
EnsureUpperBoundOffset = 13,
NextLowerBoundOffset = 14,
NextUpperBoundOffset = 15,
NumIterationsOffset = 16,
PrevLowerBoundVariableOffset = 17,
PrevUpperBoundVariableOffset = 18,
// Offset to the end (and start of the following counters/updates/finals
// arrays) for worksharing loop directives.
WorksharingEnd = 19,
};
/// \brief Get the counters storage.
MutableArrayRef<Expr *> getCounters() {
Expr **Storage = reinterpret_cast<Expr **>(
&(*(std::next(child_begin(), getArraysOffset(getDirectiveKind())))));
return MutableArrayRef<Expr *>(Storage, CollapsedNum);
}
/// \brief Get the private counters storage.
MutableArrayRef<Expr *> getPrivateCounters() {
Expr **Storage = reinterpret_cast<Expr **>(&*std::next(
child_begin(), getArraysOffset(getDirectiveKind()) + CollapsedNum));
return MutableArrayRef<Expr *>(Storage, CollapsedNum);
}
/// \brief Get the updates storage.
MutableArrayRef<Expr *> getInits() {
Expr **Storage = reinterpret_cast<Expr **>(
&*std::next(child_begin(),
getArraysOffset(getDirectiveKind()) + 2 * CollapsedNum));
return MutableArrayRef<Expr *>(Storage, CollapsedNum);
}
/// \brief Get the updates storage.
MutableArrayRef<Expr *> getUpdates() {
Expr **Storage = reinterpret_cast<Expr **>(
&*std::next(child_begin(),
getArraysOffset(getDirectiveKind()) + 3 * CollapsedNum));
return MutableArrayRef<Expr *>(Storage, CollapsedNum);
}
/// \brief Get the final counter updates storage.
MutableArrayRef<Expr *> getFinals() {
Expr **Storage = reinterpret_cast<Expr **>(
&*std::next(child_begin(),
getArraysOffset(getDirectiveKind()) + 4 * CollapsedNum));
return MutableArrayRef<Expr *>(Storage, CollapsedNum);
}
protected:
/// \brief Build instance of loop directive of class \a Kind.
///
/// \param SC Statement class.
/// \param Kind Kind of OpenMP directive.
/// \param StartLoc Starting location of the directive (directive keyword).
/// \param EndLoc Ending location of the directive.
/// \param CollapsedNum Number of collapsed loops from 'collapse' clause.
/// \param NumClauses Number of clauses.
/// \param NumSpecialChildren Number of additional directive-specific stmts.
///
template <typename T>
OMPLoopDirective(const T *That, StmtClass SC, OpenMPDirectiveKind Kind,
SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, unsigned NumClauses,
unsigned NumSpecialChildren = 0)
: OMPExecutableDirective(That, SC, Kind, StartLoc, EndLoc, NumClauses,
numLoopChildren(CollapsedNum, Kind) +
NumSpecialChildren),
CollapsedNum(CollapsedNum) {}
/// \brief Offset to the start of children expression arrays.
static unsigned getArraysOffset(OpenMPDirectiveKind Kind) {
return (isOpenMPWorksharingDirective(Kind) ||
isOpenMPTaskLoopDirective(Kind) ||
isOpenMPDistributeDirective(Kind))
? WorksharingEnd
: DefaultEnd;
}
/// \brief Children number.
static unsigned numLoopChildren(unsigned CollapsedNum,
OpenMPDirectiveKind Kind) {
return getArraysOffset(Kind) + 5 * CollapsedNum; // Counters,
// PrivateCounters, Inits,
// Updates and Finals
}
void setIterationVariable(Expr *IV) {
*std::next(child_begin(), IterationVariableOffset) = IV;
}
void setLastIteration(Expr *LI) {
*std::next(child_begin(), LastIterationOffset) = LI;
}
void setCalcLastIteration(Expr *CLI) {
*std::next(child_begin(), CalcLastIterationOffset) = CLI;
}
void setPreCond(Expr *PC) {
*std::next(child_begin(), PreConditionOffset) = PC;
}
void setCond(Expr *Cond) {
*std::next(child_begin(), CondOffset) = Cond;
}
void setInit(Expr *Init) { *std::next(child_begin(), InitOffset) = Init; }
void setInc(Expr *Inc) { *std::next(child_begin(), IncOffset) = Inc; }
void setPreInits(Stmt *PreInits) {
*std::next(child_begin(), PreInitsOffset) = PreInits;
}
void setIsLastIterVariable(Expr *IL) {
assert((isOpenMPWorksharingDirective(getDirectiveKind()) ||
isOpenMPTaskLoopDirective(getDirectiveKind()) ||
isOpenMPDistributeDirective(getDirectiveKind())) &&
"expected worksharing loop directive");
*std::next(child_begin(), IsLastIterVariableOffset) = IL;
}
void setLowerBoundVariable(Expr *LB) {
assert((isOpenMPWorksharingDirective(getDirectiveKind()) ||
isOpenMPTaskLoopDirective(getDirectiveKind()) ||
isOpenMPDistributeDirective(getDirectiveKind())) &&
"expected worksharing loop directive");
*std::next(child_begin(), LowerBoundVariableOffset) = LB;
}
void setUpperBoundVariable(Expr *UB) {
assert((isOpenMPWorksharingDirective(getDirectiveKind()) ||
isOpenMPTaskLoopDirective(getDirectiveKind()) ||
isOpenMPDistributeDirective(getDirectiveKind())) &&
"expected worksharing loop directive");
*std::next(child_begin(), UpperBoundVariableOffset) = UB;
}
void setStrideVariable(Expr *ST) {
assert((isOpenMPWorksharingDirective(getDirectiveKind()) ||
isOpenMPTaskLoopDirective(getDirectiveKind()) ||
isOpenMPDistributeDirective(getDirectiveKind())) &&
"expected worksharing loop directive");
*std::next(child_begin(), StrideVariableOffset) = ST;
}
void setEnsureUpperBound(Expr *EUB) {
assert((isOpenMPWorksharingDirective(getDirectiveKind()) ||
isOpenMPTaskLoopDirective(getDirectiveKind()) ||
isOpenMPDistributeDirective(getDirectiveKind())) &&
"expected worksharing loop directive");
*std::next(child_begin(), EnsureUpperBoundOffset) = EUB;
}
void setNextLowerBound(Expr *NLB) {
assert((isOpenMPWorksharingDirective(getDirectiveKind()) ||
isOpenMPTaskLoopDirective(getDirectiveKind()) ||
isOpenMPDistributeDirective(getDirectiveKind())) &&
"expected worksharing loop directive");
*std::next(child_begin(), NextLowerBoundOffset) = NLB;
}
void setNextUpperBound(Expr *NUB) {
assert((isOpenMPWorksharingDirective(getDirectiveKind()) ||
isOpenMPTaskLoopDirective(getDirectiveKind()) ||
isOpenMPDistributeDirective(getDirectiveKind())) &&
"expected worksharing loop directive");
*std::next(child_begin(), NextUpperBoundOffset) = NUB;
}
void setNumIterations(Expr *NI) {
assert((isOpenMPWorksharingDirective(getDirectiveKind()) ||
isOpenMPTaskLoopDirective(getDirectiveKind()) ||
isOpenMPDistributeDirective(getDirectiveKind())) &&
"expected worksharing loop directive");
*std::next(child_begin(), NumIterationsOffset) = NI;
}
void setPrevLowerBoundVariable(Expr *PrevLB) {
assert((isOpenMPWorksharingDirective(getDirectiveKind()) ||
isOpenMPTaskLoopDirective(getDirectiveKind()) ||
isOpenMPDistributeDirective(getDirectiveKind())) &&
"expected worksharing loop directive");
*std::next(child_begin(), PrevLowerBoundVariableOffset) = PrevLB;
}
void setPrevUpperBoundVariable(Expr *PrevUB) {
assert((isOpenMPWorksharingDirective(getDirectiveKind()) ||
isOpenMPTaskLoopDirective(getDirectiveKind()) ||
isOpenMPDistributeDirective(getDirectiveKind())) &&
"expected worksharing loop directive");
*std::next(child_begin(), PrevUpperBoundVariableOffset) = PrevUB;
}
void setCounters(ArrayRef<Expr *> A);
void setPrivateCounters(ArrayRef<Expr *> A);
void setInits(ArrayRef<Expr *> A);
void setUpdates(ArrayRef<Expr *> A);
void setFinals(ArrayRef<Expr *> A);
public:
/// \brief The expressions built for the OpenMP loop CodeGen for the
/// whole collapsed loop nest.
struct HelperExprs {
/// \brief Loop iteration variable.
Expr *IterationVarRef;
/// \brief Loop last iteration number.
Expr *LastIteration;
/// \brief Loop number of iterations.
Expr *NumIterations;
/// \brief Calculation of last iteration.
Expr *CalcLastIteration;
/// \brief Loop pre-condition.
Expr *PreCond;
/// \brief Loop condition.
Expr *Cond;
/// \brief Loop iteration variable init.
Expr *Init;
/// \brief Loop increment.
Expr *Inc;
/// \brief IsLastIteration - local flag variable passed to runtime.
Expr *IL;
/// \brief LowerBound - local variable passed to runtime.
Expr *LB;
/// \brief UpperBound - local variable passed to runtime.
Expr *UB;
/// \brief Stride - local variable passed to runtime.
Expr *ST;
/// \brief EnsureUpperBound -- expression LB = min(LB, NumIterations).
Expr *EUB;
/// \brief Update of LowerBound for statically sheduled 'omp for' loops.
Expr *NLB;
/// \brief Update of UpperBound for statically sheduled 'omp for' loops.
Expr *NUB;
/// \brief PreviousLowerBound - local variable passed to runtime in the
/// enclosing schedule or null if that does not apply.
Expr *PrevLB;
/// \brief PreviousUpperBound - local variable passed to runtime in the
/// enclosing schedule or null if that does not apply.
Expr *PrevUB;
/// \brief Counters Loop counters.
SmallVector<Expr *, 4> Counters;
/// \brief PrivateCounters Loop counters.
SmallVector<Expr *, 4> PrivateCounters;
/// \brief Expressions for loop counters inits for CodeGen.
SmallVector<Expr *, 4> Inits;
/// \brief Expressions for loop counters update for CodeGen.
SmallVector<Expr *, 4> Updates;
/// \brief Final loop counter values for GodeGen.
SmallVector<Expr *, 4> Finals;
/// Init statement for all captured expressions.
Stmt *PreInits;
/// \brief Check if all the expressions are built (does not check the
/// worksharing ones).
bool builtAll() {
return IterationVarRef != nullptr && LastIteration != nullptr &&
NumIterations != nullptr && PreCond != nullptr &&
Cond != nullptr && Init != nullptr && Inc != nullptr;
}
/// \brief Initialize all the fields to null.
/// \param Size Number of elements in the counters/finals/updates arrays.
void clear(unsigned Size) {
IterationVarRef = nullptr;
LastIteration = nullptr;
CalcLastIteration = nullptr;
PreCond = nullptr;
Cond = nullptr;
Init = nullptr;
Inc = nullptr;
IL = nullptr;
LB = nullptr;
UB = nullptr;
ST = nullptr;
EUB = nullptr;
NLB = nullptr;
NUB = nullptr;
NumIterations = nullptr;
PrevLB = nullptr;
PrevUB = nullptr;
Counters.resize(Size);
PrivateCounters.resize(Size);
Inits.resize(Size);
Updates.resize(Size);
Finals.resize(Size);
for (unsigned i = 0; i < Size; ++i) {
Counters[i] = nullptr;
PrivateCounters[i] = nullptr;
Inits[i] = nullptr;
Updates[i] = nullptr;
Finals[i] = nullptr;
}
PreInits = nullptr;
}
};
/// \brief Get number of collapsed loops.
unsigned getCollapsedNumber() const { return CollapsedNum; }
Expr *getIterationVariable() const {
return const_cast<Expr *>(reinterpret_cast<const Expr *>(
*std::next(child_begin(), IterationVariableOffset)));
}
Expr *getLastIteration() const {
return const_cast<Expr *>(reinterpret_cast<const Expr *>(
*std::next(child_begin(), LastIterationOffset)));
}
Expr *getCalcLastIteration() const {
return const_cast<Expr *>(reinterpret_cast<const Expr *>(
*std::next(child_begin(), CalcLastIterationOffset)));
}
Expr *getPreCond() const {
return const_cast<Expr *>(reinterpret_cast<const Expr *>(
*std::next(child_begin(), PreConditionOffset)));
}
Expr *getCond() const {
return const_cast<Expr *>(
reinterpret_cast<const Expr *>(*std::next(child_begin(), CondOffset)));
}
Expr *getInit() const {
return const_cast<Expr *>(
reinterpret_cast<const Expr *>(*std::next(child_begin(), InitOffset)));
}
Expr *getInc() const {
return const_cast<Expr *>(
reinterpret_cast<const Expr *>(*std::next(child_begin(), IncOffset)));
}
const Stmt *getPreInits() const {
return *std::next(child_begin(), PreInitsOffset);
}
Stmt *getPreInits() { return *std::next(child_begin(), PreInitsOffset); }
Expr *getIsLastIterVariable() const {
assert((isOpenMPWorksharingDirective(getDirectiveKind()) ||
isOpenMPTaskLoopDirective(getDirectiveKind()) ||
isOpenMPDistributeDirective(getDirectiveKind())) &&
"expected worksharing loop directive");
return const_cast<Expr *>(reinterpret_cast<const Expr *>(
*std::next(child_begin(), IsLastIterVariableOffset)));
}
Expr *getLowerBoundVariable() const {
assert((isOpenMPWorksharingDirective(getDirectiveKind()) ||
isOpenMPTaskLoopDirective(getDirectiveKind()) ||
isOpenMPDistributeDirective(getDirectiveKind())) &&
"expected worksharing loop directive");
return const_cast<Expr *>(reinterpret_cast<const Expr *>(
*std::next(child_begin(), LowerBoundVariableOffset)));
}
Expr *getUpperBoundVariable() const {
assert((isOpenMPWorksharingDirective(getDirectiveKind()) ||
isOpenMPTaskLoopDirective(getDirectiveKind()) ||
isOpenMPDistributeDirective(getDirectiveKind())) &&
"expected worksharing loop directive");
return const_cast<Expr *>(reinterpret_cast<const Expr *>(
*std::next(child_begin(), UpperBoundVariableOffset)));
}
Expr *getStrideVariable() const {
assert((isOpenMPWorksharingDirective(getDirectiveKind()) ||
isOpenMPTaskLoopDirective(getDirectiveKind()) ||
isOpenMPDistributeDirective(getDirectiveKind())) &&
"expected worksharing loop directive");
return const_cast<Expr *>(reinterpret_cast<const Expr *>(
*std::next(child_begin(), StrideVariableOffset)));
}
Expr *getEnsureUpperBound() const {
assert((isOpenMPWorksharingDirective(getDirectiveKind()) ||
isOpenMPTaskLoopDirective(getDirectiveKind()) ||
isOpenMPDistributeDirective(getDirectiveKind())) &&
"expected worksharing loop directive");
return const_cast<Expr *>(reinterpret_cast<const Expr *>(
*std::next(child_begin(), EnsureUpperBoundOffset)));
}
Expr *getNextLowerBound() const {
assert((isOpenMPWorksharingDirective(getDirectiveKind()) ||
isOpenMPTaskLoopDirective(getDirectiveKind()) ||
isOpenMPDistributeDirective(getDirectiveKind())) &&
"expected worksharing loop directive");
return const_cast<Expr *>(reinterpret_cast<const Expr *>(
*std::next(child_begin(), NextLowerBoundOffset)));
}
Expr *getNextUpperBound() const {
assert((isOpenMPWorksharingDirective(getDirectiveKind()) ||
isOpenMPTaskLoopDirective(getDirectiveKind()) ||
isOpenMPDistributeDirective(getDirectiveKind())) &&
"expected worksharing loop directive");
return const_cast<Expr *>(reinterpret_cast<const Expr *>(
*std::next(child_begin(), NextUpperBoundOffset)));
}
Expr *getNumIterations() const {
assert((isOpenMPWorksharingDirective(getDirectiveKind()) ||
isOpenMPTaskLoopDirective(getDirectiveKind()) ||
isOpenMPDistributeDirective(getDirectiveKind())) &&
"expected worksharing loop directive");
return const_cast<Expr *>(reinterpret_cast<const Expr *>(
*std::next(child_begin(), NumIterationsOffset)));
}
Expr *getPrevLowerBoundVariable() const {
assert((isOpenMPWorksharingDirective(getDirectiveKind()) ||
isOpenMPTaskLoopDirective(getDirectiveKind()) ||
isOpenMPDistributeDirective(getDirectiveKind())) &&
"expected worksharing loop directive");
return const_cast<Expr *>(reinterpret_cast<const Expr *>(
*std::next(child_begin(), PrevLowerBoundVariableOffset)));
}
Expr *getPrevUpperBoundVariable() const {
assert((isOpenMPWorksharingDirective(getDirectiveKind()) ||
isOpenMPTaskLoopDirective(getDirectiveKind()) ||
isOpenMPDistributeDirective(getDirectiveKind())) &&
"expected worksharing loop directive");
return const_cast<Expr *>(reinterpret_cast<const Expr *>(
*std::next(child_begin(), PrevUpperBoundVariableOffset)));
}
const Stmt *getBody() const {
// This relies on the loop form is already checked by Sema.
Stmt *Body = getAssociatedStmt()->IgnoreContainers(true);
Body = cast<ForStmt>(Body)->getBody();
for (unsigned Cnt = 1; Cnt < CollapsedNum; ++Cnt) {
Body = Body->IgnoreContainers();
Body = cast<ForStmt>(Body)->getBody();
}
return Body;
}
ArrayRef<Expr *> counters() { return getCounters(); }
ArrayRef<Expr *> counters() const {
return const_cast<OMPLoopDirective *>(this)->getCounters();
}
ArrayRef<Expr *> private_counters() { return getPrivateCounters(); }
ArrayRef<Expr *> private_counters() const {
return const_cast<OMPLoopDirective *>(this)->getPrivateCounters();
}
ArrayRef<Expr *> inits() { return getInits(); }
ArrayRef<Expr *> inits() const {
return const_cast<OMPLoopDirective *>(this)->getInits();
}
ArrayRef<Expr *> updates() { return getUpdates(); }
ArrayRef<Expr *> updates() const {
return const_cast<OMPLoopDirective *>(this)->getUpdates();
}
ArrayRef<Expr *> finals() { return getFinals(); }
ArrayRef<Expr *> finals() const {
return const_cast<OMPLoopDirective *>(this)->getFinals();
}
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPSimdDirectiveClass ||
T->getStmtClass() == OMPForDirectiveClass ||
T->getStmtClass() == OMPForSimdDirectiveClass ||
T->getStmtClass() == OMPParallelForDirectiveClass ||
T->getStmtClass() == OMPParallelForSimdDirectiveClass ||
T->getStmtClass() == OMPTaskLoopDirectiveClass ||
T->getStmtClass() == OMPTaskLoopSimdDirectiveClass ||
T->getStmtClass() == OMPDistributeDirectiveClass ||
T->getStmtClass() == OMPTargetParallelForDirectiveClass ||
T->getStmtClass() == OMPDistributeParallelForDirectiveClass ||
T->getStmtClass() == OMPDistributeParallelForSimdDirectiveClass ||
T->getStmtClass() == OMPDistributeSimdDirectiveClass ||
T->getStmtClass() == OMPTargetParallelForSimdDirectiveClass ||
T->getStmtClass() == OMPTargetSimdDirectiveClass ||
T->getStmtClass() == OMPTeamsDistributeDirectiveClass ||
T->getStmtClass() == OMPTeamsDistributeSimdDirectiveClass ||
T->getStmtClass() == OMPTeamsDistributeParallelForSimdDirectiveClass ||
T->getStmtClass() == OMPTeamsDistributeParallelForDirectiveClass;
}
};
/// \brief This represents '#pragma omp simd' directive.
///
/// \code
/// #pragma omp simd private(a,b) linear(i,j:s) reduction(+:c,d)
/// \endcode
/// In this example directive '#pragma omp simd' has clauses 'private'
/// with the variables 'a' and 'b', 'linear' with variables 'i', 'j' and
/// linear step 's', 'reduction' with operator '+' and variables 'c' and 'd'.
///
class OMPSimdDirective : public OMPLoopDirective {
friend class ASTStmtReader;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
OMPSimdDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, unsigned NumClauses)
: OMPLoopDirective(this, OMPSimdDirectiveClass, OMPD_simd, StartLoc,
EndLoc, CollapsedNum, NumClauses) {}
/// \brief Build an empty directive.
///
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
explicit OMPSimdDirective(unsigned CollapsedNum, unsigned NumClauses)
: OMPLoopDirective(this, OMPSimdDirectiveClass, OMPD_simd,
SourceLocation(), SourceLocation(), CollapsedNum,
NumClauses) {}
public:
/// \brief Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param CollapsedNum Number of collapsed loops.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param Exprs Helper expressions for CodeGen.
///
static OMPSimdDirective *Create(const ASTContext &C, SourceLocation StartLoc,
SourceLocation EndLoc, unsigned CollapsedNum,
ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt,
const HelperExprs &Exprs);
/// \brief Creates an empty directive with the place
/// for \a NumClauses clauses.
///
/// \param C AST context.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
static OMPSimdDirective *CreateEmpty(const ASTContext &C, unsigned NumClauses,
unsigned CollapsedNum, EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPSimdDirectiveClass;
}
};
/// \brief This represents '#pragma omp for' directive.
///
/// \code
/// #pragma omp for private(a,b) reduction(+:c,d)
/// \endcode
/// In this example directive '#pragma omp for' has clauses 'private' with the
/// variables 'a' and 'b' and 'reduction' with operator '+' and variables 'c'
/// and 'd'.
///
class OMPForDirective : public OMPLoopDirective {
friend class ASTStmtReader;
/// \brief true if current directive has inner cancel directive.
bool HasCancel;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
OMPForDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, unsigned NumClauses)
: OMPLoopDirective(this, OMPForDirectiveClass, OMPD_for, StartLoc, EndLoc,
CollapsedNum, NumClauses),
HasCancel(false) {}
/// \brief Build an empty directive.
///
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
explicit OMPForDirective(unsigned CollapsedNum, unsigned NumClauses)
: OMPLoopDirective(this, OMPForDirectiveClass, OMPD_for, SourceLocation(),
SourceLocation(), CollapsedNum, NumClauses),
HasCancel(false) {}
/// \brief Set cancel state.
void setHasCancel(bool Has) { HasCancel = Has; }
public:
/// \brief Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param CollapsedNum Number of collapsed loops.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param Exprs Helper expressions for CodeGen.
/// \param HasCancel true if current directive has inner cancel directive.
///
static OMPForDirective *Create(const ASTContext &C, SourceLocation StartLoc,
SourceLocation EndLoc, unsigned CollapsedNum,
ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt, const HelperExprs &Exprs,
bool HasCancel);
/// \brief Creates an empty directive with the place
/// for \a NumClauses clauses.
///
/// \param C AST context.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
static OMPForDirective *CreateEmpty(const ASTContext &C, unsigned NumClauses,
unsigned CollapsedNum, EmptyShell);
/// \brief Return true if current directive has inner cancel directive.
bool hasCancel() const { return HasCancel; }
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPForDirectiveClass;
}
};
/// \brief This represents '#pragma omp for simd' directive.
///
/// \code
/// #pragma omp for simd private(a,b) linear(i,j:s) reduction(+:c,d)
/// \endcode
/// In this example directive '#pragma omp for simd' has clauses 'private'
/// with the variables 'a' and 'b', 'linear' with variables 'i', 'j' and
/// linear step 's', 'reduction' with operator '+' and variables 'c' and 'd'.
///
class OMPForSimdDirective : public OMPLoopDirective {
friend class ASTStmtReader;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
OMPForSimdDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, unsigned NumClauses)
: OMPLoopDirective(this, OMPForSimdDirectiveClass, OMPD_for_simd,
StartLoc, EndLoc, CollapsedNum, NumClauses) {}
/// \brief Build an empty directive.
///
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
explicit OMPForSimdDirective(unsigned CollapsedNum, unsigned NumClauses)
: OMPLoopDirective(this, OMPForSimdDirectiveClass, OMPD_for_simd,
SourceLocation(), SourceLocation(), CollapsedNum,
NumClauses) {}
public:
/// \brief Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param CollapsedNum Number of collapsed loops.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param Exprs Helper expressions for CodeGen.
///
static OMPForSimdDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt, const HelperExprs &Exprs);
/// \brief Creates an empty directive with the place
/// for \a NumClauses clauses.
///
/// \param C AST context.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
static OMPForSimdDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses,
unsigned CollapsedNum, EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPForSimdDirectiveClass;
}
};
/// \brief This represents '#pragma omp sections' directive.
///
/// \code
/// #pragma omp sections private(a,b) reduction(+:c,d)
/// \endcode
/// In this example directive '#pragma omp sections' has clauses 'private' with
/// the variables 'a' and 'b' and 'reduction' with operator '+' and variables
/// 'c' and 'd'.
///
class OMPSectionsDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
/// \brief true if current directive has inner cancel directive.
bool HasCancel;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param NumClauses Number of clauses.
///
OMPSectionsDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned NumClauses)
: OMPExecutableDirective(this, OMPSectionsDirectiveClass, OMPD_sections,
StartLoc, EndLoc, NumClauses, 1),
HasCancel(false) {}
/// \brief Build an empty directive.
///
/// \param NumClauses Number of clauses.
///
explicit OMPSectionsDirective(unsigned NumClauses)
: OMPExecutableDirective(this, OMPSectionsDirectiveClass, OMPD_sections,
SourceLocation(), SourceLocation(), NumClauses,
1),
HasCancel(false) {}
/// \brief Set cancel state.
void setHasCancel(bool Has) { HasCancel = Has; }
public:
/// \brief Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param HasCancel true if current directive has inner directive.
///
static OMPSectionsDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
ArrayRef<OMPClause *> Clauses, Stmt *AssociatedStmt, bool HasCancel);
/// \brief Creates an empty directive with the place for \a NumClauses
/// clauses.
///
/// \param C AST context.
/// \param NumClauses Number of clauses.
///
static OMPSectionsDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses, EmptyShell);
/// \brief Return true if current directive has inner cancel directive.
bool hasCancel() const { return HasCancel; }
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPSectionsDirectiveClass;
}
};
/// \brief This represents '#pragma omp section' directive.
///
/// \code
/// #pragma omp section
/// \endcode
///
class OMPSectionDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
/// \brief true if current directive has inner cancel directive.
bool HasCancel;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
///
OMPSectionDirective(SourceLocation StartLoc, SourceLocation EndLoc)
: OMPExecutableDirective(this, OMPSectionDirectiveClass, OMPD_section,
StartLoc, EndLoc, 0, 1),
HasCancel(false) {}
/// \brief Build an empty directive.
///
explicit OMPSectionDirective()
: OMPExecutableDirective(this, OMPSectionDirectiveClass, OMPD_section,
SourceLocation(), SourceLocation(), 0, 1),
HasCancel(false) {}
public:
/// \brief Creates directive.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param HasCancel true if current directive has inner directive.
///
static OMPSectionDirective *Create(const ASTContext &C,
SourceLocation StartLoc,
SourceLocation EndLoc,
Stmt *AssociatedStmt, bool HasCancel);
/// \brief Creates an empty directive.
///
/// \param C AST context.
///
static OMPSectionDirective *CreateEmpty(const ASTContext &C, EmptyShell);
/// \brief Set cancel state.
void setHasCancel(bool Has) { HasCancel = Has; }
/// \brief Return true if current directive has inner cancel directive.
bool hasCancel() const { return HasCancel; }
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPSectionDirectiveClass;
}
};
/// \brief This represents '#pragma omp single' directive.
///
/// \code
/// #pragma omp single private(a,b) copyprivate(c,d)
/// \endcode
/// In this example directive '#pragma omp single' has clauses 'private' with
/// the variables 'a' and 'b' and 'copyprivate' with variables 'c' and 'd'.
///
class OMPSingleDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param NumClauses Number of clauses.
///
OMPSingleDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned NumClauses)
: OMPExecutableDirective(this, OMPSingleDirectiveClass, OMPD_single,
StartLoc, EndLoc, NumClauses, 1) {}
/// \brief Build an empty directive.
///
/// \param NumClauses Number of clauses.
///
explicit OMPSingleDirective(unsigned NumClauses)
: OMPExecutableDirective(this, OMPSingleDirectiveClass, OMPD_single,
SourceLocation(), SourceLocation(), NumClauses,
1) {}
public:
/// \brief Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
///
static OMPSingleDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
ArrayRef<OMPClause *> Clauses, Stmt *AssociatedStmt);
/// \brief Creates an empty directive with the place for \a NumClauses
/// clauses.
///
/// \param C AST context.
/// \param NumClauses Number of clauses.
///
static OMPSingleDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses, EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPSingleDirectiveClass;
}
};
/// \brief This represents '#pragma omp master' directive.
///
/// \code
/// #pragma omp master
/// \endcode
///
class OMPMasterDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
///
OMPMasterDirective(SourceLocation StartLoc, SourceLocation EndLoc)
: OMPExecutableDirective(this, OMPMasterDirectiveClass, OMPD_master,
StartLoc, EndLoc, 0, 1) {}
/// \brief Build an empty directive.
///
explicit OMPMasterDirective()
: OMPExecutableDirective(this, OMPMasterDirectiveClass, OMPD_master,
SourceLocation(), SourceLocation(), 0, 1) {}
public:
/// \brief Creates directive.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param AssociatedStmt Statement, associated with the directive.
///
static OMPMasterDirective *Create(const ASTContext &C,
SourceLocation StartLoc,
SourceLocation EndLoc,
Stmt *AssociatedStmt);
/// \brief Creates an empty directive.
///
/// \param C AST context.
///
static OMPMasterDirective *CreateEmpty(const ASTContext &C, EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPMasterDirectiveClass;
}
};
/// \brief This represents '#pragma omp critical' directive.
///
/// \code
/// #pragma omp critical
/// \endcode
///
class OMPCriticalDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
/// \brief Name of the directive.
DeclarationNameInfo DirName;
/// \brief Build directive with the given start and end location.
///
/// \param Name Name of the directive.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param NumClauses Number of clauses.
///
OMPCriticalDirective(const DeclarationNameInfo &Name, SourceLocation StartLoc,
SourceLocation EndLoc, unsigned NumClauses)
: OMPExecutableDirective(this, OMPCriticalDirectiveClass, OMPD_critical,
StartLoc, EndLoc, NumClauses, 1),
DirName(Name) {}
/// \brief Build an empty directive.
///
/// \param NumClauses Number of clauses.
///
explicit OMPCriticalDirective(unsigned NumClauses)
: OMPExecutableDirective(this, OMPCriticalDirectiveClass, OMPD_critical,
SourceLocation(), SourceLocation(), NumClauses,
1),
DirName() {}
/// \brief Set name of the directive.
///
/// \param Name Name of the directive.
///
void setDirectiveName(const DeclarationNameInfo &Name) { DirName = Name; }
public:
/// \brief Creates directive.
///
/// \param C AST context.
/// \param Name Name of the directive.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
///
static OMPCriticalDirective *
Create(const ASTContext &C, const DeclarationNameInfo &Name,
SourceLocation StartLoc, SourceLocation EndLoc,
ArrayRef<OMPClause *> Clauses, Stmt *AssociatedStmt);
/// \brief Creates an empty directive.
///
/// \param C AST context.
/// \param NumClauses Number of clauses.
///
static OMPCriticalDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses, EmptyShell);
/// \brief Return name of the directive.
///
DeclarationNameInfo getDirectiveName() const { return DirName; }
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPCriticalDirectiveClass;
}
};
/// \brief This represents '#pragma omp parallel for' directive.
///
/// \code
/// #pragma omp parallel for private(a,b) reduction(+:c,d)
/// \endcode
/// In this example directive '#pragma omp parallel for' has clauses 'private'
/// with the variables 'a' and 'b' and 'reduction' with operator '+' and
/// variables 'c' and 'd'.
///
class OMPParallelForDirective : public OMPLoopDirective {
friend class ASTStmtReader;
/// \brief true if current region has inner cancel directive.
bool HasCancel;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
OMPParallelForDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, unsigned NumClauses)
: OMPLoopDirective(this, OMPParallelForDirectiveClass, OMPD_parallel_for,
StartLoc, EndLoc, CollapsedNum, NumClauses),
HasCancel(false) {}
/// \brief Build an empty directive.
///
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
explicit OMPParallelForDirective(unsigned CollapsedNum, unsigned NumClauses)
: OMPLoopDirective(this, OMPParallelForDirectiveClass, OMPD_parallel_for,
SourceLocation(), SourceLocation(), CollapsedNum,
NumClauses),
HasCancel(false) {}
/// \brief Set cancel state.
void setHasCancel(bool Has) { HasCancel = Has; }
public:
/// \brief Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param CollapsedNum Number of collapsed loops.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param Exprs Helper expressions for CodeGen.
/// \param HasCancel true if current directive has inner cancel directive.
///
static OMPParallelForDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt, const HelperExprs &Exprs, bool HasCancel);
/// \brief Creates an empty directive with the place
/// for \a NumClauses clauses.
///
/// \param C AST context.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
static OMPParallelForDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses,
unsigned CollapsedNum,
EmptyShell);
/// \brief Return true if current directive has inner cancel directive.
bool hasCancel() const { return HasCancel; }
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPParallelForDirectiveClass;
}
};
/// \brief This represents '#pragma omp parallel for simd' directive.
///
/// \code
/// #pragma omp parallel for simd private(a,b) linear(i,j:s) reduction(+:c,d)
/// \endcode
/// In this example directive '#pragma omp parallel for simd' has clauses
/// 'private' with the variables 'a' and 'b', 'linear' with variables 'i', 'j'
/// and linear step 's', 'reduction' with operator '+' and variables 'c' and
/// 'd'.
///
class OMPParallelForSimdDirective : public OMPLoopDirective {
friend class ASTStmtReader;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
OMPParallelForSimdDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, unsigned NumClauses)
: OMPLoopDirective(this, OMPParallelForSimdDirectiveClass,
OMPD_parallel_for_simd, StartLoc, EndLoc, CollapsedNum,
NumClauses) {}
/// \brief Build an empty directive.
///
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
explicit OMPParallelForSimdDirective(unsigned CollapsedNum,
unsigned NumClauses)
: OMPLoopDirective(this, OMPParallelForSimdDirectiveClass,
OMPD_parallel_for_simd, SourceLocation(),
SourceLocation(), CollapsedNum, NumClauses) {}
public:
/// \brief Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param CollapsedNum Number of collapsed loops.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param Exprs Helper expressions for CodeGen.
///
static OMPParallelForSimdDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt, const HelperExprs &Exprs);
/// \brief Creates an empty directive with the place
/// for \a NumClauses clauses.
///
/// \param C AST context.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
static OMPParallelForSimdDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses,
unsigned CollapsedNum,
EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPParallelForSimdDirectiveClass;
}
};
/// \brief This represents '#pragma omp parallel sections' directive.
///
/// \code
/// #pragma omp parallel sections private(a,b) reduction(+:c,d)
/// \endcode
/// In this example directive '#pragma omp parallel sections' has clauses
/// 'private' with the variables 'a' and 'b' and 'reduction' with operator '+'
/// and variables 'c' and 'd'.
///
class OMPParallelSectionsDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
/// \brief true if current directive has inner cancel directive.
bool HasCancel;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param NumClauses Number of clauses.
///
OMPParallelSectionsDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned NumClauses)
: OMPExecutableDirective(this, OMPParallelSectionsDirectiveClass,
OMPD_parallel_sections, StartLoc, EndLoc,
NumClauses, 1),
HasCancel(false) {}
/// \brief Build an empty directive.
///
/// \param NumClauses Number of clauses.
///
explicit OMPParallelSectionsDirective(unsigned NumClauses)
: OMPExecutableDirective(this, OMPParallelSectionsDirectiveClass,
OMPD_parallel_sections, SourceLocation(),
SourceLocation(), NumClauses, 1),
HasCancel(false) {}
/// \brief Set cancel state.
void setHasCancel(bool Has) { HasCancel = Has; }
public:
/// \brief Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param HasCancel true if current directive has inner cancel directive.
///
static OMPParallelSectionsDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
ArrayRef<OMPClause *> Clauses, Stmt *AssociatedStmt, bool HasCancel);
/// \brief Creates an empty directive with the place for \a NumClauses
/// clauses.
///
/// \param C AST context.
/// \param NumClauses Number of clauses.
///
static OMPParallelSectionsDirective *
CreateEmpty(const ASTContext &C, unsigned NumClauses, EmptyShell);
/// \brief Return true if current directive has inner cancel directive.
bool hasCancel() const { return HasCancel; }
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPParallelSectionsDirectiveClass;
}
};
/// \brief This represents '#pragma omp task' directive.
///
/// \code
/// #pragma omp task private(a,b) final(d)
/// \endcode
/// In this example directive '#pragma omp task' has clauses 'private' with the
/// variables 'a' and 'b' and 'final' with condition 'd'.
///
class OMPTaskDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
/// \brief true if this directive has inner cancel directive.
bool HasCancel;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param NumClauses Number of clauses.
///
OMPTaskDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned NumClauses)
: OMPExecutableDirective(this, OMPTaskDirectiveClass, OMPD_task, StartLoc,
EndLoc, NumClauses, 1),
HasCancel(false) {}
/// \brief Build an empty directive.
///
/// \param NumClauses Number of clauses.
///
explicit OMPTaskDirective(unsigned NumClauses)
: OMPExecutableDirective(this, OMPTaskDirectiveClass, OMPD_task,
SourceLocation(), SourceLocation(), NumClauses,
1),
HasCancel(false) {}
/// \brief Set cancel state.
void setHasCancel(bool Has) { HasCancel = Has; }
public:
/// \brief Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param HasCancel true, if current directive has inner cancel directive.
///
static OMPTaskDirective *Create(const ASTContext &C, SourceLocation StartLoc,
SourceLocation EndLoc,
ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt, bool HasCancel);
/// \brief Creates an empty directive with the place for \a NumClauses
/// clauses.
///
/// \param C AST context.
/// \param NumClauses Number of clauses.
///
static OMPTaskDirective *CreateEmpty(const ASTContext &C, unsigned NumClauses,
EmptyShell);
/// \brief Return true if current directive has inner cancel directive.
bool hasCancel() const { return HasCancel; }
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPTaskDirectiveClass;
}
};
/// \brief This represents '#pragma omp taskyield' directive.
///
/// \code
/// #pragma omp taskyield
/// \endcode
///
class OMPTaskyieldDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
///
OMPTaskyieldDirective(SourceLocation StartLoc, SourceLocation EndLoc)
: OMPExecutableDirective(this, OMPTaskyieldDirectiveClass, OMPD_taskyield,
StartLoc, EndLoc, 0, 0) {}
/// \brief Build an empty directive.
///
explicit OMPTaskyieldDirective()
: OMPExecutableDirective(this, OMPTaskyieldDirectiveClass, OMPD_taskyield,
SourceLocation(), SourceLocation(), 0, 0) {}
public:
/// \brief Creates directive.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
///
static OMPTaskyieldDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc);
/// \brief Creates an empty directive.
///
/// \param C AST context.
///
static OMPTaskyieldDirective *CreateEmpty(const ASTContext &C, EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPTaskyieldDirectiveClass;
}
};
/// \brief This represents '#pragma omp barrier' directive.
///
/// \code
/// #pragma omp barrier
/// \endcode
///
class OMPBarrierDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
///
OMPBarrierDirective(SourceLocation StartLoc, SourceLocation EndLoc)
: OMPExecutableDirective(this, OMPBarrierDirectiveClass, OMPD_barrier,
StartLoc, EndLoc, 0, 0) {}
/// \brief Build an empty directive.
///
explicit OMPBarrierDirective()
: OMPExecutableDirective(this, OMPBarrierDirectiveClass, OMPD_barrier,
SourceLocation(), SourceLocation(), 0, 0) {}
public:
/// \brief Creates directive.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
///
static OMPBarrierDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc);
/// \brief Creates an empty directive.
///
/// \param C AST context.
///
static OMPBarrierDirective *CreateEmpty(const ASTContext &C, EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPBarrierDirectiveClass;
}
};
/// \brief This represents '#pragma omp taskwait' directive.
///
/// \code
/// #pragma omp taskwait
/// \endcode
///
class OMPTaskwaitDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
///
OMPTaskwaitDirective(SourceLocation StartLoc, SourceLocation EndLoc)
: OMPExecutableDirective(this, OMPTaskwaitDirectiveClass, OMPD_taskwait,
StartLoc, EndLoc, 0, 0) {}
/// \brief Build an empty directive.
///
explicit OMPTaskwaitDirective()
: OMPExecutableDirective(this, OMPTaskwaitDirectiveClass, OMPD_taskwait,
SourceLocation(), SourceLocation(), 0, 0) {}
public:
/// \brief Creates directive.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
///
static OMPTaskwaitDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc);
/// \brief Creates an empty directive.
///
/// \param C AST context.
///
static OMPTaskwaitDirective *CreateEmpty(const ASTContext &C, EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPTaskwaitDirectiveClass;
}
};
/// \brief This represents '#pragma omp taskgroup' directive.
///
/// \code
/// #pragma omp taskgroup
/// \endcode
///
class OMPTaskgroupDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
///
OMPTaskgroupDirective(SourceLocation StartLoc, SourceLocation EndLoc)
: OMPExecutableDirective(this, OMPTaskgroupDirectiveClass, OMPD_taskgroup,
StartLoc, EndLoc, 0, 1) {}
/// \brief Build an empty directive.
///
explicit OMPTaskgroupDirective()
: OMPExecutableDirective(this, OMPTaskgroupDirectiveClass, OMPD_taskgroup,
SourceLocation(), SourceLocation(), 0, 1) {}
public:
/// \brief Creates directive.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param AssociatedStmt Statement, associated with the directive.
///
static OMPTaskgroupDirective *Create(const ASTContext &C,
SourceLocation StartLoc,
SourceLocation EndLoc,
Stmt *AssociatedStmt);
/// \brief Creates an empty directive.
///
/// \param C AST context.
///
static OMPTaskgroupDirective *CreateEmpty(const ASTContext &C, EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPTaskgroupDirectiveClass;
}
};
/// \brief This represents '#pragma omp flush' directive.
///
/// \code
/// #pragma omp flush(a,b)
/// \endcode
/// In this example directive '#pragma omp flush' has 2 arguments- variables 'a'
/// and 'b'.
/// 'omp flush' directive does not have clauses but have an optional list of
/// variables to flush. This list of variables is stored within some fake clause
/// FlushClause.
class OMPFlushDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param NumClauses Number of clauses.
///
OMPFlushDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned NumClauses)
: OMPExecutableDirective(this, OMPFlushDirectiveClass, OMPD_flush,
StartLoc, EndLoc, NumClauses, 0) {}
/// \brief Build an empty directive.
///
/// \param NumClauses Number of clauses.
///
explicit OMPFlushDirective(unsigned NumClauses)
: OMPExecutableDirective(this, OMPFlushDirectiveClass, OMPD_flush,
SourceLocation(), SourceLocation(), NumClauses,
0) {}
public:
/// \brief Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param Clauses List of clauses (only single OMPFlushClause clause is
/// allowed).
///
static OMPFlushDirective *Create(const ASTContext &C, SourceLocation StartLoc,
SourceLocation EndLoc,
ArrayRef<OMPClause *> Clauses);
/// \brief Creates an empty directive with the place for \a NumClauses
/// clauses.
///
/// \param C AST context.
/// \param NumClauses Number of clauses.
///
static OMPFlushDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses, EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPFlushDirectiveClass;
}
};
/// \brief This represents '#pragma omp ordered' directive.
///
/// \code
/// #pragma omp ordered
/// \endcode
///
class OMPOrderedDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param NumClauses Number of clauses.
