serial_no int64 1 24.2k | cuda_source stringlengths 11 9.01M |
|---|---|
8,901 | /*
Implementation of SAXPY accelerated with CUDA.
A CPU implementation is also included for comparison.
No timing calls or error checks in this version, for clarity.
Compile on monk with:
nvcc -arch=sm_20 -O2 saxpy_cuda.cu
*/
#include <cuda.h> /* CUDA runtime API */
#include <cstdio>
void saxpy_cpu(float *vecY, float *vecX, float alpha, int n)
{
int i;
for (i = 0; i < n; i++)
vecY[i] = alpha * vecX[i] + vecY[i];
}
__global__ void saxpy_gpu(float *vecY, float *vecX, float alpha ,int n)
{
int i;
i = blockIdx.x * blockDim.x + threadIdx.x;
if (i<n)
vecY[i] = alpha * vecX[i] + vecY[i];
}
int main(int argc, char *argv[])
{
float *x_host, *y_host; /* arrays for computation on host*/
float *x_dev, *y_dev; /* arrays for computation on device */
float *y_shadow; /* host-side copy of device results */
int n = 32*1024;
float alpha = 0.5f;
int nerror;
size_t memsize;
int i, blockSize, nBlocks;
memsize = n * sizeof(float);
/* allocate arrays on host */
x_host = (float *)malloc(memsize);
y_host = (float *)malloc(memsize);
y_shadow = (float *)malloc(memsize);
/* allocate arrays on device */
cudaMalloc((void **) &x_dev, memsize);
cudaMalloc((void **) &y_dev, memsize);
/* catch any errors */
/* initialize arrays on host */
for ( i = 0; i < n; i++)
{
x_host[i] = rand() / (float)RAND_MAX;
y_host[i] = rand() / (float)RAND_MAX;
}
/* copy arrays to device memory (synchronous) */
cudaMemcpy(x_dev, x_host, memsize, cudaMemcpyHostToDevice);
cudaMemcpy(y_dev, y_host, memsize, cudaMemcpyHostToDevice);
/* set up device execution configuration */
blockSize = 512;
nBlocks = n / blockSize + (n % blockSize > 0);
/* execute kernel (asynchronous!) */
saxpy_gpu<<<nBlocks, blockSize>>>(y_dev, x_dev, alpha, n);
/* execute host version (i.e. baseline reference results) */
saxpy_cpu(y_host, x_host, alpha, n);
/* retrieve results from device (synchronous) */
cudaMemcpy(y_shadow, y_dev, memsize, cudaMemcpyDeviceToHost);
/* guarantee synchronization */
cudaDeviceSynchronize();
/* check results */
nerror=0;
for(i=0; i < n; i++)
{
if(y_shadow[i]!=y_host[i]) nerror=nerror+1;
}
printf("test comparison shows %d errors\n",nerror);
/* free memory */
cudaFree(x_dev);
cudaFree(y_dev);
free(x_host);
free(y_host);
free(y_shadow);
return 0;
}
|
8,902 | //xfail:REPAIR_ERROR
//--blockDim=64 --gridDim=64 --no-inline
//
#include "cuda.h"
__global__ void foo() {
__shared__ int a;
a = threadIdx.x;
}
|
8,903 | #include<iostream>
#include<cstdio>
#include<math.h>
#define N (2048 * 2048)
#define THREADS_PER_BLOCK 256
using namespace std;
__global__ void add(int *a, int*b, int *c,int n){
int index = threadIdx.x + blockIdx.x*blockDim.x;
if(index<n){
c[index] = a[index] + b[index];
}
}
int main() {
int *a, *b, *c;
int *d_a, *d_b, *d_c;
int size = N * sizeof(int);
a=(int *)malloc(size);
b=(int *)malloc(size);
c=(int *)malloc(size);
int i;
for(i=0;i<N;i++) {
a[i] = rand()%70;
b[i] = rand()%70;
}
cudaMalloc(&d_a,size);
cudaMalloc(&d_b,size);
cudaMalloc(&d_c,size);
cudaMemcpy(d_a,a,size,cudaMemcpyHostToDevice);
cudaMemcpy(d_b,b,size,cudaMemcpyHostToDevice);
add<<<(N + THREADS_PER_BLOCK-1)/THREADS_PER_BLOCK,THREADS_PER_BLOCK>>>(d_a,d_b,d_c,N);
cudaMemcpy(c,d_c,size,cudaMemcpyDeviceToHost);
double error = 0;
for(i = 0;i<N;i++) {
double diff = double((a[i]+b[i])-c[i]);
error+=diff;
if(diff>0){
printf("A+B=%d",a[i]+b[i]);
printf("C = %d",c[i]);
}
}
error = sqrt(error);
cout<<"error = "<<error<<endl;
free(a); free(b); free(c);
cudaFree(d_a); cudaFree(d_b); cudaFree(d_c);
return 0;
} |
8,904 | #include "includes.h"
__global__ void histo_kernel_2 (unsigned char *buffer, int img_w, int img_h, int *histo)
{
int id_x = blockIdx.x * blockDim.x + threadIdx.x ;
int id_y = blockIdx.y * blockDim.y + threadIdx.y ;
atomicAdd (&histo[buffer[id_y*img_w + id_x]] , 1 );
} |
8,905 | #include <stdio.h>
#include <stdlib.h>
#include <cuda_runtime.h>
#include <cuda.h>
#define SIZEOFINT sizeof(int)
const int INF = ((1 << 30) - 1);
const int blockdim_x = 8, blockdim_y = 64;
// const int blockdim_x = 2, blockdim_y = 2;
const dim3 block_dim(blockdim_x, blockdim_y);
const int B = 64;
// const int B = 2;
const int Share_Mem_Size = 64;
const int Share_Mem_Row_Size = B;
int n, m;
int *Dist;
int *Dist_cuda;
void show_mat(int *start_p, int vertex_num){
for(int i = 0; i < vertex_num; i++){
for(int j = 0; j < vertex_num; j++){
if(start_p[i * vertex_num + j] == INF){
printf("INF\t ");
}else{
printf("%d\t ", start_p[i * vertex_num + j]);
}
}
printf("\n");
}
}
void malloc_Dist(int vertex_num){Dist = (int*)malloc(SIZEOFINT * vertex_num * vertex_num);}
int getDist(int i, int j, int vertex_num){return Dist[i * vertex_num + j];}
int *getDistAddr(int i, int j, int vertex_num){return &(Dist[i * vertex_num + j]);}
void setDist(int i, int j, int val, int vertex_num){Dist[i * vertex_num + j] = val;}
void setup_DistCuda(int vertex_num){
cudaMalloc((void **)&Dist_cuda, SIZEOFINT * vertex_num * vertex_num);
cudaMemcpy(Dist_cuda, Dist, (n * n * SIZEOFINT), cudaMemcpyHostToDevice);
}
void back_DistCuda(int vertex_num){
cudaMemcpy(Dist, Dist_cuda, (n * n * SIZEOFINT), cudaMemcpyDeviceToHost);
}
// int getDistCuda(int i, int j, int vertex_num){return Dist_cuda[i * vertex_num + j];}
// int *getDistAddrCuda(int i, int j, int vertex_num){return &(Dist_cuda[i * vertex_num + j]);}
// void setDistCuda(int i, int j, int val, int vertex_num){Dist_cuda[i * vertex_num + j] = val;}
void input(char* infile) {
FILE* file = fopen(infile, "rb");
fread(&n, sizeof(int), 1, file);
fread(&m, sizeof(int), 1, file);
malloc_Dist(n);
// malloc_DistCuda(n);
for (int i = 0; i < n; i++) {
for (int j = 0; j < n; j++) {
if (i == j) {
setDist(i, j, 0, n);
// Dist[i][j] = 0;
} else {
setDist(i, j, INF, n);
// Dist[i][j] = INF;
}
}
}
int pair[3];
for (int i = 0; i < m; i++) {
fread(pair, sizeof(int), 3, file);
setDist(pair[0], pair[1], pair[2], n);
// Dist[pair[0]][pair[1]] = pair[2];
}
// cudaMemcpy(Dist_cuda, Dist, (n * n * SIZEOFINT), cudaMemcpyHostToDevice);
fclose(file);
}
void output(char* outFileName) {
FILE* outfile = fopen(outFileName, "w");
for (int i = 0; i < n; i++) {
for (int j = 0; j < n; j++) {
// if (Dist[i][j] >= INF) Dist[i][j] = INF;
if (getDist(i, j, n) >= INF) setDist(i, j, INF, n);
}
// fwrite(Dist[i], sizeof(int), n, outfile);
// fwrite(getDistAddr(i, 0, n), sizeof(int), n, outfile);
}
fwrite(getDistAddr(0, 0, n), sizeof(int), n * n, outfile);
fclose(outfile);
}
__device__ void assignAij(int *dist, int a[Share_Mem_Size * Share_Mem_Size], int vertex_num, int Round, int block_internal_start_x, int block_internal_end_x, int block_internal_start_y, int block_internal_end_y){
for (int i = block_internal_start_x + threadIdx.x; i < block_internal_end_x; i+=blockDim.x) {
for (int j = block_internal_start_y + threadIdx.y; j < block_internal_end_y; j+=blockDim.y) {
a[(i - block_internal_start_x) * Share_Mem_Row_Size + (j - block_internal_start_y)] = dist[i * vertex_num + j];
}
}
}
__device__ void assignCkj(int *dist, int c[Share_Mem_Size * Share_Mem_Size], int vertex_num, int Round, int block_internal_start_x, int block_internal_end_x, int block_internal_start_y, int block_internal_end_y){
for (int k = Round * B + threadIdx.x; k < (Round + 1) * B && k < vertex_num; k+=blockDim.x) {
for (int j = block_internal_start_y + threadIdx.y; j < block_internal_end_y; j+=blockDim.y) {
c[(k - Round * B) * Share_Mem_Row_Size + (j - block_internal_start_y)] = dist[k * vertex_num + j];
}
}
}
__device__ void assignBik(int *dist, int b[Share_Mem_Size * Share_Mem_Size], int vertex_num, int Round, int block_internal_start_x, int block_internal_end_x, int block_internal_start_y, int block_internal_end_y){
for (int k = Round * B + threadIdx.y; k < (Round + 1) * B && k < vertex_num; k+=blockDim.y) {
for (int i = block_internal_start_x + threadIdx.x; i < block_internal_end_x; i+=blockDim.x) {
b[(i - block_internal_start_x) * Share_Mem_Row_Size + (k - Round * B)] = dist[i * vertex_num + k];
}
}
}
__device__ void assignBik_r(int *dist, int b[Share_Mem_Size * Share_Mem_Size], int vertex_num, int Round, int block_internal_start_x, int block_internal_end_x, int block_internal_start_y, int block_internal_end_y){
for (int k = Round * B + threadIdx.y; k < (Round + 1) * B && k < vertex_num; k+=blockDim.y) {
for (int i = block_internal_start_x + threadIdx.x; i < block_internal_end_x; i+=blockDim.x) {
b[(k - Round * B) * Share_Mem_Row_Size + (i - block_internal_start_x)] = dist[i * vertex_num + k];
}
}
}
__device__ void relax(int a[Share_Mem_Size * Share_Mem_Size], int b[Share_Mem_Size * Share_Mem_Size], int c[Share_Mem_Size * Share_Mem_Size], int vertex_num, int Round, int block_internal_start_x, int block_internal_end_x, int block_internal_start_y, int block_internal_end_y){
// Relax Path
for (int k = Round * B; k < (Round + 1) * B && k < vertex_num; k++) {
for (int i = block_internal_start_x + threadIdx.x; i < block_internal_end_x; i+=blockDim.x) {
int bv = b[(i - block_internal_start_x) * Share_Mem_Row_Size + (k - Round * B)];
for (int j = block_internal_start_y + threadIdx.y; j < block_internal_end_y; j+=blockDim.y) {
int d = bv + c[(k - Round * B) * Share_Mem_Row_Size + (j - block_internal_start_y)];
if (d < a[(i - block_internal_start_x) * Share_Mem_Row_Size + (j - block_internal_start_y)]) {
a[(i - block_internal_start_x) * Share_Mem_Row_Size + (j - block_internal_start_y)] = d;
}
}
}
__syncthreads();
}
}
__device__ void relax_r(int a[Share_Mem_Size * Share_Mem_Size], int b[Share_Mem_Size * Share_Mem_Size], int c[Share_Mem_Size * Share_Mem_Size], int vertex_num, int Round, int block_internal_start_x, int block_internal_end_x, int block_internal_start_y, int block_internal_end_y){
// Relax Path
for (int k = Round * B; k < (Round + 1) * B && k < vertex_num; k++) {
for (int i = block_internal_start_x + threadIdx.x; i < block_internal_end_x; i+=blockDim.x) {
int bv = b[(k - Round * B) * Share_Mem_Row_Size + (i - block_internal_start_x)];
for (int j = block_internal_start_y + threadIdx.y; j < block_internal_end_y; j+=blockDim.y) {
int d = bv + c[(k - Round * B) * Share_Mem_Row_Size + (j - block_internal_start_y)];
if (d < a[(i - block_internal_start_x) * Share_Mem_Row_Size + (j - block_internal_start_y)]) {
a[(i - block_internal_start_x) * Share_Mem_Row_Size + (j - block_internal_start_y)] = d;
}
}
}
__syncthreads();
}
// __syncthreads();
}
__device__ void flush(int *dist, int a[Share_Mem_Size * Share_Mem_Size], int vertex_num, int block_internal_start_x, int block_internal_end_x, int block_internal_start_y, int block_internal_end_y){
// Move modified block to global memory
for (int i = block_internal_start_x + threadIdx.x; i < block_internal_end_x; i+=blockDim.x) {
for (int j = block_internal_start_y + threadIdx.y; j < block_internal_end_y; j+=blockDim.y) {
dist[i * vertex_num + j] = a[(i - block_internal_start_x) * Share_Mem_Row_Size + (j - block_internal_start_y)];
}
}
}
__global__ void phase1_cal_cuda(int *dist, int vertex_num, int edge_num, int B, int Round, int block_start_x, int block_start_y, int block_width, int block_height) {
int block_end_x = block_start_x + block_height;
int block_end_y = block_start_y + block_width;
// printf("%d\n", dist[1]);
// i-j block
__shared__ int a[Share_Mem_Size * Share_Mem_Size];
// i-k block
__shared__ int b[Share_Mem_Size * Share_Mem_Size];
// k-j block
__shared__ int c[Share_Mem_Size * Share_Mem_Size];
for (int b_i = block_start_x + blockIdx.x; b_i < block_end_x; b_i+=gridDim.x) {
for (int b_j = block_start_y + blockIdx.y; b_j < block_end_y; b_j+=gridDim.y) {
// To calculate B*B elements in the block (b_i, b_j)
// For each block, it need to compute B times
// To calculate original index of elements in the block (b_i, b_j)
// For instance, original index of (0,0) in block (1,2) is (2,5) for V=6,B=2
int block_internal_start_x = b_i * B;
int block_internal_end_x = (b_i + 1) * B;
int block_internal_start_y = b_j * B;
int block_internal_end_y = (b_j + 1) * B;
if (block_internal_end_x > vertex_num) block_internal_end_x = vertex_num;
if (block_internal_end_y > vertex_num) block_internal_end_y = vertex_num;
assignAij(dist, a, vertex_num, Round, block_internal_start_x, block_internal_end_x, block_internal_start_y, block_internal_end_y);
// assignCkj(dist, c, vertex_num, Round, block_internal_start_x, block_internal_end_x, block_internal_start_y, block_internal_end_y);
// Reverse the row and column to ensure column-major iteration
// assignBik_r(dist, b, vertex_num, Round, block_internal_start_x, block_internal_end_x, block_internal_start_y, block_internal_end_y);
__syncthreads();
// Relax Path
relax(a, a, a, vertex_num, Round, block_internal_start_x, block_internal_end_x, block_internal_start_y, block_internal_end_y);
// Move modified block to global memory
flush(dist, a, vertex_num, block_internal_start_x, block_internal_end_x, block_internal_start_y, block_internal_end_y);
}
}
}
__global__ void phase3_cal_cuda(int *dist, int vertex_num, int edge_num, int B, int Round, int block_start_x, int block_start_y, int block_width, int block_height) {
int block_end_x = block_start_x + block_height;
int block_end_y = block_start_y + block_width;
// printf("%d\n", dist[1]);
// i-j block
__shared__ int a[Share_Mem_Size * Share_Mem_Size];
// i-k block
__shared__ int b[Share_Mem_Size * Share_Mem_Size];
// k-j block
__shared__ int c[Share_Mem_Size * Share_Mem_Size];
for (int b_i = block_start_x + blockIdx.x; b_i < block_end_x; b_i+=gridDim.x) {
for (int b_j = block_start_y + blockIdx.y; b_j < block_end_y; b_j+=gridDim.y) {
// To calculate B*B elements in the block (b_i, b_j)
// For each block, it need to compute B times
// To calculate original index of elements in the block (b_i, b_j)
// For instance, original index of (0,0) in block (1,2) is (2,5) for V=6,B=2
int block_internal_start_x = b_i * B;
int block_internal_end_x = (b_i + 1) * B;
int block_internal_start_y = b_j * B;
int block_internal_end_y = (b_j + 1) * B;
if (block_internal_end_x > vertex_num) block_internal_end_x = vertex_num;
if (block_internal_end_y > vertex_num) block_internal_end_y = vertex_num;
assignAij(dist, a, vertex_num, Round, block_internal_start_x, block_internal_end_x, block_internal_start_y, block_internal_end_y);
assignCkj(dist, c, vertex_num, Round, block_internal_start_x, block_internal_end_x, block_internal_start_y, block_internal_end_y);
// Reverse the row and column to ensure column-major iteration
assignBik_r(dist, b, vertex_num, Round, block_internal_start_x, block_internal_end_x, block_internal_start_y, block_internal_end_y);
// assignBik(dist, b, vertex_num, Round, block_internal_start_x, block_internal_end_x, block_internal_start_y, block_internal_end_y);
__syncthreads();
// Relax Path
relax_r(a, b, c, vertex_num, Round, block_internal_start_x, block_internal_end_x, block_internal_start_y, block_internal_end_y);
// relax(a, b, c, vertex_num, Round, block_internal_start_x, block_internal_end_x, block_internal_start_y, block_internal_end_y);
// Move modified block to global memory
flush(dist, a, vertex_num, block_internal_start_x, block_internal_end_x, block_internal_start_y, block_internal_end_y);
}
}
}
__global__ void phase21_cal_cuda(int *dist, int vertex_num, int edge_num, int B, int Round, int block_start_x, int block_start_y, int block_width, int block_height) {
int block_end_x = block_start_x + block_height;
int block_end_y = block_start_y + block_width;
// printf("%d\n", dist[1]);
// i-j block
__shared__ int a[Share_Mem_Size * Share_Mem_Size];
// i-k block
__shared__ int b[Share_Mem_Size * Share_Mem_Size];
// k-j block
__shared__ int c[Share_Mem_Size * Share_Mem_Size];
for (int b_i = block_start_x + blockIdx.x; b_i < block_end_x; b_i+=gridDim.x) {
for (int b_j = block_start_y + blockIdx.y; b_j < block_end_y; b_j+=gridDim.y) {
// To calculate B*B elements in the block (b_i, b_j)
// For each block, it need to compute B times
// To calculate original index of elements in the block (b_i, b_j)
// For instance, original index of (0,0) in block (1,2) is (2,5) for V=6,B=2
int block_internal_start_x = b_i * B;
int block_internal_end_x = (b_i + 1) * B;
int block_internal_start_y = b_j * B;
int block_internal_end_y = (b_j + 1) * B;
if (block_internal_end_x > vertex_num) block_internal_end_x = vertex_num;
if (block_internal_end_y > vertex_num) block_internal_end_y = vertex_num;
assignAij(dist, a, vertex_num, Round, block_internal_start_x, block_internal_end_x, block_internal_start_y, block_internal_end_y);
// assignCkj(dist, c, vertex_num, Round, block_internal_start_x, block_internal_end_x, block_internal_start_y, block_internal_end_y);
// Reverse the row and column to ensure column-major iteration
assignBik_r(dist, b, vertex_num, Round, block_internal_start_x, block_internal_end_x, block_internal_start_y, block_internal_end_y);
__syncthreads();
// Relax Path
relax_r(a, b, a, vertex_num, Round, block_internal_start_x, block_internal_end_x, block_internal_start_y, block_internal_end_y);
// Move modified block to global memory
flush(dist, a, vertex_num, block_internal_start_x, block_internal_end_x, block_internal_start_y, block_internal_end_y);
}
}
}
__global__ void phase22_cal_cuda(int *dist, int vertex_num, int edge_num, int B, int Round, int block_start_x, int block_start_y, int block_width, int block_height) {
int block_end_x = block_start_x + block_height;
int block_end_y = block_start_y + block_width;
// printf("%d\n", dist[1]);
// i-j block
__shared__ int a[Share_Mem_Size * Share_Mem_Size];
// i-k block
__shared__ int b[Share_Mem_Size * Share_Mem_Size];
// k-j block
__shared__ int c[Share_Mem_Size * Share_Mem_Size];
for (int b_i = block_start_x + blockIdx.x; b_i < block_end_x; b_i+=gridDim.x) {
for (int b_j = block_start_y + blockIdx.y; b_j < block_end_y; b_j+=gridDim.y) {
// To calculate B*B elements in the block (b_i, b_j)
// For each block, it need to compute B times
// To calculate original index of elements in the block (b_i, b_j)
// For instance, original index of (0,0) in block (1,2) is (2,5) for V=6,B=2
int block_internal_start_x = b_i * B;
int block_internal_end_x = (b_i + 1) * B;
int block_internal_start_y = b_j * B;
int block_internal_end_y = (b_j + 1) * B;
if (block_internal_end_x > vertex_num) block_internal_end_x = vertex_num;
if (block_internal_end_y > vertex_num) block_internal_end_y = vertex_num;
assignAij(dist, a, vertex_num, Round, block_internal_start_x, block_internal_end_x, block_internal_start_y, block_internal_end_y);
assignCkj(dist, c, vertex_num, Round, block_internal_start_x, block_internal_end_x, block_internal_start_y, block_internal_end_y);
// Reverse the row and column to ensure column-major iteration
// assignBik_r(dist, b, vertex_num, Round, block_internal_start_x, block_internal_end_x, block_internal_start_y, block_internal_end_y);
__syncthreads();
// Relax Path
relax(a, a, c, vertex_num, Round, block_internal_start_x, block_internal_end_x, block_internal_start_y, block_internal_end_y);
// Move modified block to global memory
flush(dist, a, vertex_num, block_internal_start_x, block_internal_end_x, block_internal_start_y, block_internal_end_y);