///
OMPOrderedDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned NumClauses)
: OMPExecutableDirective(this, OMPOrderedDirectiveClass, OMPD_ordered,
StartLoc, EndLoc, NumClauses, 1) {}
/// \brief Build an empty directive.
///
/// \param NumClauses Number of clauses.
///
explicit OMPOrderedDirective(unsigned NumClauses)
: OMPExecutableDirective(this, OMPOrderedDirectiveClass, OMPD_ordered,
SourceLocation(), SourceLocation(), NumClauses,
1) {}
public:
/// \brief Creates directive.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
///
static OMPOrderedDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
ArrayRef<OMPClause *> Clauses, Stmt *AssociatedStmt);
/// \brief Creates an empty directive.
///
/// \param C AST context.
/// \param NumClauses Number of clauses.
///
static OMPOrderedDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses, EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPOrderedDirectiveClass;
}
};
/// \brief This represents '#pragma omp atomic' directive.
///
/// \code
/// #pragma omp atomic capture
/// \endcode
/// In this example directive '#pragma omp atomic' has clause 'capture'.
///
class OMPAtomicDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
/// \brief Used for 'atomic update' or 'atomic capture' constructs. They may
/// have atomic expressions of forms
/// \code
/// x = x binop expr;
/// x = expr binop x;
/// \endcode
/// This field is true for the first form of the expression and false for the
/// second. Required for correct codegen of non-associative operations (like
/// << or >>).
bool IsXLHSInRHSPart;
/// \brief Used for 'atomic update' or 'atomic capture' constructs. They may
/// have atomic expressions of forms
/// \code
/// v = x; <update x>;
/// <update x>; v = x;
/// \endcode
/// This field is true for the first(postfix) form of the expression and false
/// otherwise.
bool IsPostfixUpdate;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param NumClauses Number of clauses.
///
OMPAtomicDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned NumClauses)
: OMPExecutableDirective(this, OMPAtomicDirectiveClass, OMPD_atomic,
StartLoc, EndLoc, NumClauses, 5),
IsXLHSInRHSPart(false), IsPostfixUpdate(false) {}
/// \brief Build an empty directive.
///
/// \param NumClauses Number of clauses.
///
explicit OMPAtomicDirective(unsigned NumClauses)
: OMPExecutableDirective(this, OMPAtomicDirectiveClass, OMPD_atomic,
SourceLocation(), SourceLocation(), NumClauses,
5),
IsXLHSInRHSPart(false), IsPostfixUpdate(false) {}
/// \brief Set 'x' part of the associated expression/statement.
void setX(Expr *X) { *std::next(child_begin()) = X; }
/// \brief Set helper expression of the form
/// 'OpaqueValueExpr(x) binop OpaqueValueExpr(expr)' or
/// 'OpaqueValueExpr(expr) binop OpaqueValueExpr(x)'.
void setUpdateExpr(Expr *UE) { *std::next(child_begin(), 2) = UE; }
/// \brief Set 'v' part of the associated expression/statement.
void setV(Expr *V) { *std::next(child_begin(), 3) = V; }
/// \brief Set 'expr' part of the associated expression/statement.
void setExpr(Expr *E) { *std::next(child_begin(), 4) = E; }
public:
/// \brief Creates directive with a list of \a Clauses and 'x', 'v' and 'expr'
/// parts of the atomic construct (see Section 2.12.6, atomic Construct, for
/// detailed description of 'x', 'v' and 'expr').
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param X 'x' part of the associated expression/statement.
/// \param V 'v' part of the associated expression/statement.
/// \param E 'expr' part of the associated expression/statement.
/// \param UE Helper expression of the form
/// 'OpaqueValueExpr(x) binop OpaqueValueExpr(expr)' or
/// 'OpaqueValueExpr(expr) binop OpaqueValueExpr(x)'.
/// \param IsXLHSInRHSPart true if \a UE has the first form and false if the
/// second.
/// \param IsPostfixUpdate true if original value of 'x' must be stored in
/// 'v', not an updated one.
static OMPAtomicDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
ArrayRef<OMPClause *> Clauses, Stmt *AssociatedStmt, Expr *X, Expr *V,
Expr *E, Expr *UE, bool IsXLHSInRHSPart, bool IsPostfixUpdate);
/// \brief Creates an empty directive with the place for \a NumClauses
/// clauses.
///
/// \param C AST context.
/// \param NumClauses Number of clauses.
///
static OMPAtomicDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses, EmptyShell);
/// \brief Get 'x' part of the associated expression/statement.
Expr *getX() { return cast_or_null<Expr>(*std::next(child_begin())); }
const Expr *getX() const {
return cast_or_null<Expr>(*std::next(child_begin()));
}
/// \brief Get helper expression of the form
/// 'OpaqueValueExpr(x) binop OpaqueValueExpr(expr)' or
/// 'OpaqueValueExpr(expr) binop OpaqueValueExpr(x)'.
Expr *getUpdateExpr() {
return cast_or_null<Expr>(*std::next(child_begin(), 2));
}
const Expr *getUpdateExpr() const {
return cast_or_null<Expr>(*std::next(child_begin(), 2));
}
/// \brief Return true if helper update expression has form
/// 'OpaqueValueExpr(x) binop OpaqueValueExpr(expr)' and false if it has form
/// 'OpaqueValueExpr(expr) binop OpaqueValueExpr(x)'.
bool isXLHSInRHSPart() const { return IsXLHSInRHSPart; }
/// \brief Return true if 'v' expression must be updated to original value of
/// 'x', false if 'v' must be updated to the new value of 'x'.
bool isPostfixUpdate() const { return IsPostfixUpdate; }
/// \brief Get 'v' part of the associated expression/statement.
Expr *getV() { return cast_or_null<Expr>(*std::next(child_begin(), 3)); }
const Expr *getV() const {
return cast_or_null<Expr>(*std::next(child_begin(), 3));
}
/// \brief Get 'expr' part of the associated expression/statement.
Expr *getExpr() { return cast_or_null<Expr>(*std::next(child_begin(), 4)); }
const Expr *getExpr() const {
return cast_or_null<Expr>(*std::next(child_begin(), 4));
}
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPAtomicDirectiveClass;
}
};
/// \brief This represents '#pragma omp target' directive.
///
/// \code
/// #pragma omp target if(a)
/// \endcode
/// In this example directive '#pragma omp target' has clause 'if' with
/// condition 'a'.
///
class OMPTargetDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param NumClauses Number of clauses.
///
OMPTargetDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned NumClauses)
: OMPExecutableDirective(this, OMPTargetDirectiveClass, OMPD_target,
StartLoc, EndLoc, NumClauses, 1) {}
/// \brief Build an empty directive.
///
/// \param NumClauses Number of clauses.
///
explicit OMPTargetDirective(unsigned NumClauses)
: OMPExecutableDirective(this, OMPTargetDirectiveClass, OMPD_target,
SourceLocation(), SourceLocation(), NumClauses,
1) {}
public:
/// \brief Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
///
static OMPTargetDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
ArrayRef<OMPClause *> Clauses, Stmt *AssociatedStmt);
/// \brief Creates an empty directive with the place for \a NumClauses
/// clauses.
///
/// \param C AST context.
/// \param NumClauses Number of clauses.
///
static OMPTargetDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses, EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPTargetDirectiveClass;
}
};
/// \brief This represents '#pragma omp target data' directive.
///
/// \code
/// #pragma omp target data device(0) if(a) map(b[:])
/// \endcode
/// In this example directive '#pragma omp target data' has clauses 'device'
/// with the value '0', 'if' with condition 'a' and 'map' with array
/// section 'b[:]'.
///
class OMPTargetDataDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param NumClauses The number of clauses.
///
OMPTargetDataDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned NumClauses)
: OMPExecutableDirective(this, OMPTargetDataDirectiveClass,
OMPD_target_data, StartLoc, EndLoc, NumClauses,
1) {}
/// \brief Build an empty directive.
///
/// \param NumClauses Number of clauses.
///
explicit OMPTargetDataDirective(unsigned NumClauses)
: OMPExecutableDirective(this, OMPTargetDataDirectiveClass,
OMPD_target_data, SourceLocation(),
SourceLocation(), NumClauses, 1) {}
public:
/// \brief Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
///
static OMPTargetDataDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
ArrayRef<OMPClause *> Clauses, Stmt *AssociatedStmt);
/// \brief Creates an empty directive with the place for \a N clauses.
///
/// \param C AST context.
/// \param N The number of clauses.
///
static OMPTargetDataDirective *CreateEmpty(const ASTContext &C, unsigned N,
EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPTargetDataDirectiveClass;
}
};
/// \brief This represents '#pragma omp target enter data' directive.
///
/// \code
/// #pragma omp target enter data device(0) if(a) map(b[:])
/// \endcode
/// In this example directive '#pragma omp target enter data' has clauses
/// 'device' with the value '0', 'if' with condition 'a' and 'map' with array
/// section 'b[:]'.
///
class OMPTargetEnterDataDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param NumClauses The number of clauses.
///
OMPTargetEnterDataDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned NumClauses)
: OMPExecutableDirective(this, OMPTargetEnterDataDirectiveClass,
OMPD_target_enter_data, StartLoc, EndLoc,
NumClauses, /*NumChildren=*/0) {}
/// \brief Build an empty directive.
///
/// \param NumClauses Number of clauses.
///
explicit OMPTargetEnterDataDirective(unsigned NumClauses)
: OMPExecutableDirective(this, OMPTargetEnterDataDirectiveClass,
OMPD_target_enter_data, SourceLocation(),
SourceLocation(), NumClauses,
/*NumChildren=*/0) {}
public:
/// \brief Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param Clauses List of clauses.
///
static OMPTargetEnterDataDirective *Create(const ASTContext &C,
SourceLocation StartLoc,
SourceLocation EndLoc,
ArrayRef<OMPClause *> Clauses);
/// \brief Creates an empty directive with the place for \a N clauses.
///
/// \param C AST context.
/// \param N The number of clauses.
///
static OMPTargetEnterDataDirective *CreateEmpty(const ASTContext &C,
unsigned N, EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPTargetEnterDataDirectiveClass;
}
};
/// \brief This represents '#pragma omp target exit data' directive.
///
/// \code
/// #pragma omp target exit data device(0) if(a) map(b[:])
/// \endcode
/// In this example directive '#pragma omp target exit data' has clauses
/// 'device' with the value '0', 'if' with condition 'a' and 'map' with array
/// section 'b[:]'.
///
class OMPTargetExitDataDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param NumClauses The number of clauses.
///
OMPTargetExitDataDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned NumClauses)
: OMPExecutableDirective(this, OMPTargetExitDataDirectiveClass,
OMPD_target_exit_data, StartLoc, EndLoc,
NumClauses, /*NumChildren=*/0) {}
/// \brief Build an empty directive.
///
/// \param NumClauses Number of clauses.
///
explicit OMPTargetExitDataDirective(unsigned NumClauses)
: OMPExecutableDirective(this, OMPTargetExitDataDirectiveClass,
OMPD_target_exit_data, SourceLocation(),
SourceLocation(), NumClauses,
/*NumChildren=*/0) {}
public:
/// \brief Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param Clauses List of clauses.
///
static OMPTargetExitDataDirective *Create(const ASTContext &C,
SourceLocation StartLoc,
SourceLocation EndLoc,
ArrayRef<OMPClause *> Clauses);
/// \brief Creates an empty directive with the place for \a N clauses.
///
/// \param C AST context.
/// \param N The number of clauses.
///
static OMPTargetExitDataDirective *CreateEmpty(const ASTContext &C,
unsigned N, EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPTargetExitDataDirectiveClass;
}
};
/// \brief This represents '#pragma omp target parallel' directive.
///
/// \code
/// #pragma omp target parallel if(a)
/// \endcode
/// In this example directive '#pragma omp target parallel' has clause 'if' with
/// condition 'a'.
///
class OMPTargetParallelDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param NumClauses Number of clauses.
///
OMPTargetParallelDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned NumClauses)
: OMPExecutableDirective(this, OMPTargetParallelDirectiveClass,
OMPD_target_parallel, StartLoc, EndLoc,
NumClauses, /*NumChildren=*/1) {}
/// \brief Build an empty directive.
///
/// \param NumClauses Number of clauses.
///
explicit OMPTargetParallelDirective(unsigned NumClauses)
: OMPExecutableDirective(this, OMPTargetParallelDirectiveClass,
OMPD_target_parallel, SourceLocation(),
SourceLocation(), NumClauses,
/*NumChildren=*/1) {}
public:
/// \brief Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
///
static OMPTargetParallelDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
ArrayRef<OMPClause *> Clauses, Stmt *AssociatedStmt);
/// \brief Creates an empty directive with the place for \a NumClauses
/// clauses.
///
/// \param C AST context.
/// \param NumClauses Number of clauses.
///
static OMPTargetParallelDirective *
CreateEmpty(const ASTContext &C, unsigned NumClauses, EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPTargetParallelDirectiveClass;
}
};
/// \brief This represents '#pragma omp target parallel for' directive.
///
/// \code
/// #pragma omp target parallel for private(a,b) reduction(+:c,d)
/// \endcode
/// In this example directive '#pragma omp target parallel for' has clauses
/// 'private' with the variables 'a' and 'b' and 'reduction' with operator '+'
/// and variables 'c' and 'd'.
///
class OMPTargetParallelForDirective : public OMPLoopDirective {
friend class ASTStmtReader;
/// \brief true if current region has inner cancel directive.
bool HasCancel;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
OMPTargetParallelForDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, unsigned NumClauses)
: OMPLoopDirective(this, OMPTargetParallelForDirectiveClass,
OMPD_target_parallel_for, StartLoc, EndLoc,
CollapsedNum, NumClauses),
HasCancel(false) {}
/// \brief Build an empty directive.
///
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
explicit OMPTargetParallelForDirective(unsigned CollapsedNum,
unsigned NumClauses)
: OMPLoopDirective(this, OMPTargetParallelForDirectiveClass,
OMPD_target_parallel_for, SourceLocation(),
SourceLocation(), CollapsedNum, NumClauses),
HasCancel(false) {}
/// \brief Set cancel state.
void setHasCancel(bool Has) { HasCancel = Has; }
public:
/// \brief Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param CollapsedNum Number of collapsed loops.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param Exprs Helper expressions for CodeGen.
/// \param HasCancel true if current directive has inner cancel directive.
///
static OMPTargetParallelForDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt, const HelperExprs &Exprs, bool HasCancel);
/// \brief Creates an empty directive with the place
/// for \a NumClauses clauses.
///
/// \param C AST context.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
static OMPTargetParallelForDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses,
unsigned CollapsedNum,
EmptyShell);
/// \brief Return true if current directive has inner cancel directive.
bool hasCancel() const { return HasCancel; }
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPTargetParallelForDirectiveClass;
}
};
/// \brief This represents '#pragma omp teams' directive.
///
/// \code
/// #pragma omp teams if(a)
/// \endcode
/// In this example directive '#pragma omp teams' has clause 'if' with
/// condition 'a'.
///
class OMPTeamsDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param NumClauses Number of clauses.
///
OMPTeamsDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned NumClauses)
: OMPExecutableDirective(this, OMPTeamsDirectiveClass, OMPD_teams,
StartLoc, EndLoc, NumClauses, 1) {}
/// \brief Build an empty directive.
///
/// \param NumClauses Number of clauses.
///
explicit OMPTeamsDirective(unsigned NumClauses)
: OMPExecutableDirective(this, OMPTeamsDirectiveClass, OMPD_teams,
SourceLocation(), SourceLocation(), NumClauses,
1) {}
public:
/// \brief Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
///
static OMPTeamsDirective *Create(const ASTContext &C, SourceLocation StartLoc,
SourceLocation EndLoc,
ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt);
/// \brief Creates an empty directive with the place for \a NumClauses
/// clauses.
///
/// \param C AST context.
/// \param NumClauses Number of clauses.
///
static OMPTeamsDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses, EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPTeamsDirectiveClass;
}
};
/// \brief This represents '#pragma omp cancellation point' directive.
///
/// \code
/// #pragma omp cancellation point for
/// \endcode
///
/// In this example a cancellation point is created for innermost 'for' region.
class OMPCancellationPointDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
OpenMPDirectiveKind CancelRegion;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
///
OMPCancellationPointDirective(SourceLocation StartLoc, SourceLocation EndLoc)
: OMPExecutableDirective(this, OMPCancellationPointDirectiveClass,
OMPD_cancellation_point, StartLoc, EndLoc, 0, 0),
CancelRegion(OMPD_unknown) {}
/// \brief Build an empty directive.
///
explicit OMPCancellationPointDirective()
: OMPExecutableDirective(this, OMPCancellationPointDirectiveClass,
OMPD_cancellation_point, SourceLocation(),
SourceLocation(), 0, 0),
CancelRegion(OMPD_unknown) {}
/// \brief Set cancel region for current cancellation point.
/// \param CR Cancellation region.
void setCancelRegion(OpenMPDirectiveKind CR) { CancelRegion = CR; }
public:
/// \brief Creates directive.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
///
static OMPCancellationPointDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
OpenMPDirectiveKind CancelRegion);
/// \brief Creates an empty directive.
///
/// \param C AST context.
///
static OMPCancellationPointDirective *CreateEmpty(const ASTContext &C,
EmptyShell);
/// \brief Get cancellation region for the current cancellation point.
OpenMPDirectiveKind getCancelRegion() const { return CancelRegion; }
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPCancellationPointDirectiveClass;
}
};
/// \brief This represents '#pragma omp cancel' directive.
///
/// \code
/// #pragma omp cancel for
/// \endcode
///
/// In this example a cancel is created for innermost 'for' region.
class OMPCancelDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
OpenMPDirectiveKind CancelRegion;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param NumClauses Number of clauses.
///
OMPCancelDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned NumClauses)
: OMPExecutableDirective(this, OMPCancelDirectiveClass, OMPD_cancel,
StartLoc, EndLoc, NumClauses, 0),
CancelRegion(OMPD_unknown) {}
/// \brief Build an empty directive.
///
/// \param NumClauses Number of clauses.
explicit OMPCancelDirective(unsigned NumClauses)
: OMPExecutableDirective(this, OMPCancelDirectiveClass, OMPD_cancel,
SourceLocation(), SourceLocation(), NumClauses,
0),
CancelRegion(OMPD_unknown) {}
/// \brief Set cancel region for current cancellation point.
/// \param CR Cancellation region.
void setCancelRegion(OpenMPDirectiveKind CR) { CancelRegion = CR; }
public:
/// \brief Creates directive.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param Clauses List of clauses.
///
static OMPCancelDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
ArrayRef<OMPClause *> Clauses, OpenMPDirectiveKind CancelRegion);
/// \brief Creates an empty directive.
///
/// \param C AST context.
/// \param NumClauses Number of clauses.
///
static OMPCancelDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses, EmptyShell);
/// \brief Get cancellation region for the current cancellation point.
OpenMPDirectiveKind getCancelRegion() const { return CancelRegion; }
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPCancelDirectiveClass;
}
};
/// \brief This represents '#pragma omp taskloop' directive.
///
/// \code
/// #pragma omp taskloop private(a,b) grainsize(val) num_tasks(num)
/// \endcode
/// In this example directive '#pragma omp taskloop' has clauses 'private'
/// with the variables 'a' and 'b', 'grainsize' with expression 'val' and
/// 'num_tasks' with expression 'num'.
///
class OMPTaskLoopDirective : public OMPLoopDirective {
friend class ASTStmtReader;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
OMPTaskLoopDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, unsigned NumClauses)
: OMPLoopDirective(this, OMPTaskLoopDirectiveClass, OMPD_taskloop,
StartLoc, EndLoc, CollapsedNum, NumClauses) {}
/// \brief Build an empty directive.
///
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
explicit OMPTaskLoopDirective(unsigned CollapsedNum, unsigned NumClauses)
: OMPLoopDirective(this, OMPTaskLoopDirectiveClass, OMPD_taskloop,
SourceLocation(), SourceLocation(), CollapsedNum,
NumClauses) {}
public:
/// \brief Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param CollapsedNum Number of collapsed loops.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param Exprs Helper expressions for CodeGen.
///
static OMPTaskLoopDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt, const HelperExprs &Exprs);
/// \brief Creates an empty directive with the place
/// for \a NumClauses clauses.
///
/// \param C AST context.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
static OMPTaskLoopDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses,
unsigned CollapsedNum, EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPTaskLoopDirectiveClass;
}
};
/// \brief This represents '#pragma omp taskloop simd' directive.
///
/// \code
/// #pragma omp taskloop simd private(a,b) grainsize(val) num_tasks(num)
/// \endcode
/// In this example directive '#pragma omp taskloop simd' has clauses 'private'
/// with the variables 'a' and 'b', 'grainsize' with expression 'val' and
/// 'num_tasks' with expression 'num'.
///
class OMPTaskLoopSimdDirective : public OMPLoopDirective {
friend class ASTStmtReader;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
OMPTaskLoopSimdDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, unsigned NumClauses)
: OMPLoopDirective(this, OMPTaskLoopSimdDirectiveClass,
OMPD_taskloop_simd, StartLoc, EndLoc, CollapsedNum,
NumClauses) {}
/// \brief Build an empty directive.
///
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
explicit OMPTaskLoopSimdDirective(unsigned CollapsedNum, unsigned NumClauses)
: OMPLoopDirective(this, OMPTaskLoopSimdDirectiveClass,
OMPD_taskloop_simd, SourceLocation(), SourceLocation(),
CollapsedNum, NumClauses) {}
public:
/// \brief Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param CollapsedNum Number of collapsed loops.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param Exprs Helper expressions for CodeGen.
///
static OMPTaskLoopSimdDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt, const HelperExprs &Exprs);
/// \brief Creates an empty directive with the place
/// for \a NumClauses clauses.
///
/// \param C AST context.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
static OMPTaskLoopSimdDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses,
unsigned CollapsedNum,
EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPTaskLoopSimdDirectiveClass;
}
};
/// \brief This represents '#pragma omp distribute' directive.
///
/// \code
/// #pragma omp distribute private(a,b)
/// \endcode
/// In this example directive '#pragma omp distribute' has clauses 'private'
/// with the variables 'a' and 'b'
///
class OMPDistributeDirective : public OMPLoopDirective {
friend class ASTStmtReader;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
OMPDistributeDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, unsigned NumClauses)
: OMPLoopDirective(this, OMPDistributeDirectiveClass, OMPD_distribute,
StartLoc, EndLoc, CollapsedNum, NumClauses)
{}
/// \brief Build an empty directive.
///
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
explicit OMPDistributeDirective(unsigned CollapsedNum, unsigned NumClauses)
: OMPLoopDirective(this, OMPDistributeDirectiveClass, OMPD_distribute,
SourceLocation(), SourceLocation(), CollapsedNum,
NumClauses)
{}
public:
/// \brief Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param CollapsedNum Number of collapsed loops.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param Exprs Helper expressions for CodeGen.
///
static OMPDistributeDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt, const HelperExprs &Exprs);
/// \brief Creates an empty directive with the place
/// for \a NumClauses clauses.
///
/// \param C AST context.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
static OMPDistributeDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses,
unsigned CollapsedNum, EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPDistributeDirectiveClass;
}
};
/// \brief This represents '#pragma omp target update' directive.
///
/// \code
/// #pragma omp target update to(a) from(b) device(1)
/// \endcode
/// In this example directive '#pragma omp target update' has clause 'to' with
/// argument 'a', clause 'from' with argument 'b' and clause 'device' with
/// argument '1'.
///
class OMPTargetUpdateDirective : public OMPExecutableDirective {
friend class ASTStmtReader;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param NumClauses The number of clauses.
///
OMPTargetUpdateDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned NumClauses)
: OMPExecutableDirective(this, OMPTargetUpdateDirectiveClass,
OMPD_target_update, StartLoc, EndLoc, NumClauses,
0) {}
/// \brief Build an empty directive.
///
/// \param NumClauses Number of clauses.
///
explicit OMPTargetUpdateDirective(unsigned NumClauses)
: OMPExecutableDirective(this, OMPTargetUpdateDirectiveClass,
OMPD_target_update, SourceLocation(),
SourceLocation(), NumClauses, 0) {}
public:
/// \brief Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param Clauses List of clauses.
///
static OMPTargetUpdateDirective *Create(const ASTContext &C,
SourceLocation StartLoc,
SourceLocation EndLoc,
ArrayRef<OMPClause *> Clauses);
/// \brief Creates an empty directive with the place for \a NumClauses
/// clauses.
///
/// \param C AST context.
/// \param NumClauses The number of clauses.
///
static OMPTargetUpdateDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses, EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPTargetUpdateDirectiveClass;
}
};
/// \brief This represents '#pragma omp distribute parallel for' composite
/// directive.
///
/// \code
/// #pragma omp distribute parallel for private(a,b)
/// \endcode
/// In this example directive '#pragma omp distribute parallel for' has clause
/// 'private' with the variables 'a' and 'b'
///
class OMPDistributeParallelForDirective : public OMPLoopDirective {
friend class ASTStmtReader;
/// \brief Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
OMPDistributeParallelForDirective(SourceLocation StartLoc,
SourceLocation EndLoc,
unsigned CollapsedNum, unsigned NumClauses)
: OMPLoopDirective(this, OMPDistributeParallelForDirectiveClass,
OMPD_distribute_parallel_for, StartLoc, EndLoc,
CollapsedNum, NumClauses) {}
/// \brief Build an empty directive.
///
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
explicit OMPDistributeParallelForDirective(unsigned CollapsedNum,
unsigned NumClauses)
: OMPLoopDirective(this, OMPDistributeParallelForDirectiveClass,
OMPD_distribute_parallel_for, SourceLocation(),
SourceLocation(), CollapsedNum, NumClauses) {}
public:
/// \brief Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param CollapsedNum Number of collapsed loops.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param Exprs Helper expressions for CodeGen.
///
static OMPDistributeParallelForDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt, const HelperExprs &Exprs);
/// \brief Creates an empty directive with the place
/// for \a NumClauses clauses.
///
/// \param C AST context.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
static OMPDistributeParallelForDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses,
unsigned CollapsedNum,
EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPDistributeParallelForDirectiveClass;
}
};
/// This represents '#pragma omp distribute parallel for simd' composite
/// directive.
///
/// \code
/// #pragma omp distribute parallel for simd private(x)
/// \endcode
/// In this example directive '#pragma omp distribute parallel for simd' has
/// clause 'private' with the variables 'x'
///
class OMPDistributeParallelForSimdDirective final : public OMPLoopDirective {
friend class ASTStmtReader;
/// Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
OMPDistributeParallelForSimdDirective(SourceLocation StartLoc,
SourceLocation EndLoc,
unsigned CollapsedNum,
unsigned NumClauses)
: OMPLoopDirective(this, OMPDistributeParallelForSimdDirectiveClass,
OMPD_distribute_parallel_for_simd, StartLoc,
EndLoc, CollapsedNum, NumClauses) {}
/// Build an empty directive.
///
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
explicit OMPDistributeParallelForSimdDirective(unsigned CollapsedNum,
unsigned NumClauses)
: OMPLoopDirective(this, OMPDistributeParallelForSimdDirectiveClass,
OMPD_distribute_parallel_for_simd,
SourceLocation(), SourceLocation(), CollapsedNum,
NumClauses) {}
public:
/// Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param CollapsedNum Number of collapsed loops.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param Exprs Helper expressions for CodeGen.
///
static OMPDistributeParallelForSimdDirective *Create(
const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt, const HelperExprs &Exprs);
/// Creates an empty directive with the place for \a NumClauses clauses.
///
/// \param C AST context.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
static OMPDistributeParallelForSimdDirective *CreateEmpty(
const ASTContext &C, unsigned NumClauses, unsigned CollapsedNum,
EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPDistributeParallelForSimdDirectiveClass;
}
};
/// This represents '#pragma omp distribute simd' composite directive.
///
/// \code
/// #pragma omp distribute simd private(x)
/// \endcode
/// In this example directive '#pragma omp distribute simd' has clause
/// 'private' with the variables 'x'
///
class OMPDistributeSimdDirective final : public OMPLoopDirective {
friend class ASTStmtReader;
/// Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
OMPDistributeSimdDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, unsigned NumClauses)
: OMPLoopDirective(this, OMPDistributeSimdDirectiveClass,
OMPD_distribute_simd, StartLoc, EndLoc, CollapsedNum,
NumClauses) {}
/// Build an empty directive.
///
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
explicit OMPDistributeSimdDirective(unsigned CollapsedNum,
unsigned NumClauses)
: OMPLoopDirective(this, OMPDistributeSimdDirectiveClass,
OMPD_distribute_simd, SourceLocation(),
SourceLocation(), CollapsedNum, NumClauses) {}
public:
/// Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param CollapsedNum Number of collapsed loops.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param Exprs Helper expressions for CodeGen.
///
static OMPDistributeSimdDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt, const HelperExprs &Exprs);
/// Creates an empty directive with the place for \a NumClauses clauses.
///
/// \param C AST context.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
static OMPDistributeSimdDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses,
unsigned CollapsedNum,
EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPDistributeSimdDirectiveClass;
}
};
/// This represents '#pragma omp target parallel for simd' directive.
///
/// \code
/// #pragma omp target parallel for simd private(a) map(b) safelen(c)
/// \endcode
/// In this example directive '#pragma omp target parallel for simd' has clauses
/// 'private' with the variable 'a', 'map' with the variable 'b' and 'safelen'
/// with the variable 'c'.
///
class OMPTargetParallelForSimdDirective final : public OMPLoopDirective {
friend class ASTStmtReader;
/// Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
OMPTargetParallelForSimdDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, unsigned NumClauses)
: OMPLoopDirective(this, OMPTargetParallelForSimdDirectiveClass,
OMPD_target_parallel_for_simd, StartLoc, EndLoc,
CollapsedNum, NumClauses) {}
/// Build an empty directive.
///
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
explicit OMPTargetParallelForSimdDirective(unsigned CollapsedNum,
unsigned NumClauses)
: OMPLoopDirective(this, OMPTargetParallelForSimdDirectiveClass,
OMPD_target_parallel_for_simd, SourceLocation(),
SourceLocation(), CollapsedNum, NumClauses) {}
public:
/// Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param CollapsedNum Number of collapsed loops.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param Exprs Helper expressions for CodeGen.
///
static OMPTargetParallelForSimdDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt, const HelperExprs &Exprs);
/// Creates an empty directive with the place for \a NumClauses clauses.
///
/// \param C AST context.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
static OMPTargetParallelForSimdDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses,
unsigned CollapsedNum,
EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPTargetParallelForSimdDirectiveClass;
}
};
/// This represents '#pragma omp target simd' directive.
///
/// \code
/// #pragma omp target simd private(a) map(b) safelen(c)
/// \endcode
/// In this example directive '#pragma omp target simd' has clauses 'private'
/// with the variable 'a', 'map' with the variable 'b' and 'safelen' with
/// the variable 'c'.
///
class OMPTargetSimdDirective final : public OMPLoopDirective {
friend class ASTStmtReader;
/// Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
OMPTargetSimdDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, unsigned NumClauses)
: OMPLoopDirective(this, OMPTargetSimdDirectiveClass,
OMPD_target_simd, StartLoc, EndLoc, CollapsedNum,
NumClauses) {}
/// Build an empty directive.
///
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
explicit OMPTargetSimdDirective(unsigned CollapsedNum, unsigned NumClauses)
: OMPLoopDirective(this, OMPTargetSimdDirectiveClass, OMPD_target_simd,
SourceLocation(),SourceLocation(), CollapsedNum,
NumClauses) {}
public:
/// Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param CollapsedNum Number of collapsed loops.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param Exprs Helper expressions for CodeGen.
///
static OMPTargetSimdDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt, const HelperExprs &Exprs);
/// Creates an empty directive with the place for \a NumClauses clauses.
///
/// \param C AST context.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
static OMPTargetSimdDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses,
unsigned CollapsedNum,
EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPTargetSimdDirectiveClass;
}
};
/// This represents '#pragma omp teams distribute' directive.
///
/// \code
/// #pragma omp teams distribute private(a,b)
/// \endcode
/// In this example directive '#pragma omp teams distribute' has clauses
/// 'private' with the variables 'a' and 'b'
///
class OMPTeamsDistributeDirective final : public OMPLoopDirective {
friend class ASTStmtReader;
/// Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
OMPTeamsDistributeDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, unsigned NumClauses)
: OMPLoopDirective(this, OMPTeamsDistributeDirectiveClass,
OMPD_teams_distribute, StartLoc, EndLoc,
CollapsedNum, NumClauses) {}
/// Build an empty directive.
///
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
explicit OMPTeamsDistributeDirective(unsigned CollapsedNum,
unsigned NumClauses)
: OMPLoopDirective(this, OMPTeamsDistributeDirectiveClass,
OMPD_teams_distribute, SourceLocation(),
SourceLocation(), CollapsedNum, NumClauses) {}
public:
/// Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param CollapsedNum Number of collapsed loops.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param Exprs Helper expressions for CodeGen.
///
static OMPTeamsDistributeDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt, const HelperExprs &Exprs);
/// Creates an empty directive with the place for \a NumClauses clauses.
///
/// \param C AST context.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
static OMPTeamsDistributeDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses,
unsigned CollapsedNum,
EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPTeamsDistributeDirectiveClass;
}
};
/// This represents '#pragma omp teams distribute simd'
/// combined directive.
///
/// \code
/// #pragma omp teams distribute simd private(a,b)
/// \endcode
/// In this example directive '#pragma omp teams distribute simd'
/// has clause 'private' with the variables 'a' and 'b'
///
class OMPTeamsDistributeSimdDirective final : public OMPLoopDirective {
friend class ASTStmtReader;
/// Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
OMPTeamsDistributeSimdDirective(SourceLocation StartLoc,
SourceLocation EndLoc, unsigned CollapsedNum,
unsigned NumClauses)
: OMPLoopDirective(this, OMPTeamsDistributeSimdDirectiveClass,
OMPD_teams_distribute_simd, StartLoc, EndLoc,
CollapsedNum, NumClauses) {}
/// Build an empty directive.
///
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
explicit OMPTeamsDistributeSimdDirective(unsigned CollapsedNum,
unsigned NumClauses)
: OMPLoopDirective(this, OMPTeamsDistributeSimdDirectiveClass,
OMPD_teams_distribute_simd, SourceLocation(),
SourceLocation(), CollapsedNum, NumClauses) {}
public:
/// Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param CollapsedNum Number of collapsed loops.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param Exprs Helper expressions for CodeGen.
///
static OMPTeamsDistributeSimdDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt, const HelperExprs &Exprs);
/// Creates an empty directive with the place
/// for \a NumClauses clauses.
///
/// \param C AST context.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
static OMPTeamsDistributeSimdDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses,
unsigned CollapsedNum,
EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPTeamsDistributeSimdDirectiveClass;
}
};
/// This represents '#pragma omp teams distribute parallel for simd' composite
/// directive.
///
/// \code
/// #pragma omp teams distribute parallel for simd private(x)
/// \endcode
/// In this example directive '#pragma omp teams distribute parallel for simd'
/// has clause 'private' with the variables 'x'
///
class OMPTeamsDistributeParallelForSimdDirective final
: public OMPLoopDirective {
friend class ASTStmtReader;
/// Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
OMPTeamsDistributeParallelForSimdDirective(SourceLocation StartLoc,
SourceLocation EndLoc,
unsigned CollapsedNum,
unsigned NumClauses)
: OMPLoopDirective(this, OMPTeamsDistributeParallelForSimdDirectiveClass,
OMPD_teams_distribute_parallel_for_simd, StartLoc,
EndLoc, CollapsedNum, NumClauses) {}
/// Build an empty directive.
///
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
explicit OMPTeamsDistributeParallelForSimdDirective(unsigned CollapsedNum,
unsigned NumClauses)
: OMPLoopDirective(this, OMPTeamsDistributeParallelForSimdDirectiveClass,
OMPD_teams_distribute_parallel_for_simd,
SourceLocation(), SourceLocation(), CollapsedNum,
NumClauses) {}
public:
/// Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param CollapsedNum Number of collapsed loops.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param Exprs Helper expressions for CodeGen.
///
static OMPTeamsDistributeParallelForSimdDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt, const HelperExprs &Exprs);
/// Creates an empty directive with the place for \a NumClauses clauses.
///
/// \param C AST context.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
static OMPTeamsDistributeParallelForSimdDirective *
CreateEmpty(const ASTContext &C, unsigned NumClauses, unsigned CollapsedNum,
EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPTeamsDistributeParallelForSimdDirectiveClass;
}
};
/// This represents '#pragma omp teams distribute parallel for' composite
/// directive.
///
/// \code
/// #pragma omp teams distribute parallel for private(x)
/// \endcode
/// In this example directive '#pragma omp teams distribute parallel for'
/// has clause 'private' with the variables 'x'
///
class OMPTeamsDistributeParallelForDirective final : public OMPLoopDirective {
friend class ASTStmtReader;
/// Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
OMPTeamsDistributeParallelForDirective(SourceLocation StartLoc,
SourceLocation EndLoc,
unsigned CollapsedNum,
unsigned NumClauses)
: OMPLoopDirective(this, OMPTeamsDistributeParallelForDirectiveClass,
OMPD_teams_distribute_parallel_for, StartLoc, EndLoc,
CollapsedNum, NumClauses) {}
/// Build an empty directive.
///
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
explicit OMPTeamsDistributeParallelForDirective(unsigned CollapsedNum,
unsigned NumClauses)
: OMPLoopDirective(this, OMPTeamsDistributeParallelForDirectiveClass,
OMPD_teams_distribute_parallel_for, SourceLocation(),
SourceLocation(), CollapsedNum, NumClauses) {}
public:
/// Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param CollapsedNum Number of collapsed loops.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param Exprs Helper expressions for CodeGen.
///
static OMPTeamsDistributeParallelForDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt, const HelperExprs &Exprs);
/// Creates an empty directive with the place for \a NumClauses clauses.
///
/// \param C AST context.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
static OMPTeamsDistributeParallelForDirective *
CreateEmpty(const ASTContext &C, unsigned NumClauses, unsigned CollapsedNum,
EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPTeamsDistributeParallelForDirectiveClass;
}
};
/// This represents '#pragma omp target teams' directive.
///
/// \code
/// #pragma omp target teams if(a>0)
/// \endcode
/// In this example directive '#pragma omp target teams' has clause 'if' with
/// condition 'a>0'.
///
class OMPTargetTeamsDirective final : public OMPExecutableDirective {
friend class ASTStmtReader;
/// Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param NumClauses Number of clauses.
///
OMPTargetTeamsDirective(SourceLocation StartLoc, SourceLocation EndLoc,
unsigned NumClauses)
: OMPExecutableDirective(this, OMPTargetTeamsDirectiveClass,
OMPD_target_teams, StartLoc, EndLoc, NumClauses,
1) {}
/// Build an empty directive.
///
/// \param NumClauses Number of clauses.
///
explicit OMPTargetTeamsDirective(unsigned NumClauses)
: OMPExecutableDirective(this, OMPTargetTeamsDirectiveClass,
OMPD_target_teams, SourceLocation(),
SourceLocation(), NumClauses, 1) {}
public:
/// Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
///
static OMPTargetTeamsDirective *Create(const ASTContext &C,
SourceLocation StartLoc,
SourceLocation EndLoc,
ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt);
/// Creates an empty directive with the place for \a NumClauses clauses.
///
/// \param C AST context.
/// \param NumClauses Number of clauses.
///
static OMPTargetTeamsDirective *CreateEmpty(const ASTContext &C,
unsigned NumClauses, EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPTargetTeamsDirectiveClass;
}
};
/// This represents '#pragma omp target teams distribute' combined directive.
///
/// \code
/// #pragma omp target teams distribute private(x)
/// \endcode
/// In this example directive '#pragma omp target teams distribute' has clause
/// 'private' with the variables 'x'
///
class OMPTargetTeamsDistributeDirective final : public OMPLoopDirective {
friend class ASTStmtReader;
/// Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
OMPTargetTeamsDistributeDirective(SourceLocation StartLoc,
SourceLocation EndLoc,
unsigned CollapsedNum, unsigned NumClauses)
: OMPLoopDirective(this, OMPTargetTeamsDistributeDirectiveClass,
OMPD_target_teams_distribute, StartLoc, EndLoc,
CollapsedNum, NumClauses) {}
/// Build an empty directive.
///
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
explicit OMPTargetTeamsDistributeDirective(unsigned CollapsedNum,
unsigned NumClauses)
: OMPLoopDirective(this, OMPTargetTeamsDistributeDirectiveClass,
OMPD_target_teams_distribute, SourceLocation(),
SourceLocation(), CollapsedNum, NumClauses) {}
public:
/// Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param CollapsedNum Number of collapsed loops.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param Exprs Helper expressions for CodeGen.
///
static OMPTargetTeamsDistributeDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt, const HelperExprs &Exprs);
/// Creates an empty directive with the place for \a NumClauses clauses.
///
/// \param C AST context.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
static OMPTargetTeamsDistributeDirective *
CreateEmpty(const ASTContext &C, unsigned NumClauses, unsigned CollapsedNum,
EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPTargetTeamsDistributeDirectiveClass;
}
};
/// This represents '#pragma omp target teams distribute parallel for' combined
/// directive.
///
/// \code
/// #pragma omp target teams distribute parallel for private(x)
/// \endcode
/// In this example directive '#pragma omp target teams distribute parallel
/// for' has clause 'private' with the variables 'x'
///
class OMPTargetTeamsDistributeParallelForDirective final
: public OMPLoopDirective {
friend class ASTStmtReader;
/// Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
OMPTargetTeamsDistributeParallelForDirective(SourceLocation StartLoc,
SourceLocation EndLoc,
unsigned CollapsedNum,
unsigned NumClauses)
: OMPLoopDirective(this,
OMPTargetTeamsDistributeParallelForDirectiveClass,
OMPD_target_teams_distribute_parallel_for, StartLoc,
EndLoc, CollapsedNum, NumClauses) {}
/// Build an empty directive.
///
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
explicit OMPTargetTeamsDistributeParallelForDirective(unsigned CollapsedNum,
unsigned NumClauses)
: OMPLoopDirective(
this, OMPTargetTeamsDistributeParallelForDirectiveClass,
OMPD_target_teams_distribute_parallel_for, SourceLocation(),
SourceLocation(), CollapsedNum, NumClauses) {}
public:
/// Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param CollapsedNum Number of collapsed loops.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param Exprs Helper expressions for CodeGen.
///
static OMPTargetTeamsDistributeParallelForDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt, const HelperExprs &Exprs);
/// Creates an empty directive with the place for \a NumClauses clauses.
///
/// \param C AST context.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
static OMPTargetTeamsDistributeParallelForDirective *
CreateEmpty(const ASTContext &C, unsigned NumClauses, unsigned CollapsedNum,
EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() ==
OMPTargetTeamsDistributeParallelForDirectiveClass;
}
};
/// This represents '#pragma omp target teams distribute parallel for simd'
/// combined directive.
///
/// \code
/// #pragma omp target teams distribute parallel for simd private(x)
/// \endcode
/// In this example directive '#pragma omp target teams distribute parallel
/// for simd' has clause 'private' with the variables 'x'
///
class OMPTargetTeamsDistributeParallelForSimdDirective final
: public OMPLoopDirective {
friend class ASTStmtReader;
/// Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
OMPTargetTeamsDistributeParallelForSimdDirective(SourceLocation StartLoc,
SourceLocation EndLoc,
unsigned CollapsedNum,
unsigned NumClauses)
: OMPLoopDirective(this,
OMPTargetTeamsDistributeParallelForSimdDirectiveClass,
OMPD_target_teams_distribute_parallel_for_simd,
StartLoc, EndLoc, CollapsedNum, NumClauses) {}
/// Build an empty directive.
///
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
explicit OMPTargetTeamsDistributeParallelForSimdDirective(
unsigned CollapsedNum, unsigned NumClauses)
: OMPLoopDirective(
this, OMPTargetTeamsDistributeParallelForSimdDirectiveClass,
OMPD_target_teams_distribute_parallel_for_simd, SourceLocation(),
SourceLocation(), CollapsedNum, NumClauses) {}
public:
/// Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param CollapsedNum Number of collapsed loops.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param Exprs Helper expressions for CodeGen.
///
static OMPTargetTeamsDistributeParallelForSimdDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt, const HelperExprs &Exprs);
/// Creates an empty directive with the place for \a NumClauses clauses.
///
/// \param C AST context.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
static OMPTargetTeamsDistributeParallelForSimdDirective *
CreateEmpty(const ASTContext &C, unsigned NumClauses, unsigned CollapsedNum,
EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() ==
OMPTargetTeamsDistributeParallelForSimdDirectiveClass;
}
};
/// This represents '#pragma omp target teams distribute simd' combined
/// directive.
///
/// \code
/// #pragma omp target teams distribute simd private(x)
/// \endcode
/// In this example directive '#pragma omp target teams distribute simd'
/// has clause 'private' with the variables 'x'
///
class OMPTargetTeamsDistributeSimdDirective final : public OMPLoopDirective {
friend class ASTStmtReader;
/// Build directive with the given start and end location.
///
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending location of the directive.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
OMPTargetTeamsDistributeSimdDirective(SourceLocation StartLoc,
SourceLocation EndLoc,
unsigned CollapsedNum,
unsigned NumClauses)
: OMPLoopDirective(this, OMPTargetTeamsDistributeSimdDirectiveClass,
OMPD_target_teams_distribute_simd, StartLoc, EndLoc,
CollapsedNum, NumClauses) {}
/// Build an empty directive.
///
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
explicit OMPTargetTeamsDistributeSimdDirective(unsigned CollapsedNum,
unsigned NumClauses)
: OMPLoopDirective(this, OMPTargetTeamsDistributeSimdDirectiveClass,
OMPD_target_teams_distribute_simd, SourceLocation(),
SourceLocation(), CollapsedNum, NumClauses) {}
public:
/// Creates directive with a list of \a Clauses.
///
/// \param C AST context.
/// \param StartLoc Starting location of the directive kind.
/// \param EndLoc Ending Location of the directive.
/// \param CollapsedNum Number of collapsed loops.
/// \param Clauses List of clauses.
/// \param AssociatedStmt Statement, associated with the directive.
/// \param Exprs Helper expressions for CodeGen.
///
static OMPTargetTeamsDistributeSimdDirective *
Create(const ASTContext &C, SourceLocation StartLoc, SourceLocation EndLoc,
unsigned CollapsedNum, ArrayRef<OMPClause *> Clauses,
Stmt *AssociatedStmt, const HelperExprs &Exprs);
/// Creates an empty directive with the place for \a NumClauses clauses.
///
/// \param C AST context.
/// \param CollapsedNum Number of collapsed nested loops.
/// \param NumClauses Number of clauses.
///
static OMPTargetTeamsDistributeSimdDirective *
CreateEmpty(const ASTContext &C, unsigned NumClauses, unsigned CollapsedNum,
EmptyShell);
static bool classof(const Stmt *T) {
return T->getStmtClass() == OMPTargetTeamsDistributeSimdDirectiveClass;
}
};
} // end namespace clang
#endif
|
GB_binop__min_int16.c |
//------------------------------------------------------------------------------
// GB_binop: hard-coded functions for each built-in binary operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2021, All Rights Reserved.
// SPDX-License-Identifier: Apache-2.0
//------------------------------------------------------------------------------
// If this file is in the Generated2/ folder, do not edit it
// (it is auto-generated from Generator/*).
#include "GB.h"
#ifndef GBCOMPACT
#include "GB_emult.h"
#include "GB_control.h"
#include "GB_ek_slice.h"
#include "GB_dense.h"
#include "GB_atomics.h"
#include "GB_bitmap_assign_methods.h"
#include "GB_binop__include.h"
// C=binop(A,B) is defined by the following types and operators:
// A+B function (eWiseAdd): GB (_AaddB__min_int16)
// A.*B function (eWiseMult): GB (_AemultB_08__min_int16)
// A.*B function (eWiseMult): GB (_AemultB_02__min_int16)
// A.*B function (eWiseMult): GB (_AemultB_04__min_int16)
// A.*B function (eWiseMult): GB (_AemultB_bitmap__min_int16)
// A*D function (colscale): GB (_AxD__min_int16)
// D*A function (rowscale): GB (_DxB__min_int16)
// C+=B function (dense accum): GB (_Cdense_accumB__min_int16)
// C+=b function (dense accum): GB (_Cdense_accumb__min_int16)
// C+=A+B function (dense ewise3): GB (_Cdense_ewise3_accum__min_int16)
// C=A+B function (dense ewise3): GB (_Cdense_ewise3_noaccum__min_int16)
// C=scalar+B GB (_bind1st__min_int16)
// C=scalar+B' GB (_bind1st_tran__min_int16)
// C=A+scalar GB (_bind2nd__min_int16)
// C=A'+scalar GB (_bind2nd_tran__min_int16)
// C type: int16_t
// A type: int16_t
// A pattern? 0
// B type: int16_t
// B pattern? 0
// BinaryOp: cij = GB_IMIN (aij, bij)
#define GB_ATYPE \
int16_t
#define GB_BTYPE \
int16_t
#define GB_CTYPE \
int16_t
// true if the types of A and B are identical
#define GB_ATYPE_IS_BTYPE \
1
// true if the types of C and A are identical
#define GB_CTYPE_IS_ATYPE \
1
// true if the types of C and B are identical
#define GB_CTYPE_IS_BTYPE \
1
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA,A_iso) \
int16_t aij = GBX (Ax, pA, A_iso)
// true if values of A are not used
#define GB_A_IS_PATTERN \
0 \
// bij = Bx [pB]
#define GB_GETB(bij,Bx,pB,B_iso) \
int16_t bij = GBX (Bx, pB, B_iso)
// true if values of B are not used
#define GB_B_IS_PATTERN \
0 \
// declare scalar of the same type as C
#define GB_CTYPE_SCALAR(t) \
int16_t t
// cij = Ax [pA]
#define GB_COPY_A_TO_C(cij,Ax,pA,A_iso) \
cij = GBX (Ax, pA, A_iso)
// cij = Bx [pB]
#define GB_COPY_B_TO_C(cij,Bx,pB,B_iso) \
cij = GBX (Bx, pB, B_iso)
#define GB_CX(p) Cx [p]
// binary operator
#define GB_BINOP(z,x,y,i,j) \
z = GB_IMIN (x, y) ;
// true if the binop must be flipped
#define GB_BINOP_FLIP \
0
// op is second
#define GB_OP_IS_SECOND \
0
// do the numerical phases of GB_add and GB_emult
#define GB_PHASE_2_OF_2
// hard-coded loops can be vectorized
#define GB_PRAGMA_SIMD_VECTORIZE GB_PRAGMA_SIMD
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_MIN || GxB_NO_INT16 || GxB_NO_MIN_INT16)
//------------------------------------------------------------------------------
// C += A+B, all 3 matrices dense
//------------------------------------------------------------------------------
// The op must be MIN, MAX, PLUS, MINUS, RMINUS, TIMES, DIV, or RDIV.
void GB (_Cdense_ewise3_accum__min_int16)
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix B,
const int nthreads
)
{
#include "GB_dense_ewise3_accum_template.c"
}
//------------------------------------------------------------------------------
// C = A+B, all 3 matrices dense
//------------------------------------------------------------------------------
void GB (_Cdense_ewise3_noaccum__min_int16)
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix B,
const int nthreads
)
{
#include "GB_dense_ewise3_noaccum_template.c"
}
//------------------------------------------------------------------------------
// C += B, accumulate a sparse matrix into a dense matrix
//------------------------------------------------------------------------------
GrB_Info GB (_Cdense_accumB__min_int16)
(
GrB_Matrix C,
const GrB_Matrix B,
const int64_t *B_ek_slicing, const int B_ntasks, const int B_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
{
#include "GB_dense_subassign_23_template.c"
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C += b, accumulate a scalar into a dense matrix
//------------------------------------------------------------------------------
GrB_Info GB (_Cdense_accumb__min_int16)
(
GrB_Matrix C,
const GB_void *p_bwork,
const int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
{
// get the scalar b for C += b, of type int16_t
int16_t bwork = (*((int16_t *) p_bwork)) ;
#include "GB_dense_subassign_22_template.c"
return (GrB_SUCCESS) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = A*D, column scale with diagonal D matrix
//------------------------------------------------------------------------------
GrB_Info GB (_AxD__min_int16)
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix D,
const int64_t *A_ek_slicing, const int A_ntasks, const int A_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int16_t *restrict Cx = (int16_t *) C->x ;
#include "GB_AxB_colscale_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = D*B, row scale with diagonal D matrix
//------------------------------------------------------------------------------
GrB_Info GB (_DxB__min_int16)
(
GrB_Matrix C,
const GrB_Matrix D,
const GrB_Matrix B,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int16_t *restrict Cx = (int16_t *) C->x ;
#include "GB_AxB_rowscale_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseAdd: C=A+B, C<M>=A+B, C<!M>=A+B
//------------------------------------------------------------------------------
GrB_Info GB (_AaddB__min_int16)
(
GrB_Matrix C,
const int C_sparsity,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const bool is_eWiseUnion,
const GB_void *alpha_scalar_in,
const GB_void *beta_scalar_in,
const bool Ch_is_Mh,
const int64_t *restrict C_to_M,
const int64_t *restrict C_to_A,
const int64_t *restrict C_to_B,
const GB_task_struct *restrict TaskList,
const int C_ntasks,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
GB_WERK_DECLARE (M_ek_slicing, int64_t) ;
GB_WERK_DECLARE (A_ek_slicing, int64_t) ;
GB_WERK_DECLARE (B_ek_slicing, int64_t) ;
int16_t alpha_scalar ;
int16_t beta_scalar ;
if (is_eWiseUnion)
{
alpha_scalar = (*((int16_t *) alpha_scalar_in)) ;
beta_scalar = (*((int16_t *) beta_scalar_in )) ;
}
#include "GB_add_template.c"
GB_FREE_WORKSPACE ;
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C=A.*B, C<M>=A.*B, or C<M!>=A.*B where C is sparse/hyper
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_08__min_int16)
(
GrB_Matrix C,
const int C_sparsity,
const int ewise_method,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *restrict C_to_M,
const int64_t *restrict C_to_A,
const int64_t *restrict C_to_B,
const GB_task_struct *restrict TaskList,
const int C_ntasks,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_emult_08_meta.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C<#> = A.*B when A is sparse/hyper and B is bitmap/full
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_02__min_int16)
(
GrB_Matrix C,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const bool flipxy,
const int64_t *restrict Cp_kfirst,
const int64_t *A_ek_slicing, const int A_ntasks, const int A_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#if GB_BINOP_FLIP
// The operator is not commutative, and does not have a flipped
// variant. For example z=atan2(y,x).
if (flipxy)
{
// use fmult(y,x)
#undef GB_FLIPPED
#define GB_FLIPPED 1
#include "GB_emult_02_template.c"
}
else
{
// use fmult(x,y)
#undef GB_FLIPPED
#define GB_FLIPPED 0
#include "GB_emult_02_template.c"
}
#else
// No need to handle the flip: the operator is either commutative, or
// has been handled by changing z=div(y,x) to z=rdiv(x,y) for example.
#undef GB_FLIPPED
#define GB_FLIPPED 0
#include "GB_emult_02_template.c"
#endif
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C<M> = A.*B, M sparse/hyper, A and B bitmap/full
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_04__min_int16)
(
GrB_Matrix C,
const GrB_Matrix M,
const bool Mask_struct,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *restrict Cp_kfirst,
const int64_t *M_ek_slicing, const int M_ntasks, const int M_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_emult_04_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C=A.*B, C<M>=A.*B, C<!M>=A.*B where C is bitmap
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_bitmap__min_int16)
(
GrB_Matrix C,
const int ewise_method,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *M_ek_slicing, const int M_ntasks, const int M_nthreads,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_bitmap_emult_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (x,Bx): apply a binary operator to a matrix with scalar bind1st
//------------------------------------------------------------------------------
GrB_Info GB (_bind1st__min_int16)
(
GB_void *Cx_output, // Cx and Bx may be aliased
const GB_void *x_input,
const GB_void *Bx_input,
const int8_t *restrict Bb,
int64_t bnz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int16_t *Cx = (int16_t *) Cx_output ;
int16_t x = (*((int16_t *) x_input)) ;
int16_t *Bx = (int16_t *) Bx_input ;
int64_t p ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < bnz ; p++)
{
if (!GBB (Bb, p)) continue ;
int16_t bij = GBX (Bx, p, false) ;
Cx [p] = GB_IMIN (x, bij) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (Ax,y): apply a binary operator to a matrix with scalar bind2nd
//------------------------------------------------------------------------------
GrB_Info GB (_bind2nd__min_int16)
(
GB_void *Cx_output, // Cx and Ax may be aliased
const GB_void *Ax_input,
const GB_void *y_input,
const int8_t *restrict Ab,
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t p ;
int16_t *Cx = (int16_t *) Cx_output ;
int16_t *Ax = (int16_t *) Ax_input ;
int16_t y = (*((int16_t *) y_input)) ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
if (!GBB (Ab, p)) continue ;
int16_t aij = GBX (Ax, p, false) ;
Cx [p] = GB_IMIN (aij, y) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (x, A'): transpose and apply a binary operator
//------------------------------------------------------------------------------
// cij = op (x, aij), no typecasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
int16_t aij = GBX (Ax, pA, false) ; \
Cx [pC] = GB_IMIN (x, aij) ; \
}
GrB_Info GB (_bind1st_tran__min_int16)
(
GrB_Matrix C,
const GB_void *x_input,
const GrB_Matrix A,
int64_t *restrict *Workspaces,
const int64_t *restrict A_slice,
int nworkspaces,
int nthreads
)
{
// GB_unop_transpose.c uses GB_ATYPE, but A is
// the 2nd input to binary operator z=f(x,y).
#undef GB_ATYPE
#define GB_ATYPE \
int16_t
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int16_t x = (*((const int16_t *) x_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
#undef GB_ATYPE
#define GB_ATYPE \
int16_t
}
//------------------------------------------------------------------------------
// C = op (A', y): transpose and apply a binary operator
//------------------------------------------------------------------------------
// cij = op (aij, y), no typecasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
int16_t aij = GBX (Ax, pA, false) ; \
Cx [pC] = GB_IMIN (aij, y) ; \
}
GrB_Info GB (_bind2nd_tran__min_int16)
(
GrB_Matrix C,
const GrB_Matrix A,
const GB_void *y_input,
int64_t *restrict *Workspaces,
const int64_t *restrict A_slice,
int nworkspaces,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int16_t y = (*((const int16_t *) y_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
pooling.h | // Copyright 2018 Xiaomi, Inc. All rights reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#ifndef MACE_KERNELS_POOLING_H_
#define MACE_KERNELS_POOLING_H_
#include <algorithm>
#include <limits>
#include <memory>
#include <vector>
#include "mace/core/future.h"
#include "mace/core/tensor.h"
#include "mace/kernels/conv_pool_2d_util.h"
#include "mace/kernels/kernel.h"
#if defined(MACE_ENABLE_NEON)
#include <arm_neon.h>
#endif
namespace mace {
enum PoolingType {
AVG = 1, // avg_pool
MAX = 2, // max_pool
};
namespace kernels {
struct PoolingFunctorBase : OpKernel {
PoolingFunctorBase(OpKernelContext *context,
const PoolingType pooling_type,
const int *kernels,
const int *strides,
const Padding padding_type,
const std::vector<int> &paddings,
const int *dilations)
: OpKernel(context),
pooling_type_(pooling_type),
kernels_(kernels),
strides_(strides),
padding_type_(padding_type),
paddings_(paddings),
dilations_(dilations) {}
const PoolingType pooling_type_;
const int *kernels_;
const int *strides_;
const Padding padding_type_;
std::vector<int> paddings_;
const int *dilations_;
};
template <DeviceType D, typename T>
struct PoolingFunctor;
template <>
struct PoolingFunctor<DeviceType::CPU, float>: PoolingFunctorBase {
PoolingFunctor(OpKernelContext *context,
const PoolingType pooling_type,
const int *kernels,
const int *strides,
const Padding padding_type,
const std::vector<int> &paddings,
const int *dilations)
: PoolingFunctorBase(context,
pooling_type,
kernels,
strides,
padding_type,
paddings,
dilations) {}
void MaxPooling(const float *input,
const index_t *in_shape,
const index_t *out_shape,
const int *filter_hw,
const int *stride_hw,
const int *dilation_hw,
const int *pad_hw,
float *output) {
const index_t in_image_size = in_shape[2] * in_shape[3];
const index_t out_image_size = out_shape[2] * out_shape[3];
const index_t in_batch_size = in_shape[1] * in_image_size;
const index_t out_batch_size = out_shape[1] * out_image_size;
#pragma omp parallel for collapse(2)
for (index_t b = 0; b < out_shape[0]; ++b) {
for (index_t c = 0; c < out_shape[1]; ++c) {
const index_t out_base = b * out_batch_size + c * out_image_size;
const index_t in_base = b * in_batch_size + c * in_image_size;
const index_t out_height = out_shape[2];
const index_t out_width = out_shape[3];
const index_t in_height = in_shape[2];
const index_t in_width = in_shape[3];
for (index_t h = 0; h < out_height; ++h) {
for (index_t w = 0; w < out_width; ++w) {
const index_t out_offset = out_base + h * out_width + w;
float res = std::numeric_limits<float>::lowest();
for (int fh = 0; fh < filter_hw[0]; ++fh) {
for (int fw = 0; fw < filter_hw[1]; ++fw) {
index_t inh =
h * stride_hw[0] + dilation_hw[0] * fh - pad_hw[0];
index_t inw =
w * stride_hw[1] + dilation_hw[1] * fw - pad_hw[1];
if (inh >= 0 && inh < in_height && inw >= 0 && inw < in_width) {
index_t input_offset = in_base + inh * in_width + inw;
res = std::max(res, input[input_offset]);
}
}
}
output[out_offset] = res;
}
}
}
}
}
void AvgPooling(const float *input,
const index_t *in_shape,
const index_t *out_shape,
const int *filter_hw,
const int *stride_hw,
const int *dilation_hw,
const int *pad_hw,
float *output) {
const index_t in_image_size = in_shape[2] * in_shape[3];
const index_t out_image_size = out_shape[2] * out_shape[3];
const index_t in_batch_size = in_shape[1] * in_image_size;
const index_t out_batch_size = out_shape[1] * out_image_size;
#pragma omp parallel for collapse(2)
for (index_t b = 0; b < out_shape[0]; ++b) {
for (index_t c = 0; c < out_shape[1]; ++c) {
const index_t out_base = b * out_batch_size + c * out_image_size;
const index_t in_base = b * in_batch_size + c * in_image_size;
const index_t in_height = in_shape[2];
const index_t in_width = in_shape[3];
const index_t out_height = out_shape[2];
const index_t out_width = out_shape[3];
for (index_t h = 0; h < out_height; ++h) {
for (index_t w = 0; w < out_width; ++w) {
const index_t out_offset = out_base + h * out_width + w;
float res = 0;
int block_size = 0;
for (int fh = 0; fh < filter_hw[0]; ++fh) {
for (int fw = 0; fw < filter_hw[1]; ++fw) {
index_t inh =
h * stride_hw[0] + dilation_hw[0] * fh - pad_hw[0];
index_t inw =
w * stride_hw[1] + dilation_hw[1] * fw - pad_hw[1];
if (inh >= 0 && inh < in_height && inw >= 0 && inw < in_width) {
index_t input_offset = in_base + inh * in_width + inw;
res += input[input_offset];
++block_size;
}
}
}
output[out_offset] = res / block_size;
}
}
}
}
}
MaceStatus operator()(const Tensor *input_tensor, // NCHW
Tensor *output_tensor, // NCHW
StatsFuture *future) {
MACE_UNUSED(future);
std::vector<index_t> output_shape(4);
std::vector<index_t> filter_shape = {
input_tensor->dim(1), input_tensor->dim(1), kernels_[0], kernels_[1]};
std::vector<int> paddings(2);
if (paddings_.empty()) {
kernels::CalcNCHWPaddingAndOutputSize(
input_tensor->shape().data(), filter_shape.data(), dilations_,
strides_, padding_type_, output_shape.data(), paddings.data());
} else {
paddings = paddings_;
CalcNCHWOutputSize(input_tensor->shape().data(),
filter_shape.data(),
paddings_.data(),
dilations_,
strides_,
RoundType::CEIL,
output_shape.data());
}
MACE_RETURN_IF_ERROR(output_tensor->Resize(output_shape));
Tensor::MappingGuard input_guard(input_tensor);
Tensor::MappingGuard output_guard(output_tensor);
const float *input = input_tensor->data<float>();
float *output = output_tensor->mutable_data<float>();
const index_t *input_shape = input_tensor->shape().data();
int pad_hw[2] = {paddings[0] / 2, paddings[1] / 2};
if (pooling_type_ == PoolingType::MAX) {
MaxPooling(input,
input_shape,
output_shape.data(),
kernels_,
strides_,
dilations_,
pad_hw,
output);
} else if (pooling_type_ == PoolingType::AVG) {
AvgPooling(input,
input_shape,
output_shape.data(),
kernels_,
strides_,
dilations_,
pad_hw,
output);
} else {
MACE_NOT_IMPLEMENTED;
}
return MACE_SUCCESS;
}
};
template <>
struct PoolingFunctor<DeviceType::CPU, uint8_t>: PoolingFunctorBase {
PoolingFunctor(OpKernelContext *context,
const PoolingType pooling_type,
const int *kernels,
const int *strides,
const Padding padding_type,
const std::vector<int> &paddings,
const int *dilations)
: PoolingFunctorBase(context,
pooling_type,
kernels,
strides,
padding_type,
paddings,
dilations) {}
void MaxPooling(const uint8_t *input,
const index_t *in_shape,
const index_t *out_shape,
const int *filter_hw,
const int *stride_hw,
const int *pad_hw,
uint8_t *output) {
#pragma omp parallel for collapse(3)
for (index_t b = 0; b < out_shape[0]; ++b) {
for (index_t h = 0; h < out_shape[1]; ++h) {
for (index_t w = 0; w < out_shape[2]; ++w) {
const index_t out_height = out_shape[1];
const index_t out_width = out_shape[2];
const index_t channels = out_shape[3];
const index_t in_height = in_shape[1];
const index_t in_width = in_shape[2];
const index_t in_h_base = h * stride_hw[0] - pad_hw[0];
const index_t in_w_base = w * stride_hw[1] - pad_hw[1];
const index_t in_h_begin = std::max<index_t>(0, in_h_base);
const index_t in_w_begin = std::max<index_t>(0, in_w_base);
const index_t in_h_end =
std::min(in_height, in_h_base + filter_hw[0]);
const index_t in_w_end =
std::min(in_width, in_w_base + filter_hw[1]);
uint8_t *out_ptr =
output + ((b * out_height + h) * out_width + w) * channels;
for (index_t ih = in_h_begin; ih < in_h_end; ++ih) {
for (index_t iw = in_w_begin; iw < in_w_end; ++iw) {
const uint8_t *in_ptr = input +
((b * in_height + ih) * in_width + iw) * channels;
index_t c = 0;
#if defined(MACE_ENABLE_NEON)
for (; c <= channels - 16; c += 16) {
uint8x16_t out_vec = vld1q_u8(out_ptr + c);
uint8x16_t in_vec = vld1q_u8(in_ptr + c);
out_vec = vmaxq_u8(out_vec, in_vec);
vst1q_u8(out_ptr + c, out_vec);
}
for (; c <= channels - 8; c += 8) {
uint8x8_t out_vec = vld1_u8(out_ptr + c);
uint8x8_t in_vec = vld1_u8(in_ptr + c);
out_vec = vmax_u8(out_vec, in_vec);
vst1_u8(out_ptr + c, out_vec);
}
#endif
for (; c < channels; ++c) {
out_ptr[c] = std::max(out_ptr[c], in_ptr[c]);
}
}
}
}
}
}
}
void AvgPooling(const uint8_t *input,
const index_t *in_shape,
const index_t *out_shape,
const int *filter_hw,
const int *stride_hw,
const int *pad_hw,
uint8_t *output) {
#pragma omp parallel for collapse(3)
for (index_t b = 0; b < out_shape[0]; ++b) {
for (index_t h = 0; h < out_shape[1]; ++h) {
for (index_t w = 0; w < out_shape[2]; ++w) {
const index_t out_height = out_shape[1];
const index_t out_width = out_shape[2];
const index_t channels = out_shape[3];
const index_t in_height = in_shape[1];
const index_t in_width = in_shape[2];
const index_t in_h_base = h * stride_hw[0] - pad_hw[0];
const index_t in_w_base = w * stride_hw[1] - pad_hw[1];
const index_t in_h_begin = std::max<index_t>(0, in_h_base);
const index_t in_w_begin = std::max<index_t>(0, in_w_base);
const index_t in_h_end =
std::min(in_height, in_h_base + filter_hw[0]);
const index_t in_w_end =
std::min(in_width, in_w_base + filter_hw[1]);
const index_t block_size =
(in_h_end - in_h_begin) * (in_w_end - in_w_begin);
MACE_CHECK(block_size > 0);
std::vector<uint16_t> average_buffer(channels);
uint16_t *avg_buffer = average_buffer.data();
std::fill_n(avg_buffer, channels, 0);
for (index_t ih = in_h_begin; ih < in_h_end; ++ih) {
for (index_t iw = in_w_begin; iw < in_w_end; ++iw) {
const uint8_t *in_ptr = input +
((b * in_height + ih) * in_width + iw) * channels;
index_t c = 0;
#if defined(MACE_ENABLE_NEON)
for (; c <= channels - 16; c += 16) {
uint16x8_t avg_vec[2];
avg_vec[0] = vld1q_u16(avg_buffer + c);
avg_vec[1] = vld1q_u16(avg_buffer + c + 8);
uint8x16_t in_vec = vld1q_u8(in_ptr + c);
avg_vec[0] = vaddw_u8(avg_vec[0], vget_low_u8(in_vec));
avg_vec[1] = vaddw_u8(avg_vec[1], vget_high_u8(in_vec));
vst1q_u16(avg_buffer + c, avg_vec[0]);
vst1q_u16(avg_buffer + c + 8, avg_vec[1]);
}
for (; c <= channels - 8; c += 8) {
uint16x8_t avg_vec = vld1q_u16(avg_buffer + c);
uint8x8_t in_vec = vld1_u8(in_ptr + c);
avg_vec = vaddw_u8(avg_vec, in_vec);
vst1q_u16(avg_buffer + c, avg_vec);
}
#endif
for (; c < channels; ++c) {
avg_buffer[c] += in_ptr[c];
}
}
}
uint8_t *out_ptr =
output + ((b * out_height + h) * out_width + w) * channels;
for (index_t c = 0; c < channels; ++c) {
out_ptr[c] = static_cast<uint8_t>(
(avg_buffer[c] + block_size / 2) / block_size);
}
}
}
}
}
MaceStatus operator()(const Tensor *input_tensor, // NHWC
Tensor *output_tensor, // NHWC
StatsFuture *future) {
MACE_UNUSED(future);
MACE_CHECK(dilations_[0] == 1 && dilations_[1] == 1,
"Quantized pooling does not support dilation > 1 yet.");
// Use the same scale and zero point with input and output.
output_tensor->SetScale(input_tensor->scale());
output_tensor->SetZeroPoint(input_tensor->zero_point());
std::vector<index_t> output_shape(4);
std::vector<index_t> filter_shape = {
input_tensor->dim(3), kernels_[0], kernels_[1], input_tensor->dim(3)};
std::vector<int> paddings(2);
if (paddings_.empty()) {
CalcPaddingAndOutputSize(input_tensor->shape().data(),
NHWC,
filter_shape.data(),
OHWI,
dilations_,
strides_,
padding_type_,
output_shape.data(),
paddings.data());
} else {
paddings = paddings_;
CalcOutputSize(input_tensor->shape().data(),
NHWC,
filter_shape.data(),
OHWI,
paddings_.data(),
dilations_,
strides_,
RoundType::CEIL,
output_shape.data());
}
MACE_RETURN_IF_ERROR(output_tensor->Resize(output_shape));
const index_t out_channels = output_tensor->dim(3);
const index_t in_channels = input_tensor->dim(3);
MACE_CHECK(out_channels == in_channels);
Tensor::MappingGuard input_guard(input_tensor);
Tensor::MappingGuard output_guard(output_tensor);
const uint8_t *input = input_tensor->data<uint8_t>();
uint8_t *output = output_tensor->mutable_data<uint8_t>();
int pad_hw[2] = {paddings[0] / 2, paddings[1] / 2};
if (pooling_type_ == PoolingType::MAX) {
MaxPooling(input,
input_tensor->shape().data(),
output_shape.data(),
kernels_,
strides_,
pad_hw,
output);
} else if (pooling_type_ == PoolingType::AVG) {
AvgPooling(input,
input_tensor->shape().data(),
output_shape.data(),
kernels_,
strides_,
pad_hw,
output);
} else {
MACE_NOT_IMPLEMENTED;
}
return MACE_SUCCESS;
}
};
#ifdef MACE_ENABLE_OPENCL
class OpenCLPoolingKernel {
public:
virtual MaceStatus Compute(
OpKernelContext *context,
const Tensor *input,
const PoolingType pooling_type,
const int *kernels,
const int *strides,
const Padding &padding_type,
const std::vector<int> &padding_data,
const int *dilations,
Tensor *output,
StatsFuture *future) = 0;
MACE_VIRTUAL_EMPTY_DESTRUCTOR(OpenCLPoolingKernel);
};
template <typename T>
struct PoolingFunctor<DeviceType::GPU, T> : PoolingFunctorBase {
PoolingFunctor(OpKernelContext *context,
const PoolingType pooling_type,
const int *kernels,
const int *strides,
const Padding padding_type,
const std::vector<int> &paddings,
const int *dilations);
MaceStatus operator()(const Tensor *input_tensor,
Tensor *output_tensor,
StatsFuture *future);
std::unique_ptr<OpenCLPoolingKernel> kernel_;
};
#endif // MACE_ENABLE_OPENCL
} // namespace kernels
} // namespace mace
#endif // MACE_KERNELS_POOLING_H_
|
reduction_max.c | // PASS: *
// RUN: ${CATO_ROOT}/src/scripts/cexecute_pass.py %s -o %t
// RUN: diff <(mpirun -np 4 %t) %s.reference_output
#include <stdio.h>
#include <omp.h>
int main()
{
int result = 0;
#pragma omp parallel reduction(max:result)
{
result = omp_get_thread_num();
}
printf("Result: %d\n", result);
}
|
atomic_vs_reduction.c | #include <stdio.h>
#include <omp.h>
int main() {
//
// atomic_vs_reduction.c: This test shows how much faster reductions are than atomic operations
//
int main_rc = 0;
int N = 5001;
float expect = (float) (((float)N-1)*(float)N)/2.0;
for (int i = 0; i < 4; i++) {
#pragma omp target
{
}
}
float a = 0.0;
double t0 = omp_get_wtime();
#pragma omp target teams distribute parallel for map(tofrom:a)
for(int ii = 0; ii < N; ++ii) {
#pragma omp atomic hint(AMD_fast_fp_atomics)
a+=(float)ii;;
}
double t1 = omp_get_wtime()-t0;
if (a == expect) {
printf("Success atomic with hint (fast FP atomic) sum of %d integers is: %f in \t\t%f secs\n",N,a,t1);
} else {
printf("FAIL ATOMIC SUM N:%d result: %f != expect: %f \n", N,a,expect);
main_rc=1;
}
float casa = 0.0;
double t_cas0 = omp_get_wtime();
#pragma omp target teams distribute parallel for map(tofrom:casa)
for(int ii = 0; ii < N; ++ii) {
#pragma omp atomic
casa+=(float)ii;;
}
double t_cas1 = omp_get_wtime()-t_cas0;
if (casa == expect) {
printf("Success atomic without hint (cas loop) sum of %d integers is: %f in \t\t%f secs\n",N,casa,t_cas1);
} else {
printf("FAIL ATOMIC SUM N:%d result: %f != expect: %f \n", N,casa,expect);
main_rc=1;
}
// Now do the sum as a reduction
float ra = 0.0;
double t2 = omp_get_wtime();
#pragma omp target teams distribute parallel for reduction(+:ra)
for(int ii = 0; ii < N; ++ii) {
ra+=(float)ii;;
}
double t3 = omp_get_wtime() - t2;
if (ra == expect) {
printf("Success reduction sum of %d integers is: %f in \t\t\t\t\t%f secs\n",N,ra,t3);
} else {
printf("FAIL REDUCTION SUM N:%d result: %f != expect: %f \n", N,ra,expect);
main_rc=1;
}
return main_rc;
}
|
stencil-alike.c | #include "correctness-checking-partitioned-impl.h"
#include "mpi.h"
#include <stdio.h>
#include <stdlib.h>
#define STENCIL_SIZE 1024
#define TOTAL_SIZE (STENCIL_SIZE * 5)
#define ITERATIONS 10
#define TAG 42
//buffer:
// RECV SEND LOCAL SEND RECV
// TOTAL_SIZE must be at least 4 times STENCIL_SIZE
int main(int argc, char **argv) {
assert(TOTAL_SIZE >= STENCIL_SIZE*4);
MPI_Init(&argc, &argv);
const int LOCAL_SIZE = TOTAL_SIZE - 4 * STENCIL_SIZE;
int rank, size;
MPI_Comm_rank(MPI_COMM_WORLD, &rank);
MPI_Comm_size(MPI_COMM_WORLD, &size);
int pre = (rank == 0) ? -1 : rank - 1;
int nxt = (rank == size - 1) ? -1 : rank + 1;
//printf("Rank %i in comm with %d and %d\n", rank, pre,nxt);
int *buffer = (int*) malloc(sizeof(int) * TOTAL_SIZE);
// init
#pragma omp parallel for
for (int i = 0; i < TOTAL_SIZE; ++i) {
buffer[i] = i * rank;
}
for (int iter = 0; iter < ITERATIONS; ++iter) {
int max = 0;
// some computation
#pragma omp parallel for reduction (max:max)
for (int i = 1; i < TOTAL_SIZE - 1; ++i) {
buffer[i] = buffer[i - 1] + buffer[i] - buffer[i + 1];
max = buffer[i] > max ? buffer[i] : max;
}
// communication
if (rank % 2 == 0) {
if (pre != -1) {
MPI_Send(buffer, STENCIL_SIZE, MPI_INT, pre, TAG,
MPI_COMM_WORLD);
MPI_Recv(buffer + STENCIL_SIZE, STENCIL_SIZE, MPI_INT, pre, TAG,
MPI_COMM_WORLD, MPI_STATUS_IGNORE);
}
if (nxt != -1) {
MPI_Send(
buffer + STENCIL_SIZE + STENCIL_SIZE + LOCAL_SIZE
+ STENCIL_SIZE, STENCIL_SIZE, MPI_INT, nxt, TAG,
MPI_COMM_WORLD);
MPI_Recv(buffer + STENCIL_SIZE + STENCIL_SIZE + LOCAL_SIZE,
STENCIL_SIZE, MPI_INT, nxt, TAG,
MPI_COMM_WORLD, MPI_STATUS_IGNORE);
}
} else {
// recv first to avoid deadlock
if (pre != -1) {
MPI_Recv(buffer + STENCIL_SIZE, STENCIL_SIZE, MPI_INT, pre, TAG,
MPI_COMM_WORLD, MPI_STATUS_IGNORE);
MPI_Send(buffer, STENCIL_SIZE, MPI_INT, pre, TAG,
MPI_COMM_WORLD);
}
if (nxt != -1) {
MPI_Recv(buffer + STENCIL_SIZE + STENCIL_SIZE + LOCAL_SIZE,
STENCIL_SIZE, MPI_INT, nxt, TAG,
MPI_COMM_WORLD, MPI_STATUS_IGNORE);
MPI_Send(
buffer + STENCIL_SIZE + STENCIL_SIZE + LOCAL_SIZE
+ STENCIL_SIZE, STENCIL_SIZE, MPI_INT, nxt, TAG,
MPI_COMM_WORLD);
}
}
if (rank == 0) {
MPI_Reduce(MPI_IN_PLACE,&max, 1, MPI_INT, MPI_MAX, 0, MPI_COMM_WORLD);
printf("Iteration %i (max %i)\n", iter, max);
}else{
MPI_Reduce(&max, NULL, 1, MPI_INT, MPI_MAX, 0, MPI_COMM_WORLD);
}
}
free(buffer);
MPI_Finalize();
}
|
3d25pt.lbpar.c | #include <omp.h>
#include <math.h>
#define ceild(n,d) ceil(((double)(n))/((double)(d)))
#define floord(n,d) floor(((double)(n))/((double)(d)))
#define max(x,y) ((x) > (y)? (x) : (y))
#define min(x,y) ((x) < (y)? (x) : (y))
/*
* Order-2, 3D 25 point stencil
* Adapted from PLUTO and Pochoir test bench
*
* Tareq Malas
*/
#include <stdio.h>
#include <stdlib.h>
#include <sys/time.h>
#ifdef LIKWID_PERFMON
#include <likwid.h>
#endif
#include "print_utils.h"
#define TESTS 2
#define MAX(a,b) ((a) > (b) ? a : b)
#define MIN(a,b) ((a) < (b) ? a : b)
#ifndef min
#define min(x,y) ((x) < (y)? (x) : (y))
#endif
/* Subtract the `struct timeval' values X and Y,
* storing the result in RESULT.
*
* Return 1 if the difference is negative, otherwise 0.
*/
int timeval_subtract(struct timeval *result, struct timeval *x, struct timeval *y)
{
/* Perform the carry for the later subtraction by updating y. */
if (x->tv_usec < y->tv_usec)
{
int nsec = (y->tv_usec - x->tv_usec) / 1000000 + 1;
y->tv_usec -= 1000000 * nsec;
y->tv_sec += nsec;
}
if (x->tv_usec - y->tv_usec > 1000000)
{
int nsec = (x->tv_usec - y->tv_usec) / 1000000;
y->tv_usec += 1000000 * nsec;
y->tv_sec -= nsec;
}
/* Compute the time remaining to wait.
* tv_usec is certainly positive.
*/
result->tv_sec = x->tv_sec - y->tv_sec;
result->tv_usec = x->tv_usec - y->tv_usec;
/* Return 1 if result is negative. */
return x->tv_sec < y->tv_sec;
}
int main(int argc, char *argv[])
{
int t, i, j, k, test;
int Nx, Ny, Nz, Nt;
if (argc > 3) {
Nx = atoi(argv[1])+8;
Ny = atoi(argv[2])+8;
Nz = atoi(argv[3])+8;
}
if (argc > 4)
Nt = atoi(argv[4]);
double ****A = (double ****) malloc(sizeof(double***)*2);
double ***roc2 = (double ***) malloc(sizeof(double**));
A[0] = (double ***) malloc(sizeof(double**)*Nz);
A[1] = (double ***) malloc(sizeof(double**)*Nz);
roc2 = (double ***) malloc(sizeof(double**)*Nz);
for(i=0; i<Nz; i++){
A[0][i] = (double**) malloc(sizeof(double*)*Ny);
A[1][i] = (double**) malloc(sizeof(double*)*Ny);
roc2[i] = (double**) malloc(sizeof(double*)*Ny);
for(j=0;j<Ny;j++){
A[0][i][j] = (double*) malloc(sizeof(double)*Nx);
A[1][i][j] = (double*) malloc(sizeof(double)*Nx);
roc2[i][j] = (double*) malloc(sizeof(double)*Nx);
}
}
// tile size information, including extra element to decide the list length
int *tile_size = (int*) malloc(sizeof(int));
tile_size[0] = -1;
// The list is modified here before source-to-source transformations
tile_size = (int*) realloc((void *)tile_size, sizeof(int)*5);
tile_size[0] = 24;
tile_size[1] = 24;
tile_size[2] = 16;
tile_size[3] = 256;
tile_size[4] = -1;
// for timekeeping
int ts_return = -1;
struct timeval start, end, result;
double tdiff = 0.0, min_tdiff=1.e100;
const int BASE = 1024;
// initialize variables
//
srand(42);
for (i = 1; i < Nz; i++) {
for (j = 1; j < Ny; j++) {
for (k = 1; k < Nx; k++) {
A[0][i][j][k] = 1.0 * (rand() % BASE);
roc2[i][j][k] = 2.0 * (rand() % BASE);
}
}
}
#ifdef LIKWID_PERFMON
LIKWID_MARKER_INIT;
#pragma omp parallel
{
LIKWID_MARKER_THREADINIT;
#pragma omp barrier
LIKWID_MARKER_START("calc");
}
#endif
int num_threads = 1;
#if defined(_OPENMP)
num_threads = omp_get_max_threads();
#endif
const double coef0 = -0.28472;
const double coef1 = 0.16000;
const double coef2 = -0.02000;
const double coef3 = 0.00254;
const double coef4 = -0.00018;
for(test=0; test<TESTS; test++){
gettimeofday(&start, 0);
// serial execution - Addition: 6 && Multiplication: 2
/* Copyright (C) 1991-2014 Free Software Foundation, Inc.
This file is part of the GNU C Library.