}
}
}
// __global__ void cal_cuda(int *dist, int vertex_num, int edge_num, int B, int Round, int block_start_x, int block_start_y, int block_width, int block_height) {
// int block_end_x = block_start_x + block_height;
// int block_end_y = block_start_y + block_width;
// // printf("%d\n", dist[1]);
// // i-j block
// int (*AM)[Share_Mem_Size * Share_Mem_Size];
// __shared__ int a[Share_Mem_Size * Share_Mem_Size];
// // i-k block
// int (*BM)[Share_Mem_Size * Share_Mem_Size];
// __shared__ int b[Share_Mem_Size * Share_Mem_Size];
// // k-j block
// int (*CM)[Share_Mem_Size * Share_Mem_Size];
// __shared__ int c[Share_Mem_Size * Share_Mem_Size];
// for (int b_i = block_start_x + blockIdx.x; b_i < block_end_x; b_i+=gridDim.x) {
// for (int b_j = block_start_y + blockIdx.y; b_j < block_end_y; b_j+=gridDim.y) {
// // To calculate B*B elements in the block (b_i, b_j)
// // For each block, it need to compute B times
// // To calculate original index of elements in the block (b_i, b_j)
// // For instance, original index of (0,0) in block (1,2) is (2,5) for V=6,B=2
// char is_reverse = 0;
// int block_internal_start_x = b_i * B;
// int block_internal_end_x = (b_i + 1) * B;
// int block_internal_start_y = b_j * B;
// int block_internal_end_y = (b_j + 1) * B;
// if (block_internal_end_x > vertex_num) block_internal_end_x = vertex_num;
// if (block_internal_end_y > vertex_num) block_internal_end_y = vertex_num;
// // if(threadIdx.x == 0 && threadIdx.y == 0){
// // printf("(%d %d) A(%d:%d, %d:%d) B(%d:%d, %d:%d) C(%d:%d, %d:%d) CAL(%d:%d, %d:%d, %d:%d)\n",
// // blockDim.x, blockDim.y,
// // block_internal_start_x + threadIdx.x, block_internal_end_x, block_internal_start_y + threadIdx.y, block_internal_end_y,
// // block_internal_start_x + threadIdx.x, block_internal_end_x, Round * B, (Round + 1) * B < vertex_num? (Round + 1) * B : vertex_num,
// // Round * B, (Round + 1) * B < vertex_num? (Round + 1) * B : vertex_num, block_internal_start_y + threadIdx.y, block_internal_end_y,
// // block_internal_start_x + threadIdx.x, block_internal_end_x, block_internal_start_y + threadIdx.y, block_internal_end_y, Round * B, (Round + 1) * B < vertex_num? (Round + 1) * B : vertex_num
// // );
// // }
// AM = &a;
// for (int i = block_internal_start_x + threadIdx.x; i < block_internal_end_x; i+=blockDim.x) {
// for (int j = block_internal_start_y + threadIdx.y; j < block_internal_end_y; j+=blockDim.y) {
// a[(i - block_internal_start_x) * Share_Mem_Row_Size + (j - block_internal_start_y)] = dist[i * vertex_num + j];
// }
// }
// if(Round != b_i){
// CM = &c;
// for (int k = Round * B + threadIdx.x; k < (Round + 1) * B && k < vertex_num; k+=blockDim.x) {
// for (int j = block_internal_start_y + threadIdx.y; j < block_internal_end_y; j+=blockDim.y) {
// c[(k - Round * B) * Share_Mem_Row_Size + (j - block_internal_start_y)] = dist[k * vertex_num + j];
// }
// }
// }else{CM = &a;}
// if(Round != b_j){
// BM = &b;
// is_reverse = 1;
// for (int k = Round * B + threadIdx.y; k < (Round + 1) * B && k < vertex_num; k+=blockDim.y) {
// for (int i = block_internal_start_x + threadIdx.x; i < block_internal_end_x; i+=blockDim.x) {
// // b[(i - block_internal_start_x) * Share_Mem_Row_Size + (k - Round * B)] = dist[i * vertex_num + k];
// b[(k - Round * B) * Share_Mem_Row_Size + (i - block_internal_start_x)] = dist[i * vertex_num + k];
// }
// }
// }else{BM = &a;}
// __syncthreads();
// // Relax Path
// for (int k = Round * B; k < (Round + 1) * B && k < vertex_num; k++) {
// for (int i = block_internal_start_x + threadIdx.x; i < block_internal_end_x; i+=blockDim.x) {
// int bv = 0;
// // bv = (*BM)[(i - block_internal_start_x) * Share_Mem_Row_Size + (k - Round * B)];
// if(is_reverse){bv = (*BM)[(k - Round * B) * Share_Mem_Row_Size + (i - block_internal_start_x)];}
// else{bv = (*BM)[(i - block_internal_start_x) * Share_Mem_Row_Size + (k - Round * B)];}
// for (int j = block_internal_start_y + threadIdx.y; j < block_internal_end_y; j+=blockDim.y) {
// int d = bv + (*CM)[(k - Round * B) * Share_Mem_Row_Size + (j - block_internal_start_y)];
// if (d < (*AM)[(i - block_internal_start_x) * Share_Mem_Row_Size + (j - block_internal_start_y)]) {
// (*AM)[(i - block_internal_start_x) * Share_Mem_Row_Size + (j - block_internal_start_y)] = d;
// }
// }
// }
// __syncthreads();
// }
// // relax(AM, BM, CM, vertex_num, Round, block_internal_start_x, block_internal_end_x, block_internal_start_y, block_internal_end_y);
// // Move modified block to global memory
// flush(dist, (*AM), vertex_num, block_internal_start_x, block_internal_end_x, block_internal_start_y, block_internal_end_y);
// }
// }
// }
void block_FW_cuda(int B) {
int round = (n + B - 1) / B;
for (int r = 0; r < round; r++) {
// printf("Round: %d in total: %d\n", r, round);
fflush(stdout);
/* Phase 1*/
phase1_cal_cuda<<<1, block_dim>>>(Dist_cuda, n, m, B, r, r, r, 1, 1);
/* Phase 2*/
const int num_stream = 2;
cudaStream_t streams[num_stream];
for(int i=0; i<num_stream; i++) {cudaStreamCreate(&streams[i]);}
phase21_cal_cuda<<<round, block_dim, 0>>>(Dist_cuda, n, m, B, r, r, 0, round, 1);
phase22_cal_cuda<<<round, block_dim, 1>>>(Dist_cuda, n, m, B, r, 0, r, 1, round);
// cudaDeviceSynchronize();
for(int i=0; i<num_stream; i++) {
cudaStreamDestroy(streams[i]);
}
// printf("After\n");
/* Phase 3*/
// const dim3 grid_dim0(r, r);
// const dim3 grid_dim1(round - r - 1, r);
// const dim3 grid_dim2(r, round - r - 1);
// const dim3 grid_dim3(round - r - 1, round - r - 1);
// const int num_stream3 = 2;
// cudaStream_t streams3[num_stream];
// for(int i=0; i<num_stream3; i++) {cudaStreamCreate(&streams3[i]);}
// phase3_cal_cuda<<<grid_dim0, block_dim, 0>>>(Dist_cuda, n, m, B, r, 0, 0, r, r);
// phase3_cal_cuda<<<grid_dim1, block_dim, 1>>>(Dist_cuda, n, m, B, r, 0, r + 1, round - r - 1, r);
// phase3_cal_cuda<<<grid_dim2, block_dim, 0>>>(Dist_cuda, n, m, B, r, r + 1, 0, r, round - r - 1);
// phase3_cal_cuda<<<grid_dim3, block_dim, 1>>>(Dist_cuda, n, m, B, r, r + 1, r + 1, round - r - 1, round - r - 1);
// for(int i=0; i<num_stream3; i++) {cudaStreamDestroy(streams3[i]);}
const dim3 grid_dim(round, round);
phase3_cal_cuda<<<grid_dim, block_dim>>>(Dist_cuda, n, m, B, r, 0, 0, round, round);
// const dim3 grid_dim0(r, r);
// const dim3 grid_dim1(round - r - 1, r);
// const dim3 grid_dim2(r, round - r - 1);
// const dim3 grid_dim3(round - r - 1, round - r - 1);
// cal_cuda<<<grid_dim0, block_dim>>>(Dist_cuda, n, m, B, r, 0, 0, r, r);
// cal_cuda<<<grid_dim1, block_dim>>>(Dist_cuda, n, m, B, r, 0, r + 1, round - r - 1, r);
// cal_cuda<<<grid_dim2, block_dim>>>(Dist_cuda, n, m, B, r, r + 1, 0, r, round - r - 1);
// cal_cuda<<<grid_dim3, block_dim>>>(Dist_cuda, n, m, B, r, r + 1, r + 1, round - r - 1, round - r - 1);
}
}
int main(int argc, char* argv[]) {
input(argv[1]);
// show_mat(getDistAddr(0, 0, n), n);
setup_DistCuda(n);
// printf("Vertice: %d, Edge: %d, B: %d\n", n, m, B);
block_FW_cuda(B);
back_DistCuda(n);
// show_mat(getDistAddr(0, 0, n), n);
output(argv[2]);
// show_mat(getDistAddr(0, 0, n), n);
return 0;
} |
8,906 | #include <cuda.h>
#include <stdio.h>
CUresult cuDeviceTotalMem(size_t* bytes, CUdevice dev) {
printf("%s\n", "I just want to tell you that cuDeviceTotalMem is hijacked!");
*bytes = 1;
return CUDA_SUCCESS;
}
|
8,907 | /**
* Copyright 1993-2012 NVIDIA Corporation. All rights reserved.
*
* Please refer to the NVIDIA end user license agreement (EULA) associated
* with this source code for terms and conditions that govern your use of
* this software. Any use, reproduction, disclosure, or distribution of
* this software and related documentation outside the terms of the EULA
* is strictly prohibited.
*/
#include <stdlib.h>
#include <stdio.h>
#include <iostream>
#include <math.h>
#include <time.h>
#include <fstream>
#include <vector>
#include <fstream>
#include <curand_kernel.h>
#include <cufft.h>
#include <complex.h>
#include "float.h"
float L, LL;
int N, C, itera;
float t;
using namespace std;
// función Maxwelliana de la distribución de las partículas.
__device__ float distribution(float vb, float aleatorio, curandState *states) //generador de distribución maxwelliana para la velocidad
{
// Genera un valor random v
float fmax = 0.5 * (1.0 + exp(-2.0 * vb * vb));
float vmin = -5.0 * vb;
float vmax = +5.0 * vb;
float v;
float f;
float x;
int Idx = blockIdx.x * blockDim.x + threadIdx.x;
while (true) {
v = vmin + ((vmax - vmin) * aleatorio);
f = 0.5
* (exp(-(v - vb) * (v - vb) / 2.0)
+ exp(-(v + vb) * (v + vb) / 2.0));
x = fmax * aleatorio;
if (x > f)
aleatorio = curand_uniform(states + Idx);
else
return v;
}
return 0;
}
//Distribución aleatoria de las partículas.
__global__ void distribucionParticulas(float *rx, float *ry, float *vx,
float *vy, int N, curandState *states, float vb, float L, int seed) {
int Idx = blockIdx.x * blockDim.x + threadIdx.x;
seed = (unsigned int) (clock() * Idx);
curand_init(seed, 0, 0, states + Idx);
if (Idx < N) {
rx[Idx] = L * curand_uniform(states + Idx); //inicializando la posicion aleatoria en x
ry[Idx] = L * curand_uniform(states + Idx);
vx[Idx] = distribution(vb, curand_uniform(states + Idx), states); //;L*curand_uniform_float(states + Idx);//distribution(vb,states); //inicializa la velocidad con una distribucion maxwelliana
vy[Idx] = distribution(vb, curand_uniform(states + Idx), states); //L*curand_uniform_float(states + Idx);//distribution(vb,states); //inicializa la velocidad con una distribucion maxwelliana
}
}
// inicialización de la densidad.
__global__ void inicializacionDensidad(float *ne, int C) {
int Id = blockIdx.x * blockDim.x + threadIdx.x;
if (Id < (C * C)) {
ne[Id] = 0.0;
}
}
__global__ void inicializacionValoresReales(float *vr, int C) {
int Id = blockIdx.x * blockDim.x + threadIdx.x;
if (Id < (C * C)) {
vr[Id] = 0.0;
}
}
//Calculo de la densidad en cada celda.
__global__ void calculoDensidadInicializacionCeldas(float *rx, float *ry,
int *jx, int *jy, float *yx, float *yy, int N, int C, float L) {
int Id = blockIdx.x * blockDim.x + threadIdx.x;
float dx = L / float(C);
//float dxx = L /float(C*C);
if (Id < N) {
jx[Id] = int(rx[Id] / dx); //posicion en x de la particula
jy[Id] = int(ry[Id] / dx); //posicion en y de la particula
yx[Id] = (rx[Id] / dx) - (float) jx[Id]; //posicion exacta de la particula en x de la celda "j"
yy[Id] = (ry[Id] / dx) - (float) jy[Id];
}
}
__global__ void calculoDensidad(float *ne, int *jx, int *jy, float *yx, int C,
float L, int N) {
float dxx = L / float(C * C);
// int Id = blockIdx.x*blockDim.x + threadIdx.x;
for (int i = 0; i < N; i++) {
ne[(jy[i] * C) + jx[i]] += (1. - yx[i]) / dxx;
if (jx[i] + 1 == C)
ne[(jy[i] * C)] += yx[i] / dxx;
else
ne[(jy[i] * C) + jx[i] + 1] += yx[i] / dxx;
}
}
__global__ void normalizacionDensidad(float *ne, float *n, int N, int C,
float L) {
int Id = blockIdx.x * blockDim.x + threadIdx.x;
if (Id < C * C) {
n[Id] = float(C * C) * ne[Id] / float(N) - 1;
}
}
// función que integra la densidad normalizada con la otra densidad
void Densidad(float *ne_d, float *n_d, float *rx_d, float *ry_d, int *jx_d,
int *jy_d, float *yx_d, float *yy_d, int C, float L, int N) {
//definicion de los bloques.
float blockSize = 1024;
dim3 dimBlock(ceil(N / blockSize), 1, 1);
dim3 dimBlock2(ceil(C * C / blockSize), 1, 1);
dim3 dimGrid(blockSize, 1, 1);
calculoDensidadInicializacionCeldas<<<blockSize, dimBlock>>>(rx_d, ry_d,
jx_d, jy_d, yx_d, yy_d, N, C, L);
cudaDeviceSynchronize();
calculoDensidad<<<1, 1>>>(ne_d, jx_d, jy_d, yx_d, C, L, N); //proceso de mejora.
cudaDeviceSynchronize();
normalizacionDensidad<<<blockSize, dimBlock2>>>(ne_d, n_d, N, C, L);
cudaDeviceSynchronize();
}
//////////////////////////////////////////////////////////////////////////////////////////////////
//Calculo Poisson.
/* en este punto se asignan los valores de la densidad normalizada a una variable compleja que es la que entra a operar con la
* transformada rápida de fourier en cufft.
*/
__global__ void realTocomplex(float *n_d, cufftComplex *n_d_C, int C) {
int i = blockIdx.x * blockDim.x + threadIdx.x;
//int j= blockIdx.y*blockDim.y+threadIdx.y;
//int index= (i*C)+j;// recorrido de la matriz
if (i < C * C) {
n_d_C[i].x = n_d[i];
n_d_C[i].y = 0.0f;
}
}
/////////////////////////////////////////////////////////////////////////////////////////////////////
/*Normalizacion de la transformada hacia adelante*/
__global__ void normalizacionSalidaTranfForward(cufftComplex *T_F,
cufftComplex *T_F_N, int C) {
int i = blockIdx.x * blockDim.x + threadIdx.x;
//int j = blockIdx.y*blockDim.y + threadIdx.y;
//int index= i*C+j;
if (i < C * C) {
T_F_N[i].x = T_F[i].x / float(C * C * C * C);
T_F_N[i].y = T_F[i].y / float(C * C * C * C);
}
}
/////////////////////////////////////////////////////////////////////////////////////////////////////
__global__ void ComplexToFloat2(cufftComplex *T_F_N, float2 *poisson_d, int C) {
int i = blockIdx.x * blockDim.x + threadIdx.x;
if (i < C * C) {
poisson_d[i].x = T_F_N[i].x;
poisson_d[i].y = T_F_N[i].y;
}
}
/////////////////////////////////////////////////////////////////////////////////////////////////////
///*Calculo Poisson*/
void Poisson(float2 *calculoPoisson_h, float L, int C) {// pasar a calculo paralelo
float dx = L / float(C);
calculoPoisson_h[0].x = 0.0;
calculoPoisson_h[0].y = 0.0;
float2 i;
i.x = 0.0;
i.y = L; //creamos una variable compleja para poder aplicar la discretizacion.
float2 W;
W.x = exp(2.0 * M_PI * i.x / float(C));
W.y = exp(2.0 * M_PI * i.y / float(C));
float2 Wm;
Wm.x = L;
Wm.y = L;
float2 Wn;
Wn.x = L;
Wn.y = L;
for (int m = 0; m < C; m++) {
for (int n = 0; n < C; n++) {
float2 denom;
denom.x = 4.0;
denom.y = 4.0;
denom.x -= Wm.x + L / Wm.x + Wn.x + L / Wn.x;
denom.y -= Wm.y + L / Wm.y + Wn.y + L / Wn.y; //se calcula el denominador para cada celda, segun el equema de discretizacion
if (denom.x != 0.0 && denom.y != 0.0) {
calculoPoisson_h[m * C + n].x *= dx * dx / denom.x;
calculoPoisson_h[m * C + n].y *= dx * dx / denom.y;
}
Wn.x *= W.x; //se multiplica por la constante W
Wn.y *= W.y;
}
Wm.x *= W.x;
Wm.y *= W.y;
}
}
//////////////////////////////////////////////////////////////////////////////////////////////////////
__global__ void float2ToComplex(float2 *calculoPoisson_d,
cufftComplex *Phi_Poisson, int C) {
int i = blockIdx.x * blockDim.x + threadIdx.x;
if (i < C * C) {
Phi_Poisson[i].x = calculoPoisson_d[i].x;
Phi_Poisson[i].y = calculoPoisson_d[i].y;
}
}
//////////////////////////////////////////////////////////////////////////////////////////////////////
__global__ void ComplexToReal(cufftComplex *T_I, float *poissonFinal_d, int C) {
int i = blockIdx.x * blockDim.x + threadIdx.x;
if (i < C * C) {
poissonFinal_d[i] = T_I[i].x / float(1.e-6);
}
}
////////////////////////////////////////////////////////////////////////////////////////////////////////////
void calculoPotencialElectroestatico(float *n_d, int C, cufftComplex *n_d_C,
cufftComplex *T_F, cufftComplex *T_F_N, cufftComplex *Phi_Poisson,
cufftComplex *T_I, float2 *calculoPoisson_d, float2 *calculoPoisson_h,
float *poissonFinal_d) {
int size_ne2 = C * C * sizeof(float2);
float blockSize = 1024;
dim3 dimBlock(ceil(N / blockSize), 1, 1);
dim3 dimBlock2(ceil(C * C / blockSize), 1, 1);
dim3 dimBlock3(ceil(C * C / blockSize), ceil(C * C / blockSize), 1);
dim3 dimGrid(blockSize, 1, 1);
dim3 dimGrid3(blockSize, blockSize, 1);
realTocomplex<<<blockSize, dimBlock2>>>(n_d, n_d_C, C);
cudaDeviceSynchronize();
cufftHandle plan;
cufftPlan2d(&plan, C, C, CUFFT_C2C);
cufftExecC2C(plan, n_d_C, T_F, CUFFT_FORWARD); // transformada hacia adelante en x and y.
/*Valor de la transformada hacia adelante de latransformada rápida normalizada*/
normalizacionSalidaTranfForward<<<blockSize, dimBlock2>>>(T_F, T_F_N, C);
cudaDeviceSynchronize();
/*Calculo Poisson*/
ComplexToFloat2<<<blockSize, dimBlock2>>>(T_F_N, calculoPoisson_d, C);
cudaDeviceSynchronize();
//Comprobacion del resultado de la transformada hacia adelante.
cudaMemcpy(calculoPoisson_h, calculoPoisson_d, size_ne2,
cudaMemcpyDeviceToHost);
//Calculo Poisson antes de la transformada inversa
Poisson(calculoPoisson_h, L, C);
// Pasar el calculo de Poisson al dispositivo
cudaMemcpy(calculoPoisson_d, calculoPoisson_h, size_ne2,
cudaMemcpyHostToDevice);
//Hacer la transformada Inversa
float2ToComplex<<<blockSize, dimBlock2>>>(calculoPoisson_d, Phi_Poisson, C);
cudaDeviceSynchronize();
//Aplicar la transformada inversa de la matriz
cufftExecC2C(plan, Phi_Poisson, T_I, CUFFT_INVERSE);
//tomando la transformada final.
ComplexToReal<<<blockSize, dimBlock2>>>(T_I, poissonFinal_d, C);
cudaDeviceSynchronize();
cufftDestroy(plan);
}
//////////////////////////////////////////////////////////////////////////////////////////////////////////
// Calculo campo electrico.
__global__ void ElectricBordes(float *poissonFinal_d, float *Ex, float *Ey,
float L, int C) // recibe el potencial electroestatico calculado por la funcion poisson y se calcula el campo electrico, tanto para X como para Y
{
int i = blockIdx.x * blockDim.x + threadIdx.x;
float dx = L / float(C); // el delta de x representa el tamano de la malla
if (i < C) {
Ex[i * C] = (poissonFinal_d[((i + 1) * C) - 1]
- poissonFinal_d[(i * C) + 1]) / (2. * dx); // hallando el campo en x, en la primera columna
Ex[((i + 1) * C) - 1] = (poissonFinal_d[((i + 1) * C) - 2]
- poissonFinal_d[(i * C)]) / (2. * dx); // hallando el campo en x, en la ultima columna
Ey[((C - 1) * C) + i] = (poissonFinal_d[((C - 2) * C) + i]
- poissonFinal_d[i]) / (2. * dx); //hallando el campo en "y" para la ultima fila
Ey[i] = (poissonFinal_d[((C - 1) * C) + i] - poissonFinal_d[i + C])
/ (2. * dx); //hallando el campo para la primera fila y la ultima
}
}
__global__ void calculoCampoElectricoX(float *poissonFinal_d, float *Ex,
float L, int C) {
int i = blockIdx.x * blockDim.x + threadIdx.x;
int j = blockIdx.y * blockDim.y + threadIdx.y;
float dx = L / float(C); // el delta de x representa el tamano de la malla
if (i < C && j < C - 2) {
Ex[j + (C * i)] = (poissonFinal_d[j - 1] - poissonFinal_d[j + 1])
/ (2. * dx);
}
}
__global__ void calculoCampoElectricoY(float *poissonFinal_d, float *Ey,
float L, int C) {
int i = blockIdx.x * blockDim.x + threadIdx.x;
float dx = L / float(C); // el delta de x representa el tamano de la malla
if (i < ((C * C) - C)) {
Ey[i] = (poissonFinal_d[i - C] - poissonFinal_d[i + C]) / (2. * dx);
}
}
////////////////////////////////////////////////////////////////////////////////////////////////////////
void calculoCampoElectricoXY(float *poissonFinal_d, float *Ey_d, float *Ex_d,
float L, int C) {
float blockSize = 1024;
dim3 dimBlock(ceil(N / blockSize), 1, 1);
dim3 dimBlock2(ceil(C * C / blockSize), 1, 1);
dim3 dimBlock3(ceil(C * C / blockSize), ceil(C * C / blockSize), 1);
dim3 dimGrid(blockSize, 1, 1);
dim3 dimGrid3(blockSize, blockSize, 1);
ElectricBordes<<<blockSize, dimBlock2>>>(poissonFinal_d, Ex_d, Ey_d, L, C); // Campo Electrico en los bordes.
cudaDeviceSynchronize();
/*Calculo del campo electrico para x*/
calculoCampoElectricoX<<<dimGrid3, dimBlock3>>>(poissonFinal_d, Ex_d, L, C); // se utilizan dos hilos de debe organizar la manera como se envian.