The GNU C Library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
The GNU C Library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with the GNU C Library; if not, see
<http://www.gnu.org/licenses/>. */
/* This header is separate from features.h so that the compiler can
include it implicitly at the start of every compilation. It must
not itself include <features.h> or any other header that includes
<features.h> because the implicit include comes before any feature
test macros that may be defined in a source file before it first
explicitly includes a system header. GCC knows the name of this
header in order to preinclude it. */
/* glibc's intent is to support the IEC 559 math functionality, real
and complex. If the GCC (4.9 and later) predefined macros
specifying compiler intent are available, use them to determine
whether the overall intent is to support these features; otherwise,
presume an older compiler has intent to support these features and
define these macros by default. */
/* wchar_t uses ISO/IEC 10646 (2nd ed., published 2011-03-15) /
Unicode 6.0. */
/* We do not support C11 <threads.h>. */
int t1, t2, t3, t4, t5, t6, t7, t8;
int lb, ub, lbp, ubp, lb2, ub2;
register int lbv, ubv;
/* Start of CLooG code */
if ((Nt >= 1) && (Nx >= 9) && (Ny >= 9) && (Nz >= 9)) {
for (t1=-1;t1<=floord(Nt-1,3);t1++) {
lbp=max(ceild(t1,2),ceild(6*t1-Nt+2,6));
ubp=min(floord(4*Nt+Nz-9,24),floord(12*t1+Nz+6,24));
#pragma omp parallel for private(lbv,ubv,t3,t4,t5,t6,t7,t8)
for (t2=lbp;t2<=ubp;t2++) {
for (t3=max(max(max(0,ceild(3*t1-3*t2,2)),ceild(3*t1-2,4)),ceild(24*t2-Nz-3,16));t3<=min(min(min(floord(4*Nt+Ny-9,16),floord(12*t1+Ny+15,16)),floord(24*t2+Ny+11,16)),floord(24*t1-24*t2+Nz+Ny+13,16));t3++) {
for (t4=max(max(max(max(0,ceild(3*t1-3*t2-30,32)),ceild(3*t1-62,64)),ceild(24*t2-Nz-243,256)),ceild(16*t3-Ny-243,256));t4<=min(min(min(min(floord(4*Nt+Nx-9,256),floord(12*t1+Nx+15,256)),floord(24*t2+Nx+11,256)),floord(16*t3+Nx+3,256)),floord(24*t1-24*t2+Nz+Nx+13,256));t4++) {
for (t5=max(max(max(max(max(0,ceild(24*t2-Nz+5,4)),ceild(16*t3-Ny+5,4)),ceild(256*t4-Nx+5,4)),3*t1),6*t1-6*t2+1);t5<=min(min(min(min(min(floord(24*t1-24*t2+Nz+18,4),Nt-1),3*t1+5),6*t2+4),4*t3+2),64*t4+62);t5++) {
for (t6=max(max(24*t2,4*t5+4),-24*t1+24*t2+8*t5-23);t6<=min(min(24*t2+23,-24*t1+24*t2+8*t5),4*t5+Nz-5);t6++) {
for (t7=max(16*t3,4*t5+4);t7<=min(16*t3+15,4*t5+Ny-5);t7++) {
lbv=max(256*t4,4*t5+4);
ubv=min(256*t4+255,4*t5+Nx-5);
#pragma ivdep
#pragma vector always
for (t8=lbv;t8<=ubv;t8++) {
A[( t5 + 1) % 2][ (-4*t5+t6)][ (-4*t5+t7)][ (-4*t5+t8)] = (((2.0 * A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7)][ (-4*t5+t8)]) - A[( t5 + 1) % 2][ (-4*t5+t6)][ (-4*t5+t7)][ (-4*t5+t8)]) + (roc2[ (-4*t5+t6)][ (-4*t5+t7)][ (-4*t5+t8)] * (((((coef0 * A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7)][ (-4*t5+t8)]) + (coef1 * (((((A[ t5 % 2][ (-4*t5+t6) - 1][ (-4*t5+t7)][ (-4*t5+t8)] + A[ t5 % 2][ (-4*t5+t6) + 1][ (-4*t5+t7)][ (-4*t5+t8)]) + A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7) - 1][ (-4*t5+t8)]) + A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7) + 1][ (-4*t5+t8)]) + A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7)][ (-4*t5+t8) - 1]) + A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7)][ (-4*t5+t8) + 1]))) + (coef2 * (((((A[ t5 % 2][ (-4*t5+t6) - 2][ (-4*t5+t7)][ (-4*t5+t8)] + A[ t5 % 2][ (-4*t5+t6) + 2][ (-4*t5+t7)][ (-4*t5+t8)]) + A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7) - 2][ (-4*t5+t8)]) + A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7) + 2][ (-4*t5+t8)]) + A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7)][ (-4*t5+t8) - 2]) + A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7)][ (-4*t5+t8) + 2]))) + (coef3 * (((((A[ t5 % 2][ (-4*t5+t6) - 3][ (-4*t5+t7)][ (-4*t5+t8)] + A[ t5 % 2][ (-4*t5+t6) + 3][ (-4*t5+t7)][ (-4*t5+t8)]) + A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7) - 3][ (-4*t5+t8)]) + A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7) + 3][ (-4*t5+t8)]) + A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7)][ (-4*t5+t8) - 3]) + A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7)][ (-4*t5+t8) + 3]))) + (coef4 * (((((A[ t5 % 2][ (-4*t5+t6) - 4][ (-4*t5+t7)][ (-4*t5+t8)] + A[ t5 % 2][ (-4*t5+t6) + 4][ (-4*t5+t7)][ (-4*t5+t8)]) + A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7) - 4][ (-4*t5+t8)]) + A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7) + 4][ (-4*t5+t8)]) + A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7)][ (-4*t5+t8) - 4]) + A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7)][ (-4*t5+t8) + 4])))));;
}
}
}
}
}
}
}
}
}
/* End of CLooG code */
gettimeofday(&end, 0);
ts_return = timeval_subtract(&result, &end, &start);
tdiff = (double) (result.tv_sec + result.tv_usec * 1.0e-6);
min_tdiff = MIN(min_tdiff, tdiff);
printf("Rank 0 TEST# %d time: %f\n", test, tdiff);
}
PRINT_RESULTS(4, "constant")
#ifdef LIKWID_PERFMON
#pragma omp parallel
{
LIKWID_MARKER_STOP("calc");
}
LIKWID_MARKER_CLOSE;
#endif
// Free allocated arrays
for(i=0; i<Nz; i++){
for(j=0;j<Ny;j++){
free(A[0][i][j]);
free(A[1][i][j]);
free(roc2[i][j]);
}
free(A[0][i]);
free(A[1][i]);
free(roc2[i]);
}
free(A[0]);
free(A[1]);
free(roc2);
return 0;
}
|
1d_array_ptr.c | #include <stdlib.h>
#include <omp.h>
int main()
{
int* arr = malloc(sizeof(int) * 4);
#pragma omp parallel
{
arr[0] = 0;
arr[1] = 1;
arr[2] = 2;
arr[3] = 3;
printf("[%d, %d, %d, %d]\n", arr[0], arr[1], arr[2], arr[3]);
}
free(arr);
}
|
SOCRSStorage.h | //
// Created by iskakoff on 28/07/16.
//
#ifndef EDLIB_SOCRSSTORAGE_H
#define EDLIB_SOCRSSTORAGE_H
#include <vector>
#include <iomanip>
#ifdef _OPENMP
#include <omp.h>
#endif
#include "Storage.h"
namespace EDLib {
namespace Storage {
template<class ModelType>
class SOCRSStorage : public Storage < typename ModelType::precision > {
typedef typename ModelType::precision prec;
public:
typedef ModelType Model;
using Storage < prec >::n;
using Storage < prec >::ntot;
#ifdef USE_MPI
SOCRSStorage(alps::params &p, Model &m, alps::mpi::communicator &comm) : Storage < prec >(p, comm),
#else
SOCRSStorage(alps::params &p, Model &m) : Storage < prec >(p),
#endif
_max_size(p["storage.MAX_SIZE"]),
#ifdef _OPENMP
_nthreads(omp_get_max_threads()),
#else
_nthreads(1),
#endif
_row_offset(_nthreads + 1), _vind_offset(_nthreads + 1),
_vind(_nthreads), _vind_byte(_nthreads), _vind_bit(_nthreads), _vind_start(_nthreads),
_max_dim(p["storage.MAX_DIM"]), _model(m) {
/** init what you need from parameters*/
col_ind.assign(_max_size, 0);
// XXX I don't trust myself about this one:
signs.assign(std::ceil(_max_size / sizeof(char)), 1);
dvalues.assign(_max_dim, prec(0.0));
};
virtual void av(prec *v, prec *w, int n, bool clear = true) {
_model.symmetry().init();
#ifdef _OPENMP
#pragma omp parallel
{
int myid = omp_get_thread_num();
#else
int myid = 0;
#endif
size_t _vind = _vind_offset[myid];
size_t _vind_byte = _vind / sizeof(char);
size_t _vind_bit = _vind % sizeof(char);
// Iteration over rows.
for(int i = _row_offset[myid]; (i < _row_offset[myid + 1]) && (i < n); ++i){
long long nst = _model.symmetry().state_by_index(i);
// Diagonal contribution.
w[i] = dvalues[i] * v[i] + (clear ? 0.0 : w[i]);
// Offdiagonal contribution.
// Iteration over columns(unordered).
for (int kkk = 0; kkk < _model.T_states().size(); ++kkk) {
int test = _model.valid(_model.T_states()[kkk], nst);
// If transition between states corresponding to row and column is possible, calculate the offdiagonal element.
w[i] += test * _model.T_states()[kkk].value() * (1 - 2 * ((signs[_vind_byte] >> _vind_bit) & 1)) * v[col_ind[_vind]];
_vind_bit += test;
_vind_byte += _vind_bit / sizeof(char);
_vind_bit %= sizeof(char);
_vind += test;
}
for (int kkk = 0; kkk < _model.V_states().size(); ++kkk) {
int test = _model.valid(_model.V_states()[kkk], nst);
// If transition between states corresponding to row and column is possible, calculate the offdiagonal element.
w[i] += test * _model.V_states()[kkk].value() * (1 - 2 * ((signs[_vind_byte] >> _vind_bit) & 1)) * v[col_ind[_vind]];
_vind_bit += test;
_vind_byte += _vind_bit / sizeof(char);
_vind_bit %= sizeof(char);
_vind += test;
}
}
#ifdef _OPENMP
}
#endif
}
void init() {
_model.symmetry().init();
}
void reset() {
_model.symmetry().init();
size_t sector_size = _model.symmetry().sector().size();
if (sector_size > _max_dim) {
std::stringstream s;
s << "New sector request more memory than allocated. Increase MAX_DIM parameter. Requested " << sector_size << ", allocated " << _max_dim << ".";
throw std::runtime_error(s.str().c_str());
}
if (sector_size * (_model.T_states().size() + _model.V_states().size()) > _max_size) {
std::stringstream s;
s << "New sector request more memory than allocated. Increase MAX_SIZE parameter. Requested " << sector_size * (_model.T_states().size() + _model.V_states().size()) << ", allocated " << _max_size << ".";
throw std::runtime_error(s.str().c_str());
}
for(int myid = 0; myid < _nthreads; ++myid){
_vind[myid] = 0;
_vind_byte[myid] = 0;
_vind_bit[myid] = 0;
}
ntot() = sector_size;
n() = ntot();
}
void fill() {
reset();
int i = 0;
long long k = 0;
int isign = 0;
// Size chunks equally.
int step = (int)std::floor(_model.symmetry().sector().size() / _nthreads);
for (int i = 0; i <= _nthreads; i++){
_row_offset[i] = step * i;
}
// Put the rest into some of the first threads.
int more = _model.symmetry().sector().size() - _row_offset[_nthreads];
for (int i = 0; i < more; i++){
_row_offset[i] += i;
}
for (int i = more; i <= _nthreads; i++){
_row_offset[i] += more;
}
for(int myid = 0; myid <= _nthreads; ++myid){
_vind_offset[myid] = (_model.T_states().size() + _model.V_states().size()) * _row_offset[myid];
}
#ifdef _OPENMP
#pragma omp parallel
{
int myid = omp_get_thread_num();
#else
int myid = 0;
#endif
// Variant: serial, but more compact.
// for (int myid = 0; myid < _nthreads; ++myid){
_vind[myid] = _vind_offset[myid];
_vind_byte[myid] = _vind[myid] / sizeof(char);
_vind_bit[myid] = _vind[myid] % sizeof(char);
for (int i = _row_offset[myid]; i < _row_offset[myid + 1]; ++i) {
long long nst = _model.symmetry().state_by_index(i);
// Compute diagonal element for current i state
addDiagonal(i, _model.diagonal(nst), myid);
// non-diagonal terms calculation
off_diagonal < decltype(_model.T_states()) >(nst, i, _model.T_states(), myid);
off_diagonal < decltype(_model.V_states()) >(nst, i, _model.V_states(), myid);
}
// _vind_offset[myid + 1] = _vind[myid];
#ifdef _OPENMP
}
#endif
// }
}
void print() {
// See: av().
// Each row of the matrix is first restored from the arrays.
std::vector < prec > line(n(), prec(0.0));
_model.symmetry().init();
std::cout << std::setprecision(2) << std::fixed;
std::cout << "[";
for (int myid = 0; myid < _nthreads; ++myid) {
size_t _vind = _vind_offset[myid];
size_t _vind_byte = _vind / sizeof(char);
size_t _vind_bit = _vind % sizeof(char);
for (int i = _row_offset[myid]; i < _row_offset[myid + 1]; ++i) {
_model.symmetry().next_state();
long long nst = _model.symmetry().state();
std::fill(line.begin(), line.end(), prec(0.0));
line[i] = dvalues[i];
for (int kkk = 0; kkk < _model.T_states().size(); ++kkk) {
int test = _model.valid(_model.T_states()[kkk], nst);
line[col_ind[_vind]] += test * _model.T_states()[kkk].value() * (1 - 2 * ((signs[_vind_byte] >> _vind_bit) & 1));
_vind_bit += test;
_vind_byte += _vind_bit / sizeof(char);
_vind_bit %= sizeof(char);
_vind += test;
}
for (int kkk = 0; kkk < _model.V_states().size(); ++kkk) {
int test = _model.valid(_model.V_states()[kkk], nst);
line[col_ind[_vind]] += test * _model.V_states()[kkk].value() * (1 - 2 * ((signs[_vind_byte] >> _vind_bit) & 1));
_vind_bit += test;
_vind_byte += _vind_bit / sizeof(char);
_vind_bit %= sizeof(char);
_vind += test;
}
std::cout << "[";
for (int j = 0; j < n(); ++j) {
std::cout << std::setw(6) << line[j] << (j == n() - 1 ? "" : ", ");
}
std::cout << "]" << (i == n() - 1 ? "" : ", \n");
}
std::cout << "]" << std::endl;
}
}
virtual void zero_eigenapair() {
Storage < prec >::eigenvalues().resize(1);
Storage < prec >::eigenvalues()[0] = dvalues[0];
Storage < prec >::eigenvectors().assign(1, std::vector < prec >(1, prec(1.0)));
}
size_t vector_size(typename Model::Sector sector) {
return sector.size();
}
#ifdef USE_MPI
prec vv(const std::vector<prec> & v, const std::vector<prec> & w, MPI_Comm com) {
return vv(v, w);
}
#endif
prec vv(const std::vector<prec> & v, const std::vector<prec> & w) {
prec alf = prec(0.0);
for (int k = 0; k < v.size(); ++k) {
alf += w[k] * v[k];
}
return alf;
}
void a_adag(int iii, const std::vector < prec > &invec, std::vector < prec > &outvec, const typename Model::Sector& next_sec, bool a) {
long long k;
int sign;
int i = 0;
while (_model.symmetry().next_state()) {
long long nst = _model.symmetry().state();
if (_model.checkState(nst, iii, _model.max_total_electrons()) == (a ? 1 : 0)) {
if(a) _model.a(iii, nst, k, sign);
else _model.adag(iii, nst, k, sign);
int i1 = _model.symmetry().index(k, next_sec);
outvec[i1] = sign * invec[i];
}
++i;
};
}
#ifdef _OPENMP
int &nprocs() { return _nthreads; }
#endif
void constant_shift(prec shift) {
std::transform( dvalues.begin(), dvalues.end(), dvalues.begin(), std::bind2nd(std::plus<prec>(), shift));
}
private:
// Internal storage structure
std::vector < prec > dvalues;
std::vector < int > col_ind;
std::vector < char > signs;
// the maximum sizes of all the objects
size_t _max_size;
size_t _max_dim;
// number of OMP threads, "1" for serial mode.
int _nthreads;
// OMP chunks offset
std::vector < size_t > _row_offset;
std::vector < size_t > _vind_offset;
// internal indicies, only used for filling
std::vector < size_t > _vind;
// start of current row, used for checks
std::vector < size_t > _vind_start;
// bit and byte of the bitmap corresponding to CRS index
std::vector < size_t > _vind_bit;
std::vector < size_t > _vind_byte;
// Hubbard model parameters
Model &_model;
template<typename T_states>
inline void off_diagonal(long long nst, int i, T_states& states, int chunk) {
long long k = 0;
int isign = 0;
for (int kkk = 0; kkk < states.size(); ++kkk) {
if (_model.valid(states[kkk], nst)) {
_model.set(states[kkk], nst, k, isign);
int k_index = _model.symmetry().index(k);
addElement(i, k_index, states[kkk].value(), isign, chunk);
}
}
};
/**
* Add diagonal H(i,i) element with value v.
*/
void inline addDiagonal(int i, prec v, int chunk) {
dvalues[i] = v;
_vind_start[chunk] = _vind[chunk];
}
/**
* Add off-diagonal H(i,j) element with value t (discarded here, restored in av) and Fermi sign.
*/
void inline addElement(const int &i, int j, prec t, int sign, int chunk) {
if (i == j) {
throw std::logic_error("Attempt to use addElement() to add diagonal element. Use addDiagonal() instead!");
}
// It is an error to add the element (i, j) twice.
for (size_t iii = _vind_start[chunk]; iii < _vind[chunk]; iii++) {
if (col_ind[iii] == j) {
throw std::logic_error("Collision. Check a, adag, numState, ninv_value!");
}
}
if (_vind[chunk] >= _vind_offset[chunk+1]) {
std::stringstream s;
s << "Current sector request more memory than allocated. Increase MAX_SIZE parameter.";
throw std::runtime_error(s.str().c_str());
}
// Store sign in CRS-like array, one bit per sign.
col_ind[_vind[chunk]] = j;
signs[_vind_byte[chunk]] &= ~(1ll << _vind_bit[chunk]);
signs[_vind_byte[chunk]] |= sign < 0 ? 1ll << _vind_bit[chunk] : 0;
++_vind_bit[chunk];
++_vind[chunk];
_vind_byte[chunk] += _vind_bit[chunk] / sizeof(char);
_vind_bit[chunk] %= sizeof(char);
}
};
}
}
#endif //EDLIB_SOCRSSTORAGE_H
|
ecn2_opt.c | /*
* MIRACL E(F_p^2) support functions
* mrecn2.c
*
*/
#include <stdlib.h>
#include "miracl.h"
#ifdef MR_STATIC
#include <string.h>
#endif
static inline void zzn2_div2_i(zzn2 *w)
{
moddiv2(w->a->w);
w->a->len=2;
moddiv2(w->b->w);
w->b->len=2;
}
static inline void zzn2_tim2_i(zzn2 *w)
{
#ifdef MR_COUNT_OPS
fpa+=2;
#endif
modtim2(w->a->w);
modtim2(w->b->w);
w->a->len=2;
w->b->len=2;
}
static inline void zzn2_tim3_i(zzn2 *w)
{
#ifdef MR_COUNT_OPS
fpa+=4;
#endif
modtim3(w->a->w);
modtim3(w->b->w);
w->a->len=2;
w->b->len=2;
}
static inline void zzn2_copy_i(zzn2 *x,zzn2 *w)
{
if (x==w) return;
w->a->len=x->a->len;
w->a->w[0]=x->a->w[0];
w->a->w[1]=x->a->w[1];
w->b->len=x->b->len;
w->b->w[0]=x->b->w[0];
w->b->w[1]=x->b->w[1];
}
static inline void zzn2_add_i(zzn2 *x,zzn2 *y,zzn2 *w)
{
#ifdef MR_COUNT_OPS
fpa+=2;
#endif
modadd(x->a->w,y->a->w,w->a->w);
modadd(x->b->w,y->b->w,w->b->w);
w->a->len=2;
w->b->len=2;
}
static inline void zzn2_sub_i(zzn2 *x,zzn2 *y,zzn2 *w)
{
#ifdef MR_COUNT_OPS
fpa+=2;
#endif
modsub(x->a->w,y->a->w,w->a->w);
modsub(x->b->w,y->b->w,w->b->w);
w->a->len=2;
w->b->len=2;
}
static inline void zzn2_timesi_i(zzn2 *u)
{
mr_small w1[2];
w1[0]=u->a->w[0];
w1[1]=u->a->w[1];
u->a->w[0]=u->b->w[0];
u->a->w[1]=u->b->w[1];
modneg(u->a->w);
u->b->w[0]=w1[0];
u->b->w[1]=w1[1];
}
static inline void zzn2_txx_i(zzn2 *u)
{
/* multiply w by t^2 where x^2-t is irreducible polynomial for ZZn4
for p=5 mod 8 t=sqrt(sqrt(-2)), qnr=-2
for p=3 mod 8 t=sqrt(1+sqrt(-1)), qnr=-1
for p=7 mod 8 and p=2,3 mod 5 t=sqrt(2+sqrt(-1)), qnr=-1 */
zzn2 t;
struct bigtype aa,bb;
big a,b;
mr_small w3[2],w4[2];
a=&aa;
b=&bb;
a->len=2;
b->len=2;
a->w=w3;
b->w=w4;
t.a=a;
t.b=b;
zzn2_copy_i(u,&t);
zzn2_timesi_i(u);
zzn2_add_i(u,&t,u);
zzn2_add_i(u,&t,u);
u->a->len=2;
u->b->len=2;
}
static inline void zzn2_pmul_i(int i,zzn2 *x)
{
modpmul(i,x->a->w);
modpmul(i,x->b->w);
}
static inline void zzn2_sqr_i(zzn2 *x,zzn2 *w)
{
static mr_small w1[2],w2[2];
#ifdef MR_COUNT_OPS
fpa+=3;
fpc+=2;
#endif
modadd(x->a->w,x->b->w,w1);
modsub(x->a->w,x->b->w,w2);
modmult(x->a->w,x->b->w,w->b->w);
modmult(w1,w2,w->a->w); // routine that calculates (a+b)(a-b) ??
modtim2(w->b->w);
w->a->len=2;
w->b->len=2;
}
static inline void zzn2_dblsub_i(zzn2 *x,zzn2 *y,zzn2 *w)
{
#ifdef MR_COUNT_OPS
fpa+=4;
#endif
moddblsub(w->a->w,x->a->w,y->a->w);
moddblsub(w->b->w,x->b->w,y->b->w);
w->a->len=2;
w->b->len=2;
}
static inline void zzn2_mul_i(zzn2 *x,zzn2 *y,zzn2 *w)
{
static mr_small w1[2],w2[2],w5[2];
#ifdef MR_COUNT_OPS
fpa+=5;
fpc+=3;
#endif
/*#pragma omp parallel sections
{
#pragma omp section */
modmult(x->a->w,y->a->w,w1);
/* #pragma omp section */
modmult(x->b->w,y->b->w,w2);
/*}*/
modadd(x->a->w,x->b->w,w5);
modadd(y->a->w,y->b->w,w->b->w);
modmult(w->b->w,w5,w->b->w);
moddblsub(w->b->w,w1,w2); /* w->b->w - w1 -w2 */
modsub(w1,w2,w->a->w);
w->a->len=2;
w->b->len=2;
}
void zzn2_inv_i(_MIPD_ zzn2 *w)
{
#ifdef MR_OS_THREADS
miracl *mr_mip=get_mip();
#endif
if (mr_mip->ERNUM) return;
#ifdef MR_COUNT_OPS
fpc+=4;
fpa+=1;
#endif
MR_IN(163)
modsqr(w->a->w,mr_mip->w1->w);
modsqr(w->b->w,mr_mip->w2->w);
modadd(mr_mip->w1->w,mr_mip->w2->w,mr_mip->w1->w);
mr_mip->w1->len=2;
/* redc(_MIPP_ mr_mip->w1,mr_mip->w6); */
copy(mr_mip->w1,mr_mip->w6);
xgcd(_MIPP_ mr_mip->w6,mr_mip->modulus,mr_mip->w6,mr_mip->w6,mr_mip->w6);
/* nres(_MIPP_ mr_mip->w6,mr_mip->w6); */
modmult(w->a->w,mr_mip->w6->w,w->a->w);
modneg(mr_mip->w6->w);
modmult(w->b->w,mr_mip->w6->w,w->b->w);
MR_OUT
}
BOOL nres_sqroot(_MIPD_ big x,big w)
{ /* w=sqrt(x) mod p. This depends on p being prime! */
int i,t,js;
#ifdef MR_COUNT_OPS
fpc+=125;
#endif
#ifdef MR_OS_THREADS
miracl *mr_mip=get_mip();
#endif
if (mr_mip->ERNUM) return FALSE;
copy(x,w);
if (size(w)==0) return TRUE;
copy(w,mr_mip->w1);
for (i=0;i<25;i++)
{
modsqr(w->w,w->w);
modsqr(w->w,w->w);
modsqr(w->w,w->w);
modsqr(w->w,w->w);
modsqr(w->w,w->w);
}
w->len=2;
modsqr(w->w,mr_mip->w2->w);
mr_mip->w2->len=2;
if (compare(mr_mip->w1,mr_mip->w2)!=0) {zero(w);return FALSE;}
return TRUE;
}
BOOL zzn2_sqrt(_MIPD_ zzn2 *u,zzn2 *w)
{ /* sqrt(a+ib) = sqrt(a+sqrt(a*a-n*b*b)/2)+ib/(2*sqrt(a+sqrt(a*a-n*b*b)/2))
where i*i=n */
#ifdef MR_OS_THREADS
miracl *mr_mip=get_mip();
#endif
#ifdef MR_COUNT_OPS
fpc+=2;
fpa+=1;
#endif
if (mr_mip->ERNUM) return FALSE;
zzn2_copy(u,w);
if (zzn2_iszero(w)) return TRUE;
MR_IN(204)
modsqr(w->b->w,mr_mip->w7->w);
modsqr(w->a->w,mr_mip->w1->w);
modadd(mr_mip->w1->w,mr_mip->w7->w,mr_mip->w7->w);
mr_mip->w7->len=2;
// nres_modmult(_MIPP_ w->b,w->b,mr_mip->w7);
// nres_modmult(_MIPP_ w->a,w->a,mr_mip->w1);
// nres_modadd(_MIPP_ mr_mip->w7,mr_mip->w1,mr_mip->w7);
if (!nres_sqroot(_MIPP_ mr_mip->w7,mr_mip->w7)) /* s=w7 */
{
zzn2_zero(w);
MR_OUT
return FALSE;
}
#ifdef MR_COUNT_OPS
fpa+=1;
#endif
modadd(w->a->w,mr_mip->w7->w,mr_mip->w15->w);
moddiv2(mr_mip->w15->w);
mr_mip->w15->len=2;
// nres_modadd(_MIPP_ w->a,mr_mip->w7,mr_mip->w15);
// nres_div2(_MIPP_ mr_mip->w15,mr_mip->w15);
if (!nres_sqroot(_MIPP_ mr_mip->w15,mr_mip->w15))
{
#ifdef MR_COUNT_OPS
fpa+=1;
#endif
modsub(w->a->w,mr_mip->w7->w,mr_mip->w15->w);
moddiv2(mr_mip->w15->w);
mr_mip->w15->len=2;
// nres_modsub(_MIPP_ w->a,mr_mip->w7,mr_mip->w15);
// nres_div2(_MIPP_ mr_mip->w15,mr_mip->w15);
if (!nres_sqroot(_MIPP_ mr_mip->w15,mr_mip->w15))
{
zzn2_zero(w);
MR_OUT
return FALSE;
}
// else printf("BBBBBBBBBBBBBBBBBB\n");
}
// else printf("AAAAAAAAAAAAAAAAAAA\n");
#ifdef MR_COUNT_OPS
fpa+=1;
#endif
copy(mr_mip->w15,w->a);
modadd(mr_mip->w15->w,mr_mip->w15->w,mr_mip->w15->w);
nres_moddiv(_MIPP_ w->b,mr_mip->w15,w->b);
MR_OUT
return TRUE;
}
/*
BOOL zzn2_multi_inverse(_MIPD_ int m,zzn2 *x,zzn2 *w)
{
int i;
zzn2 t1,t2;
#ifdef MR_OS_THREADS
miracl *mr_mip=get_mip();
#endif
if (m==0) return TRUE;
if (m<0) return FALSE;
MR_IN(214)
if (x==w)
{
mr_berror(_MIPP_ MR_ERR_BAD_PARAMETERS);
MR_OUT
return FALSE;
}
if (m==1)
{
zzn2_copy_i(&x[0],&w[0]);
zzn2_inv_i(_MIPP_ &w[0]);
MR_OUT
return TRUE;
}
zzn2_from_int(_MIPP_ 1,&w[0]);
zzn2_copy_i(&x[0],&w[1]);
for (i=2;i<m;i++)
{
if (zzn2_isunity(_MIPP_ &x[i-1]))
zzn2_copy_i(&w[i-1],&w[i]);
else
zzn2_mul_i(&w[i-1],&x[i-1],&w[i]);
}
t1.a=mr_mip->w8;
t1.b=mr_mip->w9;
t2.a=mr_mip->w10;
t2.b=mr_mip->w11;
zzn2_mul_i(&w[m-1],&x[m-1],&t1);
if (zzn2_iszero(&t1))
{
mr_berror(_MIPP_ MR_ERR_DIV_BY_ZERO);
MR_OUT
return FALSE;
}
zzn2_inv_i(_MIPP_ &t1);
zzn2_copy_i(&x[m-1],&t2);
zzn2_mul_i(&w[m-1],&t1,&w[m-1]);
for (i=m-2;;i--)
{
if (i==0)
{
zzn2_mul_i(&t2,&t1,&w[0]);
break;
}
zzn2_mul_i(&w[i],&t2,&w[i]);
zzn2_mul_i(&w[i],&t1,&w[i]);
if (!zzn2_isunity(_MIPP_ &x[i])) zzn2_mul_i(&t2,&x[i],&t2);
}
MR_OUT
return TRUE;
}
*/
BOOL ecn2_iszero(ecn2 *a)
{
if (a->marker==MR_EPOINT_INFINITY) return TRUE;
return FALSE;
}
void ecn2_copy(ecn2 *a,ecn2 *b)
{
zzn2_copy_i(&(a->x),&(b->x));
zzn2_copy_i(&(a->y),&(b->y));
#ifndef MR_AFFINE_ONLY
if (a->marker==MR_EPOINT_GENERAL) zzn2_copy_i(&(a->z),&(b->z));
#endif
b->marker=a->marker;
}
void ecn2_zero(ecn2 *a)
{
zzn2_zero(&(a->x)); zzn2_zero(&(a->y));
#ifndef MR_AFFINE_ONLY
if (a->marker==MR_EPOINT_GENERAL) zzn2_zero(&(a->z));
#endif
a->marker=MR_EPOINT_INFINITY;
}
BOOL ecn2_compare(_MIPD_ ecn2 *a,ecn2 *b)
{
#ifdef MR_OS_THREADS
miracl *mr_mip=get_mip();
#endif
if (mr_mip->ERNUM) return FALSE;
MR_IN(193)
ecn2_norm(_MIPP_ a);
ecn2_norm(_MIPP_ b);
MR_OUT
if (zzn2_compare(&(a->x),&(b->x)) && zzn2_compare(&(a->y),&(b->y)) && a->marker==b->marker) return TRUE;
return FALSE;
}
void ecn2_norm(_MIPD_ ecn2 *a)
{
zzn2 t;
#ifdef MR_OS_THREADS
miracl *mr_mip=get_mip();
#endif
#ifndef MR_AFFINE_ONLY
if (mr_mip->ERNUM) return;
if (a->marker!=MR_EPOINT_GENERAL) return;
MR_IN(194)
zzn2_inv_i(_MIPP_ &(a->z));
t.a=mr_mip->w3;
t.b=mr_mip->w4;
zzn2_copy_i(&(a->z),&t);
zzn2_sqr_i( &(a->z),&(a->z));
zzn2_mul_i( &(a->x),&(a->z),&(a->x));
zzn2_mul_i( &(a->z),&t,&(a->z));
zzn2_mul_i( &(a->y),&(a->z),&(a->y));
zzn2_from_int(_MIPP_ 1,&(a->z));
a->marker=MR_EPOINT_NORMALIZED;
MR_OUT
#endif
}
void ecn2_get(_MIPD_ ecn2 *e,zzn2 *x,zzn2 *y,zzn2 *z)
{
zzn2_copy_i(&(e->x),x);
zzn2_copy_i(&(e->y),y);
#ifndef MR_AFFINE_ONLY
if (e->marker==MR_EPOINT_GENERAL) zzn2_copy_i(&(e->z),z);
else zzn2_from_zzn(mr_mip->one,z);
#endif
}
void ecn2_getxy(ecn2 *e,zzn2 *x,zzn2 *y)
{
zzn2_copy_i(&(e->x),x);
zzn2_copy_i(&(e->y),y);
}
void ecn2_getx(ecn2 *e,zzn2 *x)
{
zzn2_copy_i(&(e->x),x);
}
inline void zzn2_conj_i(zzn2 *x,zzn2 *w)
{
zzn2_copy_i(x,w);
modneg(w->b->w);
}
void ecn2_psi(_MIPD_ zzn2 *psi,ecn2 *P)
{
ecn2_norm(_MIPP_ P);
zzn2_conj_i(&(P->x),&(P->x));
zzn2_conj_i(&(P->y),&(P->y));
zzn2_mul_i(&(P->x),&psi[0],&(P->x));
zzn2_mul_i(&(P->y),&psi[1],&(P->y));
}
#ifndef MR_AFFINE_ONLY
void ecn2_getz(_MIPD_ ecn2 *e,zzn2 *z)
{
if (e->marker==MR_EPOINT_GENERAL) zzn2_copy_i(&(e->z),z);
else zzn2_from_zzn(mr_mip->one,z);
}
#endif
void ecn2_rhs(_MIPD_ zzn2 *x,zzn2 *rhs)
{ /* calculate RHS of elliptic curve equation */
BOOL twist;
zzn2 A,B;
#ifdef MR_OS_THREADS
miracl *mr_mip=get_mip();
#endif
if (mr_mip->ERNUM) return;
twist=mr_mip->TWIST;
MR_IN(202)
A.a=mr_mip->w10;
A.b=mr_mip->w11;
B.a=mr_mip->w12;
B.b=mr_mip->w13;
if (mr_abs(mr_mip->Asize)<MR_TOOBIG) zzn2_from_int(_MIPP_ mr_mip->Asize,&A);
else zzn2_from_zzn(mr_mip->A,&A);
if (mr_abs(mr_mip->Bsize)<MR_TOOBIG) zzn2_from_int(_MIPP_ mr_mip->Bsize,&B);
else zzn2_from_zzn(mr_mip->B,&B);
if (twist)
{
if (mr_mip->Asize==0 || mr_mip->Bsize==0)
{
if (mr_mip->Asize==0)
{
zzn2_txd(_MIPP_ &B);
}
if (mr_mip->Bsize==0)
{
zzn2_mul_i( &A,x,&B);
zzn2_txd(_MIPP_ &B);
}
zzn2_negate(_MIPP_ &B,&B);
}
else
{
zzn2_txx_i(&B);
zzn2_txx_i(&B);
zzn2_txx_i(&B);
zzn2_mul_i( &A,x,&A);
zzn2_txx_i(&A);
zzn2_txx_i(&A);
zzn2_add_i(&B,&A,&B);
}
}
else
{
zzn2_mul_i( &A,x,&A);
zzn2_add_i(&B,&A,&B);
}
zzn2_sqr_i( x,&A);
zzn2_mul_i( &A,x,&A);
zzn2_add_i(&B,&A,rhs);
MR_OUT
}
BOOL ecn2_set(_MIPD_ zzn2 *x,zzn2 *y,ecn2 *e)
{
zzn2 lhs,rhs;
#ifdef MR_OS_THREADS
miracl *mr_mip=get_mip();
#endif
if (mr_mip->ERNUM) return FALSE;
MR_IN(195)
lhs.a=mr_mip->w10;
lhs.b=mr_mip->w11;
rhs.a=mr_mip->w12;
rhs.b=mr_mip->w13;
ecn2_rhs(_MIPP_ x,&rhs);
zzn2_sqr_i( y,&lhs);
if (!zzn2_compare(&lhs,&rhs))
{
MR_OUT
return FALSE;
}
zzn2_copy_i(x,&(e->x));
zzn2_copy_i(y,&(e->y));
e->marker=MR_EPOINT_NORMALIZED;
MR_OUT
return TRUE;
}
#ifndef MR_NOSUPPORT_COMPRESSION
BOOL ecn2_setx(_MIPD_ zzn2 *x,ecn2 *e)
{
zzn2 rhs;
#ifdef MR_OS_THREADS
miracl *mr_mip=get_mip();
#endif
if (mr_mip->ERNUM) return FALSE;
MR_IN(201)
rhs.a=mr_mip->w12;
rhs.b=mr_mip->w13;
ecn2_rhs(_MIPP_ x,&rhs);
if (!zzn2_iszero(&rhs))
{
if (!zzn2_sqrt(_MIPP_ &rhs,&rhs))
{
MR_OUT
return FALSE;
}
}
zzn2_copy_i(x,&(e->x));
zzn2_copy_i(&rhs,&(e->y));
e->marker=MR_EPOINT_NORMALIZED;
MR_OUT
return TRUE;
}
#endif
#ifndef MR_AFFINE_ONLY
void ecn2_setxyz(zzn2 *x,zzn2 *y,zzn2 *z,ecn2 *e)
{
zzn2_copy_i(x,&(e->x));
zzn2_copy_i(y,&(e->y));
zzn2_copy_i(z,&(e->z));
e->marker=MR_EPOINT_GENERAL;
}
#endif
void ecn2_negate(_MIPD_ ecn2 *u,ecn2 *w)
{
ecn2_copy(u,w);
if (!w->marker!=MR_EPOINT_INFINITY)
zzn2_negate(_MIPP_ &(w->y),&(w->y));
}
/*
BOOL ecn2_add2(_MIPD_ ecn2 *Q,ecn2 *P,zzn2 *lam,zzn2 *ex1)
{
BOOL Doubling;
#ifdef MR_OS_THREADS
miracl *mr_mip=get_mip();
#endif
Doubling=ecn2_add3(_MIPP_ Q,P,lam,ex1,NULL);
return Doubling;
}
BOOL ecn2_add1(_MIPD_ ecn2 *Q,ecn2 *P,zzn2 *lam)
{
BOOL Doubling;
#ifdef MR_OS_THREADS
miracl *mr_mip=get_mip();
#endif
Doubling=ecn2_add3(_MIPP_ Q,P,lam,NULL,NULL);
return Doubling;
}
*/
BOOL ecn2_sub(_MIPD_ ecn2 *Q,ecn2 *P)
{
BOOL Doubling;
#ifdef MR_OS_THREADS
miracl *mr_mip=get_mip();
#endif
ecn2_negate(_MIPP_ Q,Q);
Doubling=ecn2_add(_MIPP_ Q,P);
ecn2_negate(_MIPP_ Q,Q);
return Doubling;
}
/*
static void zzn2_print(_MIPD_ char *label, zzn2 *x)
{
char s1[1024], s2[1024];
big a, b;
#ifdef MR_STATIC
char mem_big[MR_BIG_RESERVE(2)];
memset(mem_big, 0, MR_BIG_RESERVE(2));
a=mirvar_mem(_MIPP_ mem_big,0);
b=mirvar_mem(_MIPP_ mem_big,1);
#else
a = mirvar(_MIPP_ 0);
b = mirvar(_MIPP_ 0);
#endif
redc(_MIPP_ x->a, a); otstr(_MIPP_ a, s1);
redc(_MIPP_ x->b, b); otstr(_MIPP_ b, s2);
printf("%s: [%s,%s]\n", label, s1, s2);
#ifndef MR_STATIC
mr_free(a); mr_free(b);
#endif
}
static void nres_print(_MIPD_ char *label, big x)
{
char s[1024];
big a;
a = mirvar(_MIPP_ 0);
redc(_MIPP_ x, a);
otstr(_MIPP_ a, s);
printf("%s: %s\n", label, s);
mr_free(a);
}
*/
BOOL ecn2_add_sub(_MIPD_ ecn2 *P,ecn2 *Q,ecn2 *PP,ecn2 *PM)
{ /* PP=P+Q, PM=P-Q. Assumes P and Q are both normalized, and P!=Q */
#ifdef MR_OS_THREADS
miracl *mr_mip=get_mip();
#endif
zzn2 t1,t2,lam;
if (mr_mip->ERNUM) return FALSE;
MR_IN(211)
if (P->marker==MR_EPOINT_GENERAL || P->marker==MR_EPOINT_GENERAL)
{ /* Sorry, some restrictions.. */
mr_berror(_MIPP_ MR_ERR_BAD_PARAMETERS);
MR_OUT
return FALSE;
}
if (zzn2_compare(&(P->x),&(Q->x)))
{ /* P=Q or P=-Q - shouldn't happen */
ecn2_copy(P,PP);
ecn2_add(_MIPP_ Q,PP);
ecn2_copy(P,PM);
ecn2_sub(_MIPP_ Q,PM);
MR_OUT
return TRUE;
}
t1.a = mr_mip->w8;
t1.b = mr_mip->w9;
t2.a = mr_mip->w10;
t2.b = mr_mip->w11;
lam.a = mr_mip->w12;
lam.b = mr_mip->w13;
zzn2_copy_i(&(P->x),&t2);
zzn2_sub_i(&t2,&(Q->x),&t2);
zzn2_inv_i(_MIPP_ &t2); /* only one inverse required */
zzn2_add_i(&(P->x),&(Q->x),&(PP->x));
zzn2_copy_i(&(PP->x),&(PM->x));
zzn2_copy_i(&(P->y),&t1);
zzn2_sub_i(&t1,&(Q->y),&t1);
zzn2_copy_i(&t1,&lam);
zzn2_mul_i( &lam,&t2,&lam);
zzn2_copy_i(&lam,&t1);
zzn2_sqr_i( &t1,&t1);
zzn2_sub_i(&t1,&(PP->x),&(PP->x));
zzn2_copy_i(&(Q->x),&(PP->y));
zzn2_sub_i(&(PP->y),&(PP->x),&(PP->y));
zzn2_mul_i( &(PP->y),&lam,&(PP->y));
zzn2_sub_i(&(PP->y),&(Q->y),&(PP->y));
zzn2_copy_i(&(P->y),&t1);
zzn2_add_i(&t1,&(Q->y),&t1);
zzn2_copy_i(&t1,&lam);
zzn2_mul_i( &lam,&t2,&lam);
zzn2_copy_i(&lam,&t1);
zzn2_sqr_i( &t1,&t1);
zzn2_sub_i(&t1,&(PM->x),&(PM->x));
zzn2_copy_i(&(Q->x),&(PM->y));
zzn2_sub_i(&(PM->y),&(PM->x),&(PM->y));
zzn2_mul_i( &(PM->y),&lam,&(PM->y));
zzn2_add_i(&(PM->y),&(Q->y),&(PM->y));
PP->marker=MR_EPOINT_NORMALIZED;
PM->marker=MR_EPOINT_NORMALIZED;
MR_OUT
return TRUE;
}
BOOL ecn2_add(_MIPD_ ecn2 *Q,ecn2 *P)
{ /* P+=Q */
BOOL Doubling=FALSE;
BOOL twist;
int iA;
zzn2 t1,t2,t3,lam;
#ifdef MR_OS_THREADS
miracl *mr_mip=get_mip();
#endif
t1.a = mr_mip->w8;
t1.b = mr_mip->w9;
t2.a = mr_mip->w10;
t2.b = mr_mip->w11;
t3.a = mr_mip->w12;
t3.b = mr_mip->w13;
lam.a = mr_mip->w14;
lam.b = mr_mip->w15;
twist=mr_mip->TWIST;
if (mr_mip->ERNUM) return FALSE;
if (P->marker==MR_EPOINT_INFINITY)
{
ecn2_copy(Q,P);
return Doubling;
}
if (Q->marker==MR_EPOINT_INFINITY) return Doubling;
MR_IN(205)
if (Q!=P && Q->marker==MR_EPOINT_GENERAL)
{ /* Sorry, this code is optimized for mixed addition only */
mr_berror(_MIPP_ MR_ERR_BAD_PARAMETERS);
MR_OUT
return Doubling;
}
#ifndef MR_AFFINE_ONLY
if (mr_mip->coord==MR_AFFINE)
{
#endif
if (!zzn2_compare(&(P->x),&(Q->x)))
{
zzn2_copy_i(&(P->y),&t1);
zzn2_sub_i(&t1,&(Q->y),&t1);
zzn2_copy_i(&(P->x),&t2);
zzn2_sub_i(&t2,&(Q->x),&t2);
zzn2_copy_i(&t1,&lam);
zzn2_inv_i(_MIPP_ &t2);
zzn2_mul_i( &lam,&t2,&lam);
zzn2_add_i(&(P->x),&(Q->x),&(P->x));
zzn2_copy_i(&lam,&t1);
zzn2_sqr_i( &t1,&t1);
zzn2_sub_i(&t1,&(P->x),&(P->x));
zzn2_copy_i(&(Q->x),&(P->y));
zzn2_sub_i(&(P->y),&(P->x),&(P->y));
zzn2_mul_i( &(P->y),&lam,&(P->y));
zzn2_sub_i(&(P->y),&(Q->y),&(P->y));
}
else
{
if (!zzn2_compare(&(P->y),&(Q->y)) || zzn2_iszero(&(P->y)))
{
ecn2_zero(P);
zzn2_from_int(_MIPP_ 1,&lam);
MR_OUT
return Doubling;
}
zzn2_copy_i(&(P->x),&t1);
zzn2_copy_i(&(P->x),&t2);
zzn2_copy_i(&(P->x),&lam);
zzn2_sqr_i( &lam,&lam);
zzn2_copy_i(&lam,&t3);
zzn2_tim2_i(&t3);
zzn2_add_i(&lam,&t3,&lam);
if (mr_abs(mr_mip->Asize)<MR_TOOBIG) zzn2_from_int(_MIPP_ mr_mip->Asize,&t3);
else zzn2_from_zzn(mr_mip->A,&t3);
if (twist)
{
zzn2_txx_i(&t3);
zzn2_txx_i(&t3);
}
zzn2_add_i(&lam,&t3,&lam);
zzn2_copy_i(&(P->y),&t3);
zzn2_tim2_i(&t3);
zzn2_inv_i(_MIPP_ &t3);
zzn2_mul_i( &lam,&t3,&lam);
zzn2_add_i(&t2,&(P->x),&t2);
zzn2_copy_i(&lam,&(P->x));
zzn2_sqr_i( &(P->x),&(P->x));
zzn2_sub_i(&(P->x),&t2,&(P->x));
zzn2_sub_i(&t1,&(P->x),&t1);
zzn2_mul_i( &t1,&lam,&t1);
zzn2_sub_i(&t1,&(P->y),&(P->y));
}
#ifndef MR_AFFINE_ONLY
zzn2_from_int(_MIPP_ 1,&(P->z));
#endif
P->marker=MR_EPOINT_NORMALIZED;
MR_OUT
return Doubling;
#ifndef MR_AFFINE_ONLY
}
if (Q==P) Doubling=TRUE;
if (!Doubling)
{
if (P->marker!=MR_EPOINT_NORMALIZED)
{
zzn2_sqr_i(&(P->z),&t1);
zzn2_mul_i(&t1,&(P->z),&t2);
zzn2_mul_i(&t1,&(Q->x),&t1);
zzn2_mul_i(&t2,&(Q->y),&t2);
// zzn2_sqr_i( &(P->z),&t1); /* 1S */
// zzn2_mul_i( &t3,&t1,&t3); /* 1M */
// zzn2_mul_i( &t1,&(P->z),&t1); /* 1M */
// zzn2_mul_i( &Yzzz,&t1,&Yzzz); /* 1M */
}
else
{
zzn2_copy(&(Q->x),&t1);
zzn2_copy(&(Q->y),&t2);
}
if (zzn2_compare(&t1,&(P->x))) /*?*/
{
if (!zzn2_compare(&t2,&(P->y)) || zzn2_iszero(&(P->y)))
{
ecn2_zero(P);
zzn2_from_int(_MIPP_ 1,&lam);
MR_OUT
return Doubling;
}
else Doubling=TRUE;
}
}
if (!Doubling)
{ /* Addition */
zzn2_sub_i(&t1,&(P->x),&t1);
zzn2_sub_i(&t2,&(P->y),&t2);
if (P->marker==MR_EPOINT_NORMALIZED) zzn2_copy_i(&t1,&(P->z));
else zzn2_mul_i(&(P->z),&t1,&(P->z));
zzn2_sqr_i(&t1,&t3);
zzn2_mul_i(&t3,&t1,&lam);
zzn2_mul_i(&t3,&(P->x),&t3);
zzn2_copy_i(&t3,&t1);
zzn2_tim2_i(&t1);
zzn2_sqr_i(&t2,&(P->x));
zzn2_dblsub_i(&t1,&lam,&(P->x));
zzn2_sub_i(&t3,&(P->x),&t3);
zzn2_mul_i(&t3,&t2,&t3);
zzn2_mul_i(&lam,&(P->y),&lam);
zzn2_sub_i(&t3,&lam,&(P->y));
}
else
{ /* doubling */
if (P->marker==MR_EPOINT_NORMALIZED) zzn2_from_int(_MIPP_ 1,&t1);
else zzn2_sqr_i(&(P->z),&t1);
if (twist) zzn2_txx_i(&t1);
zzn2_sub_i(&(P->x),&t1,&t2);
zzn2_add_i(&t1,&(P->x),&t1);
zzn2_mul_i(&t2,&t1,&t2);
zzn2_tim3_i(&t2);
zzn2_tim2_i(&(P->y));
if (P->marker==MR_EPOINT_NORMALIZED) zzn2_copy_i(&(P->y),&(P->z));
else zzn2_mul_i(&(P->z),&(P->y),&(P->z));
zzn2_sqr_i(&(P->y),&(P->y));
zzn2_mul_i(&(P->y),&(P->x),&t3);
zzn2_sqr_i(&(P->y),&(P->y));
zzn2_div2_i(&(P->y));
zzn2_sqr_i(&t2,&(P->x));
zzn2_copy_i(&t3,&t1);
zzn2_tim2_i(&t1);
zzn2_sub_i(&(P->x),&t1,&(P->x));
zzn2_sub_i(&t3,&(P->x),&t1);
zzn2_mul_i(&t1,&t2,&t1);
zzn2_sub_i(&t1,&(P->y),&(P->y));
}
P->marker=MR_EPOINT_GENERAL;
MR_OUT
return Doubling;
#endif
}
static int calc_n(int w)
{ /* number of precomputed values needed for given window size */
if (w==3) return 3;
if (w==4) return 5;
if (w==5) return 11;
if (w==6) return 41;
return 0;
}
/* Dahmen, Okeya and Schepers "Affine Precomputation with Sole Inversion in Elliptic Curve Cryptography" */
/* Precomputes table into T. Assumes first P has been copied to P[0], then calculates 3P, 5P, 7P etc. into T */
#define MR_DOS_2 (14+4*MR_STR_SZ_2P)
static void ecn2_dos(_MIPD_ int win,ecn2 *PT)
{
BOOL twist;
int i,j,sz;
zzn2 A,B,C,D,E,T,W,d[MR_STR_SZ_2P],e[MR_STR_SZ_2P];
#ifdef MR_OS_THREADS
miracl *mr_mip=get_mip();
#endif
#ifndef MR_STATIC
char *mem = memalloc(_MIPP_ MR_DOS_2);
#else
char mem[MR_BIG_RESERVE(MR_DOS_2)];
memset(mem, 0, MR_BIG_RESERVE(MR_DOS_2));
#endif
twist=mr_mip->TWIST;
j=0;
sz=calc_n(win);
A.a= mirvar_mem(_MIPP_ mem, j++);
A.b= mirvar_mem(_MIPP_ mem, j++);
B.a= mirvar_mem(_MIPP_ mem, j++);
B.b= mirvar_mem(_MIPP_ mem, j++);
C.a= mirvar_mem(_MIPP_ mem, j++);
C.b= mirvar_mem(_MIPP_ mem, j++);
D.a= mirvar_mem(_MIPP_ mem, j++);
D.b= mirvar_mem(_MIPP_ mem, j++);
E.a= mirvar_mem(_MIPP_ mem, j++);
E.b= mirvar_mem(_MIPP_ mem, j++);
T.a= mirvar_mem(_MIPP_ mem, j++);
T.b= mirvar_mem(_MIPP_ mem, j++);
W.a= mirvar_mem(_MIPP_ mem, j++);
W.b= mirvar_mem(_MIPP_ mem, j++);
for (i=0;i<sz;i++)
{
d[i].a= mirvar_mem(_MIPP_ mem, j++);
d[i].b= mirvar_mem(_MIPP_ mem, j++);
e[i].a= mirvar_mem(_MIPP_ mem, j++);
e[i].b= mirvar_mem(_MIPP_ mem, j++);
}
zzn2_add_i(&(PT[0].y),&(PT[0].y),&d[0]); /* 1. d_0=2.y */
zzn2_sqr_i(&d[0],&C); /* 2. C=d_0^2 */
zzn2_sqr_i(&(PT[0].x),&T);
zzn2_add_i(&T,&T,&A);
zzn2_add_i(&T,&A,&T);
if (mr_abs(mr_mip->Asize)<MR_TOOBIG) zzn2_from_int(_MIPP_ mr_mip->Asize,&A);
else zzn2_from_zzn(mr_mip->A,&A);
if (twist)
{
zzn2_txx_i(&A);
zzn2_txx_i(&A);
}
zzn2_add_i(&A,&T,&A); /* 3. A=3x^2+a */
zzn2_copy_i(&A,&W);
zzn2_add_i(&C,&C,&B);
zzn2_add_i(&B,&C,&B);
zzn2_mul_i(&B,&(PT[0].x),&B); /* 4. B=3C.x */
zzn2_sqr_i(&A,&d[1]);
zzn2_sub_i(&d[1],&B,&d[1]); /* 5. d_1=A^2-B */
zzn2_sqr_i(&d[1],&E); /* 6. E=d_1^2 */
zzn2_mul_i(&B,&E,&B); /* 7. B=E.B */
zzn2_sqr_i(&C,&C); /* 8. C=C^2 */
zzn2_mul_i(&E,&d[1],&D); /* 9. D=E.d_1 */
zzn2_mul_i(&A,&d[1],&A);
zzn2_add_i(&A,&C,&A);
zzn2_negate(_MIPP_ &A,&A); /* 10. A=-d_1*A-C */
zzn2_add_i(&D,&D,&T);
zzn2_sqr_i(&A,&d[2]);
zzn2_sub_i(&d[2],&T,&d[2]);
zzn2_sub_i(&d[2],&B,&d[2]); /* 11. d_2=A^2-2D-B */
if (sz>3)
{
zzn2_sqr_i(&d[2],&E); /* 12. E=d_2^2 */
zzn2_add_i(&T,&D,&T);
zzn2_add_i(&T,&B,&T);
zzn2_mul_i(&T,&E,&B); /* 13. B=E(B+3D) */
zzn2_add_i(&A,&A,&T);
zzn2_add_i(&C,&T,&C);
zzn2_mul_i(&C,&D,&C); /* 14. C=D(2A+C) */
zzn2_mul_i(&d[2],&E,&D); /* 15. D=E.d_2 */
zzn2_mul_i(&A,&d[2],&A);
zzn2_add_i(&A,&C,&A);
zzn2_negate(_MIPP_ &A,&A); /* 16. A=-d_2*A-C */
zzn2_sqr_i(&A,&d[3]);
zzn2_sub_i(&d[3],&D,&d[3]);
zzn2_sub_i(&d[3],&B,&d[3]); /* 17. d_3=A^2-D-B */
for (i=4;i<sz;i++)
{
zzn2_sqr_i(&d[i-1],&E); /* 19. E=d(i-1)^2 */
zzn2_mul_i(&B,&E,&B); /* 20. B=E.B */
zzn2_mul_i(&C,&D,&C); /* 21. C=D.C */
zzn2_mul_i(&E,&d[i-1],&D); /* 22. D=E.d(i-1) */
zzn2_mul_i(&A,&d[i-1],&A);
zzn2_add_i(&A,&C,&A);
zzn2_negate(_MIPP_ &A,&A); /* 23. A=-d(i-1)*A-C */
zzn2_sqr_i(&A,&d[i]);
zzn2_sub_i(&d[i],&D,&d[i]);
zzn2_sub_i(&d[i],&B,&d[i]); /* 24. d(i)=A^2-D-B */
}
}
zzn2_copy_i(&d[0],&e[0]);
for (i=1;i<sz;i++)
zzn2_mul_i(&e[i-1],&d[i],&e[i]);
zzn2_copy_i(&e[sz-1],&A);
zzn2_inv_i(_MIPP_ &A);
for (i=sz-1;i>0;i--)
{
zzn2_copy_i(&d[i],&B);
zzn2_mul_i(&e[i-1],&A,&d[i]);
zzn2_mul_i(&A,&B,&A);
}
zzn2_copy_i(&A,&d[0]);
for (i=1;i<sz;i++)
{
zzn2_sqr_i(&e[i-1],&T);
zzn2_mul_i(&d[i],&T,&d[i]); /** */
}
zzn2_mul_i(&W,&d[0],&W);
zzn2_sqr_i(&W,&A);
zzn2_sub_i(&A,&(PT[0].x),&A);
zzn2_sub_i(&A,&(PT[0].x),&A);
zzn2_sub_i(&(PT[0].x),&A,&B);
zzn2_mul_i(&B,&W,&B);
zzn2_sub_i(&B,&(PT[0].y),&B);
zzn2_sub_i(&B,&(PT[0].y),&T);
zzn2_mul_i(&T,&d[1],&T);
zzn2_sqr_i(&T,&(PT[1].x));
zzn2_sub_i(&(PT[1].x),&A,&(PT[1].x));
zzn2_sub_i(&(PT[1].x),&(PT[0].x),&(PT[1].x));
zzn2_sub_i(&A,&(PT[1].x),&(PT[1].y));
zzn2_mul_i(&(PT[1].y),&T,&(PT[1].y));
zzn2_sub_i(&(PT[1].y),&B,&(PT[1].y));
for (i=2;i<sz;i++)
{
zzn2_sub_i(&(PT[i-1].y),&B,&T);
zzn2_mul_i(&T,&d[i],&T);
zzn2_sqr_i(&T,&(PT[i].x));
zzn2_sub_i(&(PT[i].x),&A,&(PT[i].x));
zzn2_sub_i(&(PT[i].x),&(PT[i-1].x),&(PT[i].x));
zzn2_sub_i(&A,&(PT[i].x),&(PT[i].y));
zzn2_mul_i(&(PT[i].y),&T,&(PT[i].y));
zzn2_sub_i(&(PT[i].y),&B,&(PT[i].y));
}
for (i=0;i<sz;i++) PT[i].marker=MR_EPOINT_NORMALIZED;
#ifndef MR_STATIC
memkill(_MIPP_ mem, MR_DOS_2);
#else
memset(mem, 0, MR_BIG_RESERVE(MR_DOS_2));
#endif
}
#ifndef MR_DOUBLE_BIG
#define MR_MUL_RESERVE (1+4*MR_STR_SZ_2)
#else
#define MR_MUL_RESERVE (2+4*MR_STR_SZ_2)
#endif
int ecn2_mul(_MIPD_ big k,ecn2 *P)
{
int i,j,nb,n,nbs,nzs,nadds;
big h;
ecn2 T[MR_STR_SZ_2];
#ifdef MR_OS_THREADS
miracl *mr_mip=get_mip();
#endif
#ifndef MR_STATIC
char *mem = memalloc(_MIPP_ MR_MUL_RESERVE);
#else
char mem[MR_BIG_RESERVE(MR_MUL_RESERVE)];
memset(mem, 0, MR_BIG_RESERVE(MR_MUL_RESERVE));
#endif
j=0;
#ifndef MR_DOUBLE_BIG
h=mirvar_mem(_MIPP_ mem, j++);
#else
h=mirvar_mem(_MIPP_ mem, j); j+=2;
#endif
for (i=0;i<MR_STR_SZ_2;i++)
{
T[i].x.a= mirvar_mem(_MIPP_ mem, j++);
T[i].x.b= mirvar_mem(_MIPP_ mem, j++);
T[i].y.a= mirvar_mem(_MIPP_ mem, j++);
T[i].y.b= mirvar_mem(_MIPP_ mem, j++);
}
MR_IN(207)
ecn2_norm(_MIPP_ P);
nadds=0;
premult(_MIPP_ k,3,h);
ecn2_copy(P,&T[0]);
ecn2_dos(_MIPP_ MR_WIN_SZ_2,T);
nb=logb2(_MIPP_ h);
for (i=nb-2;i>=1;)
{
if (mr_mip->user!=NULL) (*mr_mip->user)();
n=mr_naf_window(_MIPP_ k,h,i,&nbs,&nzs,MR_WIN_SZ_2);
for (j=0;j<nbs;j++) ecn2_add(_MIPP_ P,P);
if (n>0) {nadds++; ecn2_add(_MIPP_ &T[n/2],P);}
if (n<0) {nadds++; ecn2_sub(_MIPP_ &T[(-n)/2],P);}
i-=nbs;
if (nzs)
{
for (j=0;j<nzs;j++) ecn2_add(_MIPP_ P,P);
i-=nzs;
}
}
ecn2_norm(_MIPP_ P);
MR_OUT
#ifndef MR_STATIC
memkill(_MIPP_ mem, MR_MUL_RESERVE);
#else
memset(mem, 0, MR_BIG_RESERVE(MR_MUL_RESERVE));
#endif
return nadds;
}
/* Double addition, using Joint Sparse Form */
/* R=aP+bQ */
#define MR_MUL2_JSF_RESERVE 20
int ecn2_mul2_jsf(_MIPD_ big a,ecn2 *P,big b,ecn2 *Q,ecn2 *R)
{
int e1,h1,e2,h2,bb,nadds;
ecn2 P1,P2,PS,PD;
big c,d,e,f;
#ifdef MR_OS_THREADS
miracl *mr_mip=get_mip();
#endif
#ifndef MR_STATIC
char *mem = memalloc(_MIPP_ MR_MUL2_JSF_RESERVE);
#else
char mem[MR_BIG_RESERVE(MR_MUL2_JSF_RESERVE)];
memset(mem, 0, MR_BIG_RESERVE(MR_MUL2_JSF_RESERVE));
#endif
c = mirvar_mem(_MIPP_ mem, 0);
d = mirvar_mem(_MIPP_ mem, 1);
e = mirvar_mem(_MIPP_ mem, 2);
f = mirvar_mem(_MIPP_ mem, 3);
P1.x.a= mirvar_mem(_MIPP_ mem, 4);
P1.x.b= mirvar_mem(_MIPP_ mem, 5);
P1.y.a= mirvar_mem(_MIPP_ mem, 6);
P1.y.b= mirvar_mem(_MIPP_ mem, 7);
P2.x.a= mirvar_mem(_MIPP_ mem, 8);
P2.x.b= mirvar_mem(_MIPP_ mem, 9);
P2.y.a= mirvar_mem(_MIPP_ mem, 10);
P2.y.b= mirvar_mem(_MIPP_ mem, 11);
PS.x.a= mirvar_mem(_MIPP_ mem, 12);
PS.x.b= mirvar_mem(_MIPP_ mem, 13);
PS.y.a= mirvar_mem(_MIPP_ mem, 14);
PS.y.b= mirvar_mem(_MIPP_ mem, 15);
PD.x.a= mirvar_mem(_MIPP_ mem, 16);
PD.x.b= mirvar_mem(_MIPP_ mem, 17);
PD.y.a= mirvar_mem(_MIPP_ mem, 18);
PD.y.b= mirvar_mem(_MIPP_ mem, 19);
MR_IN(206)
ecn2_norm(_MIPP_ Q);
ecn2_copy(Q,&P2);
copy(b,d);
if (size(d)<0)
{
negify(d,d);
ecn2_negate(_MIPP_ &P2,&P2);
}
ecn2_norm(_MIPP_ P);
ecn2_copy(P,&P1);
copy(a,c);
if (size(c)<0)
{
negify(c,c);
ecn2_negate(_MIPP_ &P1,&P1);
}
mr_jsf(_MIPP_ d,c,e,d,f,c); /* calculate joint sparse form */
if (compare(e,f)>0) bb=logb2(_MIPP_ e)-1;
else bb=logb2(_MIPP_ f)-1;
ecn2_add_sub(_MIPP_ &P1,&P2,&PS,&PD);
ecn2_zero(R);
nadds=0;
while (bb>=0)
{ /* add/subtract method */
if (mr_mip->user!=NULL) (*mr_mip->user)();
ecn2_add(_MIPP_ R,R);
e1=h1=e2=h2=0;
if (mr_testbit(_MIPP_ d,bb)) e2=1;
if (mr_testbit(_MIPP_ e,bb)) h2=1;
if (mr_testbit(_MIPP_ c,bb)) e1=1;
if (mr_testbit(_MIPP_ f,bb)) h1=1;
if (e1!=h1)
{
if (e2==h2)
{
if (h1==1) {ecn2_add(_MIPP_ &P1,R); nadds++;}
else {ecn2_sub(_MIPP_ &P1,R); nadds++;}
}
else
{
if (h1==1)
{
if (h2==1) {ecn2_add(_MIPP_ &PS,R); nadds++;}
else {ecn2_add(_MIPP_ &PD,R); nadds++;}
}
else
{
if (h2==1) {ecn2_sub(_MIPP_ &PD,R); nadds++;}
else {ecn2_sub(_MIPP_ &PS,R); nadds++;}
}
}
}
else if (e2!=h2)
{
if (h2==1) {ecn2_add(_MIPP_ &P2,R); nadds++;}
else {ecn2_sub(_MIPP_ &P2,R); nadds++;}
}
bb-=1;
}
ecn2_norm(_MIPP_ R);
MR_OUT
#ifndef MR_STATIC
memkill(_MIPP_ mem, MR_MUL2_JSF_RESERVE);
#else
memset(mem, 0, MR_BIG_RESERVE(MR_MUL2_JSF_RESERVE));
#endif
return nadds;
}
/* General purpose multi-exponentiation engine, using inter-leaving algorithm. Calculate aP+bQ+cR+dS...
Inputs are divided into two groups of sizes wa<4 and wb<4. For the first group if the points are fixed the
first precomputed Table Ta[] may be taken from ROM. For the second group if the points are variable Tb[j] will
have to computed online. Each group has its own window size, wina (=5?) and winb (=4?) respectively. The values
a,b,c.. are provided in ma[] and mb[], and 3.a,3.b,3.c (as required by the NAF) are provided in ma3[] and
mb3[]. If only one group is required, set wb=0 and pass NULL pointers.
*/
int ecn2_muln_engine(_MIPD_ int wa,int wina,int wb,int winb,big *ma,big *ma3,big *mb,big *mb3,ecn2 *Ta,ecn2 *Tb,ecn2 *R)
{ /* general purpose interleaving algorithm engine for multi-exp */
int i,j,tba[4],pba[4],na[4],sa[4],tbb[4],pbb[4],nb[4],sb[4],nbits,nbs,nzs;
int sza,szb,nadds;
#ifdef MR_OS_THREADS
miracl *mr_mip=get_mip();
#endif
sza=calc_n(wina);
szb=calc_n(winb);
ecn2_zero(R);
nbits=0;
for (i=0;i<wa;i++) {sa[i]=exsign(ma[i]); tba[i]=0; j=logb2(_MIPP_ ma3[i]); if (j>nbits) nbits=j; }
for (i=0;i<wb;i++) {sb[i]=exsign(mb[i]); tbb[i]=0; j=logb2(_MIPP_ mb3[i]); if (j>nbits) nbits=j; }
nadds=0;
for (i=nbits-1;i>=1;i--)
{
if (mr_mip->user!=NULL) (*mr_mip->user)();
if (R->marker!=MR_EPOINT_INFINITY) ecn2_add(_MIPP_ R,R);
for (j=0;j<wa;j++)
{ /* deal with the first group */
if (tba[j]==0)
{
na[j]=mr_naf_window(_MIPP_ ma[j],ma3[j],i,&nbs,&nzs,wina);
tba[j]=nbs+nzs;
pba[j]=nbs;
}
tba[j]--; pba[j]--;
if (pba[j]==0)
{
if (sa[j]==PLUS)
{
if (na[j]>0) {ecn2_add(_MIPP_ &Ta[j*sza+na[j]/2],R); nadds++;}
if (na[j]<0) {ecn2_sub(_MIPP_ &Ta[j*sza+(-na[j])/2],R); nadds++;}
}
else
{
if (na[j]>0) {ecn2_sub(_MIPP_ &Ta[j*sza+na[j]/2],R); nadds++;}
if (na[j]<0) {ecn2_add(_MIPP_ &Ta[j*sza+(-na[j])/2],R); nadds++;}
}
}
}
for (j=0;j<wb;j++)
{ /* deal with the second group */
if (tbb[j]==0)
{
nb[j]=mr_naf_window(_MIPP_ mb[j],mb3[j],i,&nbs,&nzs,winb);
tbb[j]=nbs+nzs;
pbb[j]=nbs;
}
tbb[j]--; pbb[j]--;
if (pbb[j]==0)
{
if (sb[j]==PLUS)
{
if (nb[j]>0) {ecn2_add(_MIPP_ &Tb[j*szb+nb[j]/2],R); nadds++;}
if (nb[j]<0) {ecn2_sub(_MIPP_ &Tb[j*szb+(-nb[j])/2],R); nadds++;}
}
else
{
if (nb[j]>0) {ecn2_sub(_MIPP_ &Tb[j*szb+nb[j]/2],R); nadds++;}
if (nb[j]<0) {ecn2_add(_MIPP_ &Tb[j*szb+(-nb[j])/2],R); nadds++;}
}
}
}
}
ecn2_norm(_MIPP_ R);
return nadds;
}
/* Routines to support Galbraith, Lin, Scott (GLS) method for ECC */
/* requires an endomorphism psi */
/* *********************** */
/* Precompute T - first half from i.P, second half from i.psi(P) */
void ecn2_precomp_gls(_MIPD_ int win,ecn2 *P,zzn2 *psi,ecn2 *T)
{
int i,j,sz;
#ifdef MR_OS_THREADS
miracl *mr_mip=get_mip();
#endif
j=0;
sz=calc_n(win);
MR_IN(219)
ecn2_norm(_MIPP_ P);
ecn2_copy(P,&T[0]);
ecn2_dos(_MIPP_ win,T); /* precompute table */
for (i=sz;i<sz+sz;i++)
{
ecn2_copy(&T[i-sz],&T[i]);
ecn2_psi(_MIPP_ psi,&T[i]);
}
MR_OUT
}
/* Calculate a[0].P+a[1].psi(P) using interleaving method */
#define MR_MUL2_GLS_RESERVE (2+2*MR_STR_SZ_2*4)
int ecn2_mul2_gls(_MIPD_ big *a,ecn2 *P,zzn2 *psi,ecn2 *R)
{
int i,j,nadds;
ecn2 T[2*MR_STR_SZ_2];
big a3[2];
#ifdef MR_OS_THREADS
miracl *mr_mip=get_mip();
#endif
#ifndef MR_STATIC
char *mem = memalloc(_MIPP_ MR_MUL2_GLS_RESERVE);
#else
char mem[MR_BIG_RESERVE(MR_MUL2_GLS_RESERVE)];
memset(mem, 0, MR_BIG_RESERVE(MR_MUL2_GLS_RESERVE));
#endif
for (j=i=0;i<2;i++)
a3[i]=mirvar_mem(_MIPP_ mem, j++);
for (i=0;i<2*MR_STR_SZ_2;i++)
{
T[i].x.a=mirvar_mem(_MIPP_ mem, j++);
T[i].x.b=mirvar_mem(_MIPP_ mem, j++);
T[i].y.a=mirvar_mem(_MIPP_ mem, j++);
T[i].y.b=mirvar_mem(_MIPP_ mem, j++);
T[i].marker=MR_EPOINT_INFINITY;
}
MR_IN(220)
ecn2_precomp_gls(_MIPP_ MR_WIN_SZ_2,P,psi,T);
for (i=0;i<2;i++) premult(_MIPP_ a[i],3,a3[i]); /* calculate for NAF */
nadds=ecn2_muln_engine(_MIPP_ 0,0,2,MR_WIN_SZ_2,NULL,NULL,a,a3,NULL,T,R);
ecn2_norm(_MIPP_ R);
MR_OUT
#ifndef MR_STATIC
memkill(_MIPP_ mem, MR_MUL2_GLS_RESERVE);
#else
memset(mem, 0, MR_BIG_RESERVE(MR_MUL2_GLS_RESERVE));
#endif
return nadds;
}
/* Calculates a[0]*P+a[1]*psi(P) + b[0]*Q+b[1]*psi(Q)
where P is fixed, and precomputations are already done off-line into FT
using ecn2_precomp_gls. Useful for signature verification */
#define MR_MUL4_GLS_V_RESERVE (4+2*MR_STR_SZ_2*4)
int ecn2_mul4_gls_v(_MIPD_ big *a,ecn2 *FT,big *b,ecn2 *Q,zzn2 *psi,ecn2 *R)
{
int i,j,nadds;
ecn2 VT[2*MR_STR_SZ_2];
big a3[2],b3[2];
#ifdef MR_OS_THREADS
miracl *mr_mip=get_mip();
#endif
#ifndef MR_STATIC
char *mem = memalloc(_MIPP_ MR_MUL4_GLS_V_RESERVE);
#else
char mem[MR_BIG_RESERVE(MR_MUL4_GLS_V_RESERVE)];
memset(mem, 0, MR_BIG_RESERVE(MR_MUL4_GLS_V_RESERVE));
#endif
j=0;
for (i=0;i<2;i++)
{
a3[i]=mirvar_mem(_MIPP_ mem, j++);
b3[i]=mirvar_mem(_MIPP_ mem, j++);
}
for (i=0;i<2*MR_STR_SZ_2;i++)
{
VT[i].x.a=mirvar_mem(_MIPP_ mem, j++);
VT[i].x.b=mirvar_mem(_MIPP_ mem, j++);
VT[i].y.a=mirvar_mem(_MIPP_ mem, j++);
VT[i].y.b=mirvar_mem(_MIPP_ mem, j++);
VT[i].marker=MR_EPOINT_INFINITY;
}
MR_IN(217)
ecn2_precomp_gls(_MIPP_ MR_WIN_SZ_2,Q,psi,VT); /* precompute for the variable points */
for (i=0;i<2;i++)
{ /* needed for NAF */
premult(_MIPP_ a[i],3,a3[i]);
premult(_MIPP_ b[i],3,b3[i]);
}
nadds=ecn2_muln_engine(_MIPP_ 2,MR_WIN_SZ_2P,2,MR_WIN_SZ_2,a,a3,b,b3,FT,VT,R);
ecn2_norm(_MIPP_ R);
MR_OUT
#ifndef MR_STATIC
memkill(_MIPP_ mem, MR_MUL4_GLS_V_RESERVE);
#else
memset(mem, 0, MR_BIG_RESERVE(MR_MUL4_GLS_V_RESERVE));
#endif
return nadds;
}
/* Calculate a.P+b.Q using interleaving method. P is fixed and FT is precomputed from it */
void ecn2_precomp(_MIPD_ int win,ecn2 *P,ecn2 *T)
{
int sz;
#ifdef MR_OS_THREADS
miracl *mr_mip=get_mip();
#endif
sz=calc_n(win);
MR_IN(216)
ecn2_norm(_MIPP_ P);
ecn2_copy(P,&T[0]);
ecn2_dos(_MIPP_ win,T);
MR_OUT
}
#ifndef MR_DOUBLE_BIG
#define MR_MUL2_RESERVE (2+2*MR_STR_SZ_2*4)
#else
#define MR_MUL2_RESERVE (4+2*MR_STR_SZ_2*4)
#endif
int ecn2_mul2(_MIPD_ big a,ecn2 *FT,big b,ecn2 *Q,ecn2 *R)
{
int i,j,nadds;
ecn2 T[2*MR_STR_SZ_2];
big a3,b3;
#ifdef MR_OS_THREADS
miracl *mr_mip=get_mip();
#endif
#ifndef MR_STATIC
char *mem = memalloc(_MIPP_ MR_MUL2_RESERVE);
#else
char mem[MR_BIG_RESERVE(MR_MUL2_RESERVE)];
memset(mem, 0, MR_BIG_RESERVE(MR_MUL2_RESERVE));
#endif
j=0;
#ifndef MR_DOUBLE_BIG
a3=mirvar_mem(_MIPP_ mem, j++);
b3=mirvar_mem(_MIPP_ mem, j++);
#else
a3=mirvar_mem(_MIPP_ mem, j); j+=2;
b3=mirvar_mem(_MIPP_ mem, j); j+=2;
#endif
for (i=0;i<2*MR_STR_SZ_2;i++)
{
T[i].x.a=mirvar_mem(_MIPP_ mem, j++);
T[i].x.b=mirvar_mem(_MIPP_ mem, j++);
T[i].y.a=mirvar_mem(_MIPP_ mem, j++);
T[i].y.b=mirvar_mem(_MIPP_ mem, j++);
T[i].marker=MR_EPOINT_INFINITY;
}
MR_IN(218)
ecn2_precomp(_MIPP_ MR_WIN_SZ_2,Q,T);
premult(_MIPP_ a,3,a3);
premult(_MIPP_ b,3,b3);
nadds=ecn2_muln_engine(_MIPP_ 1,MR_WIN_SZ_2P,1,MR_WIN_SZ_2,&a,&a3,&b,&b3,FT,T,R);
ecn2_norm(_MIPP_ R);
MR_OUT
#ifndef MR_STATIC
memkill(_MIPP_ mem, MR_MUL2_RESERVE);
#else
memset(mem, 0, MR_BIG_RESERVE(MR_MUL2_RESERVE));
#endif
return nadds;
}
#ifndef MR_STATIC
BOOL ecn2_brick_init(_MIPD_ ebrick *B,zzn2 *x,zzn2 *y,big a,big b,big n,int window,int nb)
{ /* Uses Montgomery arithmetic internally *
* (x,y) is the fixed base *
* a,b and n are parameters and modulus of the curve *
* window is the window size in bits and *
* nb is the maximum number of bits in the multiplier */
int i,j,k,t,bp,len,bptr;
ecn2 *table;
ecn2 w;
#ifdef MR_OS_THREADS
miracl *mr_mip=get_mip();
#endif
if (nb<2 || window<1 || window>nb || mr_mip->ERNUM) return FALSE;
t=MR_ROUNDUP(nb,window);
if (t<2) return FALSE;
MR_IN(221)
#ifndef MR_ALWAYS_BINARY
if (mr_mip->base != mr_mip->base2)
{
mr_berror(_MIPP_ MR_ERR_NOT_SUPPORTED);
MR_OUT
return FALSE;
}
#endif
B->window=window;
B->max=nb;
table=mr_alloc(_MIPP_ (1<<window),sizeof(ecn2));
if (table==NULL)
{
mr_berror(_MIPP_ MR_ERR_OUT_OF_MEMORY);
MR_OUT
return FALSE;
}
B->a=mirvar(_MIPP_ 0);
B->b=mirvar(_MIPP_ 0);
B->n=mirvar(_MIPP_ 0);
copy(a,B->a);
copy(b,B->b);
copy(n,B->n);
ecurve_init(_MIPP_ a,b,n,MR_AFFINE);
mr_mip->TWIST=TRUE;
w.x.a=mirvar(_MIPP_ 0);
w.x.b=mirvar(_MIPP_ 0);
w.y.a=mirvar(_MIPP_ 0);
w.y.b=mirvar(_MIPP_ 0);
w.marker=MR_EPOINT_INFINITY;
ecn2_set(_MIPP_ x,y,&w);
table[0].x.a=mirvar(_MIPP_ 0);
table[0].x.b=mirvar(_MIPP_ 0);
table[0].y.a=mirvar(_MIPP_ 0);
table[0].y.b=mirvar(_MIPP_ 0);
table[0].marker=MR_EPOINT_INFINITY;
table[1].x.a=mirvar(_MIPP_ 0);
table[1].x.b=mirvar(_MIPP_ 0);
table[1].y.a=mirvar(_MIPP_ 0);
table[1].y.b=mirvar(_MIPP_ 0);
table[1].marker=MR_EPOINT_INFINITY;
ecn2_copy(&w,&table[1]);
for (j=0;j<t;j++)
ecn2_add(_MIPP_ &w,&w);
k=1;
for (i=2;i<(1<<window);i++)
{
table[i].x.a=mirvar(_MIPP_ 0);
table[i].x.b=mirvar(_MIPP_ 0);
table[i].y.a=mirvar(_MIPP_ 0);
table[i].y.b=mirvar(_MIPP_ 0);
table[i].marker=MR_EPOINT_INFINITY;
if (i==(1<<k))
{
k++;
ecn2_copy(&w,&table[i]);
for (j=0;j<t;j++)
ecn2_add(_MIPP_ &w,&w);
continue;
}
bp=1;
for (j=0;j<k;j++)
{
if (i&bp)
ecn2_add(_MIPP_ &table[1<<j],&table[i]);
bp<<=1;
}
}
mr_free(w.x.a);
mr_free(w.x.b);
mr_free(w.y.a);
mr_free(w.y.b);
/* create the table */
len=n->len;
bptr=0;
B->table=mr_alloc(_MIPP_ 4*len*(1<<window),sizeof(mr_small));
for (i=0;i<(1<<window);i++)
{
for (j=0;j<len;j++) B->table[bptr++]=table[i].x.a->w[j];
for (j=0;j<len;j++) B->table[bptr++]=table[i].x.b->w[j];
for (j=0;j<len;j++) B->table[bptr++]=table[i].y.a->w[j];
for (j=0;j<len;j++) B->table[bptr++]=table[i].y.b->w[j];
mr_free(table[i].x.a);
mr_free(table[i].x.b);
mr_free(table[i].y.a);
mr_free(table[i].y.b);
}
mr_free(table);
MR_OUT
return TRUE;
}
void ecn2_brick_end(ebrick *B)
{
mirkill(B->n);
mirkill(B->b);
mirkill(B->a);
mr_free(B->table);
}
#else
/* use precomputated table in ROM */
void ecn2_brick_init(ebrick *B,const mr_small* rom,big a,big b,big n,int window,int nb)
{
B->table=rom;
B->a=a; /* just pass a pointer */
B->b=b;
B->n=n;
B->window=window; /* 2^4=16 stored values */
B->max=nb;
}
#endif
/*
void ecn2_mul_brick(_MIPD_ ebrick *B,big e,zzn2 *x,zzn2 *y)
{
int i,j,t,len,maxsize,promptr;
ecn2 w,z;
#ifdef MR_STATIC
char mem[MR_BIG_RESERVE(10)];
#else
char *mem;
#endif
#ifdef MR_OS_THREADS
miracl *mr_mip=get_mip();
#endif
if (size(e)<0) mr_berror(_MIPP_ MR_ERR_NEG_POWER);
t=MR_ROUNDUP(B->max,B->window);
MR_IN(116)
#ifndef MR_ALWAYS_BINARY
if (mr_mip->base != mr_mip->base2)
{
mr_berror(_MIPP_ MR_ERR_NOT_SUPPORTED);
MR_OUT
return;
}
#endif
if (logb2(_MIPP_ e) > B->max)
{
mr_berror(_MIPP_ MR_ERR_EXP_TOO_BIG);
MR_OUT
return;
}
ecurve_init(_MIPP_ B->a,B->b,B->n,MR_BEST);
mr_mip->TWIST=TRUE;
#ifdef MR_STATIC
memset(mem,0,MR_BIG_RESERVE(10));
#else
mem=memalloc(_MIPP_ 10);
#endif
w.x.a=mirvar_mem(_MIPP_ mem, 0);
w.x.b=mirvar_mem(_MIPP_ mem, 1);
w.y.a=mirvar_mem(_MIPP_ mem, 2);
w.y.b=mirvar_mem(_MIPP_ mem, 3);
w.z.a=mirvar_mem(_MIPP_ mem, 4);
w.z.b=mirvar_mem(_MIPP_ mem, 5);
w.marker=MR_EPOINT_INFINITY;
z.x.a=mirvar_mem(_MIPP_ mem, 6);
z.x.b=mirvar_mem(_MIPP_ mem, 7);
z.y.a=mirvar_mem(_MIPP_ mem, 8);
z.y.b=mirvar_mem(_MIPP_ mem, 9);
z.marker=MR_EPOINT_INFINITY;
len=B->n->len;
maxsize=4*(1<<B->window)*len;
for (i=t-1;i>=0;i--)
{
j=recode(_MIPP_ e,t,B->window,i);
ecn2_add(_MIPP_ &w,&w);
if (j>0)
{
promptr=4*j*len;
init_big_from_rom(z.x.a,len,B->table,maxsize,&promptr);
init_big_from_rom(z.x.b,len,B->table,maxsize,&promptr);
init_big_from_rom(z.y.a,len,B->table,maxsize,&promptr);
init_big_from_rom(z.y.b,len,B->table,maxsize,&promptr);
z.marker=MR_EPOINT_NORMALIZED;
ecn2_add(_MIPP_ &z,&w);
}
}
ecn2_norm(_MIPP_ &w);
ecn2_getxy(&w,x,y);
#ifndef MR_STATIC
memkill(_MIPP_ mem,10);
#else
memset(mem,0,MR_BIG_RESERVE(10));
#endif
MR_OUT
}
*/
void ecn2_mul_brick_gls(_MIPD_ ebrick *B,big *e,zzn2 *psi,zzn2 *x,zzn2 *y)
{
int i,j,k,t,len,maxsize,promptr,se[2];
ecn2 w,z;
#ifdef MR_STATIC
char mem[MR_BIG_RESERVE(10)];
#else
char *mem;
#endif
#ifdef MR_OS_THREADS
miracl *mr_mip=get_mip();
#endif
for (k=0;k<2;k++) se[k]=exsign(e[k]);
t=MR_ROUNDUP(B->max,B->window);
MR_IN(222)
#ifndef MR_ALWAYS_BINARY
if (mr_mip->base != mr_mip->base2)
{
mr_berror(_MIPP_ MR_ERR_NOT_SUPPORTED);
MR_OUT
return;
}
#endif
if (logb2(_MIPP_ e[0])>B->max || logb2(_MIPP_ e[1])>B->max)
{
mr_berror(_MIPP_ MR_ERR_EXP_TOO_BIG);
MR_OUT
return;
}
ecurve_init(_MIPP_ B->a,B->b,B->n,MR_BEST);
mr_mip->TWIST=TRUE;
#ifdef MR_STATIC
memset(mem,0,MR_BIG_RESERVE(10));
#else
mem=memalloc(_MIPP_ 10);
#endif
z.x.a=mirvar_mem(_MIPP_ mem, 0);
z.x.b=mirvar_mem(_MIPP_ mem, 1);
z.y.a=mirvar_mem(_MIPP_ mem, 2);
z.y.b=mirvar_mem(_MIPP_ mem, 3);
z.marker=MR_EPOINT_INFINITY;
w.x.a=mirvar_mem(_MIPP_ mem, 4);
w.x.b=mirvar_mem(_MIPP_ mem, 5);
w.y.a=mirvar_mem(_MIPP_ mem, 6);
w.y.b=mirvar_mem(_MIPP_ mem, 7);
#ifndef MR_AFFINE_ONLY
w.z.a=mirvar_mem(_MIPP_ mem, 8);
w.z.b=mirvar_mem(_MIPP_ mem, 9);
#endif
w.marker=MR_EPOINT_INFINITY;
len=B->n->len;
maxsize=4*(1<<B->window)*len;
for (i=t-1;i>=0;i--)
{
ecn2_add(_MIPP_ &w,&w);
for (k=0;k<2;k++)
{
j=recode(_MIPP_ e[k],t,B->window,i);
if (j>0)
{
promptr=4*j*len;
init_big_from_rom(z.x.a,len,B->table,maxsize,&promptr);
init_big_from_rom(z.x.b,len,B->table,maxsize,&promptr);
init_big_from_rom(z.y.a,len,B->table,maxsize,&promptr);
init_big_from_rom(z.y.b,len,B->table,maxsize,&promptr);
z.marker=MR_EPOINT_NORMALIZED;
if (k==1) ecn2_psi(_MIPP_ psi,&z);
if (se[k]==PLUS) ecn2_add(_MIPP_ &z,&w);
else ecn2_sub(_MIPP_ &z,&w);
}
}
}
ecn2_norm(_MIPP_ &w);
ecn2_getxy(&w,x,y);
#ifndef MR_STATIC
memkill(_MIPP_ mem,10);
#else
memset(mem,0,MR_BIG_RESERVE(10));
#endif
MR_OUT
}
|
get_pi_par_vec.c | #include <x86intrin.h>
static long num_steps = 100000;
#define MAX_THREADS 4
float scalar_four = 4.0f, scalar_zero = 0.0f, scalar_one = 1.0f;
float step;
int get_pi_par_vec_ ()
{
int i, k;
float local_sum[MAX_THREADS];
float pi, sum = 0.0;
step = 1.0f/(double) num_steps;
for (k = 0; k < MAX_THREADS; k++) local_sum[k] = 0.0;
#pragma omp parallel num_threads(4) private(i)
{
int ID = omp_get_thread_num();
float vsum[4], ival, scalar_four = 4.0;
__m128 ramp = _mm_setr_ps(0.5, 1.5, 2.5, 3.5);
__m128 one = _mm_load1_ps(&scalar_one);
__m128 four = _mm_load1_ps(&scalar_four);
__m128 vstep = _mm_load1_ps(&step);
__m128 sum = _mm_load1_ps(&scalar_zero);
__m128 xvec;
__m128 denom;
__m128 eye;
// unroll loop 4 times ... assume num_steps\%4 =0
#pragma omp for schedule(static)
for (i = 0; i < num_steps; i = i + 4){
ival = (float) i;
eye = _mm_load1_ps(&ival);
xvec = _mm_mul_ps(_mm_add_ps(eye,ramp), vstep);
denom = _mm_add_ps(_mm_mul_ps(xvec,xvec), one);
sum = _mm_add_ps(_mm_div_ps(four,denom), sum);
}
_mm_store_ps(&vsum[0], sum);
local_sum[ID] = step * (vsum[0] + vsum[1] + vsum[2] + vsum[3]);
}
for (k = 0; k < MAX_THREADS; k++) pi += local_sum[k];
return pi;
}
|
nn.c | #include <stdio.h>
#include <stdint.h>
#include <stdlib.h>
#include <math.h>
#include <string.h>
/*
portable time function
*/
#ifdef __GNUC__
#include <time.h>
float getticks()
{
struct timespec ts;
if(clock_gettime(CLOCK_MONOTONIC, &ts) < 0)
{
printf("# clock_gettime error\n");
return -1.0f;
}
return ts.tv_sec + 1e-9f*ts.tv_nsec;
}
#else
#include <windows.h>
float getticks()
{
static double freq = -1.0;
LARGE_INTEGER lint;
if(freq < 0.0)
{
if(!QueryPerformanceFrequency(&lint))
return -1.0f;
freq = lint.QuadPart;
}
if(!QueryPerformanceCounter(&lint))
return -1.0f;
return (float)( lint.QuadPart/freq );
}
#endif
/*
*/
int get_score_h(void* bag1, void* bag2)
{
int i, n;
float sim, sv1, sv2;
float* v1;
float* v2;
//
if(*(int*)bag1 != *(int*)bag2)
return 0;
n = *(int*)bag1;
//
v1 = (float*)(1+(int*)bag1);
v2 = (float*)(1+(int*)bag2);
sim = 0.0f;
sv1 = 0.0f;
sv2 = 0.0f;
for(i=0; i<n; ++i)
{
//
sim = sim + v1[i]*v2[i];
//
sv1 = sv1 + v1[i]*v1[i];
sv2 = sv2 + v2[i]*v2[i];
}
//
int score;
if(sv1<=0.0f || sv2<=0.0f)
score = 0;
else
score = (int)(1024.0f*(0.5f + 0.5f*sim/sqrtf(sv1)/sqrtf(sv2)));
return score;
/*
sim = 0.0f;
for(i=0; i<n; ++i)
if(v1[i] < v2[i])
sim = sim + v1[i];
else
sim = sim + v2[i];
return (int)(1024*sim);
*/
}
/*
*/
float edist(float v1[], float v2[], int ndims)
{
float accum;
int i;
//
accum = 0.0f;
for(i=0; i<ndims; ++i)
accum += (v1[i]-v2[i])*(v1[i]-v2[i]);
//
return sqrt(accum);
}
int get_score_f(void* bag1, void* bag2, float t)
{
int i, j, n, n1, n2, ndims;
float* s1;
float* s2;
float d;
//
ndims = *(int*)bag1;
if(ndims != *(int*)bag2)
return 0;
//
n = 0;
if(*(1+(int*)bag1) < *(1+(int*)bag2))
{
n1 = *(1+(int*)bag1);
s1 = (float*)( 2+(int*)bag1 );
n2 = *(1+(int*)bag2);
s2 = (float*)( 2+(int*)bag2 );
}
else
{
n1 = *(1+(int*)bag2);
s1 = (float*)( 2+(int*)bag2 );
n2 = *(1+(int*)bag1);
s2 = (float*)( 2+(int*)bag1 );
}
for(i=0; i<n1; ++i)
for(j=0; j<n2; ++j)
{
//
d = edist(&s1[i*ndims], &s2[j*ndims], ndims);
//
if(d < t)
{
++n;
break;
}
}
//
//return n;
return 100*n/n1;
}
/*
*/
int hamm(uint8_t s1[], uint8_t s2[], int nbytes)
{
int i, h;
static int popcntlut[256] =
{
0, 1, 1, 2, 1, 2, 2, 3, 1, 2, 2, 3, 2, 3, 3, 4,
1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5,
1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5,
2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5,
2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7,
1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5,
2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7,
2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7,
3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7,
4, 5, 5, 6, 5, 6, 6, 7, 5, 6, 6, 7, 6, 7, 7, 8
};
//
h = 0;
for(i=0; i<nbytes; ++i)
h = h + popcntlut[s1[i]^s2[i]];
//
return h;
}
int get_score_b(void* bag1, void* bag2, int t)
{
int i, j, k, h, n, nbytes;
uint8_t* s1;
uint8_t* s2;
//
nbytes = *(int*)bag1;
if(nbytes != *(int*)bag2)
return 0;
//
n = 0;
int n1, n2;
if(*(1+(int*)bag1) < *(1+(int*)bag2))
{
n1 = *(1+(int*)bag1);
s1 = (uint8_t*)( 2+(int*)bag1 );
n2 = *(1+(int*)bag2);
s2 = (uint8_t*)( 2+(int*)bag2 );
}
else
{
n1 = *(1+(int*)bag2);
s1 = (uint8_t*)( 2+(int*)bag2 );
n2 = *(1+(int*)bag1);
s2 = (uint8_t*)( 2+(int*)bag1 );
}
for(i=0; i<n1; ++i)
for(j=0; j<n2; ++j)
{
//
h = hamm(&s1[i*nbytes], &s2[j*nbytes], nbytes);
//
if(h < t)
{
++n;
break;
}
}
//
return n;
}
/*
*/
char magic[4] = "";
int ndims=0, nbags=0;
char labels[16384][32];
void* bags[16384];
int load_bags(char* path)
{
char buffer[1024];
FILE* file;
//
sprintf(buffer, "%s/list", path);
file = fopen(buffer, "r");
if(!file)
{
printf("* cannot open '%s'\n", buffer);
return 0;
}
//
nbags = 0;
while(1 == fscanf(file, "%s", &labels[nbags][0]))
{
FILE* tmpfile;
char tmpbuffer[1024];
//
sprintf(tmpbuffer, "%s/%s", path, &labels[nbags][0]);
tmpfile = fopen(tmpbuffer, "rb");
if(tmpfile)
{
int n;
//
fread(magic, 1, 4, tmpfile);
if(magic[0]=='f')
{
//
fread(&ndims, 1, sizeof(int), tmpfile);
fread(&n, 1, sizeof(int), tmpfile);
//
bags[nbags] = malloc(2*sizeof(int)+ndims*n*sizeof(float));
//
*(int*)bags[nbags] = ndims;
*(1+(int*)bags[nbags]) = n;
//
fread(2+(int*)bags[nbags], sizeof(float), n*ndims, tmpfile);
}
else if(magic[0]=='b')
{
//
fread(&ndims, 1, sizeof(int), tmpfile);
fread(&n, 1, sizeof(int), tmpfile);
//
bags[nbags] = malloc(2*sizeof(int)+ndims*n*sizeof(uint8_t));
//
*(int*)bags[nbags] = ndims;
*(1+(int*)bags[nbags]) = n;
//
fread(2+(int*)bags[nbags], sizeof(uint8_t), n*ndims, tmpfile);
}
else
{
//
fread(&ndims, 1, sizeof(int), tmpfile);
//
bags[nbags] = malloc(1*sizeof(int)+ndims*sizeof(float));
//
*(int*)bags[nbags] = ndims;
//
fread(1+(int*)bags[nbags], sizeof(float), ndims, tmpfile);
}
//
fclose(tmpfile);
//
char* str = &labels[nbags][0];
while(*str!='.')