/*Calculo del campo electrico para y*/
calculoCampoElectricoY<<<blockSize, dimBlock2>>>(poissonFinal_d, Ey_d, L,
C);
cudaDeviceSynchronize();
}
/////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
__global__ void cargar(float *rx_d, float *vx_d,
float *salidax, int N) {
int i = blockIdx.x * blockDim.x + threadIdx.x;
if (i < (N)) {
salidax[i] = rx_d[i];
salidax[N+i] = vx_d[i];
}
}
//////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
__global__ void descargar(float *rx_d, float *vx_d,
float *salidax, int N) {
int i = blockIdx.x * blockDim.x + threadIdx.x;
if (i < N) {
rx_d[i] = salidax[i];
vx_d[i] = salidax[N + i];
}
}
///////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
__global__ void escapeParticulas(float *rx_d, float *ry_d, int N, float L) {
int i = blockIdx.x * blockDim.x + threadIdx.x;
if (i < N) {
if (rx_d[i] < 0.)
rx_d[i] += L;
if (ry_d[i] < 0.)
ry_d[i] += L;
if (rx_d[i] > L)
rx_d[i] -= L;
if (ry_d[i] > L)
ry_d[i] -= L;
}
}
//////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
__global__ void calculoCampoELectricoPorParticula(float *campox_d, float *campoy_d,int *jx_d, int *jy_d, float *yx_d, float *yy_d, int C, int N, float *Ex_d, float *Ey_d){
int i = blockIdx.x * blockDim.x + threadIdx.x;
if (i < N) {
if ((jx_d[i]+1)%C == 0)
campox_d[i] = Ex_d[jx_d[i]] * (1. - yx_d[i]) + Ex_d[jx_d[i]-(C-1)] * yx_d[i];
else
campox_d[i] = Ex_d[jx_d[i]] * (1. - yx_d[i]) + Ex_d[jx_d[i]+1] * yx_d[i];
if ((jy_d[i]+1)%C == 0)
campoy_d[i] = Ey_d[jy_d[i]] * (1. - yy_d[i]) + Ey_d[jy_d[i]-(C-1)] * yy_d[i];
else
campoy_d[i] = Ey_d[jy_d[i]] * (1. - yy_d[i]) + Ey_d[jy_d[i]+1] * yy_d[i];
}
}
/////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
__global__ void asignacionDerivadas(float *rx_dot_d,
float *ry_dot_d, float *vx_dot_d, float *vy_dot_d,
float *vx_d, float *vy_d, float *campox_d, float *campoy_d, int N){
int i = blockIdx.x * blockDim.x + threadIdx.x;
if (i < N) {
rx_dot_d[i] = vx_d[i];
vx_dot_d[i] = - campox_d[i];
ry_dot_d[i] = vy_d[i];
vy_dot_d[i] = - campoy_d[i];
}
}
void evaluar(float *rx_d, float *ry_d, float *vx_d, float *vy_d, float *ne_d,
float *n_d, int *jx_d, int *jy_d, float *yx_d, float *yy_d, int C,
float L, cufftComplex *n_d_C, cufftComplex *T_F,
cufftComplex *T_F_N, cufftComplex *Phi_Poisson, cufftComplex *T_I,
float2 *calculoPoisson_d, float2 *calculoPoisson_h,
float *poissonFinal_d, float *Ey_d, float *Ex_d, float *rx_dot_d,
float *ry_dot_d, float *vx_dot_d, float *vy_dot_d, float *salidax_d, float *saliday_d){
float blockSize = 1024;
dim3 dimBlock(ceil(N / blockSize), 1, 1);
dim3 dimBlock4(ceil((2*N) / blockSize), 1, 1);
dim3 dimGrid(blockSize, 1, 1);
dim3 dimGrid3(blockSize, blockSize, 1);
/////////////////////////////////////////////////////////////////////////////////////////
float *campox, *campoy;
float *campox_d, *campoy_d;
/////////////////////////////////////////////////////////////////////////////////////////
int size = N * sizeof(float);
//////////////////////////////////////////////////////////////////////////////////////////
campox = (float *) malloc(size);
campoy = (float *) malloc(size);
cudaMalloc((void **) &campox_d, size);
cudaMalloc((void **) &campoy_d, size);
escapeParticulas<<<blockSize, dimBlock>>>(rx_d, ry_d, N, L);
cudaDeviceSynchronize();
///////////////////////////////////////////////////////////////////////////////////////////
Densidad(ne_d, n_d, rx_d, ry_d, jx_d, jy_d, yx_d, yy_d, C, L, N);
///////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
calculoPotencialElectroestatico(n_d, C, n_d_C, T_F, T_F_N, Phi_Poisson, T_I,
calculoPoisson_d, calculoPoisson_h, poissonFinal_d);
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
calculoCampoElectricoXY(poissonFinal_d, Ey_d, Ex_d, L, C);
/////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
calculoDensidadInicializacionCeldas<<<blockSize, dimBlock>>>(rx_d, ry_d,//Se utiliza la misma función de densidad para calcular el campo electrico en cada una de las particulas.
jx_d, jy_d, yx_d, yy_d, N, C, L);
cudaDeviceSynchronize();
/////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
calculoCampoELectricoPorParticula<<<blockSize, dimBlock>>>(campox_d, campoy_d,jx_d, jy_d, yx_d,yy_d, C, N, Ex_d,Ey_d);
cudaDeviceSynchronize();
/////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
asignacionDerivadas<<<blockSize, dimBlock>>>(rx_dot_d,ry_dot_d, vx_dot_d,vy_dot_d,
vx_d, vy_d, campox_d,campoy_d,N);
cudaDeviceSynchronize();
/////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
cargar<<<blockSize, dimBlock4>>>(rx_dot_d, vx_dot_d,salidax_d, N);
cudaDeviceSynchronize();
cargar<<<blockSize, dimBlock4>>>(ry_dot_d, vy_dot_d,saliday_d, N);
cudaDeviceSynchronize();
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
free(campox);
free(campoy);
cudaFree(campox_d);
cudaFree(campoy_d);
}
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
/////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
int main() {
// Parametros
L = 64.0; // dominio de la solucion 0 <= x <= L (en longitudes de debye)
//L=LL*LL;
N = 10000; // Numero de particulas
C = 64; // Número de celdas.
float vb = 3.0; // velocidad promedio de los electrones
//float t = 0.0;
//double kappa = 2. * M_PI / (L);
float dt=0.1; // delta tiempo (en frecuencias inversas del plasma)
//float tmax=10000; // cantidad de iteraciones. deben ser 100 mil segun el material
//int skip = int (tmax / dt) / 10; //saltos del algoritmo para reportar datos
//int itera=0;
float salida = 0.0;
float dx = L / float(C);
/////////////////////////////////////////////////////////////////////////////////////////////////////
//Inicializacion de la posición de las particulas en x, y y velocidad en vx,vy del host y dispositivo.
float *rx_h, *ry_h, *vx_h, *vy_h;
float *rx_d, *ry_d, *vx_d, *vy_d;
int *jx_d, *jy_d;
float *yx_d, *yy_d;
////////////////////////////////////////////////////////////////////////////////////////////////////
// inicialización de las variables de densidad del host y dispositivo.
float *ne_h;
float *ne_d;
float *n_h; // densidad normalizada.
float *n_d; // densidad normalizada del dispositivo.
float2 *calculoPoisson_h;
float *salidax_h;
float *salidax_d;
float *saliday_h;
float *saliday_d;
float2 *calculoPoisson_d;
float * poissonFinal_h;
float * poissonFinal_d;
float *Ex_h;
float *Ey_h; //campoElectrico
float *Ex_d;
float *Ey_d; // Campo Electrico en el dispositivo.
float *rx_dot;
float *ry_dot;
float *vx_dot;
float *vy_dot; // dot significa la derivada
float *rx_dot_d;
float *ry_dot_d;
float *vx_dot_d;
float *vy_dot_d; // dot significa la derivada
////////////////////////////////////////////////////////////////////////////////////////////////////
/*Crear la variable tipo cufftComplex*/
cufftComplex *n_d_C; // covertir la densidad en una variable compleja.
cufftComplex *T_F; // primer paso de la transformada hacia adelante
cufftComplex *T_F_N; //Trasformada hacia adelante normalizada.
cufftComplex *Phi_Poisson; // esta variable muestra la solucion de poisson.
cufftComplex *T_I; // Transformada Inversa.
////////////////////////////////////////////////////////////////////////////////////////////////////
int size = N * sizeof(float);
int size1 = 2*N * sizeof(float);
int size_ne = C * C * sizeof(float);
int size_ne2 = C * C * sizeof(float2);
//////////////////////////////////////////////////////////////////////////////////////////////////////
//reserva en memoria al host
rx_h = (float *) malloc(size);
ry_h = (float *) malloc(size);
vx_h = (float *) malloc(size);
vy_h = (float *) malloc(size);
ne_h = (float *) malloc(size_ne);
n_h = (float *) malloc(size_ne);
calculoPoisson_h = (float2 *) malloc(size_ne2);
poissonFinal_h = (float *) malloc(size_ne);
Ex_h = (float *) malloc(size_ne);
Ey_h = (float *) malloc(size_ne);
salidax_h = (float *) malloc(size1);
saliday_h = (float *) malloc(size1);
rx_dot = (float *) malloc(size);
ry_dot = (float *) malloc(size);
vx_dot = (float *) malloc(size);
vy_dot = (float *) malloc(size);
//////////////////////////////////////////////////////////////////////////////////////////////////////
//reserva de memoria del dispositivo.
cudaMalloc((void **) &rx_d, size);
cudaMalloc((void **) &ry_d, size);
cudaMalloc((void **) &vx_d, size);
cudaMalloc((void **) &vy_d, size);
cudaMalloc((void **) &ne_d, size_ne);
cudaMalloc((void **) &n_d, size_ne);
cudaMalloc((void **) &jx_d, size);
cudaMalloc((void **) &jy_d, size);
cudaMalloc((void **) &yx_d, size);
cudaMalloc((void **) &yy_d, size);
cudaMalloc((void **) &calculoPoisson_d, size_ne2);
cudaMalloc((void **) &poissonFinal_d, size_ne);
cudaMalloc((void **) &Ex_d, size_ne);
cudaMalloc((void **) &Ey_d, size_ne);
cudaMalloc((void **) &salidax_d, size1);
cudaMalloc((void **) &saliday_d, size1);
cudaMalloc((void **) &rx_dot_d, size);
cudaMalloc((void **) &ry_dot_d, size);
cudaMalloc((void **) &vx_dot_d, size);
cudaMalloc((void **) &vy_dot_d, size);
/////////////////////////////////////////////////////////////////////////////////////////////////////////
/*Asignación de memoria a la variable tipo cufftComplex */
cudaMalloc((void **) &n_d_C, sizeof(cufftComplex) * C * C);
cudaMalloc((void **) &T_F, sizeof(cufftComplex) * C * C);
cudaMalloc((void **) &T_F_N, sizeof(cufftComplex) * C * C);
cudaMalloc((void **) &Phi_Poisson, sizeof(cufftComplex) * C * C);
cudaMalloc((void **) &T_I, sizeof(cufftComplex) * C * C);
//////////////////////////////////////////////////////////////////////////////////////////////////////////
//valores aleatorios y tamaños de los vectores.
curandState *devStates;
cudaMalloc((void **) &devStates, N * sizeof(curandState));
float blockSize = 1024;
dim3 dimBlock(ceil(N / blockSize), 1, 1);
dim3 dimBlock2(ceil(C * C / blockSize), 1, 1);
dim3 dimBlock3(ceil(C * C / blockSize), ceil(C * C / blockSize), 1);
dim3 dimGrid(blockSize, 1, 1);
dim3 dimGrid3(blockSize, blockSize, 1);
int seed = time(NULL);
distribucionParticulas<<<blockSize, dimBlock>>>(rx_d, ry_d, vx_d, vy_d, N,
devStates, vb, L, seed);
cudaDeviceSynchronize();
inicializacionDensidad<<<blockSize, dimBlock2>>>(ne_d, C);
cudaDeviceSynchronize();
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
evaluar(rx_d, ry_d, vx_d, vy_d, ne_d, n_d, jx_d, jy_d, yx_d, yy_d, C,L, n_d_C, T_F,T_F_N, Phi_Poisson, T_I,calculoPoisson_d, calculoPoisson_h,
poissonFinal_d, Ey_d, Ex_d, rx_dot_d,ry_dot_d, vx_dot_d, vy_dot_d, salidax_d, saliday_d);
/////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
//posicion en x.
cudaMemcpy(rx_h, rx_d, size, cudaMemcpyDeviceToHost);
// posicion en y.
cudaMemcpy(ry_h, ry_d, size, cudaMemcpyDeviceToHost);
// velocidad en x.
cudaMemcpy(vx_h, vx_d, size, cudaMemcpyDeviceToHost);
//velocidad en y.
cudaMemcpy(vy_h, vy_d, size, cudaMemcpyDeviceToHost);
//inicializacion densidades
cudaMemcpy(ne_h, ne_d, size_ne, cudaMemcpyDeviceToHost);
//normalización de la densidad.
cudaMemcpy(n_h, n_d, size_ne, cudaMemcpyDeviceToHost);
//calculo de la transformada rapida de fourier despues de la inversa.
cudaMemcpy(poissonFinal_h, poissonFinal_d, size_ne, cudaMemcpyDeviceToHost);
//Calculo de Campo Electrico Ex, Ey.
cudaMemcpy(Ex_h, Ex_d, size_ne, cudaMemcpyDeviceToHost);
cudaMemcpy(Ey_h, Ey_d, size_ne, cudaMemcpyDeviceToHost);
//actualización del las nuevas posiciones
cudaMemcpy(rx_dot, rx_dot_d, size, cudaMemcpyDeviceToHost);
cudaMemcpy(ry_dot, ry_dot_d, size, cudaMemcpyDeviceToHost);
cudaMemcpy(vx_dot, vx_dot_d, size, cudaMemcpyDeviceToHost);
cudaMemcpy(vy_dot, vy_dot_d, size, cudaMemcpyDeviceToHost);
//verificacion del vector salida.
cudaMemcpy(salidax_h, salidax_d, size1, cudaMemcpyDeviceToHost);
cudaMemcpy(saliday_h, saliday_d, size1, cudaMemcpyDeviceToHost);
/////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
ofstream init;
init.open("distribucionInicial.txt");
for (int i = 0; i < N; i++) {
init << rx_h[i] << " " << ry_h[i] << " " << vx_h[i] << " " << vy_h[i]
<< endl;
}
init.close();
init.open("salida_densidad3.txt");
for (int i = 0; i < C * C; i++) {
init << ne_h[i] << " " << endl;
salida += ne_h[i];
}
init.close();
cout << salida << " " << dx << endl;
init.open("densidadNormalizada.txt");
for (int i = 0; i < C; i++) {
for (int j = 0; j < C; j++) {
init << n_h[(i * C) + j] << " ";
}
init << endl;
}
init.close();
cout << salida << " " << dx << endl;
init.open("CalculoPoissonAntesdeLaTranformadaInversa.txt");
for (int i = 0; i < C; i++) {
for (int j = 0; j < C; j++) {
init << calculoPoisson_h[(i * C) + j].x << " ";
}
init << endl;
}
init.close();
init.open("DespuesTransformadaInversaPoissonFinal");
for (int i = 0; i < C; i++) {
for (int j = 0; j < C; j++) {
init << poissonFinal_h[(i * C) + j] << " ";
}
init << endl;
}
init.close();
init.open("CamposElectricos");
for (int i = 0; i < C * C; i++) {
init << Ex_h[i] << " " << Ey_h[i] << endl;
}
init.close();
init.open("asignacionDerivadas");
for (int i = 0; i < (N); i++) {
init << rx_dot[i] << " " << ry_dot[i]<< " "<< vx_dot[i] << " "<< vy_dot[i] << endl;
}
init.close();
init.open("salida");
for (int i = 0; i < (2*N); i++) {
init << salidax_h[i]<< " " << saliday_h[i]<< endl;
}
init.close();
///////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
/*Liberar memoria*/
free(rx_h);
free(ry_h);
free(vx_h);
free(vy_h);
free(ne_h);
free(n_h);
free(calculoPoisson_h);
free(poissonFinal_h);
free(Ex_h);
free(Ey_h);
free(salidax_h);
free(saliday_h);
free(rx_dot);
free(ry_dot);
free(vx_dot);
free(vy_dot);
cudaFree(rx_d);
cudaFree(ry_d);
cudaFree(vx_d);
cudaFree(vy_d);
cudaFree(ne_d);
cudaFree(n_d);
cudaFree(n_d_C);
cudaFree(T_F);
cudaFree(T_F_N);
cudaFree(Phi_Poisson);
cudaFree(T_I);
cudaFree(calculoPoisson_d);
cudaFree(poissonFinal_d);
cudaFree(Ex_d);
cudaFree(Ey_d);
cudaFree(salidax_d);
cudaFree(saliday_d);
cudaFree(rx_dot_d);
cudaFree(ry_dot_d);
cudaFree(vx_dot_d);
cudaFree(vy_dot_d);
return (0);
}
|
8,908 |
// KnapsackDemo.GpuBruteForceSolver
extern "C" __global__ void add(int chunkSize, int maxWeight, int* weights, int weightsLen0, int* values, int valuesLen0, int* results, int resultsLen0, int resultsLen1);
// KnapsackDemo.GpuBruteForceSolver
extern "C" __global__ void add(int chunkSize, int maxWeight, int* weights, int weightsLen0, int* values, int valuesLen0, int* results, int resultsLen0, int resultsLen1)
{
int num = threadIdx.x + blockIdx.x * blockDim.x;
results[(num) * resultsLen1 + (0)] = 0;
results[(num) * resultsLen1 + (1)] = 0;
int num2 = valuesLen0;
int num3 = 0;
int num4 = 0;
int i = num * chunkSize;
int num5 = i + chunkSize;
while (i < num5)
{
int num6 = 0;
int num7 = 0;
for (int j = 0; j < num2; j++)
{
int num8 = i & 1 << (j & 31);
if (num8 > 0)
{
num6 += values[(j)];
num7 += weights[(j)];
}
}
if (num7 <= maxWeight && num6 > num4)
{
num3 = i;
num4 = num6;
}
i++;
}
results[(num) * resultsLen1 + (0)] = num3;
results[(num) * resultsLen1 + (1)] = num4;
}
|
8,909 | #include <stdio.h>
#include <cuda_runtime.h>
__global__ void vectorAdd(float *d_A, float *d_B, float *d_C, int n) {
//int i = blockDim.x * blockIdx.x + threadIdx.x;
int i = threadIdx.x;
// Make sure we do not go out of bounds.