++str;
*str = '\0';
//
++nbags;
}
}
fclose(file);
//
return 1;
}
/*
*/
int S[16384][16384];
void compute_similarity_matrix(float thr)
{
int i;
#pragma omp parallel for
for(i=0; i<nbags; ++i)
{
int j;
for(j=0; j<nbags; ++j)
/*if(i==j)
S[i][j] = 0;
else
*/
{
int score;
//
if(magic[0] == 'b')
score = get_score_b(bags[i], bags[j], (int)thr);
else if(magic[0] == 'f')
score = get_score_f(bags[i], bags[j], thr);
else
score = get_score_h(bags[i], bags[j]);
//
S[i][j] = score;
}
}
// print similarity matrix
/*
printf("\n-------------------\n");
for(i=0; i<nbags; ++i)
{
int j;
//
for(j=0; j<nbags; ++j)
printf("%d\t", S[i][j]);
//
printf("\n");
}
printf("-------------------\n");
//*/
}
int load_similarity_matrix(const char path[])
{
int i, j;
FILE* file;
//
file = fopen(path, "r");
if(!file)
return 0;
//
magic[0] = 'm';
magic[1] = 't';
magic[2] = 'r';
magic[3] = 'x';
//
fscanf(file, "%d", &nbags);
for(i=0; i<nbags; ++i)
{
//
fscanf(file, "%s", &labels[i][0]);
//
char* str = &labels[i][0];
while(*str!='\0' && *str!='.')
++str;
*str = '\0';
//
//printf("%s\n", labels[i]);
}
for(i=0; i<nbags; ++i)
for(j=0; j<nbags; ++j)
fscanf(file, "%d", &S[i][j]);
//
fclose(file);
//
return 1;
}
/*
*/
void nn(float* onenn, float* t1, float* t2, float* avgp, float* avgn)
{
int i, ncorrect[3], nretrieved[3], nrelevant[3];
int np, nn;
//
ncorrect[0] = 0;
ncorrect[1] = 0;
ncorrect[2] = 0;
nretrieved[0] = 0;
nretrieved[1] = 0;
nretrieved[2] = 0;
nrelevant[0] = 0;
nrelevant[1] = 0;
nrelevant[2] = 0;
nn = np = 0;
*avgp = 0.0f;
*avgn = 0.0f;
//
//#pragma omp parallel for
for(i=0; i<nbags; ++i)
{
int n, nc, j, k, l, topinds[128], topscores[128];
// get the size of the class to which bag[i] belongs
nc = 0;
for(j=0; j<nbags; ++j)
if(0==strcmp(&labels[i][0], &labels[j][0]))
++nc;
//
n = 2*(nc-1);
for(k=0; k<n; ++k)
topscores[k] = -1;
for(j=0; j<nbags; ++j)
if(i!=j)
{
int score;
//
score = S[i][j];
//
topscores[n] = -1;
k=0;
while(score <= topscores[k])
++k;
for(l=n-1; l>k; --l)
{
topscores[l] = topscores[l-1];
topinds[l] = topinds[l-1];
}
topscores[k] = score;
topinds[k] = j;
//
//#pragma omp critical
{
if(0==strcmp(&labels[i][0], &labels[j][0]))
{
++np;
*avgp = *avgp + score;
}
else
{
++nn;
*avgn = *avgn + score;
}
}
}
//
//#pragma omp critical
{
// nn
if(0==strcmp(&labels[i][0], &labels[topinds[0]][0]))
++ncorrect[0];
nretrieved[0] += 1;
nrelevant[0] += nc-1;
// 1st tier
for(k=0; k<nc-1; ++k)
if(0==strcmp(&labels[i][0], &labels[topinds[k]][0]))
++ncorrect[1];
nretrieved[1] += nc-1;
nrelevant[1] += nc-1;
// 2nd tier
for(k=0; k<2*(nc-1); ++k)
if(0==strcmp(&labels[i][0], &labels[topinds[k]][0]))
++ncorrect[2];
nretrieved[2] += 2*(nc-1);
nrelevant[2] += nc-1;
}
}
//
*onenn = ncorrect[0]/(float)nretrieved[0];
*t1 = ncorrect[1]/(float)nrelevant[1];
*t2 = ncorrect[2]/(float)nrelevant[2];
*avgp = *avgp/np;
*avgn = *avgn/nn;
}
/*
*/
int main(int argc, char** argv)
{
float t, thr, t1, t2, onenn, avgp, avgn;
if(argc==2)
{
//
t = getticks();
if(!load_similarity_matrix(argv[1]))
return 0;
//
nn(&onenn, &t1, &t2, &avgp, &avgn);
printf("(t: %d [s]): nn = %f T1 = %f T2 = %f\n", (int)(getticks()-t), onenn, t1, t2);
//
return 0;
}
else if(argc!=3)
{
printf("* source folder\n");
printf("* threshold\n");
return 0;
}
//
if(!load_bags(argv[1]))
return 0;
sscanf(argv[2], "%f", &thr);
//
if(nbags == 2)
{
//
printf("%d\n", get_score_b(bags[0], bags[1], thr) );
//
return 0;
}
//
if(magic[0] == 'b')
printf("* %c%c%c%c%d@%d ", magic[0], magic[1], magic[2], magic[3], 8*ndims, (int)thr);
else
printf("* %c%c%c%c%d@%f ", magic[0], magic[1], magic[2], magic[3], ndims, thr);
//
t = getticks();
compute_similarity_matrix(thr);
nn(&onenn, &t1, &t2, &avgp, &avgn);
printf("(t: %d [s]): NN = %f FT = %f ST = %f\n", (int)(getticks()-t), onenn, t1, t2);
//
return 0;
}
|
GB_binop__first_fc64.c | //------------------------------------------------------------------------------
// GB_binop: hard-coded functions for each built-in binary operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2021, All Rights Reserved.
// SPDX-License-Identifier: Apache-2.0
//------------------------------------------------------------------------------
// If this file is in the Generated2/ folder, do not edit it
// (it is auto-generated from Generator/*).
#include "GB.h"
#ifndef GBCOMPACT
#include "GB_emult.h"
#include "GB_control.h"
#include "GB_ek_slice.h"
#include "GB_dense.h"
#include "GB_atomics.h"
#include "GB_bitmap_assign_methods.h"
#include "GB_binop__include.h"
// C=binop(A,B) is defined by the following types and operators:
// A+B function (eWiseAdd): GB (_AaddB__first_fc64)
// A.*B function (eWiseMult): GB (_AemultB_01__first_fc64)
// A.*B function (eWiseMult): GB (_AemultB_02__first_fc64)
// A.*B function (eWiseMult): GB (_AemultB_03__first_fc64)
// A.*B function (eWiseMult): GB (_AemultB_bitmap__first_fc64)
// A*D function (colscale): GB (_AxD__first_fc64)
// D*A function (rowscale): GB (_DxB__first_fc64)
// C+=B function (dense accum): GB (_Cdense_accumB__first_fc64)
// C+=b function (dense accum): GB (_Cdense_accumb__first_fc64)
// C+=A+B function (dense ewise3): GB ((none))
// C=A+B function (dense ewise3): GB (_Cdense_ewise3_noaccum__first_fc64)
// C=scalar+B GB ((none))
// C=scalar+B' GB ((none))
// C=A+scalar GB ((none))
// C=A'+scalar GB ((none))
// C type: GxB_FC64_t
// A type: GxB_FC64_t
// B,b type: GxB_FC64_t
// BinaryOp: cij = aij
#define GB_ATYPE \
GxB_FC64_t
#define GB_BTYPE \
GxB_FC64_t
#define GB_CTYPE \
GxB_FC64_t
// true if the types of A and B are identical
#define GB_ATYPE_IS_BTYPE \
1
// true if the types of C and A are identical
#define GB_CTYPE_IS_ATYPE \
1
// true if the types of C and B are identical
#define GB_CTYPE_IS_BTYPE \
1
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA,A_iso) \
GxB_FC64_t aij = GBX (Ax, pA, A_iso)
// bij = Bx [pB]
#define GB_GETB(bij,Bx,pB,B_iso) \
;
// declare scalar of the same type as C
#define GB_CTYPE_SCALAR(t) \
GxB_FC64_t t
// cij = Ax [pA]
#define GB_COPY_A_TO_C(cij,Ax,pA,A_iso) \
cij = GBX (Ax, pA, A_iso)
// cij = Bx [pB]
#define GB_COPY_B_TO_C(cij,Bx,pB,B_iso) \
cij = GBX (Bx, pB, B_iso)
#define GB_CX(p) Cx [p]
// binary operator
#define GB_BINOP(z,x,y,i,j) \
z = x ;
// true if the binop must be flipped
#define GB_BINOP_FLIP \
0
// op is second
#define GB_OP_IS_SECOND \
0
// do the numerical phases of GB_add and GB_emult
#define GB_PHASE_2_OF_2
// hard-coded loops can be vectorized
#define GB_PRAGMA_SIMD_VECTORIZE GB_PRAGMA_SIMD
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_FIRST || GxB_NO_FC64 || GxB_NO_FIRST_FC64)
//------------------------------------------------------------------------------
// C += A+B, all 3 matrices dense
//------------------------------------------------------------------------------
#if 0
// The op must be MIN, MAX, PLUS, MINUS, RMINUS, TIMES, DIV, or RDIV.
void GB ((none))
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix B,
const int nthreads
)
{
#include "GB_dense_ewise3_accum_template.c"
}
#endif
//------------------------------------------------------------------------------
// C = A+B, all 3 matrices dense
//------------------------------------------------------------------------------
GrB_Info GB (_Cdense_ewise3_noaccum__first_fc64)
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix B,
const int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_dense_ewise3_noaccum_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C += B, accumulate a sparse matrix into a dense matrix
//------------------------------------------------------------------------------
GrB_Info GB (_Cdense_accumB__first_fc64)
(
GrB_Matrix C,
const GrB_Matrix B,
const int64_t *B_ek_slicing, const int B_ntasks, const int B_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#if 0
{
#include "GB_dense_subassign_23_template.c"
}
#endif
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C += b, accumulate a scalar into a dense matrix
//------------------------------------------------------------------------------
GrB_Info GB (_Cdense_accumb__first_fc64)
(
GrB_Matrix C,
const GB_void *p_bwork,
const int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#if 0
{
// get the scalar b for C += b, of type GxB_FC64_t
GxB_FC64_t bwork = (*((GxB_FC64_t *) p_bwork)) ;
#include "GB_dense_subassign_22_template.c"
return (GrB_SUCCESS) ;
}
#endif
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = A*D, column scale with diagonal D matrix
//------------------------------------------------------------------------------
GrB_Info GB (_AxD__first_fc64)
(
GrB_Matrix C,
const GrB_Matrix A, bool A_is_pattern,
const GrB_Matrix D, bool D_is_pattern,
const int64_t *A_ek_slicing, const int A_ntasks, const int A_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
GxB_FC64_t *restrict Cx = (GxB_FC64_t *) C->x ;
#include "GB_AxB_colscale_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = D*B, row scale with diagonal D matrix
//------------------------------------------------------------------------------
GrB_Info GB (_DxB__first_fc64)
(
GrB_Matrix C,
const GrB_Matrix D, bool D_is_pattern,
const GrB_Matrix B, bool B_is_pattern,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
GxB_FC64_t *restrict Cx = (GxB_FC64_t *) C->x ;
#include "GB_AxB_rowscale_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseAdd: C = A+B or C<M> = A+B
//------------------------------------------------------------------------------
GrB_Info GB (_AaddB__first_fc64)
(
GrB_Matrix C,
const int C_sparsity,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const bool Ch_is_Mh,
const int64_t *restrict C_to_M,
const int64_t *restrict C_to_A,
const int64_t *restrict C_to_B,
const GB_task_struct *restrict TaskList,
const int C_ntasks,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
GB_WERK_DECLARE (M_ek_slicing, int64_t) ;
GB_WERK_DECLARE (A_ek_slicing, int64_t) ;
GB_WERK_DECLARE (B_ek_slicing, int64_t) ;
#include "GB_add_template.c"
GB_FREE_WORK ;
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C = A.*B or C<M> = A.*B
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_01__first_fc64)
(
GrB_Matrix C,
const int C_sparsity,
const int ewise_method,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *restrict C_to_M,
const int64_t *restrict C_to_A,
const int64_t *restrict C_to_B,
const GB_task_struct *restrict TaskList,
const int C_ntasks,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_emult_01_meta.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C<#> = A.*B when A is sparse/hyper and B is bitmap/full
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_02__first_fc64)
(
GrB_Matrix C,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const bool flipxy,
const int64_t *restrict Cp_kfirst,
const int64_t *A_ek_slicing, const int A_ntasks, const int A_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#if GB_BINOP_FLIP
// The operator is not commutative, and does not have a flipped
// variant. For example z=atan2(y,x).
if (flipxy)
{
// use fmult(y,x)
#undef GB_FLIPPED
#define GB_FLIPPED 1
#include "GB_emult_02_template.c"
}
else
{
// use fmult(x,y)
#undef GB_FLIPPED
#define GB_FLIPPED 0
#include "GB_emult_02_template.c"
}
#else
// No need to handle the flip: the operator is either commutative, or
// has been handled by changing z=div(y,x) to z=rdiv(x,y) for example.
#undef GB_FLIPPED
#define GB_FLIPPED 0
#include "GB_emult_02_template.c"
#endif
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C<M> = A.*B, M sparse/hyper, A and B bitmap/full
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_03__first_fc64)
(
GrB_Matrix C,
const GrB_Matrix M,
const bool Mask_struct,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *restrict Cp_kfirst,
const int64_t *M_ek_slicing, const int M_ntasks, const int M_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_emult_03_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C=A.*B, C<M>=A.*B, C<!M>=A.*B where C is bitmap
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_bitmap__first_fc64)
(
GrB_Matrix C,
const int ewise_method,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *M_ek_slicing, const int M_ntasks, const int M_nthreads,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_bitmap_emult_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (x,Bx): apply a binary operator to a matrix with scalar bind1st
//------------------------------------------------------------------------------
#if 0
GrB_Info GB ((none))
(
GB_void *Cx_output, // Cx and Bx may be aliased
const GB_void *x_input,
const GB_void *Bx_input,
const int8_t *restrict Bb,
int64_t bnz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
GxB_FC64_t *Cx = (GxB_FC64_t *) Cx_output ;
GxB_FC64_t x = (*((GxB_FC64_t *) x_input)) ;
GxB_FC64_t *Bx = (GxB_FC64_t *) Bx_input ;
int64_t p ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < bnz ; p++)
{
if (!GBB (Bb, p)) continue ;
; ;
Cx [p] = x ;
}
return (GrB_SUCCESS) ;
#endif
}
#endif
//------------------------------------------------------------------------------
// Cx = op (Ax,y): apply a binary operator to a matrix with scalar bind2nd
//------------------------------------------------------------------------------
#if 0
GrB_Info GB ((none))
(
GB_void *Cx_output, // Cx and Ax may be aliased
const GB_void *Ax_input,
const GB_void *y_input,
const int8_t *restrict Ab,
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t p ;
GxB_FC64_t *Cx = (GxB_FC64_t *) Cx_output ;
GxB_FC64_t *Ax = (GxB_FC64_t *) Ax_input ;
GxB_FC64_t y = (*((GxB_FC64_t *) y_input)) ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
if (!GBB (Ab, p)) continue ;
GxB_FC64_t aij = GBX (Ax, p, false) ;
Cx [p] = aij ;
}
return (GrB_SUCCESS) ;
#endif
}
#endif
//------------------------------------------------------------------------------
// C = op (x, A'): transpose and apply a binary operator
//------------------------------------------------------------------------------
#if 0
// cij = op (x, aij), no typecasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
; ; \
Cx [pC] = x ; \
}
GrB_Info GB ((none))
(
GrB_Matrix C,
const GB_void *x_input,
const GrB_Matrix A,
int64_t *restrict *Workspaces,
const int64_t *restrict A_slice,
int nworkspaces,
int nthreads
)
{
// GB_unop_transpose.c uses GB_ATYPE, but A is
// the 2nd input to binary operator z=f(x,y).
#undef GB_ATYPE
#define GB_ATYPE \
GxB_FC64_t
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
GxB_FC64_t x = (*((const GxB_FC64_t *) x_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
#undef GB_ATYPE
#define GB_ATYPE \
GxB_FC64_t
}
#endif
//------------------------------------------------------------------------------
// C = op (A', y): transpose and apply a binary operator
//------------------------------------------------------------------------------
#if 0
// cij = op (aij, y), no typecasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
GxB_FC64_t aij = GBX (Ax, pA, false) ; \
Cx [pC] = aij ; \
}
GrB_Info GB ((none))
(
GrB_Matrix C,
const GrB_Matrix A,
const GB_void *y_input,
int64_t *restrict *Workspaces,
const int64_t *restrict A_slice,
int nworkspaces,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
GxB_FC64_t y = (*((const GxB_FC64_t *) y_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
#endif
|
displacement_lagrangemultiplier_residual_contact_criteria.h | // KRATOS ___| | | |
// \___ \ __| __| | | __| __| | | __| _` | |
// | | | | | ( | | | | ( | |
// _____/ \__|_| \__,_|\___|\__|\__,_|_| \__,_|_| MECHANICS
//
// License: BSD License
// license: StructuralMechanicsApplication/license.txt
//
// Main authors: Vicente Mataix Ferrandiz
//
#if !defined(KRATOS_DISPLACEMENT_LAGRANGE_MULTIPLIER_RESIDUAL_CONTACT_CRITERIA_H)
#define KRATOS_DISPLACEMENT_LAGRANGE_MULTIPLIER_RESIDUAL_CONTACT_CRITERIA_H
/* System includes */
/* External includes */
/* Project includes */
#include "utilities/table_stream_utility.h"
#include "solving_strategies/convergencecriterias/convergence_criteria.h"
#include "utilities/color_utilities.h"
#include "utilities/constraint_utilities.h"
namespace Kratos
{
///@addtogroup ContactStructuralMechanicsApplication
///@{
///@name Kratos Globals
///@{
///@}
///@name Type Definitions
///@{
///@}
///@name Enum's
///@{
///@}
///@name Functions
///@{
///@name Kratos Classes
///@{
/**
* @class DisplacementLagrangeMultiplierResidualContactCriteria
* @ingroup ContactStructuralMechanicsApplication
* @brief Convergence criteria for contact problems
* This class implements a convergence control based on nodal displacement and
* lagrange multiplier values. The error is evaluated separately for each of them, and
* relative and absolute tolerances for both must be specified.
* @author Vicente Mataix Ferrandiz
*/
template< class TSparseSpace,
class TDenseSpace >
class DisplacementLagrangeMultiplierResidualContactCriteria
: public ConvergenceCriteria< TSparseSpace, TDenseSpace >
{
public:
///@name Type Definitions
///@{
/// Pointer definition of DisplacementLagrangeMultiplierResidualContactCriteria
KRATOS_CLASS_POINTER_DEFINITION( DisplacementLagrangeMultiplierResidualContactCriteria );
/// Local Flags
KRATOS_DEFINE_LOCAL_FLAG( ENSURE_CONTACT );
KRATOS_DEFINE_LOCAL_FLAG( PRINTING_OUTPUT );
KRATOS_DEFINE_LOCAL_FLAG( TABLE_IS_INITIALIZED );
KRATOS_DEFINE_LOCAL_FLAG( INITIAL_RESIDUAL_IS_SET );
/// The base class definition (and it subclasses)
typedef ConvergenceCriteria< TSparseSpace, TDenseSpace > BaseType;
typedef typename BaseType::TDataType TDataType;
typedef typename BaseType::DofsArrayType DofsArrayType;
typedef typename BaseType::TSystemMatrixType TSystemMatrixType;
typedef typename BaseType::TSystemVectorType TSystemVectorType;
/// The sparse space used
typedef TSparseSpace SparseSpaceType;
/// The r_table stream definition TODO: Replace by logger
typedef TableStreamUtility::Pointer TablePrinterPointerType;
/// The index type definition
typedef std::size_t IndexType;
/// The key type definition
typedef std::size_t KeyType;
///@}
///@name Life Cycle
///@{
/**
* @brief Default constructor (parameters)
* @param DispRatioTolerance Relative tolerance for displacement residual error
* @param DispAbsTolerance Absolute tolerance for displacement residual error
* @param LMRatioTolerance Relative tolerance for lagrange multiplier residual error
* @param LMAbsTolerance Absolute tolerance for lagrange multiplier residual error
* @param EnsureContact To check if the contact is lost
* @param pTable The pointer to the output r_table
* @param PrintingOutput If the output is going to be printed in a txt file
*/
explicit DisplacementLagrangeMultiplierResidualContactCriteria(
const TDataType DispRatioTolerance,
const TDataType DispAbsTolerance,
const TDataType LMRatioTolerance,
const TDataType LMAbsTolerance,
const bool EnsureContact = false,
const bool PrintingOutput = false
)
: BaseType()
{
// Set local flags
mOptions.Set(DisplacementLagrangeMultiplierResidualContactCriteria::ENSURE_CONTACT, EnsureContact);
mOptions.Set(DisplacementLagrangeMultiplierResidualContactCriteria::PRINTING_OUTPUT, PrintingOutput);
mOptions.Set(DisplacementLagrangeMultiplierResidualContactCriteria::TABLE_IS_INITIALIZED, false);
mOptions.Set(DisplacementLagrangeMultiplierResidualContactCriteria::INITIAL_RESIDUAL_IS_SET, false);
mDispRatioTolerance = DispRatioTolerance;
mDispAbsTolerance = DispAbsTolerance;
mLMRatioTolerance = LMRatioTolerance;
mLMAbsTolerance = LMAbsTolerance;
}
/**
* @brief Default constructor (parameters)
* @param ThisParameters The configuration parameters
*/
explicit DisplacementLagrangeMultiplierResidualContactCriteria( Parameters ThisParameters = Parameters(R"({})"))
: BaseType()
{
// The default parameters
Parameters default_parameters = Parameters(R"(
{
"ensure_contact" : false,
"print_convergence_criterion" : false,
"residual_relative_tolerance" : 1.0e-4,
"residual_absolute_tolerance" : 1.0e-9,
"contact_residual_relative_tolerance" : 1.0e-4,
"contact_residual_absolute_tolerance" : 1.0e-9
})" );
ThisParameters.ValidateAndAssignDefaults(default_parameters);
// The displacement residual
mDispRatioTolerance = ThisParameters["residual_relative_tolerance"].GetDouble();
mDispAbsTolerance = ThisParameters["residual_absolute_tolerance"].GetDouble();
// The contact residual
mLMRatioTolerance = ThisParameters["contact_displacement_absolute_tolerance"].GetDouble();
mLMAbsTolerance = ThisParameters["contact_residual_absolute_tolerance"].GetDouble();
// Set local flags
mOptions.Set(DisplacementLagrangeMultiplierResidualContactCriteria::ENSURE_CONTACT, ThisParameters["ensure_contact"].GetBool());
mOptions.Set(DisplacementLagrangeMultiplierResidualContactCriteria::PRINTING_OUTPUT, ThisParameters["print_convergence_criterion"].GetBool());
mOptions.Set(DisplacementLagrangeMultiplierResidualContactCriteria::TABLE_IS_INITIALIZED, false);
mOptions.Set(DisplacementLagrangeMultiplierResidualContactCriteria::INITIAL_RESIDUAL_IS_SET, false);
}
//* Copy constructor.
DisplacementLagrangeMultiplierResidualContactCriteria( DisplacementLagrangeMultiplierResidualContactCriteria const& rOther )
:BaseType(rOther)
,mOptions(rOther.mOptions)
,mDispRatioTolerance(rOther.mDispRatioTolerance)
,mDispAbsTolerance(rOther.mDispAbsTolerance)
,mDispInitialResidualNorm(rOther.mDispInitialResidualNorm)
,mDispCurrentResidualNorm(rOther.mDispCurrentResidualNorm)
,mLMRatioTolerance(rOther.mLMRatioTolerance)
,mLMAbsTolerance(rOther.mLMAbsTolerance)
,mLMInitialResidualNorm(rOther.mLMInitialResidualNorm)
,mLMCurrentResidualNorm(rOther.mLMCurrentResidualNorm)
{
}
/// Destructor.
~DisplacementLagrangeMultiplierResidualContactCriteria() override = default;
///@}
///@name Operators
///@{
/**
* @brief Compute relative and absolute error.
* @param rModelPart Reference to the ModelPart containing the contact problem.
* @param rDofSet Reference to the container of the problem's degrees of freedom (stored by the BuilderAndSolver)
* @param rA System matrix (unused)
* @param rDx Vector of results (variations on nodal variables)
* @param rb RHS vector (residual)
* @return true if convergence is achieved, false otherwise
*/
bool PostCriteria(
ModelPart& rModelPart,
DofsArrayType& rDofSet,
const TSystemMatrixType& rA,
const TSystemVectorType& rDx,
const TSystemVectorType& rb
) override
{
if (SparseSpaceType::Size(rb) != 0) { //if we are solving for something
// Initialize
TDataType disp_residual_solution_norm = 0.0, lm_residual_solution_norm = 0.0;
IndexType disp_dof_num(0),lm_dof_num(0);
// First iterator
const auto it_dof_begin = rDofSet.begin();
// Auxiliar values
std::size_t dof_id = 0;
TDataType residual_dof_value = 0.0;
// The number of active dofs
const std::size_t number_active_dofs = rb.size();
// Loop over Dofs
#pragma omp parallel for firstprivate(dof_id, residual_dof_value) reduction(+:disp_residual_solution_norm,lm_residual_solution_norm,disp_dof_num,lm_dof_num)
for (int i = 0; i < static_cast<int>(rDofSet.size()); i++) {
auto it_dof = it_dof_begin + i;
dof_id = it_dof->EquationId();
// Check dof id is solved
if (dof_id < number_active_dofs) {
if (mActiveDofs[dof_id] == 1) {
residual_dof_value = rb[dof_id];
const auto& r_curr_var = it_dof->GetVariable();
if ((r_curr_var == VECTOR_LAGRANGE_MULTIPLIER_X) || (r_curr_var == VECTOR_LAGRANGE_MULTIPLIER_Y) || (r_curr_var == VECTOR_LAGRANGE_MULTIPLIER_Z) || (r_curr_var == LAGRANGE_MULTIPLIER_CONTACT_PRESSURE)) {
lm_residual_solution_norm += residual_dof_value * residual_dof_value;
++lm_dof_num;
} else {
disp_residual_solution_norm += residual_dof_value * residual_dof_value;
++disp_dof_num;
}
}
}
}
mDispCurrentResidualNorm = disp_residual_solution_norm;
mLMCurrentResidualNorm = lm_residual_solution_norm;
TDataType residual_disp_ratio = 1.0;
TDataType residual_lm_ratio = 1.0;
// We initialize the solution
if (mOptions.IsNot(DisplacementLagrangeMultiplierResidualContactCriteria::INITIAL_RESIDUAL_IS_SET)) {
mDispInitialResidualNorm = (disp_residual_solution_norm == 0.0) ? 1.0 : disp_residual_solution_norm;
mLMInitialResidualNorm = (lm_residual_solution_norm == 0.0) ? 1.0 : lm_residual_solution_norm;
residual_disp_ratio = 1.0;
residual_lm_ratio = 1.0;
mOptions.Set(DisplacementLagrangeMultiplierResidualContactCriteria::INITIAL_RESIDUAL_IS_SET, true);
}
// We calculate the ratio of the displacements
residual_disp_ratio = mDispCurrentResidualNorm/mDispInitialResidualNorm;
// We calculate the ratio of the LM
residual_lm_ratio = mLMCurrentResidualNorm/mLMInitialResidualNorm;
KRATOS_ERROR_IF(mOptions.Is(DisplacementLagrangeMultiplierResidualContactCriteria::ENSURE_CONTACT) && residual_lm_ratio == 0.0) << "ERROR::CONTACT LOST::ARE YOU SURE YOU ARE SUPPOSED TO HAVE CONTACT?" << std::endl;
// We calculate the absolute norms
const TDataType residual_disp_abs = mDispCurrentResidualNorm/disp_dof_num;
const TDataType residual_lm_abs = mLMCurrentResidualNorm/lm_dof_num;
// The process info of the model part
ProcessInfo& r_process_info = rModelPart.GetProcessInfo();
// We print the results // TODO: Replace for the new log
if (rModelPart.GetCommunicator().MyPID() == 0 && this->GetEchoLevel() > 0) {
if (r_process_info.Has(TABLE_UTILITY)) {
std::cout.precision(4);
TablePrinterPointerType p_table = r_process_info[TABLE_UTILITY];
auto& Table = p_table->GetTable();
Table << residual_disp_ratio << mDispRatioTolerance << residual_disp_abs << mDispAbsTolerance << residual_lm_ratio << mLMRatioTolerance << residual_lm_abs << mLMAbsTolerance;
} else {
std::cout.precision(4);
if (mOptions.IsNot(DisplacementLagrangeMultiplierResidualContactCriteria::PRINTING_OUTPUT)) {
KRATOS_INFO("DisplacementLagrangeMultiplierResidualContactCriteria") << BOLDFONT("RESIDUAL CONVERGENCE CHECK") << "\tSTEP: " << r_process_info[STEP] << "\tNL ITERATION: " << r_process_info[NL_ITERATION_NUMBER] << std::endl << std::scientific;
KRATOS_INFO("DisplacementLagrangeMultiplierResidualContactCriteria") << BOLDFONT("\tDISPLACEMENT: RATIO = ") << residual_disp_ratio << BOLDFONT(" EXP.RATIO = ") << mDispRatioTolerance << BOLDFONT(" ABS = ") << residual_disp_abs << BOLDFONT(" EXP.ABS = ") << mDispAbsTolerance << std::endl;
KRATOS_INFO("DisplacementLagrangeMultiplierResidualContactCriteria") << BOLDFONT("\tLAGRANGE MUL: RATIO = ") << residual_lm_ratio << BOLDFONT(" EXP.RATIO = ") << mLMRatioTolerance << BOLDFONT(" ABS = ") << residual_lm_abs << BOLDFONT(" EXP.ABS = ") << mLMAbsTolerance << std::endl;
} else {
KRATOS_INFO("DisplacementLagrangeMultiplierResidualContactCriteria") << "RESIDUAL CONVERGENCE CHECK" << "\tSTEP: " << r_process_info[STEP] << "\tNL ITERATION: " << r_process_info[NL_ITERATION_NUMBER] << std::endl << std::scientific;
KRATOS_INFO("DisplacementLagrangeMultiplierResidualContactCriteria") << "\tDISPLACEMENT: RATIO = " << residual_disp_ratio << " EXP.RATIO = " << mDispRatioTolerance << " ABS = " << residual_disp_abs << " EXP.ABS = " << mDispAbsTolerance << std::endl;
KRATOS_INFO("DisplacementLagrangeMultiplierResidualContactCriteria") << "\tLAGRANGE MUL: RATIO = " << residual_lm_ratio << " EXP.RATIO = " << mLMRatioTolerance << " ABS = " << residual_lm_abs << " EXP.ABS = " << mLMAbsTolerance << std::endl;
}
}
}
r_process_info[CONVERGENCE_RATIO] = (residual_disp_ratio > residual_lm_ratio) ? residual_disp_ratio : residual_lm_ratio;
r_process_info[RESIDUAL_NORM] = (residual_lm_abs > mLMAbsTolerance) ? residual_lm_abs : mLMAbsTolerance;
// We check if converged
const bool disp_converged = (residual_disp_ratio <= mDispRatioTolerance || residual_disp_abs <= mDispAbsTolerance);
const bool lm_converged = (mOptions.IsNot(DisplacementLagrangeMultiplierResidualContactCriteria::ENSURE_CONTACT) && residual_lm_ratio == 0.0) ? true : (residual_lm_ratio <= mLMRatioTolerance || residual_lm_abs <= mLMAbsTolerance);
if (disp_converged && lm_converged ) {
if (rModelPart.GetCommunicator().MyPID() == 0 && this->GetEchoLevel() > 0) {
if (r_process_info.Has(TABLE_UTILITY)) {
TablePrinterPointerType p_table = r_process_info[TABLE_UTILITY];
auto& Table = p_table->GetTable();
if (mOptions.IsNot(DisplacementLagrangeMultiplierResidualContactCriteria::PRINTING_OUTPUT))
Table << BOLDFONT(FGRN(" Achieved"));
else
Table << "Achieved";
} else {
if (mOptions.IsNot(DisplacementLagrangeMultiplierResidualContactCriteria::PRINTING_OUTPUT))
KRATOS_INFO("DisplacementLagrangeMultiplierResidualContactCriteria") << BOLDFONT("\tResidual") << " convergence is " << BOLDFONT(FGRN("achieved")) << std::endl;
else
KRATOS_INFO("DisplacementLagrangeMultiplierResidualContactCriteria") << "\tResidual convergence is achieved" << std::endl;
}
}
return true;
} else {
if (rModelPart.GetCommunicator().MyPID() == 0 && this->GetEchoLevel() > 0) {
if (r_process_info.Has(TABLE_UTILITY)) {
TablePrinterPointerType p_table = r_process_info[TABLE_UTILITY];
auto& r_table = p_table->GetTable();
if (mOptions.IsNot(DisplacementLagrangeMultiplierResidualContactCriteria::PRINTING_OUTPUT))
r_table << BOLDFONT(FRED(" Not achieved"));
else
r_table << "Not achieved";
} else {
if (mOptions.IsNot(DisplacementLagrangeMultiplierResidualContactCriteria::PRINTING_OUTPUT))
KRATOS_INFO("DisplacementLagrangeMultiplierResidualContactCriteria") << BOLDFONT("\tResidual") << " convergence is " << BOLDFONT(FRED(" not achieved")) << std::endl;
else
KRATOS_INFO("DisplacementLagrangeMultiplierResidualContactCriteria") << "\tResidual convergence is not achieved" << std::endl;
}
}
return false;
}
} else // In this case all the displacements are imposed!
return true;
}
/**
* @brief This function initialize the convergence criteria
* @param rModelPart Reference to the ModelPart containing the contact problem. (unused)
*/
void Initialize( ModelPart& rModelPart) override
{
BaseType::mConvergenceCriteriaIsInitialized = true;
ProcessInfo& r_process_info = rModelPart.GetProcessInfo();
if (r_process_info.Has(TABLE_UTILITY) && mOptions.IsNot(DisplacementLagrangeMultiplierResidualContactCriteria::TABLE_IS_INITIALIZED)) {
TablePrinterPointerType p_table = r_process_info[TABLE_UTILITY];
auto& r_table = p_table->GetTable();
r_table.AddColumn("DP RATIO", 10);
r_table.AddColumn("EXP. RAT", 10);
r_table.AddColumn("ABS", 10);
r_table.AddColumn("EXP. ABS", 10);
r_table.AddColumn("LM RATIO", 10);
r_table.AddColumn("EXP. RAT", 10);
r_table.AddColumn("ABS", 10);
r_table.AddColumn("EXP. ABS", 10);
r_table.AddColumn("CONVERGENCE", 15);
mOptions.Set(DisplacementLagrangeMultiplierResidualContactCriteria::TABLE_IS_INITIALIZED, true);
}
}
/**
* @brief This function initializes the solution step
* @param rModelPart Reference to the ModelPart containing the contact problem.
* @param rDofSet Reference to the container of the problem's degrees of freedom (stored by the BuilderAndSolver)
* @param rA System matrix (unused)
* @param rDx Vector of results (variations on nodal variables)
* @param rb RHS vector (residual)
*/
void InitializeSolutionStep(
ModelPart& rModelPart,
DofsArrayType& rDofSet,
const TSystemMatrixType& rA,
const TSystemVectorType& rDx,
const TSystemVectorType& rb
) override
{
// Initialize flag
mOptions.Set(DisplacementLagrangeMultiplierResidualContactCriteria::INITIAL_RESIDUAL_IS_SET, false);
// Filling mActiveDofs when MPC exist
ConstraintUtilities::ComputeActiveDofs(rModelPart, mActiveDofs, rDofSet);
}
///@}
///@name Operations
///@{
///@}
///@name Acces
///@{
///@}
///@name Inquiry
///@{
///@}
///@name Friends
///@{
protected:
///@name Protected static Member Variables
///@{
///@}
///@name Protected member Variables
///@{
///@}
///@name Protected Operators
///@{
///@}
///@name Protected Operations
///@{
///@}
///@name Protected Access
///@{
///@}
///@name Protected Inquiry
///@{
///@}
///@name Protected LifeCycle
///@{
///@}
private:
///@name Static Member Variables
///@{
///@}
///@name Member Variables
///@{
Flags mOptions; /// Local flags
TDataType mDispRatioTolerance; /// The ratio threshold for the norm of the displacement residual
TDataType mDispAbsTolerance; /// The absolute value threshold for the norm of the displacement residual
TDataType mDispInitialResidualNorm; /// The reference norm of the displacement residual
TDataType mDispCurrentResidualNorm; /// The current norm of the displacement residual
TDataType mLMRatioTolerance; /// The ratio threshold for the norm of the LM residual
TDataType mLMAbsTolerance; /// The absolute value threshold for the norm of the LM residual
TDataType mLMInitialResidualNorm; /// The reference norm of the LM residual
TDataType mLMCurrentResidualNorm; /// The current norm of the LM residual
std::vector<int> mActiveDofs; /// This vector contains the dofs that are active
///@}
///@name Private Operators
///@{
///@}
///@name Private Operations
///@{
///@}
///@name Private Access
///@{
///@}
///@}
///@name Serialization
///@{
///@name Private Inquiry
///@{
///@}
///@name Unaccessible methods
///@{
///@}
}; // Kratos DisplacementLagrangeMultiplierResidualContactCriteria
///@name Local flags creation
///@{
/// Local Flags
template<class TSparseSpace, class TDenseSpace>
const Kratos::Flags DisplacementLagrangeMultiplierResidualContactCriteria<TSparseSpace, TDenseSpace>::ENSURE_CONTACT(Kratos::Flags::Create(0));
template<class TSparseSpace, class TDenseSpace>
const Kratos::Flags DisplacementLagrangeMultiplierResidualContactCriteria<TSparseSpace, TDenseSpace>::PRINTING_OUTPUT(Kratos::Flags::Create(1));
template<class TSparseSpace, class TDenseSpace>
const Kratos::Flags DisplacementLagrangeMultiplierResidualContactCriteria<TSparseSpace, TDenseSpace>::TABLE_IS_INITIALIZED(Kratos::Flags::Create(2));
template<class TSparseSpace, class TDenseSpace>
const Kratos::Flags DisplacementLagrangeMultiplierResidualContactCriteria<TSparseSpace, TDenseSpace>::INITIAL_RESIDUAL_IS_SET(Kratos::Flags::Create(3));
}
#endif /* KRATOS_DISPLACEMENT_LAGRANGE_MULTIPLIER_RESIDUAL_CONTACT_CRITERIA_H */
|
integrateFullOrbit.c | /*
Wrappers around the C integration code for Full Orbits
*/
#ifdef _WIN32
#include <Python.h>
#endif
#include <stdio.h>
#include <stdlib.h>
#include <stdbool.h>
#include <math.h>
#include <gsl/gsl_errno.h>
#include <gsl/gsl_spline.h>
#include <bovy_coords.h>
#include <bovy_symplecticode.h>
#include <leung_dop853.h>
#include <bovy_rk.h>
#include <integrateFullOrbit.h>
//Potentials
#include <galpy_potentials.h>
#ifndef M_PI
#define M_PI 3.14159265358979323846
#endif
#ifndef ORBITS_CHUNKSIZE
#define ORBITS_CHUNKSIZE 1
#endif
//Macros to export functions in DLL on different OS
#if defined(_WIN32)
#define EXPORT __declspec(dllexport)
#elif defined(__GNUC__)
#define EXPORT __attribute__((visibility("default")))
#else
// Just do nothing?
#define EXPORT
#endif
#ifdef _WIN32
// On Windows, *need* to define this function to allow the package to be imported
#if PY_MAJOR_VERSION >= 3
PyMODINIT_FUNC PyInit_libgalpy(void) { // Python 3
return NULL;
}
#else
PyMODINIT_FUNC initlibgalpy(void) {} // Python 2
#endif
#endif
/*
Function Declarations
*/
void evalRectForce(double, double *, double *,
int, struct potentialArg *);
void evalRectDeriv(double, double *, double *,
int, struct potentialArg *);
void evalRectDeriv_dxdv(double,double *, double *,
int, struct potentialArg *);
void initMovingObjectSplines(struct potentialArg *, double ** pot_args);
void initChandrasekharDynamicalFrictionSplines(struct potentialArg *, double ** pot_args);
/*
Actual functions
*/
void parse_leapFuncArgs_Full(int npot,
struct potentialArg * potentialArgs,
int ** pot_type,
double ** pot_args){
int ii,jj,kk;
int nR, nz, nr;
double * Rgrid, * zgrid, * potGrid_splinecoeffs;
init_potentialArgs(npot,potentialArgs);
for (ii=0; ii < npot; ii++){
switch ( *(*pot_type)++ ) {
case 0: //LogarithmicHaloPotential, 4 arguments
potentialArgs->potentialEval= &LogarithmicHaloPotentialEval;
potentialArgs->Rforce= &LogarithmicHaloPotentialRforce;
potentialArgs->zforce= &LogarithmicHaloPotentialzforce;
potentialArgs->phiforce= &LogarithmicHaloPotentialphiforce;
potentialArgs->dens= &LogarithmicHaloPotentialDens;
//potentialArgs->R2deriv= &LogarithmicHaloPotentialR2deriv;
//potentialArgs->planarphi2deriv= &ZeroForce;
//potentialArgs->planarRphideriv= &ZeroForce;
potentialArgs->nargs= 4;
potentialArgs->requiresVelocity= false;
break;
case 1: //DehnenBarPotential, 6 arguments
potentialArgs->Rforce= &DehnenBarPotentialRforce;
potentialArgs->phiforce= &DehnenBarPotentialphiforce;
potentialArgs->zforce= &DehnenBarPotentialzforce;
potentialArgs->nargs= 6;
potentialArgs->requiresVelocity= false;
break;
case 5: //MiyamotoNagaiPotential, 3 arguments
potentialArgs->potentialEval= &MiyamotoNagaiPotentialEval;
potentialArgs->Rforce= &MiyamotoNagaiPotentialRforce;
potentialArgs->zforce= &MiyamotoNagaiPotentialzforce;
potentialArgs->phiforce= &ZeroForce;
potentialArgs->dens= &MiyamotoNagaiPotentialDens;
//potentialArgs->R2deriv= &MiyamotoNagaiPotentialR2deriv;
//potentialArgs->planarphi2deriv= &ZeroForce;
//potentialArgs->planarRphideriv= &ZeroForce;
potentialArgs->nargs= 3;
potentialArgs->requiresVelocity= false;
break;
case 7: //PowerSphericalPotential, 2 arguments
potentialArgs->potentialEval= &PowerSphericalPotentialEval;
potentialArgs->Rforce= &PowerSphericalPotentialRforce;
potentialArgs->zforce= &PowerSphericalPotentialzforce;
potentialArgs->phiforce= &ZeroForce;
potentialArgs->dens= &PowerSphericalPotentialDens;
//potentialArgs->R2deriv= &PowerSphericalPotentialR2deriv;
//potentialArgs->planarphi2deriv= &ZeroForce;
//potentialArgs->planarRphideriv= &ZeroForce;
potentialArgs->nargs= 2;
potentialArgs->requiresVelocity= false;
break;
case 8: //HernquistPotential, 2 arguments
potentialArgs->potentialEval= &HernquistPotentialEval;
potentialArgs->Rforce= &HernquistPotentialRforce;
potentialArgs->zforce= &HernquistPotentialzforce;
potentialArgs->phiforce= &ZeroForce;
potentialArgs->dens= &HernquistPotentialDens;
//potentialArgs->R2deriv= &HernquistPotentialR2deriv;
//potentialArgs->planarphi2deriv= &ZeroForce;
//potentialArgs->planarRphideriv= &ZeroForce;
potentialArgs->nargs= 2;
potentialArgs->requiresVelocity= false;
break;
case 9: //NFWPotential, 2 arguments
potentialArgs->potentialEval= &NFWPotentialEval;
potentialArgs->Rforce= &NFWPotentialRforce;
potentialArgs->zforce= &NFWPotentialzforce;
potentialArgs->phiforce= &ZeroForce;
potentialArgs->dens= &NFWPotentialDens;
//potentialArgs->R2deriv= &NFWPotentialR2deriv;
//potentialArgs->planarphi2deriv= &ZeroForce;
//potentialArgs->planarRphideriv= &ZeroForce;
potentialArgs->nargs= 2;
potentialArgs->requiresVelocity= false;
break;
case 10: //JaffePotential, 2 arguments
potentialArgs->potentialEval= &JaffePotentialEval;
potentialArgs->Rforce= &JaffePotentialRforce;
potentialArgs->zforce= &JaffePotentialzforce;
potentialArgs->phiforce= &ZeroForce;
potentialArgs->dens= &JaffePotentialDens;
//potentialArgs->R2deriv= &JaffePotentialR2deriv;
//potentialArgs->planarphi2deriv= &ZeroForce;
//potentialArgs->planarRphideriv= &ZeroForce;
potentialArgs->nargs= 2;
potentialArgs->requiresVelocity= false;
break;
case 11: //DoubleExponentialDiskPotential, XX arguments
potentialArgs->potentialEval= &DoubleExponentialDiskPotentialEval;
potentialArgs->Rforce= &DoubleExponentialDiskPotentialRforce;
potentialArgs->zforce= &DoubleExponentialDiskPotentialzforce;
potentialArgs->phiforce= &ZeroForce;
potentialArgs->dens= &DoubleExponentialDiskPotentialDens;
//Look at pot_args to figure out the number of arguments
potentialArgs->nargs= (int) (5 + 4 * *(*pot_args+4) );
potentialArgs->requiresVelocity= false;
break;
case 12: //FlattenedPowerPotential, 4 arguments
potentialArgs->potentialEval= &FlattenedPowerPotentialEval;
potentialArgs->Rforce= &FlattenedPowerPotentialRforce;
potentialArgs->zforce= &FlattenedPowerPotentialzforce;
potentialArgs->phiforce= &ZeroForce;
potentialArgs->dens= &FlattenedPowerPotentialDens;
potentialArgs->nargs= 4;
potentialArgs->requiresVelocity= false;
break;
case 13: //interpRZPotential, XX arguments
//Grab the grids and the coefficients
nR= (int) *(*pot_args)++;
nz= (int) *(*pot_args)++;
Rgrid= (double *) malloc ( nR * sizeof ( double ) );
zgrid= (double *) malloc ( nz * sizeof ( double ) );
potGrid_splinecoeffs= (double *) malloc ( nR * nz * sizeof ( double ) );
for (kk=0; kk < nR; kk++)
*(Rgrid+kk)= *(*pot_args)++;
for (kk=0; kk < nz; kk++)
*(zgrid+kk)= *(*pot_args)++;
for (kk=0; kk < nR; kk++)
put_row(potGrid_splinecoeffs,kk,*pot_args+kk*nz,nz);
*pot_args+= nR*nz;
potentialArgs->i2d= interp_2d_alloc(nR,nz);
interp_2d_init(potentialArgs->i2d,Rgrid,zgrid,potGrid_splinecoeffs,
INTERP_2D_LINEAR); //latter bc we already calculated the coeffs
potentialArgs->accx= gsl_interp_accel_alloc ();
potentialArgs->accy= gsl_interp_accel_alloc ();
for (kk=0; kk < nR; kk++)
put_row(potGrid_splinecoeffs,kk,*pot_args+kk*nz,nz);
*pot_args+= nR*nz;
potentialArgs->i2drforce= interp_2d_alloc(nR,nz);
interp_2d_init(potentialArgs->i2drforce,Rgrid,zgrid,potGrid_splinecoeffs,
INTERP_2D_LINEAR); //latter bc we already calculated the coeffs
potentialArgs->accxrforce= gsl_interp_accel_alloc ();
potentialArgs->accyrforce= gsl_interp_accel_alloc ();
for (kk=0; kk < nR; kk++)
put_row(potGrid_splinecoeffs,kk,*pot_args+kk*nz,nz);
*pot_args+= nR*nz;
potentialArgs->i2dzforce= interp_2d_alloc(nR,nz);
interp_2d_init(potentialArgs->i2dzforce,Rgrid,zgrid,potGrid_splinecoeffs,
INTERP_2D_LINEAR); //latter bc we already calculated the coeffs
potentialArgs->accxzforce= gsl_interp_accel_alloc ();
potentialArgs->accyzforce= gsl_interp_accel_alloc ();
potentialArgs->potentialEval= &interpRZPotentialEval;
potentialArgs->Rforce= &interpRZPotentialRforce;
potentialArgs->zforce= &interpRZPotentialzforce;
potentialArgs->phiforce= &ZeroForce;
potentialArgs->nargs= 2;
//clean up
free(Rgrid);
free(zgrid);
free(potGrid_splinecoeffs);
potentialArgs->requiresVelocity= false;
break;
case 14: //IsochronePotential, 2 arguments
potentialArgs->potentialEval= &IsochronePotentialEval;
potentialArgs->Rforce= &IsochronePotentialRforce;
potentialArgs->zforce= &IsochronePotentialzforce;
potentialArgs->phiforce= &ZeroForce;
potentialArgs->dens= &IsochronePotentialDens;
potentialArgs->nargs= 2;
potentialArgs->requiresVelocity= false;
break;
case 15: //PowerSphericalwCutoffPotential, 3 arguments
potentialArgs->potentialEval= &PowerSphericalPotentialwCutoffEval;
potentialArgs->Rforce= &PowerSphericalPotentialwCutoffRforce;
potentialArgs->zforce= &PowerSphericalPotentialwCutoffzforce;
potentialArgs->phiforce= &ZeroForce;
potentialArgs->dens= &PowerSphericalPotentialwCutoffDens;
//potentialArgs->R2deriv= &PowerSphericalPotentialR2deriv;
//potentialArgs->planarphi2deriv= &ZeroForce;
//potentialArgs->planarRphideriv= &ZeroForce;
potentialArgs->nargs= 3;
potentialArgs->requiresVelocity= false;
break;
case 16: //KuzminKutuzovStaeckelPotential, 3 arguments
potentialArgs->potentialEval= &KuzminKutuzovStaeckelPotentialEval;
potentialArgs->Rforce= &KuzminKutuzovStaeckelPotentialRforce;
potentialArgs->zforce= &KuzminKutuzovStaeckelPotentialzforce;
potentialArgs->phiforce= &ZeroForce;
//potentialArgs->R2deriv= &KuzminKutuzovStaeckelPotentialR2deriv;
potentialArgs->nargs= 3;
potentialArgs->requiresVelocity= false;
break;
case 17: //PlummerPotential, 2 arguments
potentialArgs->potentialEval= &PlummerPotentialEval;
potentialArgs->Rforce= &PlummerPotentialRforce;
potentialArgs->zforce= &PlummerPotentialzforce;
potentialArgs->phiforce= &ZeroForce;
potentialArgs->dens= &PlummerPotentialDens;
//potentialArgs->R2deriv= &PlummerPotentialR2deriv;
potentialArgs->nargs= 2;
potentialArgs->requiresVelocity= false;
break;
case 18: //PseudoIsothermalPotential, 2 arguments
potentialArgs->potentialEval= &PseudoIsothermalPotentialEval;
potentialArgs->Rforce= &PseudoIsothermalPotentialRforce;
potentialArgs->zforce= &PseudoIsothermalPotentialzforce;
potentialArgs->phiforce= &ZeroForce;
potentialArgs->dens= &PseudoIsothermalPotentialDens;
//potentialArgs->R2deriv= &PseudoIsothermalPotentialR2deriv;
potentialArgs->nargs= 2;
potentialArgs->requiresVelocity= false;
break;
case 19: //KuzminDiskPotential, 2 arguments
potentialArgs->potentialEval= &KuzminDiskPotentialEval;
potentialArgs->Rforce= &KuzminDiskPotentialRforce;
potentialArgs->zforce= &KuzminDiskPotentialzforce;
potentialArgs->phiforce= &ZeroForce;
potentialArgs->nargs= 2;
potentialArgs->requiresVelocity= false;
break;
case 20: //BurkertPotential, 2 arguments
potentialArgs->potentialEval= &BurkertPotentialEval;
potentialArgs->Rforce= &BurkertPotentialRforce;
potentialArgs->zforce= &BurkertPotentialzforce;
potentialArgs->dens= &BurkertPotentialDens;
potentialArgs->phiforce= &ZeroForce;
potentialArgs->nargs= 2;
potentialArgs->requiresVelocity= false;
break;
case 21: //TriaxialHernquistPotential, lots of arguments
potentialArgs->potentialEval= &EllipsoidalPotentialEval;
potentialArgs->Rforce = &EllipsoidalPotentialRforce;
potentialArgs->zforce = &EllipsoidalPotentialzforce;
potentialArgs->phiforce = &EllipsoidalPotentialphiforce;
potentialArgs->dens= &EllipsoidalPotentialDens;
// Also assign functions specific to EllipsoidalPotential
potentialArgs->psi= &TriaxialHernquistPotentialpsi;
potentialArgs->mdens= &TriaxialHernquistPotentialmdens;
potentialArgs->mdensDeriv= &TriaxialHernquistPotentialmdensDeriv;
potentialArgs->nargs = (int) (21 + *(*pot_args+7) + 2 * *(*pot_args
+ (int) (*(*pot_args+7) + 20)));
potentialArgs->requiresVelocity= false;
break;
case 22: //TriaxialNFWPotential, lots of arguments
potentialArgs->potentialEval= &EllipsoidalPotentialEval;
potentialArgs->Rforce = &EllipsoidalPotentialRforce;
potentialArgs->zforce = &EllipsoidalPotentialzforce;
potentialArgs->phiforce = &EllipsoidalPotentialphiforce;
potentialArgs->dens= &EllipsoidalPotentialDens;
// Also assign functions specific to EllipsoidalPotential
potentialArgs->psi= &TriaxialNFWPotentialpsi;
potentialArgs->mdens= &TriaxialNFWPotentialmdens;
potentialArgs->mdensDeriv= &TriaxialNFWPotentialmdensDeriv;
potentialArgs->nargs = (int) (21 + *(*pot_args+7) + 2 * *(*pot_args
+ (int) (*(*pot_args+7) + 20)));
potentialArgs->requiresVelocity= false;
break;
case 23: //TriaxialJaffePotential, lots of arguments
potentialArgs->potentialEval= &EllipsoidalPotentialEval;
potentialArgs->Rforce = &EllipsoidalPotentialRforce;
potentialArgs->zforce = &EllipsoidalPotentialzforce;
potentialArgs->phiforce = &EllipsoidalPotentialphiforce;
potentialArgs->dens= &EllipsoidalPotentialDens;
// Also assign functions specific to EllipsoidalPotential
potentialArgs->psi= &TriaxialJaffePotentialpsi;
potentialArgs->mdens= &TriaxialJaffePotentialmdens;
potentialArgs->mdensDeriv= &TriaxialJaffePotentialmdensDeriv;
potentialArgs->nargs = (int) (21 + *(*pot_args+7) + 2 * *(*pot_args
+ (int) (*(*pot_args+7) + 20)));
potentialArgs->requiresVelocity= false;
break;
case 24: //SCFPotential, many arguments
potentialArgs->potentialEval= &SCFPotentialEval;
potentialArgs->Rforce= &SCFPotentialRforce;
potentialArgs->zforce= &SCFPotentialzforce;
potentialArgs->phiforce= &SCFPotentialphiforce;
potentialArgs->dens= &SCFPotentialDens;
potentialArgs->nargs= (int) (5 + (1 + *(*pot_args + 1)) * *(*pot_args+2) * *(*pot_args+3)* *(*pot_args+4) + 7);
potentialArgs->requiresVelocity= false;
break;
case 25: //SoftenedNeedleBarPotential, 13 arguments
potentialArgs->potentialEval= &SoftenedNeedleBarPotentialEval;
potentialArgs->Rforce= &SoftenedNeedleBarPotentialRforce;
potentialArgs->zforce= &SoftenedNeedleBarPotentialzforce;
potentialArgs->phiforce= &SoftenedNeedleBarPotentialphiforce;
potentialArgs->nargs= (int) 13;
potentialArgs->requiresVelocity= false;
break;
case 26: //DiskSCFPotential, nsigma+3 arguments
potentialArgs->potentialEval= &DiskSCFPotentialEval;
potentialArgs->Rforce= &DiskSCFPotentialRforce;
potentialArgs->zforce= &DiskSCFPotentialzforce;
potentialArgs->dens= &DiskSCFPotentialDens;
potentialArgs->phiforce= &ZeroForce;
potentialArgs->nargs= (int) **pot_args + 3;
potentialArgs->requiresVelocity= false;
break;
case 27: // SpiralArmsPotential, 10 arguments + array of Cs
potentialArgs->Rforce = &SpiralArmsPotentialRforce;
potentialArgs->zforce = &SpiralArmsPotentialzforce;
potentialArgs->phiforce = &SpiralArmsPotentialphiforce;
//potentialArgs->R2deriv = &SpiralArmsPotentialR2deriv;
//potentialArgs->z2deriv = &SpiralArmsPotentialz2deriv;
potentialArgs->phi2deriv = &SpiralArmsPotentialphi2deriv;
//potentialArgs->Rzderiv = &SpiralArmsPotentialRzderiv;
potentialArgs->Rphideriv = &SpiralArmsPotentialRphideriv;
potentialArgs->nargs = (int) 10 + **pot_args;
potentialArgs->requiresVelocity= false;
break;
case 30: // PerfectEllipsoidPotential, lots of arguments
potentialArgs->potentialEval= &EllipsoidalPotentialEval;
potentialArgs->Rforce = &EllipsoidalPotentialRforce;
potentialArgs->zforce = &EllipsoidalPotentialzforce;
potentialArgs->phiforce = &EllipsoidalPotentialphiforce;
potentialArgs->dens= &EllipsoidalPotentialDens;
//potentialArgs->R2deriv = &EllipsoidalPotentialR2deriv;
//potentialArgs->z2deriv = &EllipsoidalPotentialz2deriv;
//potentialArgs->phi2deriv = &EllipsoidalPotentialphi2deriv;
//potentialArgs->Rzderiv = &EllipsoidalPotentialRzderiv;
//potentialArgs->Rphideriv = &EllipsoidalPotentialRphideriv;
// Also assign functions specific to EllipsoidalPotential
potentialArgs->psi= &PerfectEllipsoidPotentialpsi;
potentialArgs->mdens= &PerfectEllipsoidPotentialmdens;
potentialArgs->mdensDeriv= &PerfectEllipsoidPotentialmdensDeriv;
potentialArgs->nargs = (int) (21 + *(*pot_args+7) + 2 * *(*pot_args
+ (int) (*(*pot_args+7) + 20)));
potentialArgs->requiresVelocity= false;
break;
// 31: KGPotential
// 32: IsothermalDiskPotential
case 33: //DehnenCoreSphericalPotential, 2 arguments
potentialArgs->potentialEval= &DehnenCoreSphericalPotentialEval;
potentialArgs->Rforce= &DehnenCoreSphericalPotentialRforce;
potentialArgs->zforce= &DehnenCoreSphericalPotentialzforce;
potentialArgs->phiforce= &ZeroForce;
potentialArgs->dens= &DehnenCoreSphericalPotentialDens;
//potentialArgs->R2deriv= &DehnenCoreSphericalPotentialR2deriv;
//potentialArgs->planarphi2deriv= &ZeroForce;
//potentialArgs->planarRphideriv= &ZeroForce;
potentialArgs->nargs= 2;
potentialArgs->requiresVelocity= false;
break;
case 34: //DehnenSphericalPotential, 3 arguments
potentialArgs->potentialEval= &DehnenSphericalPotentialEval;
potentialArgs->Rforce= &DehnenSphericalPotentialRforce;
potentialArgs->zforce= &DehnenSphericalPotentialzforce;
potentialArgs->phiforce= &ZeroForce;
potentialArgs->dens= &DehnenSphericalPotentialDens;
//potentialArgs->R2deriv= &DehnenSphericalPotentialR2deriv;
//potentialArgs->planarphi2deriv= &ZeroForce;
//potentialArgs->planarRphideriv= &ZeroForce;
potentialArgs->nargs= 3;
potentialArgs->requiresVelocity= false;
break;
case 35: //HomogeneousSpherePotential, 3 arguments
potentialArgs->potentialEval= &HomogeneousSpherePotentialEval;
potentialArgs->Rforce= &HomogeneousSpherePotentialRforce;
potentialArgs->zforce= &HomogeneousSpherePotentialzforce;
potentialArgs->phiforce= &ZeroForce;
potentialArgs->dens= &HomogeneousSpherePotentialDens;
potentialArgs->nargs= 3;
potentialArgs->requiresVelocity= false;
break;
case 36: //interpSphericalPotential, XX arguments
// Set up 1 spline in potentialArgs
potentialArgs->nspline1d= 1;
potentialArgs->spline1d= (gsl_spline **) \
malloc ( potentialArgs->nspline1d*sizeof ( gsl_spline *) );
potentialArgs->acc1d= (gsl_interp_accel **) \
malloc ( potentialArgs->nspline1d * sizeof ( gsl_interp_accel * ) );
// allocate accelerator
*potentialArgs->acc1d= gsl_interp_accel_alloc();
// Set up interpolater
nr= (int) **pot_args;
*potentialArgs->spline1d= gsl_spline_alloc(gsl_interp_cspline,nr);
gsl_spline_init(*potentialArgs->spline1d,*pot_args+1,*pot_args+1+nr,nr);
*pot_args+= 2*nr+1;
// Bind forces
potentialArgs->potentialEval= &SphericalPotentialEval;
potentialArgs->Rforce = &SphericalPotentialRforce;
potentialArgs->zforce = &SphericalPotentialzforce;
potentialArgs->phiforce= &ZeroForce;
potentialArgs->dens= &SphericalPotentialDens;
// Also assign functions specific to SphericalPotential
potentialArgs->revaluate= &interpSphericalPotentialrevaluate;
potentialArgs->rforce= &interpSphericalPotentialrforce;
potentialArgs->r2deriv= &interpSphericalPotentialr2deriv;
potentialArgs->rdens= &interpSphericalPotentialrdens;
potentialArgs->nargs = (int) 6;
potentialArgs->requiresVelocity= false;
break;
case 37: // TriaxialGaussianPotential, lots of arguments
potentialArgs->potentialEval= &EllipsoidalPotentialEval;
potentialArgs->Rforce = &EllipsoidalPotentialRforce;
potentialArgs->zforce = &EllipsoidalPotentialzforce;
potentialArgs->phiforce = &EllipsoidalPotentialphiforce;
potentialArgs->dens= &EllipsoidalPotentialDens;
//potentialArgs->R2deriv = &EllipsoidalPotentialR2deriv;
//potentialArgs->z2deriv = &EllipsoidalPotentialz2deriv;
//potentialArgs->phi2deriv = &EllipsoidalPotentialphi2deriv;
//potentialArgs->Rzderiv = &EllipsoidalPotentialRzderiv;
//potentialArgs->Rphideriv = &EllipsoidalPotentialRphideriv;
// Also assign functions specific to EllipsoidalPotential
potentialArgs->psi= &TriaxialGaussianPotentialpsi;
potentialArgs->mdens= &TriaxialGaussianPotentialmdens;
potentialArgs->mdensDeriv= &TriaxialGaussianPotentialmdensDeriv;
potentialArgs->nargs = (int) (21 + *(*pot_args+7) + 2 * *(*pot_args
+ (int) (*(*pot_args+7) + 20)));
potentialArgs->requiresVelocity= false;
break;
//////////////////////////////// WRAPPERS /////////////////////////////////////
case -1: //DehnenSmoothWrapperPotential
potentialArgs->potentialEval= &DehnenSmoothWrapperPotentialEval;
potentialArgs->Rforce= &DehnenSmoothWrapperPotentialRforce;
potentialArgs->zforce= &DehnenSmoothWrapperPotentialzforce;
potentialArgs->phiforce= &DehnenSmoothWrapperPotentialphiforce;
potentialArgs->nargs= (int) 4;
potentialArgs->requiresVelocity= false;
break;
case -2: //SolidBodyRotationWrapperPotential
potentialArgs->Rforce= &SolidBodyRotationWrapperPotentialRforce;
potentialArgs->zforce= &SolidBodyRotationWrapperPotentialzforce;
potentialArgs->phiforce= &SolidBodyRotationWrapperPotentialphiforce;
potentialArgs->nargs= (int) 3;
potentialArgs->requiresVelocity= false;
break;
case -4: //CorotatingRotationWrapperPotential
potentialArgs->Rforce= &CorotatingRotationWrapperPotentialRforce;
potentialArgs->zforce= &CorotatingRotationWrapperPotentialzforce;
potentialArgs->phiforce= &CorotatingRotationWrapperPotentialphiforce;
potentialArgs->nargs= (int) 5;
potentialArgs->requiresVelocity= false;
break;
case -5: //GaussianAmplitudeWrapperPotential
potentialArgs->potentialEval= &GaussianAmplitudeWrapperPotentialEval;
potentialArgs->Rforce= &GaussianAmplitudeWrapperPotentialRforce;
potentialArgs->zforce= &GaussianAmplitudeWrapperPotentialzforce;
potentialArgs->phiforce= &GaussianAmplitudeWrapperPotentialphiforce;
potentialArgs->nargs= (int) 3;
potentialArgs->requiresVelocity= false;
break;
case -6: //MovingObjectPotential
potentialArgs->Rforce= &MovingObjectPotentialRforce;
potentialArgs->zforce= &MovingObjectPotentialzforce;
potentialArgs->phiforce= &MovingObjectPotentialphiforce;
potentialArgs->nargs= (int) 3;
potentialArgs->requiresVelocity= false;
break;
case -7: //ChandrasekharDynamicalFrictionForce
potentialArgs->RforceVelocity= &ChandrasekharDynamicalFrictionForceRforce;
potentialArgs->zforceVelocity= &ChandrasekharDynamicalFrictionForcezforce;
potentialArgs->phiforceVelocity= &ChandrasekharDynamicalFrictionForcephiforce;
potentialArgs->nargs= (int) 16;
potentialArgs->requiresVelocity= true;
break;
}
int setupMovingObjectSplines = *(*pot_type-1) == -6 ? 1 : 0;
int setupChandrasekharDynamicalFrictionSplines = *(*pot_type-1) == -7 ? 1 : 0;
if ( *(*pot_type-1) < 0 ) { // Parse wrapped potential for wrappers
potentialArgs->nwrapped= (int) *(*pot_args)++;
potentialArgs->wrappedPotentialArg= \
(struct potentialArg *) malloc ( potentialArgs->nwrapped \
* sizeof (struct potentialArg) );
parse_leapFuncArgs_Full(potentialArgs->nwrapped,
potentialArgs->wrappedPotentialArg,
pot_type,pot_args);
}
if (setupMovingObjectSplines)
initMovingObjectSplines(potentialArgs, pot_args);
if (setupChandrasekharDynamicalFrictionSplines)
initChandrasekharDynamicalFrictionSplines(potentialArgs,pot_args);
potentialArgs->args= (double *) malloc( potentialArgs->nargs * sizeof(double));
for (jj=0; jj < potentialArgs->nargs; jj++){
*(potentialArgs->args)= *(*pot_args)++;
potentialArgs->args++;
}
potentialArgs->args-= potentialArgs->nargs;
potentialArgs++;
}
potentialArgs-= npot;
}
EXPORT void integrateFullOrbit(int nobj,
double *yo,
int nt,
double *t,
int npot,
int * pot_type,
double * pot_args,
double dt,
double rtol,
double atol,
double *result,
int * err,
int odeint_type){
//Set up the forces, first count
int ii,jj;
int dim;
int max_threads;
int * thread_pot_type;
double * thread_pot_args;
max_threads= ( nobj < omp_get_max_threads() ) ? nobj : omp_get_max_threads();
// Because potentialArgs may cache, safest to have one / thread
struct potentialArg * potentialArgs= (struct potentialArg *) malloc ( max_threads * npot * sizeof (struct potentialArg) );
#pragma omp parallel for schedule(static,1) private(ii,thread_pot_type,thread_pot_args) num_threads(max_threads)
for (ii=0; ii < max_threads; ii++) {
thread_pot_type= pot_type; // need to make thread-private pointers, bc
thread_pot_args= pot_args; // these pointers are changed in parse_...
parse_leapFuncArgs_Full(npot,potentialArgs+ii*npot,
&thread_pot_type,&thread_pot_args);
}
//Integrate
void (*odeint_func)(void (*func)(double, double *, double *,
int, struct potentialArg *),
int,
double *,
int, double, double *,
int, struct potentialArg *,
double, double,
double *,int *);
void (*odeint_deriv_func)(double, double *, double *,
int,struct potentialArg *);
switch ( odeint_type ) {
case 0: //leapfrog
odeint_func= &leapfrog;
odeint_deriv_func= &evalRectForce;
dim= 3;
break;
case 1: //RK4
odeint_func= &bovy_rk4;
odeint_deriv_func= &evalRectDeriv;
dim= 6;
break;
case 2: //RK6
odeint_func= &bovy_rk6;
odeint_deriv_func= &evalRectDeriv;
dim= 6;
break;
case 3: //symplec4
odeint_func= &symplec4;
odeint_deriv_func= &evalRectForce;
dim= 3;
break;
case 4: //symplec6
odeint_func= &symplec6;
odeint_deriv_func= &evalRectForce;
dim= 3;
break;
case 5: //DOPR54
odeint_func= &bovy_dopr54;
odeint_deriv_func= &evalRectDeriv;
dim= 6;
break;
case 6: //DOP853
odeint_func= &dop853;
odeint_deriv_func= &evalRectDeriv;
dim= 6;
break;
}
#pragma omp parallel for schedule(dynamic,ORBITS_CHUNKSIZE) private(ii,jj) num_threads(max_threads)
for (ii=0; ii < nobj; ii++) {
cyl_to_rect_galpy(yo+6*ii);
odeint_func(odeint_deriv_func,dim,yo+6*ii,nt,dt,t,
npot,potentialArgs+omp_get_thread_num()*npot,rtol,atol,
result+6*nt*ii,err+ii);
for (jj=0; jj < nt; jj++)
rect_to_cyl_galpy(result+6*jj+6*nt*ii);
}
//Free allocated memory
#pragma omp parallel for schedule(static,1) private(ii) num_threads(max_threads)
for (ii=0; ii < max_threads; ii++)
free_potentialArgs(npot,potentialArgs+ii*npot);
free(potentialArgs);
//Done!
}
// LCOV_EXCL_START
void integrateOrbit_dxdv(double *yo,
int nt,
double *t,
int npot,
int * pot_type,
double * pot_args,
double rtol,
double atol,
double *result,
int * err,
int odeint_type){
//Set up the forces, first count
int dim;
struct potentialArg * potentialArgs= (struct potentialArg *) malloc ( npot * sizeof (struct potentialArg) );
parse_leapFuncArgs_Full(npot,potentialArgs,&pot_type,&pot_args);
//Integrate
void (*odeint_func)(void (*func)(double, double *, double *,
int, struct potentialArg *),
int,
double *,
int, double, double *,
int, struct potentialArg *,
double, double,
double *,int *);
void (*odeint_deriv_func)(double, double *, double *,
int,struct potentialArg *);
switch ( odeint_type ) {
case 0: //leapfrog
odeint_func= &leapfrog;
odeint_deriv_func= &evalRectForce;
dim= 6;
break;
case 1: //RK4
odeint_func= &bovy_rk4;
odeint_deriv_func= &evalRectDeriv_dxdv;
dim= 12;
break;
case 2: //RK6
odeint_func= &bovy_rk6;
odeint_deriv_func= &evalRectDeriv_dxdv;
dim= 12;
break;
case 3: //symplec4
odeint_func= &symplec4;
odeint_deriv_func= &evalRectForce;
dim= 6;
break;
case 4: //symplec6
odeint_func= &symplec6;
odeint_deriv_func= &evalRectForce;
dim= 6;
break;
case 5: //DOPR54
odeint_func= &bovy_dopr54;
odeint_deriv_func= &evalRectDeriv_dxdv;
dim= 12;
break;
case 6: //DOP853
odeint_func= &dop853;
odeint_deriv_func= &evalRectDeriv_dxdv;
dim= 12;
break;
}
odeint_func(odeint_deriv_func,dim,yo,nt,-9999.99,t,npot,potentialArgs,
rtol,atol,result,err);
//Free allocated memory
free_potentialArgs(npot,potentialArgs);
free(potentialArgs);
//Done!
}
// LCOV_EXCL_STOP
void evalRectForce(double t, double *q, double *a,
int nargs, struct potentialArg * potentialArgs){
double sinphi, cosphi, x, y, phi,R,Rforce,phiforce, z, zforce;
//q is rectangular so calculate R and phi
x= *q;
y= *(q+1);
z= *(q+2);
R= sqrt(x*x+y*y);
phi= acos(x/R);
sinphi= y/R;
cosphi= x/R;
if ( y < 0. ) phi= 2.*M_PI-phi;
//Calculate the forces
Rforce= calcRforce(R,z,phi,t,nargs,potentialArgs);
zforce= calczforce(R,z,phi,t,nargs,potentialArgs);
phiforce= calcPhiforce(R,z,phi,t,nargs,potentialArgs);
*a++= cosphi*Rforce-1./R*sinphi*phiforce;
*a++= sinphi*Rforce+1./R*cosphi*phiforce;
*a= zforce;
}
void evalRectDeriv(double t, double *q, double *a,
int nargs, struct potentialArg * potentialArgs){
double sinphi, cosphi, x, y, phi,R,Rforce,phiforce,z,zforce,vR,vT;
//first three derivatives are just the velocities
*a++= *(q+3);
*a++= *(q+4);
*a++= *(q+5);
//Rest is force
//q is rectangular so calculate R and phi, vR and vT (for dissipative)
x= *q;
y= *(q+1);
z= *(q+2);
R= sqrt(x*x+y*y);
phi= acos(x/R);
sinphi= y/R;
cosphi= x/R;
if ( y < 0. ) phi= 2.*M_PI-phi;
vR= *(q+3) * cosphi + *(q+4) * sinphi;
vT= -*(q+3) * sinphi + *(q+4) * cosphi;
//Calculate the forces
Rforce= calcRforce(R,z,phi,t,nargs,potentialArgs,vR,vT,*(q+5));
zforce= calczforce(R,z,phi,t,nargs,potentialArgs,vR,vT,*(q+5));
phiforce= calcPhiforce(R,z,phi,t,nargs,potentialArgs,vR,vT,*(q+5));
*a++= cosphi*Rforce-1./R*sinphi*phiforce;
*a++= sinphi*Rforce+1./R*cosphi*phiforce;
*a= zforce;
}
void initMovingObjectSplines(struct potentialArg * potentialArgs,
double ** pot_args){
gsl_interp_accel *x_accel_ptr = gsl_interp_accel_alloc();
gsl_interp_accel *y_accel_ptr = gsl_interp_accel_alloc();
gsl_interp_accel *z_accel_ptr = gsl_interp_accel_alloc();
int nPts = (int) **pot_args;
gsl_spline *x_spline = gsl_spline_alloc(gsl_interp_cspline, nPts);
gsl_spline *y_spline = gsl_spline_alloc(gsl_interp_cspline, nPts);
gsl_spline *z_spline = gsl_spline_alloc(gsl_interp_cspline, nPts);
double * t_arr = *pot_args+1;
double * x_arr = t_arr+1*nPts;
double * y_arr = t_arr+2*nPts;
double * z_arr = t_arr+3*nPts;
double * t= (double *) malloc ( nPts * sizeof (double) );
double tf = *(t_arr+4*nPts+2);
double to = *(t_arr+4*nPts+1);
int ii;
for (ii=0; ii < nPts; ii++)
*(t+ii) = (t_arr[ii]-to)/(tf-to);
gsl_spline_init(x_spline, t, x_arr, nPts);
gsl_spline_init(y_spline, t, y_arr, nPts);
gsl_spline_init(z_spline, t, z_arr, nPts);
potentialArgs->nspline1d= 3;
potentialArgs->spline1d= (gsl_spline **) malloc ( 3*sizeof ( gsl_spline *) );
potentialArgs->acc1d= (gsl_interp_accel **) \
malloc ( 3 * sizeof ( gsl_interp_accel * ) );
*potentialArgs->spline1d = x_spline;
*potentialArgs->acc1d = x_accel_ptr;
*(potentialArgs->spline1d+1)= y_spline;
*(potentialArgs->acc1d+1)= y_accel_ptr;
*(potentialArgs->spline1d+2)= z_spline;
*(potentialArgs->acc1d+2)= z_accel_ptr;
*pot_args = *pot_args + (int) (1+4*nPts);
free(t);
}
void initChandrasekharDynamicalFrictionSplines(struct potentialArg * potentialArgs,
double ** pot_args){
gsl_interp_accel *sr_accel_ptr = gsl_interp_accel_alloc();
int nPts = (int) **pot_args;
gsl_spline *sr_spline = gsl_spline_alloc(gsl_interp_cspline,nPts);
double * r_arr = *pot_args+1;
double * sr_arr = r_arr+1*nPts;
double * r= (double *) malloc ( nPts * sizeof (double) );
double ro = *(r_arr+2*nPts+14);
double rf = *(r_arr+2*nPts+15);
int ii;
for (ii=0; ii < nPts; ii++)
*(r+ii) = (r_arr[ii]-ro)/(rf-ro);
gsl_spline_init(sr_spline,r,sr_arr,nPts);
potentialArgs->nspline1d= 1;
potentialArgs->spline1d= (gsl_spline **) \
malloc ( potentialArgs->nspline1d*sizeof ( gsl_spline *) );
potentialArgs->acc1d= (gsl_interp_accel **) \
malloc ( potentialArgs->nspline1d * sizeof ( gsl_interp_accel * ) );
*potentialArgs->spline1d = sr_spline;
*potentialArgs->acc1d = sr_accel_ptr;
*pot_args = *pot_args + (int) (1+(1+potentialArgs->nspline1d)*nPts);
free(r);
}
// LCOV_EXCL_START
void evalRectDeriv_dxdv(double t, double *q, double *a,
int nargs, struct potentialArg * potentialArgs){
double sinphi, cosphi, x, y, phi,R,Rforce,phiforce,z,zforce;
double R2deriv, phi2deriv, Rphideriv, dFxdx, dFxdy, dFydx, dFydy;
//first three derivatives are just the velocities
*a++= *(q+3);
*a++= *(q+4);
*a++= *(q+5);
//Rest is force
//q is rectangular so calculate R and phi
x= *q;
y= *(q+1);
z= *(q+2);
R= sqrt(x*x+y*y);
phi= acos(x/R);
sinphi= y/R;
cosphi= x/R;
if ( y < 0. ) phi= 2.*M_PI-phi;
//Calculate the forces
Rforce= calcRforce(R,z,phi,t,nargs,potentialArgs);
zforce= calczforce(R,z,phi,t,nargs,potentialArgs);
phiforce= calcPhiforce(R,z,phi,t,nargs,potentialArgs);
*a++= cosphi*Rforce-1./R*sinphi*phiforce;
*a++= sinphi*Rforce+1./R*cosphi*phiforce;
*a++= zforce;
//dx derivatives are just dv
*a++= *(q+9);
*a++= *(q+10);
*a++= *(q+11);
//for the dv derivatives we need also R2deriv, phi2deriv, and Rphideriv
R2deriv= calcR2deriv(R,z,phi,t,nargs,potentialArgs);
phi2deriv= calcphi2deriv(R,z,phi,t,nargs,potentialArgs);
Rphideriv= calcRphideriv(R,z,phi,t,nargs,potentialArgs);
//..and dFxdx, dFxdy, dFydx, dFydy
dFxdx= -cosphi*cosphi*R2deriv
+2.*cosphi*sinphi/R/R*phiforce
+sinphi*sinphi/R*Rforce
+2.*sinphi*cosphi/R*Rphideriv
-sinphi*sinphi/R/R*phi2deriv;
dFxdy= -sinphi*cosphi*R2deriv
+(sinphi*sinphi-cosphi*cosphi)/R/R*phiforce
-cosphi*sinphi/R*Rforce
-(cosphi*cosphi-sinphi*sinphi)/R*Rphideriv
+cosphi*sinphi/R/R*phi2deriv;
dFydx= -cosphi*sinphi*R2deriv
+(sinphi*sinphi-cosphi*cosphi)/R/R*phiforce
+(sinphi*sinphi-cosphi*cosphi)/R*Rphideriv
-sinphi*cosphi/R*Rforce
+sinphi*cosphi/R/R*phi2deriv;
dFydy= -sinphi*sinphi*R2deriv
-2.*sinphi*cosphi/R/R*phiforce
-2.*sinphi*cosphi/R*Rphideriv
+cosphi*cosphi/R*Rforce
-cosphi*cosphi/R/R*phi2deriv;
*a++= dFxdx * *(q+4) + dFxdy * *(q+5);
*a++= dFydx * *(q+4) + dFydy * *(q+5);
*a= 0; //BOVY: PUT IN Z2DERIVS
}
// LCOV_EXCL_STOP
|
two_step_v_p_strategy.h | //
// Project Name: KratosPFEMFluidDynamicsApplication $
// Last modified by: $Author: AFranci $
// Date: $Date: January 2016 $
// Revision: $Revision: 0.0 $
//
//
#ifndef KRATOS_TWO_STEP_V_P_STRATEGY_H
#define KRATOS_TWO_STEP_V_P_STRATEGY_H
#include "includes/define.h"
#include "includes/model_part.h"
#include "includes/deprecated_variables.h"
#include "includes/cfd_variables.h"
#include "utilities/openmp_utils.h"
#include "processes/process.h"
#include "solving_strategies/schemes/scheme.h"
#include "solving_strategies/strategies/implicit_solving_strategy.h"
#include "custom_utilities/mesher_utilities.hpp"
#include "custom_utilities/boundary_normals_calculation_utilities.hpp"
#include "solving_strategies/schemes/residualbased_incrementalupdate_static_scheme.h"
#include "solving_strategies/builder_and_solvers/residualbased_elimination_builder_and_solver.h"
#include "solving_strategies/builder_and_solvers/residualbased_elimination_builder_and_solver_componentwise.h"
#include "solving_strategies/builder_and_solvers/residualbased_block_builder_and_solver.h"
#include "custom_utilities/solver_settings.h"
#include "custom_strategies/strategies/gauss_seidel_linear_strategy.h"
#include "pfem_fluid_dynamics_application_variables.h"
#include "v_p_strategy.h"
#include <stdio.h>
#include <math.h>
namespace Kratos
{
///@addtogroup PFEMFluidDynamicsApplication
///@{
///@name Kratos Globals
///@{
///@}
///@name Type Definitions
///@{
///@}
///@name Enum's
///@{
///@}
///@name Functions
///@{
///@}
///@name Kratos Classes
///@{
template <class TSparseSpace,
class TDenseSpace,
class TLinearSolver>
class TwoStepVPStrategy : public VPStrategy<TSparseSpace, TDenseSpace, TLinearSolver>
{
public:
///@name Type Definitions
///@{
KRATOS_CLASS_POINTER_DEFINITION(TwoStepVPStrategy);
typedef VPStrategy<TSparseSpace, TDenseSpace, TLinearSolver> BaseType;
typedef typename BaseType::TDataType TDataType;
typedef typename BaseType::DofsArrayType DofsArrayType;
typedef typename BaseType::TSystemMatrixType TSystemMatrixType;
typedef typename BaseType::TSystemVectorType TSystemVectorType;
typedef typename BaseType::LocalSystemVectorType LocalSystemVectorType;
typedef typename BaseType::LocalSystemMatrixType LocalSystemMatrixType;
typedef typename ImplicitSolvingStrategy<TSparseSpace, TDenseSpace, TLinearSolver>::Pointer StrategyPointerType;
typedef TwoStepVPSolverSettings<TSparseSpace, TDenseSpace, TLinearSolver> SolverSettingsType;
///@}
///@name Life Cycle
///@{
TwoStepVPStrategy(ModelPart &rModelPart,
typename TLinearSolver::Pointer pVelocityLinearSolver,
typename TLinearSolver::Pointer pPressureLinearSolver,
bool ReformDofSet = true,
double VelTol = 0.0001,
double PresTol = 0.0001,
int MaxPressureIterations = 1, // Only for predictor-corrector
unsigned int TimeOrder = 2,
unsigned int DomainSize = 2) : BaseType(rModelPart, pVelocityLinearSolver, pPressureLinearSolver, ReformDofSet, DomainSize),
mVelocityTolerance(VelTol),
mPressureTolerance(PresTol),
mMaxPressureIter(MaxPressureIterations),
mDomainSize(DomainSize),
mTimeOrder(TimeOrder),
mReformDofSet(ReformDofSet)
{
KRATOS_TRY;
BaseType::SetEchoLevel(1);
// Check that input parameters are reasonable and sufficient.
this->Check();
bool CalculateNormDxFlag = true;
bool ReformDofAtEachIteration = false; // DofSet modifiaction is managed by the fractional step strategy, auxiliary strategies should not modify the DofSet directly.