if (i < n) {
d_C[i] = d_A[i] + d_B[i];
}
}
int main() {
// Size of vectors
int n = 16;
// Size, in bytes, of each vector
size_t bytes = n * sizeof(float);
// Allocate memory for the host vectors
float *h_A = (float *)malloc(bytes);
float *h_B = (float *)malloc(bytes);
float *h_C = (float *)malloc(bytes);
// Initialize vectors
for (int i = 0; i < n; ++i) {
h_A[i] = 1;
h_B[i] = 2;
}
// Allocate memory for the device vectors
float *d_A = NULL;
cudaMalloc((void **)&d_A, bytes);
float *d_B = NULL;
cudaMalloc((void **)&d_B, bytes);
float *d_C = NULL;
cudaMalloc((void **)&d_C, bytes);
// Copy the host vectors to the device
cudaMemcpy(d_A, h_A, bytes, cudaMemcpyHostToDevice);
cudaMemcpy(d_B, h_B, bytes, cudaMemcpyHostToDevice);
// Execute the kernel
int threadsPerBlock = 256;
int blocksPerGrid =(n + threadsPerBlock - 1) / threadsPerBlock;
//vectorAdd<<<blocksPerGrid, threadsPerBlock>>>(d_A, d_B, d_C, n);
vectorAdd<<<1, n>>>(d_A, d_B, d_C, n);
printf("Kernel launch with %d blocks of %d threads\n", blocksPerGrid, threadsPerBlock);
// Copy the result back to the host result vector
cudaMemcpy(h_C, d_C, bytes, cudaMemcpyDeviceToHost);
// Sum up host result vector and print result divided by n, this should equal 4
float sum = 0;
int i;
for(i=0; i<n; i++) {
sum += h_C[i];
}
sum = sum/n;
printf("Final result: %f\n", sum);
// Free device global memory
cudaFree(d_A);
cudaFree(d_B);
cudaFree(d_C);
// Free host memory
free(h_A);
free(h_B);
free(h_C);
// Explicitly destroys and cleans up all resources associated with the current device
cudaDeviceReset();
return 0;
} |
8,910 | //============================================================================
// Name : Unordered Reduction.cpp
// Author :
// Version :
// Copyright :
// Description : Test of the segment add plug-in
//============================================================================
#include <cuda_runtime.h>
#include <iostream>
#include <string>
#include <ctime>
#include <cstdlib>
#include <cmath>
#include <limits>
#include <algorithm>
#include <limits>
static void CheckCudaErrorAux (const char *, unsigned, const char *, cudaError_t);
#define CUDA_CHECK_RETURN(value) CheckCudaErrorAux(__FILE__,__LINE__, #value, value)
#define PER_THREAD_INIT_NUM 1
#define PER_THREAD_SEG_NUM 32
#define ARRAY_SIZE (1024 * 1024 * 32)
#define MAX_NUM 4
#define THREAD_NUM 1024
#define SEGMENT_NUM 512
typedef int operand_type;
template<typename T, typename std::enable_if<std::is_same<T, int64_t>::value == false, void>::type* = nullptr>
__device__ void SumOpByType(T *addr, T value)
{
atomicAdd(addr, value);
}
template<typename T, typename std::enable_if<std::is_same<T, int64_t>::value, void>::type* = nullptr>
__device__ void SumOpByType(T *addr, T value)
{
unsigned long long int *addr_temp = (unsigned long long int *)addr;
unsigned long long int value_temp = (unsigned long long int) value;
atomicAdd(addr_temp, value_temp);
}
template <typename T>
struct SumOp {
__device__ void operator()(T *addr, T value) {
SumOpByType(addr, value);
}
};
template<typename T, typename std::enable_if<std::is_same<T, float>::value, void>::type* = nullptr>
__device__ void MaxOpByType(T *addr, T value)
{
unsigned int *address = (unsigned int *)addr;
unsigned int value_old = *address, value_assumed;
do {
value_assumed = value_old;
value_old = atomicCAS(address,
value_assumed,
__float_as_uint(value > __uint_as_float(value_assumed) ? value : __uint_as_float(value_assumed)));
} while (value_assumed != value_old);
}
template<typename T, typename std::enable_if<std::is_same<T, double>::value, void>::type* = nullptr>
__device__ void MaxOpByType(T *addr, T value)
{
unsigned long long int *address = (unsigned long long int *)addr;
unsigned long long int value_old = *address, value_assumed;
do {
value_assumed = value_old;
value_old = atomicCAS(address,
value_assumed,
__double_as_longlong(value > __longlong_as_double(value_assumed) ? value : __longlong_as_double(value_assumed)));
} while (value_assumed != value_old);
}
template<typename T, typename std::enable_if<std::is_same<T, unsigned int>::value || std::is_same<T, unsigned long long int>::value ||
std::is_same<T, int>::value || std::is_same<T, long long int>::value, void>::type* = nullptr>
__device__ void MaxOpByType(T *addr, T value)
{
atomicMax(addr, value);
}
template<typename T, typename std::enable_if<std::is_same<T, int64_t>::value, void>::type* = nullptr>
__device__ void MaxOpByType(T *addr, T value)
{
unsigned long long int *addr_temp = (unsigned long long int *)addr;
unsigned long long int value_temp = (unsigned long long int) value;
atomicMax(addr_temp, value_temp);
}
template <typename T>
struct MaxOp {
__device__ void operator()(T *addr, T value) {
MaxOpByType(addr, value);
}
};
template<typename T, typename std::enable_if<std::is_same<T, float>::value, void>::type* = nullptr>
__device__ void MulOpByType(T *addr, T value)
{
unsigned int *address = (unsigned int *)addr;
unsigned int value_old = *address, value_assumed;
do {
value_assumed = value_old;
value_old = atomicCAS(address,
value_assumed,
__float_as_uint(value * __uint_as_float(value_assumed)));
} while (value_assumed != value_old);
}
template<typename T, typename std::enable_if<std::is_same<T, int>::value || std::is_same<T, unsigned int>::value, void>::type* = nullptr>
__device__ void MulOpByType(T *addr, T value)
{
unsigned int *address = (unsigned int *)addr;
unsigned int value_old = *address, value_assumed;
do {
value_assumed = value_old;
value_old = atomicCAS(address,
value_assumed,
(value * value_assumed));
} while (value_assumed != value_old);
}
template<typename T, typename std::enable_if<std::is_same<T, double>::value, void>::type* = nullptr>
__device__ void MulOpByType(T *addr, T value)
{
unsigned long long int *address = (unsigned long long int *)addr;
unsigned long long int value_old = *address, value_assumed;
do {
value_assumed = value_old;
value_old = atomicCAS(address,
value_assumed,
__double_as_longlong(value * __longlong_as_double(value_assumed)));
} while (value_assumed != value_old);
}
template<typename T, typename std::enable_if<std::is_same<T, long long int>::value ||
std::is_same<T, unsigned long long int>::value ||
std::is_same<T, int64_t>::value, void>::type* = nullptr>
__device__ void MulOpByType(T *addr, T value)
{
unsigned long long int *address = (unsigned long long int *)addr;
unsigned long long int value_old = *address, value_assumed;
do {
value_assumed = value_old;
value_old = atomicCAS(address,
value_assumed,
((unsigned long long int)value * value_assumed));
} while (value_assumed != value_old);
}
template <typename T>
struct MulOp {
__device__ void operator()(T *addr, T value) {
MulOpByType(addr, value);
}
};
template <typename T>
__global__ void InitValue(T *input, int total_size, T value) {
int index = blockIdx.x * blockDim.x + threadIdx.x;
if (index < value) {
int split_size = total_size / PER_THREAD_INIT_NUM;
#pragma unroll
for (int i = 0; i < PER_THREAD_INIT_NUM; i++) {
input[i * split_size + index] = value;
}
}
}
template <typename ReductionF, typename T>
__global__ void Segmentation(T *__restrict__ input_data,
int *__restrict__ input_segment_id,
T *__restrict__ output_segment_result,
int segment_result_size,
int total_size,
T initial_value) {
extern __shared__ int segment_result_slm_shared[];
T *segment_result_slm = (T *)segment_result_slm_shared;
int index = blockIdx.x * blockDim.x + threadIdx.x;
int split_size = total_size / PER_THREAD_SEG_NUM;
int local_index = threadIdx.x;
int local_size = blockDim.x;
int loop_slm = (segment_result_size + local_size - 1) / local_size;
if (index < total_size) {
for (int i = 0; i < loop_slm; i++) {
int slm_index = i * local_size + local_index;
if (slm_index < segment_result_size) {
segment_result_slm[slm_index] = initial_value;
}
}
__syncthreads();
#pragma unroll
for (int i = 0; i < PER_THREAD_SEG_NUM; i++) {
int split_index = index + split_size * i;
if (split_index < total_size) {
int segment_id = input_segment_id[split_index];
T data_value = input_data[split_index];
ReductionF()(segment_result_slm + segment_id, data_value);
}
}
__syncthreads();
for (int i = 0; i < loop_slm; i++) {
int slm_index = i * local_size + local_index;
if (slm_index < segment_result_size) {
if (slm_index < segment_result_size) {
ReductionF()(output_segment_result + slm_index, segment_result_slm[slm_index]);
}
}
}
}
}
int main(int argc, char **argv) {
operand_type *input_data = nullptr;
int *input_segment_id = nullptr;
operand_type *output_segment_result = nullptr;
operand_type *input_data_cpu = nullptr;
int *input_segment_id_cpu = nullptr;
operand_type *output_segment_result_cpu = nullptr;
operand_type *output_segment_result_gold = nullptr;
int array_num = ARRAY_SIZE;
int segment_num = SEGMENT_NUM;
int thread_num = THREAD_NUM;
float time = 0.0f;
int initial_value = 0;
cudaEvent_t event1, event2;
std::srand(std::time(nullptr));
int dev = cudaSetDevice(0);
CUDA_CHECK_RETURN(cudaMalloc((void **)&input_data, array_num * sizeof(operand_type)));
CUDA_CHECK_RETURN(cudaMalloc((void **)&input_segment_id, array_num * sizeof(int)));
CUDA_CHECK_RETURN(cudaMalloc((void **)&output_segment_result, segment_num * sizeof(operand_type)));
CUDA_CHECK_RETURN(cudaEventCreate(&event1));
CUDA_CHECK_RETURN(cudaEventCreate(&event2));
if ((input_data_cpu = new operand_type[array_num]) == nullptr) {
std::cout << "Allocation memory failure!" << std::endl;
return -1;
}
if ((input_segment_id_cpu = new int[array_num]) == nullptr) {
std::cout << "Allocation memory failure!" << std::endl;
return -1;
}
if ((output_segment_result_cpu = new operand_type[segment_num]) == nullptr) {
std::cout << "Allocation memory failure!" << std::endl;
return -1;
}
if ((output_segment_result_gold = new operand_type[segment_num]) == nullptr) {
std::cout << "Allocation memory failure!" << std::endl;
return -1;
}
// Initialize array
for (int i = 0; i < array_num; i++) {
input_data_cpu[i] = (float)rand() / RAND_MAX + 1.0f;
}
CUDA_CHECK_RETURN(cudaMemcpy(input_data, input_data_cpu, array_num * sizeof(operand_type), cudaMemcpyHostToDevice));
for (int i = 0; i < array_num; i++) {
input_segment_id_cpu[i] = rand() % segment_num;
}
CUDA_CHECK_RETURN(cudaMemcpy(input_segment_id, input_segment_id_cpu, array_num * sizeof(int), cudaMemcpyHostToDevice));
CUDA_CHECK_RETURN(cudaEventRecord(event1, 0));
InitValue<operand_type><<<1, segment_num / PER_THREAD_INIT_NUM>>>(output_segment_result, segment_num, initial_value);
CUDA_CHECK_RETURN(cudaEventRecord(event2, 0));
CUDA_CHECK_RETURN(cudaEventSynchronize(event2));
CUDA_CHECK_RETURN(cudaEventElapsedTime(&time, event1, event2));
std::cout << "Kernel InitValue Execution time " << time << " ms" << std::endl;
CUDA_CHECK_RETURN(cudaEventRecord(event1, 0));
int block_num = (array_num + PER_THREAD_SEG_NUM * thread_num - 1) / (PER_THREAD_SEG_NUM * thread_num);
Segmentation<SumOp<operand_type>, operand_type><<<block_num, thread_num, segment_num * sizeof(operand_type)>>>(input_data, input_segment_id, output_segment_result, segment_num, array_num, initial_value);
CUDA_CHECK_RETURN(cudaEventRecord(event2, 0));
CUDA_CHECK_RETURN(cudaEventSynchronize(event2));
CUDA_CHECK_RETURN(cudaEventElapsedTime(&time, event1, event2));
std::cout << "Kernel Segmentation Reduction time " << time << " ms" << std::endl;
CUDA_CHECK_RETURN(cudaEventRecord(event1, 0));
CUDA_CHECK_RETURN(cudaMemcpy(output_segment_result_cpu, output_segment_result, segment_num * sizeof(operand_type), cudaMemcpyDeviceToHost));
CUDA_CHECK_RETURN(cudaEventRecord(event2, 0));
CUDA_CHECK_RETURN(cudaEventSynchronize(event2));
CUDA_CHECK_RETURN(cudaEventElapsedTime(&time, event1, event2));
std::cout << "Memory copy time: " << time << " ms" << std::endl;
// compute and compare gold
for (int i = 0; i < segment_num; i++) {
output_segment_result_gold[i] = initial_value;
}
clock_t begin_clock = std::clock();
// sum reduction
for (int i = 0; i < array_num; i++) {
output_segment_result_gold[input_segment_id_cpu[i]] += input_data_cpu[i];
}
// max reduction
/*
for (int i = 0; i < array_num; i++) {
output_segment_result_gold[input_segment_id_cpu[i]] = output_segment_result_gold[input_segment_id_cpu[i]] > input_data_cpu[i] ? output_segment_result_gold[input_segment_id_cpu[i]] : input_data_cpu[i];
}
*/
/*
// mul reduction
for (int i = 0; i < array_num; i++) {
output_segment_result_gold[input_segment_id_cpu[i]] *= input_data_cpu[i];
}
*/
clock_t end_clock = std::clock();
double elapsed_cpu = double(end_clock - begin_clock) / CLOCKS_PER_SEC * 1000.0;
std::cout << "CPU reduction time " << elapsed_cpu << " ms" << std::endl;
for (int i = 0; i < segment_num; i++) {
std::cout << "gpu result: " << output_segment_result_cpu[i] << " gold result: " << output_segment_result_gold[i] << std::endl;
if ((output_segment_result_cpu[i] != output_segment_result_gold[i])) {
std::cout << "Error comparing with Gold! " << "Position " << i << std::endl;
return -1;
}
}
std::cout << "Test passed! " << std::endl;
// clean up
if (input_data_cpu != nullptr) {
delete[] input_data_cpu;
}
if (input_segment_id_cpu != nullptr) {
delete[] input_segment_id_cpu;
}
if (output_segment_result_cpu != nullptr) {
delete[] output_segment_result_cpu;
}
if (output_segment_result_gold != nullptr) {
delete[] output_segment_result_gold;
}
cudaFree(output_segment_result);
cudaFree(input_segment_id);
cudaFree(input_data);
return 0;
}
/**
* Check the return value of the CUDA runtime API call and exit
* the application if the call has failed.
*/
static void CheckCudaErrorAux (const char *file, unsigned line, const char *statement, cudaError_t err)
{
if (err == cudaSuccess)
return;
std::cerr << statement<<" returned " << cudaGetErrorString(err) << "("<<err<< ") at "<<file<<":"<<line << std::endl;
exit (1);
}
|
8,911 | #include<iostream>
#include<vector>
const int SHARED_MEM = 256*sizeof(int);
__global__ void convKernel(int *a, int *m, int *r, int N, int M){
int index = threadIdx.x+ blockIdx.x*blockDim.x;
__shared__ int sh[SHARED_MEM];
sh[threadIdx.x] = a[index];
__syncthreads();
// int dist = M/2;
int temp = 0;
for(int j = 0; j < M; j++){
if(threadIdx.x+j<blockDim.x){
temp += sh[threadIdx.x+j]*m[j];
}
if(threadIdx.x+j>=blockDim.x){
temp += a[index+j]*m[j];
}
}
r[index] = temp;
}
int main(){
int N = 1024;
int M = 5;
int array_size = N*sizeof(int);
int filter_size = M*sizeof(int);
std::vector<int> feature(N);
std::vector<int> filter(M);
std::vector<int> result(N);
int *d_feature, *d_filter, *d_result;
cudaMalloc((void **)&d_feature, array_size);
cudaMalloc((void **)&d_filter, filter_size);
cudaMalloc((void **)&d_result, array_size);
for(auto& i:feature){i = rand()%10;}
for(auto& i:filter){i = rand()%10;}
cudaMemcpy(d_feature, feature.data(), array_size, cudaMemcpyHostToDevice);
cudaMemcpy(d_filter, filter.data(), filter_size, cudaMemcpyHostToDevice);
int threadsPerBlock = 256;
int blocksPerGrid = (N+threadsPerBlock-1)/threadsPerBlock;
convKernel<<<blocksPerGrid, threadsPerBlock>>>(d_feature, d_filter, d_result, N, M);
cudaMemcpy(result.data(), d_result, array_size, cudaMemcpyDeviceToHost);
for(const auto& i:result){std::cout << i << std::endl;}
cudaFree(d_feature);
cudaFree(d_filter);
cudaFree(d_result);
return 0;
}
|
8,912 | /*
Copyright 2016 Tommi M. Tykkl
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.
*/
#ifdef __DEVICE_EMULATION__
#define EMUSYNC __syncthreads()
#else
#define EMUSYNC
#endif
// Utility class used to avoid linker errors with extern
// unsized shared memory arrays with templated type
template<class T>
struct SharedMemory
{
__device__ inline operator T*()
{
extern __shared__ int __smem[];
return (T*)__smem;
}
__device__ inline operator const T*() const
{
extern __shared__ int __smem[];
return (T*)__smem;
}
};
// specialize for double to avoid unaligned memory
// access compile errors
template<>
struct SharedMemory<double>
{
__device__ inline operator double*()
{
extern __shared__ double __smem_d[];
return (double*)__smem_d;
}
__device__ inline operator const double*() const
{
extern __shared__ double __smem_d[];
return (double*)__smem_d;
}
};
template <class T>
__global__ void reduceProduct0(T *g_idataA, T *g_idataB, T *g_odata, unsigned int n)
{
T *sdata = SharedMemory<T>();
// load shared mem
unsigned int tid = threadIdx.x;
unsigned int i = blockIdx.x*blockDim.x + threadIdx.x;
sdata[tid] = (i < n) ? (g_idataA[i]*g_idataB[i]) : 0;
__syncthreads();
// do reduction in shared mem
for(unsigned int s=1; s < blockDim.x; s *= 2) {
// modulo arithmetic is slow!
if ((tid % (2*s)) == 0) {
sdata[tid] += sdata[tid + s];
}
__syncthreads();
}
// write result for this block to global mem
if (tid == 0) g_odata[blockIdx.x] = sdata[0];
}
template <class T>
__global__ void reduceProduct1(T *g_idataA, T *g_idataB, T *g_odata, unsigned int n)
{
T *sdata = SharedMemory<T>();
// load shared mem
unsigned int tid = threadIdx.x;
unsigned int i = blockIdx.x*blockDim.x + threadIdx.x;
sdata[tid] = (i < n) ? (g_idataA[i]*g_idataB[i]) : 0;
__syncthreads();
// do reduction in shared mem
for(unsigned int s=1; s < blockDim.x; s *= 2)
{
int index = 2 * s * tid;
if (index < blockDim.x)
{
sdata[index] += sdata[index + s];
}
__syncthreads();
}
// write result for this block to global mem
if (tid == 0) g_odata[blockIdx.x] = sdata[0];
}
template <class T>
__global__ void reduceProduct2(T *g_idataA, T *g_idataB, T *g_odata, unsigned int n)
{
T *sdata = SharedMemory<T>();
// load shared mem
unsigned int tid = threadIdx.x;
unsigned int i = blockIdx.x*blockDim.x + threadIdx.x;
sdata[tid] = (i < n) ? (g_idataA[i]*g_idataB[i]) : 0;
__syncthreads();
// do reduction in shared mem
for(unsigned int s=blockDim.x/2; s>0; s>>=1)
{
if (tid < s)
{
sdata[tid] += sdata[tid + s];
}
__syncthreads();
}
// write result for this block to global mem
if (tid == 0) g_odata[blockIdx.x] = sdata[0];
}
template <class T>
__global__ void reduceProduct3(T *g_idataA, T *g_idataB, T *g_odata, unsigned int n)
{
T *sdata = SharedMemory<T>();
// perform first level of reduction,
// reading from global memory, writing to shared memory
unsigned int tid = threadIdx.x;
unsigned int i = blockIdx.x*(blockDim.x*2) + threadIdx.x;
T mySum = (i < n) ? (g_idataA[i]*g_idataB[i]) : 0;
if (i + blockDim.x < n)
mySum += g_idataA[i+blockDim.x]*g_idataB[i+blockDim.x];
sdata[tid] = mySum;
__syncthreads();
// do reduction in shared mem
for(unsigned int s=blockDim.x/2; s>0; s>>=1)
{
if (tid < s)
{
sdata[tid] = mySum = mySum + sdata[tid + s];
}
__syncthreads();
}
// write result for this block to global mem
if (tid == 0) g_odata[blockIdx.x] = sdata[0];
}
template <class T, unsigned int blockSize>
__global__ void reduceProduct4(T *g_idataA, T *g_idataB, T *g_odata, unsigned int n)
{
T *sdata = SharedMemory<T>();
// perform first level of reduction,
// reading from global memory, writing to shared memory
unsigned int tid = threadIdx.x;
unsigned int i = blockIdx.x*(blockDim.x*2) + threadIdx.x;
T mySum = (i < n) ? (g_idataA[i]*g_idataB[i]) : 0;
if (i + blockSize < n)
mySum += g_idataA[i+blockSize]*g_idataB[i+blockSize];
sdata[tid] = mySum;
__syncthreads();
// do reduction in shared mem
for(unsigned int s=blockDim.x/2; s>32; s>>=1)
{
if (tid < s)
{
sdata[tid] = mySum = mySum + sdata[tid + s];
}
__syncthreads();
}
#ifndef __DEVICE_EMULATION__
if (tid < 32)
#endif
{
// now that we are using warp-synchronous programming (below)
// we need to declare our shared memory volatile so that the compiler
// doesn't reorder stores to it and induce incorrect behavior.
volatile T *smem = sdata;
if (blockSize >= 64) { smem[tid] = mySum = mySum + smem[tid + 32]; EMUSYNC; }
if (blockSize >= 32) { smem[tid] = mySum = mySum + smem[tid + 16]; EMUSYNC; }
if (blockSize >= 16) { smem[tid] = mySum = mySum + smem[tid + 8]; EMUSYNC; }
if (blockSize >= 8) { smem[tid] = mySum = mySum + smem[tid + 4]; EMUSYNC; }
if (blockSize >= 4) { smem[tid] = mySum = mySum + smem[tid + 2]; EMUSYNC; }
if (blockSize >= 2) { smem[tid] = mySum = mySum + smem[tid + 1]; EMUSYNC; }
}
// write result for this block to global mem
if (tid == 0) g_odata[blockIdx.x] = sdata[0];
}
template <class T, unsigned int blockSize>
__global__ void reduceProduct5(T *g_idataA, T *g_idataB, T *g_odata, unsigned int n)
{
T *sdata = SharedMemory<T>();
// perform first level of reduction,
// reading from global memory, writing to shared memory
unsigned int tid = threadIdx.x;
unsigned int i = blockIdx.x*(blockSize*2) + threadIdx.x;
T mySum = (i < n) ? (g_idataA[i]*g_idataB[i]) : 0;
if (i + blockSize < n)
mySum += g_idataA[i+blockSize]*g_idataB[i+blockSize];
sdata[tid] = mySum;
__syncthreads();
// do reduction in shared mem
if (blockSize >= 512) { if (tid < 256) { sdata[tid] = mySum = mySum + sdata[tid + 256]; } __syncthreads(); }
if (blockSize >= 256) { if (tid < 128) { sdata[tid] = mySum = mySum + sdata[tid + 128]; } __syncthreads(); }
if (blockSize >= 128) { if (tid < 64) { sdata[tid] = mySum = mySum + sdata[tid + 64]; } __syncthreads(); }
#ifndef __DEVICE_EMULATION__
if (tid < 32)
#endif
{
// now that we are using warp-synchronous programming (below)
// we need to declare our shared memory volatile so that the compiler
// doesn't reorder stores to it and induce incorrect behavior.
volatile T* smem = sdata;
if (blockSize >= 64) { smem[tid] = mySum = mySum + smem[tid + 32]; EMUSYNC; }
if (blockSize >= 32) { smem[tid] = mySum = mySum + smem[tid + 16]; EMUSYNC; }
if (blockSize >= 16) { smem[tid] = mySum = mySum + smem[tid + 8]; EMUSYNC; }
if (blockSize >= 8) { smem[tid] = mySum = mySum + smem[tid + 4]; EMUSYNC; }
if (blockSize >= 4) { smem[tid] = mySum = mySum + smem[tid + 2]; EMUSYNC; }
if (blockSize >= 2) { smem[tid] = mySum = mySum + smem[tid + 1]; EMUSYNC; }
}
// write result for this block to global mem
if (tid == 0) g_odata[blockIdx.x] = sdata[0];
}
template <class T, unsigned int blockSize, bool nIsPow2>
__global__ void reduceProduct6(T *g_idataA, T *g_idataB, T *g_odata, unsigned int n)
{
T *sdata = SharedMemory<T>();
// perform first level of reduction,
// reading from global memory, writing to shared memory
unsigned int tid = threadIdx.x;
unsigned int i = blockIdx.x*blockSize*2 + threadIdx.x;
unsigned int gridSize = blockSize*2*gridDim.x;
T mySum = 0;
// we reduce multiple elements per thread. The number is determined by the
// number of active thread blocks (via gridDim). More blocks will result
// in a larger gridSize and therefore fewer elements per thread
while (i < n)
{
mySum += g_idataA[i]*g_idataB[i];
// ensure we don't read out of bounds -- this is optimized away for powerOf2 sized arrays
if (nIsPow2 || i + blockSize < n)
mySum += g_idataA[i+blockSize]*g_idataB[i+blockSize];
i += gridSize;
}
// each thread puts its local sum into shared memory
sdata[tid] = mySum;
__syncthreads();
// do reduction in shared mem
if (blockSize >= 512) { if (tid < 256) { sdata[tid] = mySum = mySum + sdata[tid + 256]; } __syncthreads(); }
if (blockSize >= 256) { if (tid < 128) { sdata[tid] = mySum = mySum + sdata[tid + 128]; } __syncthreads(); }
if (blockSize >= 128) { if (tid < 64) { sdata[tid] = mySum = mySum + sdata[tid + 64]; } __syncthreads(); }
#ifndef __DEVICE_EMULATION__
if (tid < 32)
#endif
{
// now that we are using warp-synchronous programming (below)
// we need to declare our shared memory volatile so that the compiler
// doesn't reorder stores to it and induce incorrect behavior.
volatile T* smem = sdata;
if (blockSize >= 64) { smem[tid] = mySum = mySum + smem[tid + 32]; EMUSYNC; }
if (blockSize >= 32) { smem[tid] = mySum = mySum + smem[tid + 16]; EMUSYNC; }
if (blockSize >= 16) { smem[tid] = mySum = mySum + smem[tid + 8]; EMUSYNC; }
if (blockSize >= 8) { smem[tid] = mySum = mySum + smem[tid + 4]; EMUSYNC; }
if (blockSize >= 4) { smem[tid] = mySum = mySum + smem[tid + 2]; EMUSYNC; }
if (blockSize >= 2) { smem[tid] = mySum = mySum + smem[tid + 1]; EMUSYNC; }
}
// write result for this block to global mem
if (tid == 0) {
g_odata[blockIdx.x] = sdata[0];
}
}
bool isPow2(unsigned int x)
{
return ((x&(x-1))==0);
}
////////////////////////////////////////////////////////////////////////////////
// Wrapper function for kernel launch
////////////////////////////////////////////////////////////////////////////////
template <class T>
void reduceProducts(int size, int threads, int blocks,
int whichKernel, T *d_idataA, T *d_idataB, T *d_odata, cudaStream_t stream)
{
dim3 dimBlock(threads, 1, 1);
dim3 dimGrid(blocks, 1, 1);
// when there is only one warp per block, we need to allocate two warps
// worth of shared memory so that we don't index shared memory out of bounds
int smemSize = (threads <= 32) ? 2 * threads * sizeof(T) : threads * sizeof(T);
// choose which of the optimized versions of reduction to launch
switch (whichKernel)
{
case 0:
reduceProduct0<T><<< dimGrid, dimBlock, smemSize, stream >>>(d_idataA, d_idataB, d_odata, size);
break;
case 1:
reduceProduct1<T><<< dimGrid, dimBlock, smemSize, stream >>>(d_idataA, d_idataB, d_odata, size);
break;
case 2:
reduceProduct2<T><<< dimGrid, dimBlock, smemSize, stream >>>(d_idataA, d_idataB, d_odata, size);
break;
case 3:
reduceProduct3<T><<< dimGrid, dimBlock, smemSize, stream >>>(d_idataA, d_idataB, d_odata, size);
break;
case 4:
switch (threads)
{
case 1024:
reduceProduct4<T, 1024><<< dimGrid, dimBlock, smemSize, stream >>>(d_idataA, d_idataB, d_odata, size); break;
case 512:
reduceProduct4<T, 512><<< dimGrid, dimBlock, smemSize, stream >>>(d_idataA, d_idataB, d_odata, size); break;
case 256:
reduceProduct4<T, 256><<< dimGrid, dimBlock, smemSize, stream >>>(d_idataA, d_idataB, d_odata, size); break;
case 128:
reduceProduct4<T, 128><<< dimGrid, dimBlock, smemSize, stream >>>(d_idataA, d_idataB, d_odata, size); break;
case 64:
reduceProduct4<T, 64><<< dimGrid, dimBlock, smemSize, stream >>>(d_idataA, d_idataB, d_odata, size); break;
case 32:
reduceProduct4<T, 32><<< dimGrid, dimBlock, smemSize, stream >>>(d_idataA, d_idataB, d_odata, size); break;
case 16:
reduceProduct4<T, 16><<< dimGrid, dimBlock, smemSize, stream >>>(d_idataA, d_idataB, d_odata, size); break;
case 8:
reduceProduct4<T, 8><<< dimGrid, dimBlock, smemSize, stream >>>(d_idataA, d_idataB, d_odata, size); break;
case 4:
reduceProduct4<T, 4><<< dimGrid, dimBlock, smemSize, stream >>>(d_idataA, d_idataB, d_odata, size); break;
case 2:
reduceProduct4<T, 2><<< dimGrid, dimBlock, smemSize, stream >>>(d_idataA, d_idataB, d_odata, size); break;
case 1:
reduceProduct4<T, 1><<< dimGrid, dimBlock, smemSize, stream >>>(d_idataA, d_idataB, d_odata, size); break;
}
break;
case 5:
switch (threads)
{
case 1024:
reduceProduct5<T, 1024><<< dimGrid, dimBlock, smemSize, stream >>>(d_idataA, d_idataB, d_odata, size); break;
case 512:
reduceProduct5<T, 512><<< dimGrid, dimBlock, smemSize, stream >>>(d_idataA, d_idataB, d_odata, size); break;
case 256:
reduceProduct5<T, 256><<< dimGrid, dimBlock, smemSize, stream >>>(d_idataA, d_idataB, d_odata, size); break;
case 128:
reduceProduct5<T, 128><<< dimGrid, dimBlock, smemSize, stream >>>(d_idataA, d_idataB, d_odata, size); break;
case 64:
reduceProduct5<T, 64><<< dimGrid, dimBlock, smemSize, stream >>>(d_idataA, d_idataB, d_odata, size); break;
case 32:
reduceProduct5<T, 32><<< dimGrid, dimBlock, smemSize, stream >>>(d_idataA, d_idataB, d_odata, size); break;
case 16:
reduceProduct5<T, 16><<< dimGrid, dimBlock, smemSize, stream >>>(d_idataA, d_idataB, d_odata, size); break;
case 8:
reduceProduct5<T, 8><<< dimGrid, dimBlock, smemSize, stream >>>(d_idataA, d_idataB, d_odata, size); break;
case 4:
reduceProduct5<T, 4><<< dimGrid, dimBlock, smemSize, stream >>>(d_idataA, d_idataB, d_odata, size); break;
case 2:
reduceProduct5<T, 2><<< dimGrid, dimBlock, smemSize, stream >>>(d_idataA, d_idataB, d_odata, size); break;
case 1:
reduceProduct5<T, 1><<< dimGrid, dimBlock, smemSize, stream >>>(d_idataA, d_idataB, d_odata, size); break;
}
break;
case 6:
default:
if (isPow2(size))
{
switch (threads)
{
case 1024:
reduceProduct6<T, 1024, true><<< dimGrid, dimBlock, smemSize, stream >>>(d_idataA, d_idataB, d_odata, size); break;
case 512:
reduceProduct6<T, 512, true><<< dimGrid, dimBlock, smemSize, stream >>>(d_idataA, d_idataB, d_odata, size); break;
case 256:
reduceProduct6<T, 256, true><<< dimGrid, dimBlock, smemSize, stream >>>(d_idataA, d_idataB, d_odata, size); break;
case 128:
reduceProduct6<T, 128, true><<< dimGrid, dimBlock, smemSize, stream >>>(d_idataA, d_idataB, d_odata, size); break;
case 64:
reduceProduct6<T, 64, true><<< dimGrid, dimBlock, smemSize, stream >>>(d_idataA, d_idataB, d_odata, size); break;
case 32:
reduceProduct6<T, 32, true><<< dimGrid, dimBlock, smemSize, stream >>>(d_idataA, d_idataB, d_odata, size); break;
case 16:
reduceProduct6<T, 16, true><<< dimGrid, dimBlock, smemSize, stream >>>(d_idataA, d_idataB, d_odata, size); break;
case 8:
reduceProduct6<T, 8, true><<< dimGrid, dimBlock, smemSize, stream >>>(d_idataA, d_idataB, d_odata, size); break;
case 4:
reduceProduct6<T, 4, true><<< dimGrid, dimBlock, smemSize, stream >>>(d_idataA, d_idataB, d_odata, size); break;
case 2:
reduceProduct6<T, 2, true><<< dimGrid, dimBlock, smemSize, stream >>>(d_idataA, d_idataB, d_odata, size); break;
case 1:
reduceProduct6<T, 1, true><<< dimGrid, dimBlock, smemSize, stream >>>(d_idataA, d_idataB, d_odata, size); break;
}
}
else
{
switch (threads)
{
case 1024:
reduceProduct6<T, 1024, false><<< dimGrid, dimBlock, smemSize, stream >>>(d_idataA, d_idataB, d_odata, size); break;
case 512:
reduceProduct6<T, 512, false><<< dimGrid, dimBlock, smemSize, stream >>>(d_idataA, d_idataB, d_odata, size); break;
case 256:
reduceProduct6<T, 256, false><<< dimGrid, dimBlock, smemSize, stream >>>(d_idataA, d_idataB, d_odata, size); break;
case 128:
reduceProduct6<T, 128, false><<< dimGrid, dimBlock, smemSize, stream >>>(d_idataA, d_idataB, d_odata, size); break;
case 64:
reduceProduct6<T, 64, false><<< dimGrid, dimBlock, smemSize, stream >>>(d_idataA, d_idataB, d_odata, size); break;
case 32:
reduceProduct6<T, 32, false><<< dimGrid, dimBlock, smemSize, stream >>>(d_idataA, d_idataB, d_odata, size); break;
case 16:
reduceProduct6<T, 16, false><<< dimGrid, dimBlock, smemSize, stream >>>(d_idataA, d_idataB, d_odata, size); break;
case 8:
reduceProduct6<T, 8, false><<< dimGrid, dimBlock, smemSize, stream >>>(d_idataA, d_idataB, d_odata, size); break;
case 4:
reduceProduct6<T, 4, false><<< dimGrid, dimBlock, smemSize, stream >>>(d_idataA, d_idataB, d_odata, size); break;
case 2:
reduceProduct6<T, 2, false><<< dimGrid, dimBlock, smemSize, stream >>>(d_idataA, d_idataB, d_odata, size); break;
case 1:
reduceProduct6<T, 1, false><<< dimGrid, dimBlock, smemSize, stream >>>(d_idataA, d_idataB, d_odata, size); break;
}
}
break;
}
}
template void
reduceProducts<float>(int size, int threads, int blocks,
int whichKernel, float *d_idataA, float *d_idataB, float *d_odata, cudaStream_t stream);
|
8,913 | // cudamatrix: fixes to kernels that were using __syncthreads incorrectly (not sure if will fix a problem remi.fran6 was experiencing).
__global__ void _add_diag_mat_mat(
double alpha, double* v, int v_dim, const double* M, int M_cols, int M_row_stride,
int M_col_stride, const double *N, int N_row_stride, int N_col_stride,
double beta) {
// we actually assume blockDim.x == 256 here.
// Each diagonal element of v is processed by "threads_per_element" threads.
__shared__ double temp_data[256];
int threads_per_element = 5;
int i = blockIdx.x * blockDim.x + threadIdx.x;
int v_idx = i / threads_per_element, // v_idx is the index into v that we are supposed to
sub_idx = i % threads_per_element; // add to; 0 <= sub_idx < threads_per_element tells
// us which block of elements we sum up.
if (v_idx >= v_dim) return;
double sum = 0.0;
for (int j = sub_idx; j < M_cols; j += threads_per_element) {
int M_index = v_idx * M_row_stride + j * M_col_stride,
N_index = j * N_row_stride + v_idx * N_col_stride;
sum += M[M_index] * N[N_index];
}
temp_data[threadIdx.x] = sum;
// start_idx = threadIdx.x - sub_idx; // start of the position in temp_data
// that we want to sum up.
// The following is a tree-based reduction of the elements of temp_data from
// start_idx to start_idx + threads_per_element - 1; our own index is "sub_idx".
__syncthreads();
int num_total_threads = threads_per_element;
while (num_total_threads > 1) {
int half_point = ((1 + num_total_threads) >> 1);
if (sub_idx < half_point) {
double temp = 0.0;
if (sub_idx + half_point < num_total_threads) {
temp = temp_data[threadIdx.x + half_point];
}
temp_data[threadIdx.x] += temp;
}
__syncthreads();
num_total_threads = half_point;
}
if (sub_idx == 0) {
v[v_idx] = beta * v[v_idx] + alpha * temp_data[threadIdx.x];
}
} |
8,914 | #include <stdio.h>
__global__
void count_sort(int n, int* a, int* b, int* c) {
int i = threadIdx.x;
int iinc = blockDim.x;
int j = 0;
int jinc = gridDim.x;
for(; i < n; i += iinc) {
for(;j<n;j+=1) {
if((a[i] > a[j]) || (a[i] == a[j] && i > j)) {
c[i]++;
}
}
}
}
int main(void) {
int n = 2048;
int *a, *b, *c;
cudaMallocManaged(&a, n*sizeof(int));
cudaMallocManaged(&b, n*sizeof(int));
cudaMallocManaged(&c, n*sizeof(int));
for(int i=0;i<n;i++) a[i] = (i+1);
for(int i=0;i<n;i++) c[i] = 0;
count_sort<<<1,256>>>(n,a,b,c);
cudaDeviceSynchronize();
bool flag = true;
for(int i=0;i<n;i++) {
printf("%d ",c[i]);
if(c[i] != i) flag = false;
}
if(flag) printf("\nTrue \n");
else printf("\nFalse \n");
cudaFree(a);
cudaFree(b);
cudaFree(c);
return 0;
} |
8,915 | /*#include<stdio.h>
#include<cuda.h>
#include<cuda_runtime.h>
#define N 40000; //ThreadsLaunched
__global__ void gpuArrSet(long *d_in1, long *d_in2)
{
int M = N;
long tID = blockIdx.x;
if(tID<M)
{
d_in1[tID] = (-tID);
d_in2[tID] = (2 * tID);
}
}
__global__ void gpuArrAdd(long *d_in1, long *d_in2, long*d_out)
{
int M = N;
long tID = blockIdx.x;
if (tID < M)
{
d_out[tID] = d_in2[tID] + d_in1[tID];
}
}
int main()
{
long* d_in1;
long* d_in2;
long* d_out;
int M = N;
cudaMalloc((void**)&d_in1, sizeof(long)*M);
cudaMalloc((void**)&d_in2, sizeof(long)*M);
cudaMalloc((void**)&d_out, sizeof(long)*M);
long* h_out =(long*) malloc(sizeof(long)*M);
gpuArrSet << <M , 1>> >(d_in1,d_in2);
gpuArrAdd << <M , 1>> >(d_in1, d_in2, d_out);
cudaDeviceSynchronize();
cudaMemcpy(h_out, d_out, sizeof(int)*M, cudaMemcpyDeviceToHost);
printf("Output: ");
for (int i = 0; i < M; i++)
{
printf("%ld\n", h_out[i]);
}
free(h_out);
cudaFree(d_in1);
cudaFree(d_in2);
cudaFree(d_out);
system("Pause");
return 911;
}*/ |
8,916 | #include "cuda_runtime.h"
#include "device_launch_parameters.h"
#include <cuda.h>
//#include <device_functions.h>
#include <cuda_runtime_api.h>
#include <stdio.h>
#include <stdlib.h>
#include <math.h>
#define NUM_NODES 10
typedef struct
{
int start; // Index of first adjacent node in Ea
int length; // Number of adjacent nodes
} Node;
__global__ void CUDA_BFS_KERNEL(Node *Va, int *Ea, bool *Fa, bool *Xa, int *Ca,bool *done)
{
int id = threadIdx.x + blockIdx.x * blockDim.x;
if (id > NUM_NODES)
*done = false;
//printf("\n id is %d ", id);
printf("\n Fa[id] is %d --> Xa[id] is %d", Fa[id], Xa[id]);
if (Fa[id] == true && Xa[id] == false)
{
printf("\n id--> %d ", id); //This printf gives the order of vertices in BFS
//printf("\n Fa[id] is %d", Fa[id]);
Fa[id] = false;
Xa[id] = true;
__syncthreads();
//int k = 0;
//int i;
int start = Va[id].start;
//printf("\n Va[id] is %d", Va[id]);
int end = start + Va[id].length;
for (int i = start; i < end; i++)
{
int nid = Ea[i];
//printf("\n value of i is %d", i);
//printf("\n nid is %d", nid);
if (Xa[nid] == false)
{
//printf("\n Va[id] is %d", Va[id]);
Ca[nid] = Ca[id] + 1;
Fa[nid] = true;
*done = false;
}
}
}
}
// The BFS frontier corresponds to all the nodes being processed at the current level.
int main()
{
Node node[NUM_NODES];
//int edgesSize = 2 * NUM_NODES;
int edges[NUM_NODES];
for(int i = 0; i<10; i = i+5){
node[i+0].start = i+0;
node[i+0].length = 2;
node[i+1].start = i+2;
node[i+1].length = 1;
node[i+2].start = i+3;
node[i+2].length = 1;
node[i+3].start = i+4;
node[i+3].length = 1;
node[i+4].start = i+5;
if(i == 5)
node[i+4].length = 0;
else
node[i+4].length = 1;
edges[i+0] = i+1;
edges[i+1] = i+2;
edges[i+2] = i+4;
edges[i+3] = i+3;
if(i == 5)
edges[i+4] = i+4;
else
edges[i+4] = i+5;
}
//for(int i = 0; i< 10; i++){
// printf("\n node of %d is %d", i, node[i]);
// printf("\n edge of %d is %d", i, edges[i]);
//}
bool frontier[NUM_NODES] = { false };
bool visited[NUM_NODES] = { false };
int cost[NUM_NODES] = { 0 };
int source = 0;
frontier[source] = true;
Node* Va;
cudaMalloc((void**)&Va, sizeof(Node)*NUM_NODES);
cudaMemcpy(Va, node, sizeof(Node)*NUM_NODES, cudaMemcpyHostToDevice);
int* Ea;
cudaMalloc((void**)&Ea, sizeof(Node)*NUM_NODES);
cudaMemcpy(Ea, edges, sizeof(Node)*NUM_NODES, cudaMemcpyHostToDevice);
bool* Fa;
cudaMalloc((void**)&Fa, sizeof(bool)*NUM_NODES);
cudaMemcpy(Fa, frontier, sizeof(bool)*NUM_NODES, cudaMemcpyHostToDevice);
bool* Xa;
cudaMalloc((void**)&Xa, sizeof(bool)*NUM_NODES);
cudaMemcpy(Xa, visited, sizeof(bool)*NUM_NODES, cudaMemcpyHostToDevice);
int* Ca;
cudaMalloc((void**)&Ca, sizeof(int)*NUM_NODES);
cudaMemcpy(Ca, cost, sizeof(int)*NUM_NODES, cudaMemcpyHostToDevice);
int num_blks = 1;
int threads = 10;
bool done;
bool* d_done;
cudaMalloc((void**)&d_done, sizeof(bool));
printf("\n\n");
int count = 0;
printf("Order: ");
do {
count++;
done = true;
cudaMemcpy(d_done, &done, sizeof(bool), cudaMemcpyHostToDevice);
CUDA_BFS_KERNEL <<<num_blks, threads >>>(Va, Ea, Fa, Xa, Ca,d_done);
cudaMemcpy(&done, d_done , sizeof(bool), cudaMemcpyDeviceToHost);
} while (!done);
cudaMemcpy(cost, Ca, sizeof(int)*NUM_NODES, cudaMemcpyDeviceToHost);
printf("Number of times the kernel is called : %d \n", count);
printf("\nCost: ");
for (int i = 0; i<NUM_NODES; i++)
printf( "%d ", cost[i]);
printf("\n");
//_getch();
} |
8,917 | #include "includes.h"
__global__ void OPT_3_HIST(int* lcm, int* hist, int* lcmsizes, int n) {
//
int vertex = blockIdx.x;
int vcomp = threadIdx.x;
bool equal;
//
__shared__ int cval;
//
if(vcomp == 0)
cval = 0;
__syncthreads();
//
if(vertex < n && vcomp < n)
for(int i = vcomp; i < n; i += blockDim.x) {
if(vertex == i) {
atomicAdd(&cval, 1);
continue;
}
if((lcmsizes[vertex+1] - lcmsizes[vertex]) != (lcmsizes[i+1] - lcmsizes[i]))
continue;
equal = false;
for(int j = 0; j < lcmsizes[vertex+1] - lcmsizes[vertex]; j++) {
if(lcm[lcmsizes[vertex] + j] == lcm[lcmsizes[i] + j])
equal = true;
else {
equal = false;
break;
}
}
if(equal)
atomicAdd(&cval, 1);
}
__syncthreads();
if(vertex < n && vcomp == 0 && cval > 0) {
atomicAdd(&hist[cval], 1);
//printf("\nv%d: %d\n", vertex, cval);
}
} |
8,918 | #include<bits/stdc++.h>
#define NODES 400 //size of graph will be NODES*NODES
#define THREADS_BLOCK 256
typedef float data;
// initial graph with no weights
void init(data* graph, int num_NODES) {
int i, j;
for (i = 0; i < num_NODES; i++) {
for (j = 0; j < num_NODES; j++) {
graph[i*num_NODES + j] = (data)0;
}
}
}
// randomly allocating edge weights (g)
void edges(data* graph, int* edge_count, int num_NODES) {
int nearestNode(data* node_dist, int* visited_node, int num_NODES);
for (int i = 1; i < num_NODES; i++) {
int rand_vertex = (rand() % i);
data weight = (rand() % 500) + 1;
graph[rand_vertex*num_NODES + i] = weight;
graph[i*num_NODES + rand_vertex] = weight;
edge_count[i] += 1;
edge_count[rand_vertex] += 1;
}
}
// finding the minimum using a single thread in a single block
__global__ void nearestNode(data* node_dist, int* visited_node, int* global_closest, int num_NODES) {
data dist = 100000;
int node = -1;
int i;
for (i = 0; i < num_NODES; i++) {
if ((node_dist[i] < dist) && (visited_node[i] != 1)) {
dist = node_dist[i];
node = i;
}
}
global_closest[0] = node;
visited_node[node] = 1;
}
// finding out the heuristic using euclidean distance
int heuristicFunction(int visited_node, int end_node){
static int xd, yd, d;
int visited_node_x = visited_node/NODES;
int visited_node_y = visited_node%NODES;
int end_node_x = end_node/NODES;
int end_node_y = end_node%NODES;
xd = visited_node_x-end_node_x;
yd = visited_node_y-end_node_y;
d = static_cast<int>(sqrt(xd*xd+yd*yd));
return(d);
}
__global__ void cudasync(data* graph, data* node_dist, int* parent_node, int* visited_node, int* global_closest) {
int next = blockIdx.x*blockDim.x + threadIdx.x;
int source = global_closest[0];
data edge = graph[source*NODES + next];
data new_dist = node_dist[source] + edge;
if ((edge != 0) && (visited_node[next] != 1) && (new_dist < node_dist[next])) {
node_dist[next] = new_dist;
parent_node[next] = source;
}
__syncthreads();
}
int main() {
srand(42);
int size = NODES*NODES*sizeof(data);
int int_array = NODES*sizeof(int);
int data_array = NODES*sizeof(data);
data* graph = (data*)malloc(size);
data* node_dist = (data*)malloc(data_array);
int* parent_node = (int*)malloc(int_array);
int* edge_count = (int*)malloc(int_array);
int* visited_node = (int*)malloc(int_array);
int* pn_matrix = (int*)malloc(int_array);
data* dist_matrix = (data*)malloc(data_array);
data* cost_function = (data*)malloc(data_array);
data* gpu_graph;
data* gpu_node_dist;
int* gpu_parent_node;
int* gpu_visited_node;
cudaMalloc((void**)&gpu_graph, size);
cudaMalloc((void**)&gpu_node_dist, data_array);
cudaMalloc((void**)&gpu_parent_node, int_array);
cudaMalloc((void**)&gpu_visited_node, int_array);
int* closest_vertex = (int*)malloc(sizeof(int));
int* gpu_closest_vertex;
closest_vertex[0] = -1;
cudaMalloc((void**)&gpu_closest_vertex, (sizeof(int)));
cudaMemcpy(gpu_closest_vertex, closest_vertex, sizeof(int), cudaMemcpyHostToDevice);
init(graph, NODES);
edges(graph, edge_count, NODES);
int origin = (rand() % NODES);
printf("Origin vertex: %d\n", origin);
int goal = (rand() % NODES);
printf("Goal vertex: %d\n", goal);
int version = 1;
cudaEvent_t start, stop;
float elapsed_exec;
cudaEventCreate(&start);
cudaEventCreate(&stop);
node_dist[origin] = 0;
cudaMemcpy(gpu_graph, graph, size, cudaMemcpyHostToDevice);
cudaMemcpy(gpu_node_dist, node_dist, data_array, cudaMemcpyHostToDevice);
cudaMemcpy(gpu_parent_node, parent_node, int_array, cudaMemcpyHostToDevice);
cudaMemcpy(gpu_visited_node, visited_node, int_array, cudaMemcpyHostToDevice);
dim3 gridNearest(1, 1, 1);
dim3 blockNearest(1, 1, 1);
dim3 gridRelax(NODES / THREADS_BLOCK, 1, 1);
dim3 blockRelax(THREADS_BLOCK, 1, 1);
cudaEventRecord(start);
for (int i = 0; i < NODES; i++) {
nearestNode <<<gridNearest, blockNearest>>>(gpu_node_dist, gpu_visited_node, gpu_closest_vertex, NODES);
cudasync <<<gridRelax, blockRelax>>>(gpu_graph, gpu_node_dist, gpu_parent_node, gpu_visited_node, gpu_closest_vertex);
}
printf("optimal path found!!");
cudaEventRecord(stop);
cudaMemcpy(node_dist, gpu_node_dist, data_array, cudaMemcpyDeviceToHost);
cudaMemcpy(parent_node, gpu_parent_node, int_array, cudaMemcpyDeviceToHost);
cudaMemcpy(visited_node, gpu_visited_node, int_array, cudaMemcpyDeviceToHost);
for (int i = 0; i < NODES; i++) {
int end_dist = heuristicFunction(parent_node[i], goal);
pn_matrix[version*NODES + i] = parent_node[i];
dist_matrix[version*NODES + i] = node_dist[i];
cost_function[version*NODES + i] = node_dist[i]+end_dist;
}
//free memory
cudaFree(gpu_graph);
cudaFree(gpu_node_dist);
cudaFree(gpu_parent_node);
cudaFree(gpu_visited_node);
cudaEventElapsedTime(&elapsed_exec, start, stop); //elapsed execution time
printf("\n\nComputational time in CUDA (ms): %7.9f\n", elapsed_exec);
} |
8,919 | #include <stdio.h>
#include <stdlib.h>
#include <time.h>
#include <cuda.h>
#include <locale.h>
unsigned int getmax(unsigned int *, unsigned int);
unsigned int getmaxcu(unsigned int *, unsigned int);
__global__ void helper(unsigned int * d, unsigned int * comp, int size) {
int tid;
tid = threadIdx.x;
int i;
i = blockIdx.x * blockDim.x + threadIdx.x;
if(i < size){
for(uint stride = 1; stride < blockDim.x; stride *= 2){
if(i % (2 * stride) == 0){
if(comp[i] < comp[i + stride]){
comp[i] = comp[i + stride];
}
}
__syncthreads();
}
if(tid == 0){
if(comp[blockIdx.x * blockDim.x] > d[blockIdx.x]){
d[blockIdx.x] = comp[blockIdx.x * blockDim.x];
}
}
}
}
unsigned int getmaxcu(unsigned int num[], unsigned int size){
uint *x, *y;
cudaMalloc((void**)&x, size*sizeof(uint));
cudaMalloc((void**)&y, size*sizeof(uint));
cudaMemcpy(x, num, sizeof(uint) * size, cudaMemcpyHostToDevice);
cudaMemcpy(y, num, sizeof(uint) * size, cudaMemcpyHostToDevice);
int a = (int)((size - size % 1024)/1024) + 1;
helper<<<a, 1024>>>(x, y, size);
cudaMemcpy(num, x, sizeof(uint) * size, cudaMemcpyDeviceToHost);
uint max = 0;
for(int i = 0; i < a + 1; i++){
max = max > num[i] ? max : num[i];
}
cudaFree(x);
cudaFree(y);
return(max);
}
int main(int argc, char *argv[])
{
unsigned int size = 0; // The size of the array
unsigned int i; // loop index
unsigned int * numbers; //pointer to the array
if(argc !=2)
{
printf("usage: maxseq num\n");
printf("num = size of the array\n");
exit(1);
}
size = atol(argv[1]);
numbers = (unsigned int *)malloc(size * sizeof(unsigned int));
if( !numbers ){
printf("Unable to allocate mem for an array of size %u\n", size);
exit(1);
}
srand(time(NULL)); // setting a seed for the random number generator
// Fill-up the array with random numbers from 0 to size-1
for( i = 0; i < size; i++)
numbers[i] = rand() % size;
printf("The maximum number in the array is: %u\n", getmaxcu(numbers, size));
free(numbers);
exit(0);
}
|
8,920 | #include "includes.h"
__device__ __host__ int maximum( int a, int b, int c){
int k;
if( a <= b )
k = b;
else
k = a;
if( k <=c )
return(c);
else
return(k);
}
__global__ void lower_right(int *input_itemsets, int *reference, int *tmp, int max_rows, int max_cols, int i, int penalty)
{
int r, c;
r = i;
c = blockIdx.x*blockDim.x+threadIdx.x;
if( c >= (max_cols-(i-max_rows+1))) return;
tmp[r*max_cols+c] = maximum( tmp[(r-2)*max_cols+c+1]+ reference[(max_rows-1-c)*max_cols+c+(i-max_rows+1)],
tmp[(r-1)*max_cols+c] - penalty,
tmp[(r-1)*max_cols+c+1] - penalty);
} |
8,921 | #include <stdio.h>
#include<stdlib.h>
char* readFile(char* url){
int fileSize, readCount;
char* buffer;
FILE *filePointer;
filePointer = fopen(url, "r");
if(filePointer == NULL){
printf("failed to open the file");
}
else{
printf("opened the file successfully");
// use pointer to find the fileSize by going to the end and rewind it to the start of the file
//after work is done
fseek(filePointer, 0, SEEK_END);
fileSize = ftell(filePointer);
rewind(filePointer);
//we wanted that size to allocate a memory for a string of that size, which is job
//of buffer
//i am adding one more character size to add /0 at the end
buffer = (char*) malloc(sizeof(char) * (fileSize + 1));
readCount = fread(buffer, sizeof(char), fileSize, filePointer);
buffer[fileSize] = '\0';
if(fileSize != readCount){
free(buffer);
printf("there was some errror reading the file, please try again");
}
fclose(filePointer);
}
return buffer;
}
int main(){
char *fileString = readFile("raw file");
}
|
8,922 | #include <stdio.h>
__device__ void addSleep(void *p_us_time)
{
int time = *((int *) p_us_time);
// GTX-670
float AddPerUs = 9.89759943623274;
float adds = time*AddPerUs;
int temp=0;
while(temp<adds){
temp++;
}
} |
8,923 | /*
Program to find the sum of all the array elements given that the length of the array is a power of 2.