// Additional Typedefs
typedef typename BuilderAndSolver<TSparseSpace, TDenseSpace, TLinearSolver>::Pointer BuilderSolverTypePointer;
typedef ImplicitSolvingStrategy<TSparseSpace, TDenseSpace, TLinearSolver> BaseType;
//initializing fractional velocity solution step
typedef Scheme<TSparseSpace, TDenseSpace> SchemeType;
typename SchemeType::Pointer pScheme;
typename SchemeType::Pointer Temp = typename SchemeType::Pointer(new ResidualBasedIncrementalUpdateStaticScheme<TSparseSpace, TDenseSpace>());
pScheme.swap(Temp);
//CONSTRUCTION OF VELOCITY
BuilderSolverTypePointer vel_build = BuilderSolverTypePointer(new ResidualBasedEliminationBuilderAndSolver<TSparseSpace, TDenseSpace, TLinearSolver>(pVelocityLinearSolver));
/* BuilderSolverTypePointer vel_build = BuilderSolverTypePointer(new ResidualBasedBlockBuilderAndSolver<TSparseSpace, TDenseSpace, TLinearSolver > (pVelocityLinearSolver)); */
this->mpMomentumStrategy = typename BaseType::Pointer(new GaussSeidelLinearStrategy<TSparseSpace, TDenseSpace, TLinearSolver>(rModelPart, pScheme, pVelocityLinearSolver, vel_build, ReformDofAtEachIteration, CalculateNormDxFlag));
vel_build->SetCalculateReactionsFlag(false);
/* BuilderSolverTypePointer pressure_build = BuilderSolverTypePointer(new ResidualBasedEliminationBuilderAndSolverComponentwise<TSparseSpace, TDenseSpace, TLinearSolver, Variable<double> >(pPressureLinearSolver, PRESSURE)); */
BuilderSolverTypePointer pressure_build = BuilderSolverTypePointer(new ResidualBasedBlockBuilderAndSolver<TSparseSpace, TDenseSpace, TLinearSolver>(pPressureLinearSolver));
this->mpPressureStrategy = typename BaseType::Pointer(new GaussSeidelLinearStrategy<TSparseSpace, TDenseSpace, TLinearSolver>(rModelPart, pScheme, pPressureLinearSolver, pressure_build, ReformDofAtEachIteration, CalculateNormDxFlag));
pressure_build->SetCalculateReactionsFlag(false);
KRATOS_CATCH("");
}
/// Destructor.
virtual ~TwoStepVPStrategy() {}
int Check() override
{
KRATOS_TRY;
// Check elements and conditions in the model part
int ierr = BaseType::Check();
if (ierr != 0)
return ierr;
if (DELTA_TIME.Key() == 0)
KRATOS_THROW_ERROR(std::runtime_error, "DELTA_TIME Key is 0. Check that the application was correctly registered.", "");
ModelPart &rModelPart = BaseType::GetModelPart();
const auto &r_current_process_info = rModelPart.GetProcessInfo();
for (const auto &r_element : rModelPart.Elements())
{
ierr = r_element.Check(r_current_process_info);
if (ierr != 0)
{
break;
}
}
return ierr;
KRATOS_CATCH("");
}
void SetTimeCoefficients(ProcessInfo &rCurrentProcessInfo)
{
KRATOS_TRY;
if (mTimeOrder == 2)
{
//calculate the BDF coefficients
double Dt = rCurrentProcessInfo[DELTA_TIME];
double OldDt = rCurrentProcessInfo.GetPreviousTimeStepInfo(1)[DELTA_TIME];
double Rho = OldDt / Dt;
double TimeCoeff = 1.0 / (Dt * Rho * Rho + Dt * Rho);
Vector &BDFcoeffs = rCurrentProcessInfo[BDF_COEFFICIENTS];
BDFcoeffs.resize(3, false);
BDFcoeffs[0] = TimeCoeff * (Rho * Rho + 2.0 * Rho); //coefficient for step n+1 (3/2Dt if Dt is constant)
BDFcoeffs[1] = -TimeCoeff * (Rho * Rho + 2.0 * Rho + 1.0); //coefficient for step n (-4/2Dt if Dt is constant)
BDFcoeffs[2] = TimeCoeff; //coefficient for step n-1 (1/2Dt if Dt is constant)
}
else if (mTimeOrder == 1)
{
double Dt = rCurrentProcessInfo[DELTA_TIME];
double TimeCoeff = 1.0 / Dt;
Vector &BDFcoeffs = rCurrentProcessInfo[BDF_COEFFICIENTS];
BDFcoeffs.resize(2, false);
BDFcoeffs[0] = TimeCoeff; //coefficient for step n+1 (1/Dt)
BDFcoeffs[1] = -TimeCoeff; //coefficient for step n (-1/Dt)
}
KRATOS_CATCH("");
}
bool SolveSolutionStep() override
{
ModelPart &rModelPart = BaseType::GetModelPart();
ProcessInfo &rCurrentProcessInfo = rModelPart.GetProcessInfo();
double currentTime = rCurrentProcessInfo[TIME];
double timeInterval = rCurrentProcessInfo[DELTA_TIME];
bool timeIntervalChanged = rCurrentProcessInfo[TIME_INTERVAL_CHANGED];
unsigned int stepsWithChangedDt = rCurrentProcessInfo[STEPS_WITH_CHANGED_DT];
bool converged = false;
unsigned int maxNonLinearIterations = mMaxPressureIter;
KRATOS_INFO("\nSolution with two_step_vp_strategy at t=") << currentTime << "s" << std::endl;
if ((timeIntervalChanged == true && currentTime > 10 * timeInterval) || stepsWithChangedDt > 0)
{
maxNonLinearIterations *= 2;
}
if (currentTime < 10 * timeInterval)
{
if (BaseType::GetEchoLevel() > 1)
std::cout << "within the first 10 time steps, I consider the given iteration number x3" << std::endl;
maxNonLinearIterations *= 3;
}
if (currentTime < 20 * timeInterval && currentTime >= 10 * timeInterval)
{
if (BaseType::GetEchoLevel() > 1)
std::cout << "within the second 10 time steps, I consider the given iteration number x2" << std::endl;
maxNonLinearIterations *= 2;
}
bool momentumConverged = true;
bool continuityConverged = false;
bool fixedTimeStep = false;
double pressureNorm = 0;
double velocityNorm = 0;
this->SetBlockedAndIsolatedFlags();
for (unsigned int it = 0; it < maxNonLinearIterations; ++it)
{
momentumConverged = this->SolveMomentumIteration(it, maxNonLinearIterations, fixedTimeStep, velocityNorm);
this->UpdateTopology(rModelPart, BaseType::GetEchoLevel());
if (fixedTimeStep == false)
{
continuityConverged = this->SolveContinuityIteration(it, maxNonLinearIterations, pressureNorm);
}
if (it == maxNonLinearIterations - 1 || ((continuityConverged && momentumConverged) && it > 2))
{
//double tensilStressSign = 1.0;
// ComputeErrorL2Norm(tensilStressSign);
this->UpdateStressStrain();
}
if ((continuityConverged && momentumConverged) && it > 2)
{
rCurrentProcessInfo.SetValue(BAD_VELOCITY_CONVERGENCE, false);
rCurrentProcessInfo.SetValue(BAD_PRESSURE_CONVERGENCE, false);
converged = true;
KRATOS_INFO("TwoStepVPStrategy") << "V-P strategy converged in " << it + 1 << " iterations." << std::endl;
break;
}
if (fixedTimeStep == true)
{
break;
}
}
if (!continuityConverged && !momentumConverged && BaseType::GetEchoLevel() > 0 && rModelPart.GetCommunicator().MyPID() == 0)
std::cout << "Convergence tolerance not reached." << std::endl;
if (mReformDofSet)
this->Clear();
return converged;
}
void FinalizeSolutionStep() override
{
}
void InitializeSolutionStep() override
{
}
void UpdateStressStrain() override
{
ModelPart &rModelPart = BaseType::GetModelPart();
const ProcessInfo &rCurrentProcessInfo = rModelPart.GetProcessInfo();
#pragma omp parallel
{
ModelPart::ElementIterator ElemBegin;
ModelPart::ElementIterator ElemEnd;
OpenMPUtils::PartitionedIterators(rModelPart.Elements(), ElemBegin, ElemEnd);
for (ModelPart::ElementIterator itElem = ElemBegin; itElem != ElemEnd; ++itElem)
{
/* itElem-> InitializeElementStrainStressState(); */
itElem->InitializeSolutionStep(rCurrentProcessInfo);
}
}
this->CalculateTemporalVariables();
}
void Clear() override
{
mpMomentumStrategy->Clear();
mpPressureStrategy->Clear();
}
///@}
///@name Access
///@{
void SetEchoLevel(int Level) override
{
BaseType::SetEchoLevel(Level);
int StrategyLevel = Level > 0 ? Level - 1 : 0;
mpMomentumStrategy->SetEchoLevel(StrategyLevel);
mpPressureStrategy->SetEchoLevel(StrategyLevel);
}
///@}
///@name Inquiry
///@{
///@}
///@name Input and output
///@{
/// Turn back information as a string.
std::string Info() const override
{
std::stringstream buffer;
buffer << "TwoStepVPStrategy";
return buffer.str();
}
/// Print information about this object.
void PrintInfo(std::ostream &rOStream) const override
{
rOStream << "TwoStepVPStrategy";
}
/// Print object's data.
void PrintData(std::ostream &rOStream) const override
{
}
///@}
///@name Friends
///@{
///@}
protected:
///@name Protected Life Cycle
///@{
///@}
///@name Protected static Member Variables
///@{
///@}
///@name Protected member Variables
///@{
///@}
///@name Protected Operators
///@{
///@}
///@name Protected Operations
///@{
/// Calculate the coefficients for time iteration.
/**
* @param rCurrentProcessInfo ProcessInfo instance from the fluid ModelPart. Must contain DELTA_TIME variables.
*/
bool SolveMomentumIteration(unsigned int it, unsigned int maxIt, bool &fixedTimeStep, double &velocityNorm) override
{
ModelPart &rModelPart = BaseType::GetModelPart();
int Rank = rModelPart.GetCommunicator().MyPID();
bool ConvergedMomentum = false;
double NormDv = 0;
fixedTimeStep = false;
// build momentum system and solve for fractional step velocity increment
rModelPart.GetProcessInfo().SetValue(FRACTIONAL_STEP, 1);
if (it == 0)
{
mpMomentumStrategy->InitializeSolutionStep();
}
NormDv = mpMomentumStrategy->Solve();
if (BaseType::GetEchoLevel() > 1 && Rank == 0)
std::cout << "-------------- s o l v e d ! ------------------" << std::endl;
if (it == 0)
{
velocityNorm = this->ComputeVelocityNorm();
}
double DvErrorNorm = NormDv / velocityNorm;
unsigned int iterationForCheck = 2;
// Check convergence
if (it == maxIt - 1)
{
KRATOS_INFO("Iteration") << it << " Final Velocity error: " << DvErrorNorm << std::endl;
ConvergedMomentum = this->FixTimeStepMomentum(DvErrorNorm, fixedTimeStep);
}
else if (it > iterationForCheck)
{
KRATOS_INFO("Iteration") << it << " Velocity error: " << DvErrorNorm << std::endl;
ConvergedMomentum = this->CheckMomentumConvergence(DvErrorNorm, fixedTimeStep);
}
else
{
KRATOS_INFO("Iteration") << it << " Velocity error: " << DvErrorNorm << std::endl;
}
if (!ConvergedMomentum && BaseType::GetEchoLevel() > 0 && Rank == 0)
std::cout << "Momentum equations did not reach the convergence tolerance." << std::endl;
return ConvergedMomentum;
}
bool SolveContinuityIteration(unsigned int it, unsigned int maxIt, double &NormP) override
{
ModelPart &rModelPart = BaseType::GetModelPart();
int Rank = rModelPart.GetCommunicator().MyPID();
bool ConvergedContinuity = false;
bool fixedTimeStep = false;
double NormDp = 0;
// 2. Pressure solution
rModelPart.GetProcessInfo().SetValue(FRACTIONAL_STEP, 5);
if (it == 0)
{
mpPressureStrategy->InitializeSolutionStep();
}
NormDp = mpPressureStrategy->Solve();
if (BaseType::GetEchoLevel() > 0 && Rank == 0)
std::cout << "The norm of pressure is: " << NormDp << std::endl;
if (it == 0)
{
NormP = this->ComputePressureNorm();
}
double DpErrorNorm = NormDp / (NormP);
// Check convergence
if (it == (maxIt - 1))
{
KRATOS_INFO("Iteration") << it << " Final Pressure error: " << DpErrorNorm << std::endl;
ConvergedContinuity = this->FixTimeStepContinuity(DpErrorNorm, fixedTimeStep);
}
else
{
KRATOS_INFO("Iteration") << it << " Pressure error: " << DpErrorNorm << std::endl;
ConvergedContinuity = this->CheckContinuityConvergence(DpErrorNorm, fixedTimeStep);
}
if (!ConvergedContinuity && BaseType::GetEchoLevel() > 0 && Rank == 0)
std::cout << "Continuity equation did not reach the convergence tolerance." << std::endl;
return ConvergedContinuity;
}
bool CheckVelocityConvergence(const double NormDv, double &errorNormDv) override
{
ModelPart &rModelPart = BaseType::GetModelPart();
const int n_nodes = rModelPart.NumberOfNodes();
double NormV = 0.00;
errorNormDv = 0;
#pragma omp parallel for reduction(+ \
: NormV)
for (int i_node = 0; i_node < n_nodes; ++i_node)
{
const auto it_node = rModelPart.NodesBegin() + i_node;
const auto &r_vel = it_node->FastGetSolutionStepValue(VELOCITY);
for (unsigned int d = 0; d < 3; ++d)
{
NormV += r_vel[d] * r_vel[d];
}
}
NormV = BaseType::GetModelPart().GetCommunicator().GetDataCommunicator().SumAll(NormV);
NormV = sqrt(NormV);
const double zero_tol = 1.0e-12;
errorNormDv = (NormV < zero_tol) ? NormDv : NormDv / NormV;
if (BaseType::GetEchoLevel() > 0 && rModelPart.GetCommunicator().MyPID() == 0)
{
std::cout << "The norm of velocity increment is: " << NormDv << std::endl;
std::cout << "The norm of velocity is: " << NormV << std::endl;
std::cout << "Velocity error: " << errorNormDv << "mVelocityTolerance: " << mVelocityTolerance << std::endl;
}
if (errorNormDv < mVelocityTolerance)
{
return true;
}
else
{
return false;
}
}
bool CheckPressureConvergence(const double NormDp, double &errorNormDp, double &NormP) override
{
ModelPart &rModelPart = BaseType::GetModelPart();
const int n_nodes = rModelPart.NumberOfNodes();
NormP = 0.00;
errorNormDp = 0;
double tmp_NormP = 0.0;
#pragma omp parallel for reduction(+ : tmp_NormP)
for (int i_node = 0; i_node < n_nodes; ++i_node)
{
const auto it_node = rModelPart.NodesBegin() + i_node;
const double Pr = it_node->FastGetSolutionStepValue(PRESSURE);
tmp_NormP += Pr * Pr;
}
NormP = tmp_NormP;
NormP = BaseType::GetModelPart().GetCommunicator().GetDataCommunicator().SumAll(NormP);
NormP = sqrt(NormP);
const double zero_tol = 1.0e-12;
errorNormDp = (NormP < zero_tol) ? NormDp : NormDp / NormP;
if (BaseType::GetEchoLevel() > 0 && rModelPart.GetCommunicator().MyPID() == 0)
{
std::cout << " The norm of pressure increment is: " << NormDp << std::endl;
std::cout << " The norm of pressure is: " << NormP << std::endl;
std::cout << " Pressure error: " << errorNormDp << std::endl;
}
if (errorNormDp < mPressureTolerance)
{
return true;
}
else
return false;
}
bool FixTimeStepMomentum(const double DvErrorNorm, bool &fixedTimeStep) override
{
ModelPart &rModelPart = BaseType::GetModelPart();
ProcessInfo &rCurrentProcessInfo = rModelPart.GetProcessInfo();
double currentTime = rCurrentProcessInfo[TIME];
double timeInterval = rCurrentProcessInfo[DELTA_TIME];
double minTolerance = 0.005;
bool converged = false;
if (currentTime < 10 * timeInterval)
{
minTolerance = 10;
}
if ((DvErrorNorm > minTolerance || (DvErrorNorm < 0 && DvErrorNorm > 0) || (DvErrorNorm != DvErrorNorm)) &&
DvErrorNorm != 0 &&
(DvErrorNorm != 1 || currentTime > timeInterval))
{
rCurrentProcessInfo.SetValue(BAD_VELOCITY_CONVERGENCE, true);
std::cout << "NOT GOOD CONVERGENCE!!! I'll reduce the next time interval" << DvErrorNorm << std::endl;
minTolerance = 0.05;
if (DvErrorNorm > minTolerance)
{
std::cout << "BAD CONVERGENCE!!! I GO AHEAD WITH THE PREVIOUS VELOCITY AND PRESSURE FIELDS" << DvErrorNorm << std::endl;
fixedTimeStep = true;
#pragma omp parallel
{
ModelPart::NodeIterator NodeBegin;
ModelPart::NodeIterator NodeEnd;
OpenMPUtils::PartitionedIterators(rModelPart.Nodes(), NodeBegin, NodeEnd);
for (ModelPart::NodeIterator itNode = NodeBegin; itNode != NodeEnd; ++itNode)
{
itNode->FastGetSolutionStepValue(VELOCITY, 0) = itNode->FastGetSolutionStepValue(VELOCITY, 1);
itNode->FastGetSolutionStepValue(PRESSURE, 0) = itNode->FastGetSolutionStepValue(PRESSURE, 1);
itNode->FastGetSolutionStepValue(ACCELERATION, 0) = itNode->FastGetSolutionStepValue(ACCELERATION, 1);
}
}
}
}
else
{
rCurrentProcessInfo.SetValue(BAD_VELOCITY_CONVERGENCE, false);
if (DvErrorNorm < mVelocityTolerance)
{
converged = true;
}
}
return converged;
}
bool CheckMomentumConvergence(const double DvErrorNorm, bool &fixedTimeStep) override
{
ModelPart &rModelPart = BaseType::GetModelPart();
ProcessInfo &rCurrentProcessInfo = rModelPart.GetProcessInfo();
double currentTime = rCurrentProcessInfo[TIME];
double timeInterval = rCurrentProcessInfo[DELTA_TIME];
double minTolerance = 0.99999;
bool converged = false;
if ((DvErrorNorm > minTolerance || (DvErrorNorm < 0 && DvErrorNorm > 0) || (DvErrorNorm != DvErrorNorm)) &&
DvErrorNorm != 0 &&
(DvErrorNorm != 1 || currentTime > timeInterval))
{
rCurrentProcessInfo.SetValue(BAD_VELOCITY_CONVERGENCE, true);
std::cout << " BAD CONVERGENCE DETECTED DURING THE ITERATIVE LOOP!!! error: " << DvErrorNorm << " higher than 0.9999" << std::endl;
std::cout << " I GO AHEAD WITH THE PREVIOUS VELOCITY AND PRESSURE FIELDS" << std::endl;
fixedTimeStep = true;
#pragma omp parallel
{
ModelPart::NodeIterator NodeBegin;
ModelPart::NodeIterator NodeEnd;
OpenMPUtils::PartitionedIterators(rModelPart.Nodes(), NodeBegin, NodeEnd);
for (ModelPart::NodeIterator itNode = NodeBegin; itNode != NodeEnd; ++itNode)
{
itNode->FastGetSolutionStepValue(VELOCITY, 0) = itNode->FastGetSolutionStepValue(VELOCITY, 1);
itNode->FastGetSolutionStepValue(PRESSURE, 0) = itNode->FastGetSolutionStepValue(PRESSURE, 1);
itNode->FastGetSolutionStepValue(ACCELERATION, 0) = itNode->FastGetSolutionStepValue(ACCELERATION, 1);
}
}
}
else
{
rCurrentProcessInfo.SetValue(BAD_VELOCITY_CONVERGENCE, false);
if (DvErrorNorm < mVelocityTolerance)
{
converged = true;
}
}
return converged;
}
bool FixTimeStepContinuity(const double DvErrorNorm, bool &fixedTimeStep) override
{
ModelPart &rModelPart = BaseType::GetModelPart();
ProcessInfo &rCurrentProcessInfo = rModelPart.GetProcessInfo();
double currentTime = rCurrentProcessInfo[TIME];
double timeInterval = rCurrentProcessInfo[DELTA_TIME];
double minTolerance = 0.01;
bool converged = false;
if (currentTime < 10 * timeInterval)
{
minTolerance = 10;
}
if ((DvErrorNorm > minTolerance || (DvErrorNorm < 0 && DvErrorNorm > 0) || (DvErrorNorm != DvErrorNorm)) &&
DvErrorNorm != 0 &&
(DvErrorNorm != 1 || currentTime > timeInterval))
{
fixedTimeStep = true;
// rCurrentProcessInfo.SetValue(BAD_PRESSURE_CONVERGENCE, true);
if (DvErrorNorm > 0.9999)
{
rCurrentProcessInfo.SetValue(BAD_VELOCITY_CONVERGENCE, true);
std::cout << " BAD PRESSURE CONVERGENCE DETECTED DURING THE ITERATIVE LOOP!!! error: " << DvErrorNorm << " higher than 0.1" << std::endl;
std::cout << " I GO AHEAD WITH THE PREVIOUS VELOCITY AND PRESSURE FIELDS" << std::endl;
fixedTimeStep = true;
#pragma omp parallel
{
ModelPart::NodeIterator NodeBegin;
ModelPart::NodeIterator NodeEnd;
OpenMPUtils::PartitionedIterators(rModelPart.Nodes(), NodeBegin, NodeEnd);
for (ModelPart::NodeIterator itNode = NodeBegin; itNode != NodeEnd; ++itNode)
{
itNode->FastGetSolutionStepValue(VELOCITY, 0) = itNode->FastGetSolutionStepValue(VELOCITY, 1);
itNode->FastGetSolutionStepValue(PRESSURE, 0) = itNode->FastGetSolutionStepValue(PRESSURE, 1);
itNode->FastGetSolutionStepValue(ACCELERATION, 0) = itNode->FastGetSolutionStepValue(ACCELERATION, 1);
}
}
}
}
else if (DvErrorNorm < mPressureTolerance)
{
converged = true;
fixedTimeStep = false;
}
rCurrentProcessInfo.SetValue(BAD_PRESSURE_CONVERGENCE, false);
return converged;
}
bool CheckContinuityConvergence(const double DvErrorNorm, bool &fixedTimeStep) override
{
ModelPart &rModelPart = BaseType::GetModelPart();
ProcessInfo &rCurrentProcessInfo = rModelPart.GetProcessInfo();
bool converged = false;
if (DvErrorNorm < mPressureTolerance)
{
converged = true;
fixedTimeStep = false;
}
rCurrentProcessInfo.SetValue(BAD_PRESSURE_CONVERGENCE, false);
return converged;
}
///@}
///@name Protected Access
///@{
///@}
///@name Protected Inquiry
///@{
///@}
///@name Protected LifeCycle
///@{
///@}
///@name Static Member Variables
///@{
///@}
///@name Member Variables
///@{
double mVelocityTolerance;
double mPressureTolerance;
unsigned int mMaxPressureIter;
unsigned int mDomainSize;
unsigned int mTimeOrder;
bool mReformDofSet;
// Fractional step index.
/* 1 : Momentum step (calculate fractional step velocity)
* 2-3 : Unused (reserved for componentwise calculation of frac step velocity)
* 4 : Pressure step
* 5 : Computation of projections
* 6 : End of step velocity
*/
// unsigned int mStepId;
/// Scheme for the solution of the momentum equation
StrategyPointerType mpMomentumStrategy;
/// Scheme for the solution of the mass equation
StrategyPointerType mpPressureStrategy;
///@}
///@name Private Operators
///@{
///@}
///@name Private Operations
///@{
///@}
///@name Private Access
///@{
///@}
///@name Private Inquiry
///@{
///@}
///@name Un accessible methods
///@{
/// Assignment operator.
TwoStepVPStrategy &operator=(TwoStepVPStrategy const &rOther) {}
/// Copy constructor.
TwoStepVPStrategy(TwoStepVPStrategy const &rOther) {}
///@}
}; /// Class TwoStepVPStrategy
///@}
///@name Type Definitions
///@{
///@}
///@} // addtogroup
} // namespace Kratos.
#endif // KRATOS_TWO_STEP_V_P_STRATEGY_H
|
GB_unop__identity_bool_fc64.c | //------------------------------------------------------------------------------
// GB_unop: hard-coded functions for each built-in unary operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2020, All Rights Reserved.
// http://suitesparse.com See GraphBLAS/Doc/License.txt for license.
//------------------------------------------------------------------------------
// If this file is in the Generated/ folder, do not edit it (auto-generated).
#include "GB.h"
#ifndef GBCOMPACT
#include "GB_control.h"
#include "GB_unop__include.h"
// C=unop(A) is defined by the following types and operators:
// op(A) function: GB_unop_apply__identity_bool_fc64
// op(A') function: GB_unop_tran__identity_bool_fc64
// C type: bool
// A type: GxB_FC64_t
// cast: bool cij = (creal (aij) != 0) || (cimag (aij) != 0)
// unaryop: cij = aij
#define GB_ATYPE \
GxB_FC64_t
#define GB_CTYPE \
bool
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA) \
GxB_FC64_t aij = Ax [pA]
#define GB_CX(p) Cx [p]
// unary operator
#define GB_OP(z, x) \
z = x ;
// casting
#define GB_CAST(z, aij) \
bool z = (creal (aij) != 0) || (cimag (aij) != 0) ;
// cij = op (aij)
#define GB_CAST_OP(pC,pA) \
{ \
/* aij = Ax [pA] */ \
GxB_FC64_t aij = Ax [pA] ; \
/* Cx [pC] = op (cast (aij)) */ \
bool z = (creal (aij) != 0) || (cimag (aij) != 0) ; \
Cx [pC] = z ; \
}
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_IDENTITY || GxB_NO_BOOL || GxB_NO_FC64)
//------------------------------------------------------------------------------
// Cx = op (cast (Ax)): apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_unop_apply__identity_bool_fc64
(
bool *Cx, // Cx and Ax may be aliased
const GxB_FC64_t *Ax,
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t p ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
GxB_FC64_t aij = Ax [p] ;
bool z = (creal (aij) != 0) || (cimag (aij) != 0) ;
Cx [p] = z ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (cast (A')): transpose, typecast, and apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_unop_tran__identity_bool_fc64
(
GrB_Matrix C,
const GrB_Matrix A,
int64_t *GB_RESTRICT *Rowcounts,
GBI_single_iterator Iter,
const int64_t *GB_RESTRICT A_slice,
int naslice
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#define GB_PHASE_2_OF_2
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
omp_smithW.c | /*********************************************************************************
* Smith–Waterman algorithm
* Purpose: Local alignment of nucleotide or protein sequences
* Authors: Daniel Holanda, Hanoch Griner, Taynara Pinheiro
* Compilation: gcc omp_smithW.c -o omp_smithW -fopenmp -DDEBUG
* Execution: ./omp_smithW <number_of_threads> <number_of_col> <number_of_rows>
*********************************************************************************/
#include <stdio.h>
#include <stdlib.h>
#include <math.h>
#include <omp.h>
#include <time.h>
/*--------------------------------------------------------------------
* Text Tweaks
*/
#define RESET "\033[0m"
#define BOLDRED "\033[1m\033[31m" /* Bold Red */
/* End of text tweaks */
/*--------------------------------------------------------------------
* Constants
*/
#define PATH -1
#define NONE 0
#define UP 1
#define LEFT 2
#define DIAGONAL 3
/* End of constants */
/*--------------------------------------------------------------------
* Helpers
*/
#define min(x, y) (((x) < (y)) ? (x) : (y))
#define max(a,b) ((a) > (b) ? a : b)
// #define DEBUG
/* End of Helpers */
/*--------------------------------------------------------------------
* Functions Prototypes
*/
void similarityScore(long long int i, long long int j, int* H, int* P, long long int* maxPos);
int matchMissmatchScore(long long int i, long long int j);
void backtrack(int* P, long long int maxPos);
void printMatrix(int* matrix);
void printPredecessorMatrix(int* matrix);
void generate(void);
long long int nElement(long long int i);
void calcFirstDiagElement(long long int *i, long long int *si, long long int *sj);
/* End of prototypes */
/*--------------------------------------------------------------------
* Global Variables
*/
//Defines size of strings to be compared
long long int m ; //Columns - Size of string a
long long int n ; //Lines - Size of string b
//Defines scores
int matchScore = 5;
int missmatchScore = -3;
int gapScore = -4;
//Strings over the Alphabet Sigma
char *a, *b;
/* End of global variables */
/*--------------------------------------------------------------------
* Function: main
*/
int main(int argc, char* argv[]) {
int thread_count = strtol(argv[1], NULL, 10);
m = strtoll(argv[2], NULL, 10);
n = strtoll(argv[3], NULL, 10);
#ifdef DEBUG
printf("\nMatrix[%lld][%lld]\n", n, m);
#endif
//Allocates a and b
a = malloc(m * sizeof(char));
b = malloc(n * sizeof(char));
//Because now we have zeros
m++;
n++;
//Allocates similarity matrix H
int *H;
H = calloc(m * n, sizeof(int));
//Allocates predecessor matrix P
int *P;
P = calloc(m * n, sizeof(int));
//Gen rand arrays a and b
generate();
//Uncomment this to test the sequence available at
//http://vlab.amrita.edu/?sub=3&brch=274&sim=1433&cnt=1
// OBS: m=11 n=7
// a[0] = 'C';
// a[1] = 'G';
// a[2] = 'T';
// a[3] = 'G';
// a[4] = 'A';
// a[5] = 'A';
// a[6] = 'T';
// a[7] = 'T';
// a[8] = 'C';
// a[9] = 'A';
// a[10] = 'T';
// b[0] = 'G';
// b[1] = 'A';
// b[2] = 'C';
// b[3] = 'T';
// b[4] = 'T';
// b[5] = 'A';
// b[6] = 'C';
//Start position for backtrack
long long int maxPos = 0;
//Calculates the similarity matrix
long long int i, j;
//Gets Initial time
double initialTime = omp_get_wtime();
long long int si, sj, ai, aj;
//Because now we have zeros ((m-1) + (n-1) - 1)
long long int nDiag = m + n - 3;
long long int nEle;
#pragma omp parallel num_threads(thread_count) \
default(none) shared(H, P, maxPos, nDiag) private(nEle, i, si, sj, ai, aj)
{
for (i = 1; i <= nDiag; ++i)
{
nEle = nElement(i);
calcFirstDiagElement(&i, &si, &sj);
#pragma omp for
for (j = 1; j <= nEle; ++j)
{
ai = si - j + 1;
aj = sj + j - 1;
similarityScore(ai, aj, H, P, &maxPos);
}
}
}
backtrack(P, maxPos);
//Gets final time
double finalTime = omp_get_wtime();
printf("\nElapsed time: %f\n\n", finalTime - initialTime);
#ifdef DEBUG
printf("\nSimilarity Matrix:\n");
printMatrix(H);
printf("\nPredecessor Matrix:\n");
printPredecessorMatrix(P);
#endif
//Frees similarity matrixes
free(H);
free(P);
//Frees input arrays
free(a);
free(b);
return 0;
} /* End of main */
/*--------------------------------------------------------------------
* Function: nElement
* Purpose: Calculate the number of i-diagonal elements
*/
long long int nElement(long long int i) {
if (i < m && i < n) {
//Number of elements in the diagonal is increasing
return i;
}
else if (i < max(m, n)) {
//Number of elements in the diagonal is stable
long int min = min(m, n);
return min - 1;
}
else {
//Number of elements in the diagonal is decreasing
long int min = min(m, n);
return 2 * min - i + abs(m - n) - 2;
}
}
/*--------------------------------------------------------------------
* Function: calcElement
* Purpose: Calculate the position of (si, sj)-element
*/
void calcFirstDiagElement(long long int *i, long long int *si, long long int *sj) {
// Calculate the first element of diagonal
if (*i < n) {
*si = *i;
*sj = 1;
} else {
*si = n - 1;
*sj = *i - n + 2;
}
}
/*--------------------------------------------------------------------
* Function: SimilarityScore
* Purpose: Calculate the maximum Similarity-Score H(i,j)
*/
void similarityScore(long long int i, long long int j, int* H, int* P, long long int* maxPos) {
int up, left, diag;
//Stores index of element
long long int index = m * i + j;
//Get element above
up = H[index - m] + gapScore;
//Get element on the left
left = H[index - 1] + gapScore;
//Get element on the diagonal
diag = H[index - m - 1] + matchMissmatchScore(i, j);
//Calculates the maximum
int max = NONE;
int pred = NONE;
/* === Matrix ===
* a[0] ... a[n]
* b[0]
* ...
* b[n]
*
* generate 'a' from 'b', if '←' insert e '↑' remove
* a=GAATTCA
* b=GACTT-A
*
* generate 'b' from 'a', if '←' insert e '↑' remove
* b=GACTT-A
* a=GAATTCA
*/
if (diag > max) { //same letter ↖
max = diag;
pred = DIAGONAL;
}
if (up > max) { //remove letter ↑
max = up;
pred = UP;
}
if (left > max) { //insert letter ←
max = left;
pred = LEFT;
}
//Inserts the value in the similarity and predecessor matrixes
H[index] = max;
P[index] = pred;
//Updates maximum score to be used as seed on backtrack
#pragma omp critical
if (max > H[*maxPos]) {
*maxPos = index;
}
} /* End of similarityScore */
/*--------------------------------------------------------------------
* Function: matchMissmatchScore
* Purpose: Similarity function on the alphabet for match/missmatch
*/
int matchMissmatchScore(long long int i, long long int j) {
if (a[j - 1] == b[i - 1])
return matchScore;
else
return missmatchScore;
} /* End of matchMissmatchScore */
/*--------------------------------------------------------------------
* Function: backtrack
* Purpose: Modify matrix to print, path change from value to PATH
*/
void backtrack(int* P, long long int maxPos) {
//hold maxPos value
long long int predPos;
//backtrack from maxPos to startPos = 0
do {
if (P[maxPos] == DIAGONAL)
predPos = maxPos - m - 1;
else if (P[maxPos] == UP)
predPos = maxPos - m;
else if (P[maxPos] == LEFT)
predPos = maxPos - 1;
P[maxPos] *= PATH;
maxPos = predPos;
} while (P[maxPos] != NONE);
} /* End of backtrack */
/*--------------------------------------------------------------------
* Function: printMatrix
* Purpose: Print Matrix
*/
void printMatrix(int* matrix) {
long long int i, j;
printf("-\t-\t");
for (j = 0; j < m-1; j++) {
printf("%c\t", a[j]);
}
printf("\n-\t");
for (i = 0; i < n; i++) { //Lines
for (j = 0; j < m; j++) {
if (j==0 && i>0) printf("%c\t", b[i-1]);
printf("%d\t", matrix[m * i + j]);
}
printf("\n");
}
} /* End of printMatrix */
/*--------------------------------------------------------------------
* Function: printPredecessorMatrix
* Purpose: Print predecessor matrix
*/
void printPredecessorMatrix(int* matrix) {
long long int i, j, index;
printf(" ");
for (j = 0; j < m-1; j++) {
printf("%c ", a[j]);
}
printf("\n ");
for (i = 0; i < n; i++) { //Lines
for (j = 0; j < m; j++) {
if (j==0 && i>0) printf("%c ", b[i-1]);
index = m * i + j;
if (matrix[index] < 0) {
printf(BOLDRED);
if (matrix[index] == -UP)
printf("↑ ");
else if (matrix[index] == -LEFT)
printf("← ");
else if (matrix[index] == -DIAGONAL)
printf("↖ ");
else
printf("- ");
printf(RESET);
} else {
if (matrix[index] == UP)
printf("↑ ");
else if (matrix[index] == LEFT)
printf("← ");
else if (matrix[index] == DIAGONAL)
printf("↖ ");
else
printf("- ");
}
}
printf("\n");
}
} /* End of printPredecessorMatrix */
/*--------------------------------------------------------------------
* Function: generate
* Purpose: Generate arrays a and b
*/
void generate() {
//Random seed
srand(time(NULL));
//Generates the values of a
long long int i;
for (i = 0; i < m; i++) {
int aux = rand() % 4;
if (aux == 0)
a[i] = 'A';
else if (aux == 2)
a[i] = 'C';
else if (aux == 3)
a[i] = 'G';
else
a[i] = 'T';
}
//Generates the values of b
for (i = 0; i < n; i++) {
int aux = rand() % 4;
if (aux == 0)
b[i] = 'A';
else if (aux == 2)
b[i] = 'C';
else if (aux == 3)
b[i] = 'G';
else
b[i] = 'T';
}
} /* End of generate */
/*--------------------------------------------------------------------
* External References:
* http://vlab.amrita.edu/?sub=3&brch=274&sim=1433&cnt=1
* http://pt.slideshare.net/avrilcoghlan/the-smith-waterman-algorithm
* http://baba.sourceforge.net/
*/
|
GB_unop__bnot_int16_int16.c | //------------------------------------------------------------------------------
// GB_unop: hard-coded functions for each built-in unary operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2020, All Rights Reserved.
// http://suitesparse.com See GraphBLAS/Doc/License.txt for license.
//------------------------------------------------------------------------------
// If this file is in the Generated/ folder, do not edit it (auto-generated).
#include "GB.h"
#ifndef GBCOMPACT
#include "GB_control.h"
#include "GB_unop__include.h"
// C=unop(A) is defined by the following types and operators:
// op(A) function: GB_unop_apply__bnot_int16_int16
// op(A') function: GB_unop_tran__bnot_int16_int16
// C type: int16_t
// A type: int16_t
// cast: int16_t cij = aij
// unaryop: cij = ~(aij)
#define GB_ATYPE \
int16_t
#define GB_CTYPE \
int16_t
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA) \
int16_t aij = Ax [pA]
#define GB_CX(p) Cx [p]
// unary operator
#define GB_OP(z, x) \
z = ~(x) ;
// casting
#define GB_CAST(z, aij) \
int16_t z = aij ;
// cij = op (aij)
#define GB_CAST_OP(pC,pA) \
{ \
/* aij = Ax [pA] */ \
int16_t aij = Ax [pA] ; \
/* Cx [pC] = op (cast (aij)) */ \
int16_t z = aij ; \
Cx [pC] = ~(z) ; \
}
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_BNOT || GxB_NO_INT16)
//------------------------------------------------------------------------------
// Cx = op (cast (Ax)): apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_unop_apply__bnot_int16_int16
(
int16_t *Cx, // Cx and Ax may be aliased
const int16_t *Ax,
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t p ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
int16_t aij = Ax [p] ;
int16_t z = aij ;
Cx [p] = ~(z) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (cast (A')): transpose, typecast, and apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_unop_tran__bnot_int16_int16
(
GrB_Matrix C,
const GrB_Matrix A,
int64_t *GB_RESTRICT *Rowcounts,
GBI_single_iterator Iter,
const int64_t *GB_RESTRICT A_slice,
int naslice
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#define GB_PHASE_2_OF_2
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
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