Benchmarking is been done to compare the performance of the CPU (squential with extremely powerful cores) and
the GPU (parallel with modestly powerful cores).
*/
/*
Sequential codes takes n-1 steps whereas parallel code takes log(n) base 2 steps.
Note: Algorithm can handle only sizes less than or equal to 2^11.
*/
// Importing the required headers
#include<stdio.h>
#include<time.h>
#include<cuda.h>
// Returns the duration from start to end times in sec
double time_elapsed(struct timespec *start, struct timespec *end)
{
double t;
t = (end->tv_sec - start->tv_sec); // diff in seconds
t += (end->tv_nsec - start->tv_nsec) * 0.000000001; //diff in nanoseconds
return t;
}
// GPU Kernel
__global__ void GPU_Sum1(int *a, int len) //GPU code without shared memory.
{
int id = threadIdx.x;
int n = blockDim.x;
while(n > 0)
{
if(id < n) a[id] += a[id + n];
__syncthreads();
n = n/2;
}
return;
}
// GPU Kernel
__global__ void GPU_Sum2(int *array, int len) //GPU code with shared memory.
{
extern __shared__ int a[];
int id = threadIdx.x;
int n = blockDim.x;
a[id] = array[id];
a[id+n] = array[id+n];
__syncthreads();
while(n > 0)
{
if(id < n) a[id] += a[id + n];
__syncthreads();
n = n/2;
}
if(id == 0) array[0] = a[0];
return;
}
// CPU Function
void CPU_Sum(int *a, int n)
{
for(int i = n-1; i > 0; i--)
a[i-1] += a[i];
return;
}
// Code execution begins here
int main()
{
struct timespec start1, end1; //variables to store time for GPU
struct timespec start2, end2; //variables to store time for GPU
struct timespec start3, end3; //variables to store time for CPU
int n; //Length of the array
printf("Enter the value of n: "); //Get length
scanf("%d", &n);
int *a1, *a2, *a3;
if(cudaMallocManaged(&a1, n*sizeof(int)) != cudaSuccess) //Allocate memory
{
printf("Malloc Error!\n");
return 0;
}
if(cudaMallocManaged(&a2, n*sizeof(int)) != cudaSuccess) //Allocate memory
{
printf("Malloc Error!\n");
cudaFree(a1);
return 0;
}
if(cudaMallocManaged(&a3, n*sizeof(int)) != cudaSuccess) //Allocate memory
{
printf("Malloc Error!\n");
cudaFree(a1);
cudaFree(a2);
return 0;
}
for(int i = 0; i < n; i++) //Assign random values
{
a1[i] = rand()%10;
a2[i] = a1[i];
a3[i] = a2[i];
}
clock_gettime(CLOCK_REALTIME, &start1); //start timestamp
GPU_Sum1<<<1, n/2>>>(a1, n);
cudaDeviceSynchronize();
clock_gettime(CLOCK_REALTIME, &end1); //end timestamp
clock_gettime(CLOCK_REALTIME, &start2); //start timestamp
GPU_Sum2<<<1, n/2, n*sizeof(int)>>>(a2, n);
cudaDeviceSynchronize();
clock_gettime(CLOCK_REALTIME, &end2); //end timestamp
clock_gettime(CLOCK_REALTIME, &start3); //start timestamp
CPU_Sum(a3, n);
clock_gettime(CLOCK_REALTIME, &end3); //end timestamp
printf("\nResult of the GPU (without shared memory) : %d\n", a1[0]);
printf("Result of the GPU (with shared memory) : %d\n", a2[0]);
printf("Result of the CPU : %d\n", a3[0]);
printf("\nTime taken by GPU (no shared memory) is : %lf\n", time_elapsed(&start1, &end1)); //print result for GPU
printf("Time taken by GPU (with shared memory) is : %lf\n", time_elapsed(&start2, &end2)); //print result for GPU
printf("Time taken by CPU is : %lf\n", time_elapsed(&start3, &end3)); //print result for CPU
cudaFree(a1);
cudaFree(a2);
cudaFree(a3);
cudaDeviceReset();
return 0;
}
|
8,924 | #include <cstdio>
#include <cstdlib>
#include <vector>
__global__ void bucketsort(int *key, int *bucket, int n){
int i = blockIdx.x * blockDim.x + threadIdx.x;
if(i>=n) return;
int a = key[i];
atomicAdd(&bucket[a],1);
__syncthreads();
for(int j = 0, k = 0; j <= i; k++){
key[i] = k;
j += bucket[k];
}
}
int main() {
int n = 50;
int range = 5;
int *key;
cudaMallocManaged(&key, n*sizeof(int));
for (int i=0; i<n; i++) {
key[i] = rand() % range;
printf("%d ",key[i]);
}
printf("\n");
const int X = 32;
int *bucket;
cudaMallocManaged(&bucket, range*sizeof(int));
bucketsort<<<(n+X-1)/X,X,range>>>(key,bucket,n);
cudaDeviceSynchronize();
for (int i=0; i<n; i++) {
printf("%d ", key[i]);
}
printf("\n");
// for (int i=0; i<range; i++){
// printf("%d ", bucket[i]);
// }
// printf("\n");
cudaFree(key);
cudaFree(bucket);
}
|
8,925 | #include "cuda_runtime.h"
#include "device_launch_parameters.h"
#include "curand_kernel.h"
#include <cuda.h>
#include <curand.h>
#include <iostream>
#include <numeric>
using namespace std;
const int threadSideSize = 32;
const int blocksSideSize = 255;
__global__ void calculate(int* sum) {
int xBlock = blockIdx.x / blocksSideSize;
int yBlock = blockIdx.x % blocksSideSize;
int xThread = threadIdx.x / threadSideSize;
int yThread = threadIdx.x % threadSideSize;
int positionX = xBlock * threadSideSize + xThread;
int positionY = yBlock * threadSideSize + yThread;
if (sqrt((float) ((positionX * positionX) + (positionY * positionY))) <= (blocksSideSize * threadSideSize)) {
atomicAdd(sum, 1);
}
}
int main() {
int blockSize = threadSideSize * threadSideSize;
int numBlocks = blocksSideSize * blocksSideSize;
int sum = 0;
int *sumDevice;
cudaMalloc(&sumDevice, sizeof(int));
calculate<<<numBlocks, blockSize>>>(sumDevice);
cudaMemcpy(&sum, sumDevice, sizeof(int), cudaMemcpyDeviceToHost);
cout << "pi = " << (double)(4 * sum) / (double)((blocksSideSize * threadSideSize) * (blocksSideSize * threadSideSize)) << endl;
cudaFree(sumDevice);
return 0;
}
|
8,926 | #include <stdio.h>
#include <sys/time.h>
// This function returns the current timestamp in seconds.
double shrDeltaT()
{
static struct timeval old_time;
struct timeval new_time;
gettimeofday(&new_time, NULL);
const double DeltaT = ((double)new_time.tv_sec + 1.0e-6 * (double)new_time.tv_usec) - ((double)old_time.tv_sec + 1.0e-6 * (double)old_time.tv_usec);
old_time.tv_sec = new_time.tv_sec;
old_time.tv_usec = new_time.tv_usec;
return DeltaT;
}
int main(int argc, char* argv[])
{
// Initialize 4 transfer sizes, i.e. 3KB, 15KB, 15MB and 100MB.
const int n = 4;
const size_t sizes[n] = { 3 << 10, 15 << 10, 15 << 20, 100 << 20 };
// Initialize the number of transfer iterations, i.e. 60K, 60K, 300 and 30 iterations, respectively.
const size_t iterations[n] = { 60000, 60000, 300, 30 };
// Print header in CSV format.
printf("size (B),memory,direction,bandwidth (MB/s)\n");
// Loop through the 4 transfer sizes.
for (int s = 0; s < n; ++s)
{
// Calculate the total transfer size.
const size_t size = sizes[s];
const size_t iteration = iterations[s];
const double totalSizeInMB = (double)size * iteration / (1 << 20);
double time;
// Allocate d_p in device memory.
void* h_p;
void* d_p;
cudaMalloc(&d_p, size);
// Allocate pageable h_p in host memory.
h_p = malloc(size);
// Test host-to-device bandwidth.
shrDeltaT();
for (int i = 0; i < iteration; ++i)
{
cudaMemcpy(d_p, h_p, size, cudaMemcpyHostToDevice);
}
time = shrDeltaT();
printf("%lu,%s,%s,%.0f\n", size, "pageable", "HtoD", totalSizeInMB / time);
// Test device-to-host bandwidth.
shrDeltaT();
for (int i = 0; i < iteration; ++i)
{
cudaMemcpy(h_p, d_p, size, cudaMemcpyDeviceToHost);
}
time = shrDeltaT();
printf("%lu,%s,%s,%.0f\n", size, "pageable", "DtoH", totalSizeInMB / time);
// Deallocate pageable h_p in host memory.
free(h_p);
// Allocate pinned h_p in host memory.
cudaHostAlloc(&h_p, size, cudaHostAllocDefault);
// Test host-to-device bandwidth.
shrDeltaT();
for (int i = 0; i < iteration; ++i)
{
cudaMemcpyAsync(d_p, h_p, size, cudaMemcpyHostToDevice);
}
cudaDeviceSynchronize();
time = shrDeltaT();
printf("%lu,%s,%s,%.0f\n", size, "pinned", "HtoD", totalSizeInMB / time);
// Test device-to-host bandwidth.
shrDeltaT();
for (int i = 0; i < iteration; ++i)
{
cudaMemcpyAsync(h_p, d_p, size, cudaMemcpyDeviceToHost);
}
cudaDeviceSynchronize();
time = shrDeltaT();
printf("%lu,%s,%s,%.0f\n", size, "pinned", "DtoH", totalSizeInMB / time);
// Deallocate pinned h_p in host memory.
cudaFreeHost(h_p);
// Deallocate d_p in device memory.
cudaFree(d_p);
}
// Cleanup.
cudaDeviceReset();
}
|
8,927 | #include <iostream>
#include <cassert>
/* ******************
* Author : smher
* Data : 2017. 08. 01
* Description :
* This file implement the all-prefix-sums (scan) algorithm parallel. based on "GPU Gem 3" chapter 39.
*
* The Version 2 ( Up Sweep and Down Sweep cannot be fit to not power of 2 lenght array !!!
*
* TODO:
* There is a lot of room for optimization as for Versioin 2 !!!
*/
#define SIZE 128
//#define SIZE 127 // Not fit for Version 2
using namespace std;
//__device__ void UpSweep(float *data, int width)
__global__ void UpSweep(float *data, int width)
{
int idx = threadIdx.x + blockIdx.x * blockDim.x;
int idy = threadIdx.y + blockIdx.y * blockDim.y;
int index = idy * (blockDim.x * gridDim.x) + idx;
float times = roundf(log2f(width));
for(int i = 0; i < times; i++)
{
int offsetA = powf(2, i+1);
int offsetB = powf(2, i);
//if(index < width-offsetA)
if(index < width)
{
if(index % offsetA == 0)
data[index + offsetA - 1] += data[index + offsetB - 1];
}
__syncthreads();
}
}
__global__ void DownSweep(float *data, int width)
{
int idx = threadIdx.x + blockIdx.x * blockDim.x;
int idy = threadIdx.y + blockIdx.y * blockDim.y;
int index = idy * (blockDim.x * gridDim.x) + idx;
float times = roundf(log2f(width));
//assert(times == 7);
//float temp = 0;
if(index == (width - 1))
data[index] = 0;
for(int i = times - 1; i >= 0; i--)
{
int offsetA = powf(2, i + 1);
int offsetB = powf(2, i);
if(index <= (width - offsetA))
{
if(index % offsetA == 0)
{
float temp = data[index + offsetB - 1];
data[index + offsetB - 1] = data[index + offsetA - 1];
data[index + offsetA - 1] += temp;
}
}
__syncthreads();
}
}
void scan(float *dataIn, int width)
{
dim3 threadPerBlock(8, 8);
dim3 blockPerGrid(1, 2);
UpSweep<<<blockPerGrid, threadPerBlock>>>(dataIn, SIZE);
DownSweep<<<blockPerGrid, threadPerBlock>>>(dataIn, SIZE);
}
__global__ void scanShared(float *g_odata, float *g_idata, int n)
{
extern __shared__ float temp[]; // allocated on invocation
int thid = threadIdx.x;
int pout = 0, pin = 1;
// Load input into shared memory.
// This is exclusive scan, so shift right by one
// and set first element to 0
temp[pout*n + thid] = (thid > 0) ? g_idata[thid-1] : 0;
__syncthreads();
for (int offset = 1; offset < n; offset *= 2)
{
pout = 1 - pout; // swap double buffer indices
pin = 1 - pout;
if (thid >= offset)
temp[pout*n+thid] += temp[pin*n+thid - offset];
else
temp[pout*n+thid] = temp[pin*n+thid];
__syncthreads();
}
g_odata[thid] = temp[pout*n+thid]; // write output
}
__global__ void scanFirst(float *data, int width)
{
float times = roundf(log2f(width));
int idx = threadIdx.x + blockIdx.x * blockDim.x;
int idy = threadIdx.y + blockIdx.y * blockDim.y;
int index = idy * (blockDim.x * gridDim.x) + idx;
//assert(times == 7); // for sure that the time is correct
for(int i = 0; i < times; i++)
{
//int k = 2 << i; // the powf(2, i)
int k = powf(2, i); // k is the stride
if(index >= k && index < width)
{
data[index] = data[index - k] + data[index];
}
__syncthreads();
}
}
/*
* TODO
__global__ void scanMat(float *dataMat, int row, int col)
{
int idx = threadIdx.x + blockDim.x * blockIdx.x;
int idy = threadIdx.y + blockDim.y * blockIdx.y;
int index = idy * (blockDim.x * gridDim.x) + idx;
}
*/
void print(float *src, int width)
{
for(int i = 0; i < width; i++)
cout << src[i] << " ";
cout << endl;
}
void scanSeq(float *src, float *dst, int width)
{
for(int i = 0; i < width; i++)
dst[i] = dst[i-1] + src[i];
}
int main(int argc, char **argv)
{
cout << "hello world ..." << endl;
float *src = new float [SIZE];
float *dst = new float [SIZE]();
for(int i = 0; i < SIZE; i++)
src[i] = i;
// prepare the cuda event
cudaEvent_t start, end;
cudaEventCreate(&start);
cudaEventCreate(&end);
float elapsedTime;
// prepare datas on device
float *srcD;
float *dstD;
cudaError_t cudaState = cudaSuccess;
cudaState = cudaMalloc((void **)&srcD, SIZE * sizeof(float));
assert(cudaState == cudaSuccess);
cudaState = cudaMemcpy(srcD, src, SIZE * sizeof(float), cudaMemcpyHostToDevice);
assert(cudaState == cudaSuccess);
cudaState = cudaMalloc((void **)&dstD, SIZE * sizeof(float));
assert(cudaState == cudaSuccess);
cudaState = cudaMemset(dstD, 0, SIZE * sizeof(float));
assert(cudaState == cudaSuccess);
cudaState = cudaMemcpy(dstD, srcD, SIZE * sizeof(float), cudaMemcpyDeviceToDevice);
// sequential version
cout << "Sequential Versioin : " << endl;
scanSeq(src, dst, SIZE);
print(dst, SIZE);
cout << "Version 1 " << endl;
cudaEventRecord(start, 0);
// The first parallel version of scan algorithm
dim3 threadPerBlock(8, 8);
dim3 blockPerGrid(1,2);
scanFirst<<<blockPerGrid, threadPerBlock>>>(dstD, SIZE);
cudaEventRecord(end, 0);
cudaEventSynchronize(end);
cudaEventElapsedTime(&elapsedTime, start, end);
cudaState = cudaMemcpy(dst, dstD, SIZE * sizeof(float), cudaMemcpyDeviceToHost);
assert(cudaState == cudaSuccess);
print(dst, SIZE);
cout << "Version 1 Parallel Scan: " << elapsedTime << " ms" << endl;
// Test for complete scan function
cout << "Version 2: " << endl;
cudaState = cudaMemcpy(dstD, src, SIZE * sizeof(float), cudaMemcpyHostToDevice);
assert(cudaState == cudaSuccess);
cudaEventRecord(start, 0);
scan(dstD, SIZE);
cudaEventRecord(end, 0);
cudaEventSynchronize(end);
cudaEventElapsedTime(&elapsedTime, start, end);
cudaState = cudaMemcpy(dst, dstD, SIZE * sizeof(float), cudaMemcpyDeviceToHost);
assert(cudaState == cudaSuccess);
cout << "Exclusive Version : " << endl;
print(dst, SIZE);
// change the exclusive to inclusive version Scan
for(int i = 0; i < SIZE - 1; i++)
dst[i] = dst[i + 1];
dst[SIZE - 1] += src[SIZE - 1];
cout << "Inclusive Version : " << endl;
print(dst, SIZE);
cout << "Version 2 Parallel Scan: " << elapsedTime << " ms" << endl;
// Debug for UpSweep and DownSweep Kernels
/*
// Test for UpSweep Functioin
cudaState = cudaMemcpy(dstD, src, SIZE * sizeof(float), cudaMemcpyHostToDevice);
assert(cudaState == cudaSuccess);
UpSweep<<<blockPerGrid, threadPerBlock>>>(dstD, SIZE);
cudaState = cudaMemcpy(dst, dstD, SIZE * sizeof(float), cudaMemcpyDeviceToHost);
assert(cudaState == cudaSuccess);
print(dst, SIZE);
// Test for DownSweep Functioni
DownSweep<<<blockPerGrid, threadPerBlock>>>(dstD, SIZE);
cudaState = cudaMemcpy(dst, dstD, SIZE * sizeof(float), cudaMemcpyDeviceToHost);
assert(cudaState == cudaSuccess);
*/
/*
// test for the first shared memory version
//scanShared<<<blockPerGrid, threadPerBlock>>>(dstD, srcD, SIZE); // Error
//scanShared<<<1, SIZE>>>(dstD, srcD, SIZE);
cudaState = cudaMemcpy(dst, dstD, SIZE * sizeof(float), cudaMemcpyDeviceToHost);
assert(cudaState == cudaSuccess);
print(dst, SIZE);
*/
// free the resources
delete [] src;
delete [] dst;
cudaFree(srcD);
cudaFree(dstD);
cudaEventDestroy(start);
cudaEventDestroy(end);
return 0;
}
|
8,928 | #include <thrust/device_vector.h>
#include <thrust/host_vector.h>
#include <thrust/transform.h>
#include <thrust/functional.h>
#include <iostream>
struct saxpy_functor
{
const float a;
saxpy_functor(float _a) : a(_a) {}
__host__ __device__
float operator()(const float& x, const float& y) const {
return a * x + y;
}
};
void saxpy_host(float A, thrust::host_vector<float>& X, thrust::host_vector<float>& Y)
{
thrust::transform(X.begin(), X.end(), Y.begin(), Y.begin(), saxpy_functor(A));
}
void saxpy(float A, thrust::device_vector<float>& X, thrust::device_vector<float>& Y,
thrust::device_vector<float>& Z)
{
thrust::transform(X.begin(), X.end(), Y.begin(), Z.begin(), saxpy_functor(A));
}
void saxpy_slow(float A, thrust::device_vector<float>& X, thrust::device_vector<float>& Y)
{
thrust::device_vector<float> temp(X.size());
// temp <- A
thrust::fill(temp.begin(), temp.end(), A);
// temp <- A * X
thrust::transform(X.begin(), X.end(), temp.begin(), temp.begin(), thrust::multiplies<float>());
// Y <- A * X + Y
thrust::transform(temp.begin(), temp.end(), Y.begin(), Y.begin(), thrust::plus<float>());
}
int main(){
thrust::host_vector<float> X_H(100);
thrust::host_vector<float> Y_H(100);
thrust::host_vector<float> Z_H(100);
thrust::device_vector<float> X_D(100);
thrust::device_vector<float> Y_D(100);
thrust::device_vector<float> Z_D(100);
for(int c = 0; c < 100; c++){
X_H[c] = (float)c;
Y_H[c] = (float)(100-c);
}
X_D = X_H;
Y_D = Y_H;
try {
saxpy_slow(5.0,X_D,Y_D);
}catch(thrust::system_error &e){
std::cerr << "Error accessing vector element: " << e.what() << std::endl;
exit(-1);
}
Z_H = Z_D;
Y_H = Y_D;
for(int c = 0; c < 10; c++){
std::cout << Y_H[c] << "\n";
}
return 0;
} |
8,929 | #include <iostream>
__global__ void add_constant(int n, int *x)
{
int tid = threadIdx.x + blockIdx.x*blockDim.x;
x[tid] += n;
}
int main(void)
{
int dNum = 1<<24;
int *x, *d_x, nT=32;
size_t memSize = sizeof(int)*dNum;
// memory allocation in the host and initialization
x = (int *)malloc(memSize);
for(int i=0; i<dNum; i++) x[i] = i;
// memory allocation in the device
cudaMalloc(&d_x, memSize);
// copy from host to device
cudaMemcpy(d_x, x, memSize, cudaMemcpyHostToDevice);
// kernel launch
add_constant<<<dNum/nT, nT>>>(1, d_x);
printf("%d\n",x[0]);
// copy from device to host
cudaMemcpy(x, d_x, memSize, cudaMemcpyDeviceToHost);
printf("%d\n",x[0]);
return 0;
}
|
8,930 | #include <iostream>
#include <stdio.h>
#include <stdint.h>
#include <math.h>
#define N_DIM 1000
/* CUDA kernel parameters */
#define NUM_BLOCKS 1
#define NUM_THREADS 32
// CUDA kernel to add elements of two arrays
__global__
void add(unsigned long int n, float *x, float *y)
{
int index = blockIdx.x * blockDim.x + threadIdx.x;
int stride = blockDim.x * gridDim.x;
for (unsigned long int i = index; i < n; i += stride){
y[i] = x[i] + y[i];
//if(i%100000==0 && i > 480000000)printf("Adding i=%lu\n", i);
}
}
int main(void)
{
uint64_t n = N_DIM, N=n*n;
double *func_values;
// Allocate pinned memory
cudaMallocHost((void **) &func_values, N*sizeof(double));
printf("Writing 1.0 to function values\n");
// initialize x and y arrays on the host
for (uint64_t i = 0; i < N; i++) {
func_values[i] = 1.0;
}
printf("Finished writing values\n");
// Launch kernel on 1M elements on the GPU
int blockSize = 256;
int numBlocks = 1;
//add<<<numBlocks, blockSize>>>(N, x, y);
// Wait for GPU to finish before accessing on host
//cudaDeviceSynchronize();
cudaFreeHost(func_values);
return 0;
}
|
8,931 | #include <stdio.h>
#include <stdlib.h>
#include <cuda.h>
#include <cuda_runtime.h>
#define BLOCK_SIZE 128
__global__ void av3(int n, float *in1, float *in2, float *in3, float *out)
{
int index = threadIdx.x + blockIdx.x * blockDim.x;
if (index<n)
{
out[index] = (in1[index] + in2[index] + in3[index])/3;
}
}
float *average3(int num, float *in1, float *in2, float *in3, float *out)
{
// Initialization
float *d_in1, *d_in2, *d_in3, *d_out;
int size = num * sizeof(float);
// Allocate memory for device
cudaMalloc((void **)&d_in1, size);
cudaMalloc((void **)&d_in2, size);
cudaMalloc((void **)&d_in3, size);
cudaMalloc((void **)&d_out, size);
// Copy inputs to device
cudaMemcpy(d_in1, in1, size, cudaMemcpyHostToDevice);
cudaMemcpy(d_in2, in2, size, cudaMemcpyHostToDevice);
cudaMemcpy(d_in3, in3, size, cudaMemcpyHostToDevice);
// Launch Kernel
dim3 DimGrid((num-1)/BLOCK_SIZE+1, 1, 1);
dim3 DimBlock(BLOCK_SIZE, 1, 1);
av3<<<DimGrid,DimBlock>>>(num, d_in1, d_in2, d_in3, d_out);
// Wait for the GPU to finish
cudaDeviceSynchronize();
// Copy result back to host and cleanup
cudaMemcpy(out, d_out, size, cudaMemcpyDeviceToHost);
cudaFree(d_in1); cudaFree(d_in2); cudaFree(d_in3); cudaFree(d_out);
return out;
}
|
8,932 | __device__ float l_diff(float a, float b){
return a - b;
}
__device__ float l_div(float a, float b){
return a / b;
}
__device__ float l_mult(float a, float b){
return a * b;
}
|
8,933 | /*#include <stdio.h>
#include <cuda.h>
#include <cv.h>
#include <highgui.h>
#include <opencv2/imgproc/imgproc.hpp>
using namespace cv;
#define DIM 500
struct cuComplex
{
float r;
float i;
__device__ cuComplex( float a, float b ) : r(a), i(b) {}
__device__ float magnitude2( void )
{
return r * r + i * i;
}
__device__ cuComplex operator*(const cuComplex& a)
{
return cuComplex(r*a.r - i*a.i, i*a.r + r*a.i);
}
__device__ cuComplex operator+(const cuComplex& a)
{
return cuComplex(r+a.r, i+a.i);
}
};
__device__ int julia( int x, int y )
{
const float scale = 1.5;
float jx = scale * (float)( x - DIM/2)/(DIM/2);
float jy = scale * (float)(y - DIM/2)/(DIM/2);
cuComplex c(-0.8, 0.156);
cuComplex a(jx, jy);
int i = 0;
for (i=0; i<200; i++)
{
a = a * a + c;
if (a.magnitude2() > 1000)
return 0;
}
return 1;
}
__global__ void kernel( unsigned char *ptr )
{
// map from blockIdx to pixel position
int x = blockIdx.x;
int y = blockIdx.y;
int offset = x + y * blockDim.x * gridDim.x;
// now calculate the value at that position
int juliaValue = julia( x, y );
ptr[offset] = 255 * juliaValue;
}
int main( void )
{
unsigned char *gpu_bitmap;
unsigned char *cpu_bitmap=(unsigned char*)malloc(sizeof(unsigned char)*DIM*DIM*4);
cudaMalloc( (void**)&gpu_bitmap, DIM*DIM*4 );
dim3 grid(DIM,DIM);
kernel<<<grid,1>>>( gpu_bitmap );
cudaMemcpy( cpu_bitmap, gpu_bitmap,DIM*DIM*4 , cudaMemcpyDeviceToHost );
cudaFree( gpu_bitmap );
printf("hola \n");
Mat imgJulia = Mat::zeros(DIM, DIM, CV_8UC3);
for(int x=0; x<DIM; x++)
{
for(int y=0; y<DIM; y++)
{
int offset = x + y * DIM;
//imgJulia.at<Vec3b>(y,x)[2]= cpu_bitmap [offset + 0];
imgJulia.at<Vec3b>(y,x)[1]= cpu_bitmap [offset + 1];
//imgJulia.at<Vec3b>(y,x)[0]= cpu_bitmap [offset + 2];
}
}
imshow( "Imagen Julia", imgJulia );
waitKey(0);
return 0;
}
*/
|
8,934 | #define N 128
#define B 2
__global__ void k(int* in)
{
in[threadIdx.x] = blockIdx.x;
}
int main()
{
int* in = (int*) malloc(N * sizeof(int));
int* din;
cudaMalloc((void**) &din, N*sizeof(int));
k<<<B,N/B>>>(din);
} |
8,935 | extern "C"
{
__global__ void binaryentropyXsigmoidY(const int lengthX, const double *x, const double *y, double *z)
{
int i = threadIdx.x + blockIdx.x * blockDim.x;
if (i<lengthX)
{
z[i]=x[i]*log(x[i])+(1.0-x[i])*log(1.0-x[i])-x[i]*y[i]+log(1.0+exp(y[i]));
}
}
} |
8,936 | #include <cstdint>
#include <iostream>
__global__ void iota_kernel(float * input, uint64_t size) {
uint64_t thid = blockIdx.x*blockDim.x+threadIdx.x;
for (uint64_t i = thid; i < size; i += gridDim.x*blockDim.x)
input[i] = i;
}
int main () {
uint64_t size = 1UL << 20;
float * input = nullptr;
cudaMallocHost(&input, sizeof(float)*size);
iota_kernel<<<1024, 1024>>>(input, size);
cudaDeviceSynchronize();
for (uint64_t i = 0; i < 20; i++)
std::cout << input[i] << std::endl;
}
|
8,937 | #ifndef M_PI
#define M_PI 3.141592653589793F /* pi */
#endif
#ifndef M_EPS
#define M_EPS 1.01e-3F /* epsilon */
#endif
struct point3d
{
float x=0, y=0, z=0;
};
// database: B*N*3, (x,y,z)
// query: B*M*3, (x,y,z)
// nnIndex: B*M*K
// nnCount: B*M
// nnDist: B*M*K
// filtIndex: B*M*K
__global__ void build_spherical_kernel(int B, int N, int M, int K, int n, int p, int q,
const float radius, const float* database,
const float* query, const int* nnIndex,
const int* nnCount, const float* nnDist, int* filtIndex)
{
// get the neighbor indices
point3d ptQuery, pt, delta;
for(int i=blockIdx.x;i<B;i+=gridDim.x)
{
for(int j=threadIdx.x;j<M;j+=blockDim.x)
{
ptQuery.x = query[i*M*3+j*3];
ptQuery.y = query[i*M*3+j*3+1];
ptQuery.z = query[i*M*3+j*3+2];
int nnSize = nnCount[i*M+j];
for(int k=0;k<nnSize;k++)
{
int ptID = nnIndex[i*M*K+j*K+k]; // input point ID
pt.x = database[i*N*3+ptID*3];
pt.y = database[i*N*3+ptID*3+1];
pt.z = database[i*N*3+ptID*3+2];
delta.x = pt.x - ptQuery.x;
delta.y = pt.y - ptQuery.y;
delta.z = pt.z - ptQuery.z;
float dist = nnDist[i*M*K+j*K+k]; // the sqrt distance
float dist2D = delta.x*delta.x + delta.y*delta.y;
dist2D = sqrtf(dist2D);
filtIndex[i*M*K+j*K+k] = 0;
if (dist>M_EPS) // update the bin index
{
float theta = atan2f(delta.y, delta.x);
float phi = atan2f(delta.z, dist2D);
theta = theta<M_PI?theta:(-M_PI);
theta = theta>(-M_PI)?theta:(-M_PI);
theta += M_PI;
phi = phi<(M_PI/2)?phi:(M_PI/2);
phi = phi>(-M_PI/2)?phi:(-M_PI/2);
phi += M_PI/2;
float alpha = theta*n/2/M_PI;
float beta = phi*p/M_PI;
float gamma = dist*q/radius;
int nID = min(n-1, int(alpha));
int pID = min(p-1, int(beta));
int qID = min(q-1, int(gamma));
filtIndex[i*M*K+j*K+k] = qID*p*n + pID*n + nID + 1;
}
}
}
}
}
// database: B*N*3, (x,y,z)
// query: B*M*3, (x,y,z)
// nnIndex: B*M*K
// nnCount: B*M
// nnDist: B*M*K
// filtIndex: B*M*K
__global__ void build_fuzzy_spherical_kernel(int B, int N, int M, int K, int n, int p, int q,
const float radius, const float* database, const float* query,
const int* nnIndex, const int* nnCount, const float* nnDist,
int* filtIndex, float* filtCoeff)
{
const int F = 4;
// get the neighbor indices
point3d ptQuery, pt, delta;
for(int i=blockIdx.x;i<B;i+=gridDim.x)
{
for(int j=threadIdx.x;j<M;j+=blockDim.x)
{
ptQuery.x = query[i*M*3+j*3];
ptQuery.y = query[i*M*3+j*3+1];
ptQuery.z = query[i*M*3+j*3+2];
int nnSize = nnCount[i*M+j];
for(int k=0;k<nnSize;k++)
{
int ptID = nnIndex[i*M*K+j*K+k]; // input point ID
pt.x = database[i*N*3+ptID*3];
pt.y = database[i*N*3+ptID*3+1];
pt.z = database[i*N*3+ptID*3+2];
delta.x = pt.x - ptQuery.x;
delta.y = pt.y - ptQuery.y;
delta.z = pt.z - ptQuery.z;
float dist = nnDist[i*M*K+j*K+k]; // the sqrt distance
float dist2D = delta.x*delta.x + delta.y*delta.y;
dist2D = sqrtf(dist2D);
float selfCoeff = max(0.0,1-dist/radius);
filtIndex[i*M*K*F+j*K*F+k*F] = 0;
filtCoeff[i*M*K*F+j*K*F+k*F] = selfCoeff; // self-loop coeffcient
// compute the coefficients of fuzzy bins
float theta = atan2f(delta.y, delta.x);
float phi = atan2f(delta.z, dist2D);
theta = theta<M_PI?theta:(-M_PI);
theta = theta>(-M_PI)?theta:(-M_PI);
theta += M_PI;
phi = phi<(M_PI/2)?phi:(M_PI/2);
phi = phi>(-M_PI/2)?phi:(-M_PI/2);
phi += M_PI/2;
int nID, pID[2], qID;
float alpha, beta[2], gamma;
alpha = theta*n/2/M_PI;
beta[0] = phi*p/M_PI;
gamma = dist*q/radius;
nID = min(n-1, int(alpha));
pID[0] = min(p-1, int(beta[0]));
qID = min(q-1, int(gamma));
beta[0] -= pID[0];
pID[1] = beta[0]<0.5? max(0,pID[0]-1):min(p-1,pID[0]+1);
int pIN = (pID[0]==pID[1])?1:2;
beta[1] = (pIN==1)?0:abs(beta[0] - 0.5);
beta[0] = 1 - beta[1];
for(int pi=0;pi<pIN;pi++)
{
int f = qID*p*n + pID[pi]*n + nID + 1;
filtIndex[i*M*K*F+j*K*F+k*F+pi+1] = f;
filtCoeff[i*M*K*F+j*K*F+k*F+pi+1] = beta[pi]*(1-selfCoeff);
}
}
}
}
}
void sphericalKernelLauncher(int B, int N, int M, int K, int n, int p, int q, float radius,
const float* database, const float* query, const int* nnIndex,
const int* nnCount, const float* nnDist, int* filtIndex)
{
build_spherical_kernel<<<B,1024>>>(B, N, M, K, n, p, q, radius,
database, query, nnIndex, nnCount, nnDist, filtIndex);
}
void fuzzySphericalKernelLauncher(int B, int N, int M, int K, int n, int p, int q, float radius,
const float* database, const float* query, const int* nnIndex,
const int* nnCount, const float* nnDist,
int* filtIndex, float* filtCoeff)
{
build_fuzzy_spherical_kernel<<<B,1024>>>(B, N, M, K, n, p, q, radius,
database, query, nnIndex, nnCount, nnDist, filtIndex, filtCoeff);
}
__global__ void build_kpconv_kernel(int B, int N, int M, int T, int K, float sigma,
const float* database, const float* query, const float* kernel,
const int* nnIndex, const int* nnCount, int* filtIndex)
{
// get the neighbor indices
point3d ptQuery, pt, delta;
for(int i=blockIdx.x;i<B;i+=gridDim.x)
{
for(int j=threadIdx.x;j<M;j+=blockDim.x)
{
ptQuery.x = query[i*M*3+j*3];
ptQuery.y = query[i*M*3+j*3+1];
ptQuery.z = query[i*M*3+j*3+2];
int nnSize = nnCount[i*M+j];
for(int k=0;k<nnSize;k++)
{
int ptID = nnIndex[i*M*K+j*K+k]; // input point ID
pt.x = database[i*N*3+ptID*3];
pt.y = database[i*N*3+ptID*3+1];
pt.z = database[i*N*3+ptID*3+2];
delta.x = pt.x - ptQuery.x;
delta.y = pt.y - ptQuery.y;
delta.z = pt.z - ptQuery.z;
float min_dist = 1e20;
int binIndex = 0;
for(int t=0;t<T;t++)
{
float dist = (delta.x-kernel[t*3]) *(delta.x-kernel[t*3]) +
(delta.y-kernel[t*3+1])*(delta.y-kernel[t*3+1]) +
(delta.z-kernel[t*3+2])*(delta.z-kernel[t*3+2]);
if (dist<min_dist)
{
min_dist = dist;
binIndex = t;
}
}
filtIndex[i*M*K+j*K+k] = binIndex;
}
}
}
}
// database: B*N*3, (x,y,z)
// query: B*M*3, (x,y,z)
// nnIndex: B*M*K
// nnCount: B*M
// nnDist: B*M*K
// filtIndex: B*M*K
__global__ void build_fuzzy_kpconv_kernel(int B, int N, int M, int T, int K, float sigma,
const float* database, const float* query, const float* kernel,
const int* nnIndex, const int* nnCount, int* filtIndex, float* filtCoeff)
{
const int F = 4;
// get the neighbor indices
point3d ptQuery, pt, delta;
for(int i=blockIdx.x;i<B;i+=gridDim.x)
{
for(int j=threadIdx.x;j<M;j+=blockDim.x)
{
ptQuery.x = query[i*M*3+j*3];
ptQuery.y = query[i*M*3+j*3+1];
ptQuery.z = query[i*M*3+j*3+2];
int nnSize = nnCount[i*M+j];
for(int k=0;k<nnSize;k++)
{
int ptID = nnIndex[i*M*K+j*K+k]; // input point ID
pt.x = database[i*N*3+ptID*3];
pt.y = database[i*N*3+ptID*3+1];
pt.z = database[i*N*3+ptID*3+2];
delta.x = pt.x - ptQuery.x;
delta.y = pt.y - ptQuery.y;
delta.z = pt.z - ptQuery.z;
int iter = 0;
float coeff;
for(int t=0;t<T;t++)
{
float dist = (delta.x-kernel[t*3])*(delta.x-kernel[t*3]) +
(delta.y-kernel[t*3+1])*(delta.y-kernel[t*3+1]) +
(delta.z-kernel[t*3+2])*(delta.z-kernel[t*3+2]);
coeff = max(0.0,1-sqrtf(dist)/sigma);
if (coeff>0)
{
filtIndex[i*M*K*F+j*K*F+k*F+iter] = t;
filtCoeff[i*M*K*F+j*K*F+k*F+iter] = coeff;
iter++;
}
}
}
}
}
}
void kpconvKernelLauncher(int B, int N, int M, int T, int K, float sigma, const float* database,
const float* query, const float* kernel, const int* nnIndex,
const int* nnCount, int* filtIndex)
{
build_kpconv_kernel<<<B,1024>>>(B, N, M, T, K, sigma, database, query, kernel,
nnIndex, nnCount, filtIndex);
}
void fuzzyKpconvKernelLauncher(int B, int N, int M, int T, int K, float sigma, const float* database,
const float* query, const float* kernel, const int* nnIndex,
const int* nnCount, int* filtIndex, float* filtCoeff)
{
build_fuzzy_kpconv_kernel<<<B,1024>>>(B, N, M, T, K, sigma, database, query, kernel, nnIndex,
nnCount, filtIndex, filtCoeff);
} |
8,938 | /* THE FOLLOWING CODE IS AUTHORED BY ADAM SIMPSON FROM
* OAK RIDGE NATIONAL LABORATORY, WITH MODIFICATIONS
* DONE BY NICOLAS BARRIOS AND MUHANNED IBRAHIM. WE DO
* NOT CLAIM OWNERSHIP NOR COPYRIGHT OVER THIS MATERIAL.
* THE ORIGINAL PUBLICATION AND REPOSITORY CAN BE FOUND HERE:
* https://www.olcf.ornl.gov/tutorials/cuda-game-of-life/
*/
#include <stdio.h>
#include <stdlib.h>
#define SRAND_VALUE 1985
#define BLOCK_SIZE_x 32
#define BLOCK_SIZE_y 16
__global__ void ghostRows(int dim, int *grid) {
// We want id ∈ [1,dim]
int id = blockDim.x * blockIdx.x + threadIdx.x + 1;
if (id <= dim) {
// Copy first real row to bottom ghost row
grid[(dim + 2) * (dim + 1) + id] = grid[(dim + 2) + id];
// Copy last real row to top ghost row
grid[id] = grid[(dim + 2) * dim + id];
}
}
__global__ void ghostCols(int dim, int *grid) {
// We want id ∈ [0,dim+1]
int id = blockDim.x * blockIdx.x + threadIdx.x;
if (id <= dim + 1) {
// Copy first real column to right most ghost column
grid[id * (dim + 2) + dim + 1] = grid[id * (dim + 2) + 1];
// Copy last real column to left most ghost column
grid[id * (dim + 2)] = grid[id * (dim + 2) + dim];
}
}
__global__ void GOL(int dim, int *grid, int *newGrid) {
int iy = (blockDim.y - 2) * blockIdx.y + threadIdx.y;
int ix = (blockDim.x - 2) * blockIdx.x + threadIdx.x;
int id = iy * (dim + 2) + ix;
int i = threadIdx.y;
int j = threadIdx.x;
int numNeighbors;
// Declare the shared memory on a per block level
__shared__ int s_grid[BLOCK_SIZE_y][BLOCK_SIZE_x];
// Copy cells into shared memory
if (ix <= dim + 1 && iy <= dim + 1)
s_grid[i][j] = grid[id];
// Sync all threads in block
__syncthreads();
if (iy <= dim && ix <= dim) {
if (i != 0 && i != blockDim.y - 1 && j != 0 && j != blockDim.x - 1) {
// Get the number of neighbors for a given grid point
numNeighbors = s_grid[i + 1][j] + s_grid[i - 1][j] // upper lower
+ s_grid[i][j + 1] + s_grid[i][j - 1] // right left
+ s_grid[i + 1][j + 1] +
s_grid[i - 1][j - 1] // diagonals
+ s_grid[i - 1][j + 1] + s_grid[i + 1][j - 1];
int cell = s_grid[i][j];
// Here we have explicitly all of the game rules
if (cell == 1 && numNeighbors < 2)
newGrid[id] = 0;
else if (cell == 1 && (numNeighbors == 2 || numNeighbors == 3))
newGrid[id] = 1;
else if (cell == 1 && numNeighbors > 3)
newGrid[id] = 0;
else if (cell == 0 && numNeighbors == 3)
newGrid[id] = 1;
else
newGrid[id] = cell;
}
}
}
int main() {
int i, j, iter;
int *h_grid; // Grid on host
int *d_grid; // Grid on device
int *d_newGrid; // Second grid used on device only
int *d_tmpGrid; // tmp grid pointer used to switch between grid and newGrid
int dim = 1 << 13; // Linear dimension of our grid - not counting ghost cells
int maxIter = 100; // Number of game steps
size_t bytes = sizeof(int) * (dim + 2) * (dim + 2);
// Allocate host Grid used for initial setup and read back from device
h_grid = (int *)malloc(bytes);
// Allocate device grids
cudaMalloc(&d_grid, bytes);
cudaMalloc(&d_newGrid, bytes);
// Assign initial population randomly
srand(SRAND_VALUE);
for (i = 1; i <= dim; i++) {
for (j = 1; j <= dim; j++) {
h_grid[i * (dim + 2) + j] = rand() % 2;
}
}
// See
// https://developer.nvidia.com/blog/how-implement-performance-metrics-cuda-cc/
cudaEvent_t start, stop;
cudaEventCreate(&start);
cudaEventCreate(&stop);
cudaFuncSetCacheConfig(GOL, cudaFuncCachePreferShared);
// Copy over initial game grid (Dim-1 threads)
cudaMemcpy(d_grid, h_grid, bytes, cudaMemcpyHostToDevice);
dim3 blockSize(BLOCK_SIZE_x, BLOCK_SIZE_y, 1);
int linGrid_x = (int)ceil(dim / (float)(BLOCK_SIZE_x - 2));
int linGrid_y = (int)ceil(dim / (float)(BLOCK_SIZE_y - 2));
dim3 gridSize(linGrid_x, linGrid_y, 1);
dim3 cpyBlockSize(BLOCK_SIZE_x, 1, 1);
dim3 cpyGridRowsGridSize((int)ceil(dim / (float)cpyBlockSize.x), 1, 1);
dim3 cpyGridColsGridSize((int)ceil((dim + 2) / (float)cpyBlockSize.x), 1,
1);
// Added this myself -N
#ifdef DEBUG
printf("blockSize: { %d %d %d }\n", blockSize.x, blockSize.y, blockSize.z);
printf("gridSize: { %d %d %d }\n", gridSize.x, gridSize.y, gridSize.z);
printf("cpyBlockSize: { %d %d %d }\n", cpyBlockSize.x, cpyBlockSize.y,
cpyBlockSize.z);
printf("cpyGridRowsGridSize: { %d %d %d }\n", cpyGridRowsGridSize.x,
cpyGridRowsGridSize.y, cpyGridRowsGridSize.z);
printf("cpyGridColsGridSize: { %d %d %d }\n", cpyGridColsGridSize.x,
cpyGridColsGridSize.y, cpyGridColsGridSize.z);
#endif
cudaEventRecord(start);
// Main game loop
for (iter = 0; iter < maxIter; iter++) {
ghostRows<<<cpyGridRowsGridSize, cpyBlockSize>>>(dim, d_grid);
ghostCols<<<cpyGridColsGridSize, cpyBlockSize>>>(dim, d_grid);
GOL<<<gridSize, blockSize>>>(dim, d_grid, d_newGrid);
// Swap our grids and iterate again
d_tmpGrid = d_grid;
d_grid = d_newGrid;
d_newGrid = d_tmpGrid;
} // iter loop
cudaEventRecord(stop);
cudaError_t error = cudaGetLastError();
if (error != cudaSuccess)
printf("CUDA error %s\n", cudaGetErrorString(error));
// Copy back results and sum
cudaMemcpy(h_grid, d_grid, bytes, cudaMemcpyDeviceToHost);
cudaEventSynchronize(stop);
cudaDeviceSynchronize();
// Sum up alive cells and print results
int total = 0;
for (i = 1; i <= dim; i++) {
for (j = 1; j <= dim; j++) {
#ifdef DEBUG
printf("%d", h_grid[i * (dim + 2) + j]);
#endif
total += h_grid[i * (dim + 2) + j];
}
#ifdef DEBUG
printf("\n");
#endif
}
printf("Total Alive: %d\n", total);
float ms = 0;
cudaEventElapsedTime(&ms, start, stop);
printf("ElapsedTime: %f ms\n", ms);
cudaFree(d_grid);
cudaFree(d_newGrid);
free(h_grid);
return 0;
} |
8,939 | #include <stdlib.h>
#include <stdio.h>
#include <string.h>
#include <math.h>
#include <cuda.h>
#include <sys/time.h>
#define MAX_THREADS_PER_BLOCK 512
int no_of_nodes;
int edge_list_size;
FILE *fp;
//Structure to hold a node information
struct Node
{
int starting;
int no_of_edges;
};
__global__ void
Kernel3(Node* g_graph_nodes, int* g_graph_edges,int* cd, bool* f1d, bool *f2d,int no_of_nodes,bool *md)
{
int i = blockIdx.x*MAX_THREADS_PER_BLOCK + threadIdx.x;
//int idx, idxi;
//printf("\n Thread id: %d",i);
int ci, cj;
if(f1d[i]==true)
{
f1d[i]=false;
ci=cd[i];
bool cimod=false;
int temp;
for(int j=g_graph_nodes[i].starting;j<(g_graph_nodes[i].starting + g_graph_nodes[i].no_of_edges); j++)
{
temp=g_graph_edges[j];
cj = cd[temp];
if ( ci < cj )
{
atomicMin(&cd[temp],ci);
f2d[temp]=true;
*md=true;
}
else
if (ci>cj)
{
ci=cj;
cimod=true;
}
}
if(cimod==true)
{
atomicMin(&cd[i],ci);
f2d[i]=true;
*md=true;
}
}
// printf("\n End of kernel: %d", cd[i]);
}
long long start_timer();
long long stop_timer(long long start_time, char *name);
void GPLGraph(int argc, char** argv);
////////////////////////////////////////////////////////////////////////////////
// Main Program
////////////////////////////////////////////////////////////////////////////////
int main( int argc, char** argv)
{
no_of_nodes=0;
edge_list_size=0;
GPLGraph( argc, argv);
}
void Usage(int argc, char**argv){
fprintf(stderr,"Usage: %s <input_file>\n", argv[0]);
}
////////////////////////////////////////////////////////////////////////////////
////////////////////////////////////////////////////////////////////////////////
void GPLGraph( int argc, char** argv)
{
char *input_f;
if(argc!=2){
Usage(argc, argv);
exit(0);
}
input_f = argv[1];
printf("Reading File\n");
//Read in Graph from a file
fp = fopen(input_f,"r");
if(!fp)
{
printf("Error Reading graph file\n");
return;
}
int source = 0;
fscanf(fp,"%d",&no_of_nodes);
int num_of_blocks = 1;
int num_of_threads_per_block = no_of_nodes;
//Make execution Parameters according to the number of nodes
//Distribute threads across multiple Blocks if necessary
if(no_of_nodes>MAX_THREADS_PER_BLOCK)
{
num_of_blocks = (int)ceil(no_of_nodes/(double)MAX_THREADS_PER_BLOCK);
num_of_threads_per_block = MAX_THREADS_PER_BLOCK;
}
// allocate host memory
Node* h_graph_nodes = (Node*) malloc(sizeof(Node)*no_of_nodes);
int start, edgeno;
// initalize the memory
for( unsigned int i = 0; i < no_of_nodes; i++)
{
fscanf(fp,"%d %d",&start,&edgeno);
h_graph_nodes[i].starting = start;
h_graph_nodes[i].no_of_edges = edgeno;
}
//read the source node from the file
fscanf(fp,"%d",&source);
source=0;
fscanf(fp,"%d",&edge_list_size);
int id,cost;
int* h_graph_edges = (int*) malloc(sizeof(int)*edge_list_size);
for(unsigned int i=0; i < edge_list_size ; i++)
{
fscanf(fp,"%d",&id);
fscanf(fp,"%d",&cost);
h_graph_edges[i] = id;
}
int* c = (int*) malloc(sizeof(int)*no_of_nodes);
bool* f1 = (bool*) malloc(sizeof(bool)*no_of_nodes);
bool* f2 = (bool*) malloc(sizeof(bool)*no_of_nodes);
bool* f3 = (bool*) malloc(sizeof(bool)*no_of_nodes);
for(unsigned int i=0; i < no_of_nodes ; i++)
{
c[i]=i;
f1[i]=true;
f2[i]=false;
}
if(fp)
fclose(fp);
printf("Read File\n");
//Copy the Node list to device memory
Node* d_graph_nodes;
cudaMalloc( (void**) &d_graph_nodes, sizeof(Node)*no_of_nodes) ;
cudaMemcpy( d_graph_nodes, h_graph_nodes, sizeof(Node)*no_of_nodes, cudaMemcpyHostToDevice) ;
//Copy the Edge List to device Memory
int* d_graph_edges;
cudaMalloc( (void**) &d_graph_edges, sizeof(int)*edge_list_size) ;
cudaMemcpy( d_graph_edges, h_graph_edges, sizeof(int)*edge_list_size, cudaMemcpyHostToDevice) ;
//Allocate Color Array in device Memory
int* cd;
cudaMalloc( (void**) &cd, sizeof(int)*no_of_nodes);
cudaMemcpy( cd, c, sizeof(int)*no_of_nodes,cudaMemcpyHostToDevice);
//Allocate Boolean Array in current Iteration
bool* f1d;
cudaMalloc( (void**) &f1d, sizeof(bool)*no_of_nodes);
cudaMemcpy( f1d, f1, sizeof(bool)*no_of_nodes,cudaMemcpyHostToDevice);
//Allocate Boolean Array for next Iteration
bool* f2d;
cudaMalloc( (void**) &f2d, sizeof(bool)*no_of_nodes);
cudaMemcpy( f2d, f2, sizeof(bool)*no_of_nodes,cudaMemcpyHostToDevice);
bool* f3d;
cudaMalloc( (void**) &f3d, sizeof(bool)*no_of_nodes);
bool m;
bool *md;
cudaMalloc( (void**) &md, sizeof(bool));
printf("Copied Everything to Kernel");
// setup execution parameters
dim3 grid( num_of_blocks, 1, 1);
dim3 threads( num_of_threads_per_block, 1, 1);
long long timer;
timer = start_timer();
int k=0;
printf("Start traversing the tree\n");
//Call the Kernel untill all the elements of Frontier are not false
do
{
m=false;
//if no thread changes this value then the loop stops
cudaMemcpy( md, &m, sizeof(bool), cudaMemcpyHostToDevice) ;
Kernel3<<< grid, threads, 0 >>>( d_graph_nodes, d_graph_edges,cd,f1d,f2d, no_of_nodes,md);
// check if kernel execution generated and error
cudaMemcpy( f1, f1d, sizeof(bool)*no_of_nodes,cudaMemcpyDeviceToHost);
cudaMemcpy( f2, f2d, sizeof(bool)*no_of_nodes,cudaMemcpyDeviceToHost);
cudaMemcpy( f1d, f2, sizeof(bool)*no_of_nodes,cudaMemcpyHostToDevice);
cudaMemcpy( f2d, f1, sizeof(bool)*no_of_nodes,cudaMemcpyHostToDevice);
k++;
cudaMemcpy( &m,md , sizeof(bool), cudaMemcpyDeviceToHost) ;
// printf("\n \n Return from kernel: %d",m);
}
while(m);
printf("Kernel Executed %d times\n",k);
// copy result from device to host
cudaMemcpy( c,cd, sizeof(int)*no_of_nodes, cudaMemcpyDeviceToHost) ;
//Store the result into a file
FILE *fpo = fopen("result.txt","w");
for(unsigned int i=0;i<no_of_nodes;i++)
fprintf(fpo,"%d) color:%d\n",i,c[i]);
fclose(fpo);
printf("Result stored in result.txt\n");
// cleanup memory
free( h_graph_nodes);
free( h_graph_edges);
cudaFree(d_graph_nodes);
cudaFree(d_graph_edges);
cudaFree(cd);
cudaFree(f1d);
cudaFree(f2d);
//cudaFree(md);
stop_timer(timer, "Total Processing time");
}
long long start_timer() {
struct timeval tv;
gettimeofday(&tv, NULL);
return tv.tv_sec * 1000000 + tv.tv_usec;
}
long long stop_timer(long long start_time, char *label) {
struct timeval tv;
gettimeofday(&tv, NULL);
long long end_time = tv.tv_sec * 1000000 + tv.tv_usec;
printf("%s: %.5f sec\n", label, ((float) (end_time - start_time)) / (1000 * 1000));
return end_time - start_time;
}
|
8,940 | #include <stdio.h>
#define N 4
#define n 3
__global__ void matrixMul( float * a, float * b, float * c )
{
float val = 0;
int row = blockIdx.x * blockDim.x + threadIdx.x;
int col = blockIdx.y * blockDim.y + threadIdx.y;
if (row < n && col < n){
for ( int k = 0; k < N; ++k )
val += a[row * N + k] * b[ k*N + col];
}
c[row * N + col] = val;
}
__global__ void matrixTrans(float * M,float * MT)
{
int val=0;
int row = blockIdx.x * blockDim.x + threadIdx.x;
int col = blockIdx.y * blockDim.y + threadIdx.y;
MT[row + col*N] = 0;
if (row < N && col < N)
{
val = M[col + row*N];
MT[row + col*N] = val;
}
}
void print(float * M,int cols,int rows){
for( int row = 0; row < rows; ++row ){
for( int col = 0; col < cols; ++col )
{
printf("%f,",M[row*N + col]);
}
printf("\n");
}
}
int main()
{
float *a, *b, *c_gpu;
int size = N * n * sizeof (float); // Number of bytes of an N x N matrix
// Allocate memory
cudaMallocManaged (&a, size);
cudaMallocManaged (&b, size);
cudaMallocManaged (&c_gpu, n*n* sizeof(float));
// Initialize memory
for( int row = 0; row < N; ++row )
{
for( int col = 0; col < n; ++col )
{
a[row*N + col] = row+2.*col;
b[row*N + col] = 1.;
c_gpu[row*N + col] = 0.;
}
}
print(a,n,N);
dim3 threads_per_block (16, 16, 1); // A 16 x 16 block threads
dim3 number_of_blocks ((N / threads_per_block.x) + 1, (n / threads_per_block.y) + 1, 1);
matrixTrans <<< number_of_blocks, threads_per_block >>> ( a,b );
cudaDeviceSynchronize(); // Wait for the GPU to finish before proceeding
dim3 threads_per_block2 (16, 16, 1); // A 16 x 16 block threads
dim3 number_of_blocks2 ((n / threads_per_block.x) + 1, (n / threads_per_block.y) + 1, 1);
matrixMul <<< number_of_blocks2, threads_per_block2 >>> ( b, a, c_gpu );
cudaDeviceSynchronize(); // Wait for the GPU to finish before proceeding
print(b,N,n);
print(a,n,N);
print(c_gpu,n,n);
// Free all our allocated memory
cudaFree(a); cudaFree(b);
cudaFree( c_gpu );
}
|
8,941 | //adding two values using CUDA
#include <stdio.h>
#include <stdlib.h>
#include <cuda_runtime.h>
__global__ void add(int *d_a, int *d_b, int *d_result) {
*d_result = *d_a + *d_b;
}
int main() {
//declarre host variables
int h_a = 50;
int h_b = 50;
int h_result = 0;
//declare device variables
int *d_a;
int *d_b;
int *d_result;
//Memory allocation of device variable
cudaMalloc((void**)&d_a, sizeof(int));
cudaMalloc((void**)&d_b, sizeof(int));
cudaMalloc((void**)&d_result, sizeof(int));
//Copy Host memory to Device memory
cudaMemcpy(d_a, &h_a, sizeof(int), cudaMemcpyHostToDevice);
cudaMemcpy(d_b, &h_b, sizeof(int), cudaMemcpyHostToDevice);
//Launch Kernel
add<<<1,1>>>(d_a,d_b,d_result);
//copy device results to host results
cudaMemcpy(&h_result, d_result, sizeof(int), cudaMemcpyDeviceToHost);
printf("the result is: %d\n",h_result);
//free device memory
cudaFree(d_a);
cudaFree(d_b);
cudaFree(d_result);
return 0;
} |
8,942 | #include <iostream>
#include <iomanip>
#include <cstdlib>
#include <stdlib.h>
#include <cstdio>
__host__ __device__ inline double dg4(const double v1, const double v2, const double v3, const double v4, const double v5, const double v6, const double v7)
{
return (1./576.)*(v1+v7) + (-54./576.)*(v2+v6) + (783./576.)*(v3+v5) + (-1460./576.)*v4;
}
/*
4th order diffusion (3D), quite similar to CPU implementation MicroHH
*/
void diff_cpu_3d(double * const __restrict__ at, const double * const __restrict__ a,
const double dxidxi, const double dyidyi, const double dzidzi,
const int istart, const int iend,
const int jstart, const int jend,
const int kstart, const int kend,
const int icells, const int ijcells)
{
const int ii1 = 1;
const int ii2 = 2;
const int ii3 = 3;
const int jj1 = 1*icells;
const int jj2 = 2*icells;
const int jj3 = 3*icells;
const int kk1 = 1*ijcells;
const int kk2 = 2*ijcells;
const int kk3 = 3*ijcells;
const double visc = 0.1;
for (int k=kstart; k<kend; ++k)
for (int j=jstart; j<jend; ++j)
#pragma ivdep
for (int i=istart; i<iend; ++i)
{
const int ijk = i + j*icells + k*ijcells;
at[ijk] += visc * dg4(a[ijk-ii3], a[ijk-ii2], a[ijk-ii1], a[ijk], a[ijk+ii1], a[ijk+ii2], a[ijk+ii3])*dxidxi
+ visc * dg4(a[ijk-jj3], a[ijk-jj2], a[ijk-jj1], a[ijk], a[ijk+jj1], a[ijk+jj2], a[ijk+jj3])*dyidyi
+ visc * dg4(a[ijk-kk3], a[ijk-kk2], a[ijk-kk1], a[ijk], a[ijk+kk1], a[ijk+kk2], a[ijk+kk3])*dzidzi;
}
}
/*
4th order diffusion (3D), no shared memory use, quite similar to GPU implementation MicroHH
*/
__global__ void diff_gpu_3d(double * const __restrict__ at, const double * const __restrict__ a,
const double dxidxi, const double dyidyi, const double dzidzi,
const int istart, const int iend,
const int jstart, const int jend,
const int kstart, const int kend,
const int icells, const int ijcells)
{
const int i = blockIdx.x*blockDim.x + threadIdx.x + istart;
const int j = blockIdx.y*blockDim.y + threadIdx.y + jstart;
const int k = blockIdx.z + kstart;
const double visc = 0.1;
if(i < iend && j < jend && k < kend)
{
const int ijk = i + j*icells + k*ijcells;
const int ii1 = 1;
const int ii2 = 2;
const int ii3 = 3;
const int jj1 = 1*icells;
const int jj2 = 2*icells;
const int jj3 = 3*icells;
const int kk1 = 1*ijcells;
const int kk2 = 2*ijcells;
const int kk3 = 3*ijcells;
at[ijk] += visc * dg4(a[ijk-ii3], a[ijk-ii2], a[ijk-ii1], a[ijk], a[ijk+ii1], a[ijk+ii2], a[ijk+ii3])*dxidxi
+ visc * dg4(a[ijk-jj3], a[ijk-jj2], a[ijk-jj1], a[ijk], a[ijk+jj1], a[ijk+jj2], a[ijk+jj3])*dyidyi
+ visc * dg4(a[ijk-kk3], a[ijk-kk2], a[ijk-kk1], a[ijk], a[ijk+kk1], a[ijk+kk2], a[ijk+kk3])*dzidzi;
}
}
/*
4th order diffusion, shared memory for horizontal (i,j) stencil, global memory for vertical (k) stencil
*/
__global__ void diff_gpu_3d_s2d(double * const __restrict__ at, const double * const __restrict__ a,
const double dxidxi, const double dyidyi, const double dzidzi,
const int istart, const int iend,
const int jstart, const int jend,
const int kstart, const int kend,
const int icells, const int ijcells, const int ngc)
{
extern __shared__ double as[];
const int tx = threadIdx.x;
const int ty = threadIdx.y;
const int i = blockIdx.x*blockDim.x + threadIdx.x + istart;
const int j = blockIdx.y*blockDim.y + threadIdx.y + jstart;
const int k = blockIdx.z + kstart;
const int blockxpad = blockDim.x+2*ngc;
const double visc = 0.1;
if(i < iend && j < jend && k < kend)
{
const int ijk = i + j*icells + k*ijcells; // index in global memory
const int ijks = (tx+ngc) + (ty+ngc)*blockxpad; // Same location in 2d shared mem
const int ii1 = 1;
const int ii2 = 2;
const int ii3 = 3;
const int jj3 = 3*icells;
const int kk1 = 1*ijcells;
const int kk2 = 2*ijcells;
const int kk3 = 3*ijcells;
const int jjs1 = 1*blockxpad;
const int jjs2 = 2*blockxpad;
const int jjs3 = 3*blockxpad;
as[ijks] = a[ijk];
if(ty < ngc)
as[ijks-jjs3] = a[ijk-jj3];
if(ty >= blockDim.y-ngc)
as[ijks+jjs3] = a[ijk+jj3];
if(tx < ngc)
as[ijks-ii3] = a[ijk-ii3];
if(tx >= blockDim.x-ngc)
as[ijks+ii3] = a[ijk+ii3];
__syncthreads();
at[ijk] += visc * dg4(as[ijks-ii3 ], as[ijks-ii2 ], as[ijks-ii1 ], as[ijks], as[ijks+ii1 ], as[ijks+ii2 ], as[ijks+ii3 ])*dxidxi
+ visc * dg4(as[ijks-jjs3], as[ijks-jjs2], as[ijks-jjs1], as[ijks], as[ijks+jjs1], as[ijks+jjs2], as[ijks+jjs3])*dyidyi
+ visc * dg4(a [ijk-kk3 ], a [ijk-kk2 ], a [ijk-kk1 ], as[ijks], a [ijk+kk1 ], a [ijk+kk2 ], a [ijk+kk3 ])*dzidzi;
}
}
/*
4th order diffusion, shared memory for horizontal (i,j) stencil, vertical stencil in local variables, vertical loop on GPU
*/
__global__ void diff_gpu_3d_s3d(double * const __restrict__ at, const double * const __restrict__ a,
const double dxidxi, const double dyidyi, const double dzidzi,
const int istart, const int iend,
const int jstart, const int jend,
const int kstart, const int kend,
const int icells, const int ijcells, const int ngc)
{
extern __shared__ double as[];
const int tx = threadIdx.x;
const int ty = threadIdx.y;
const int i = blockIdx.x*blockDim.x + threadIdx.x + istart;
const int j = blockIdx.y*blockDim.y + threadIdx.y + jstart;
const int blockxpad = blockDim.x+2*ngc;
const double visc = 0.1;
if(i < iend && j < jend)
{
const int ii1 = 1;
const int ii2 = 2;
const int ii3 = 3;
const int jj3 = 3*icells;
const int kk1 = 1*ijcells;
const int kk2 = 2*ijcells;
const int kk3 = 3*ijcells;
const int kk4 = 4*ijcells;
const int jjs1 = 1*blockxpad;
const int jjs2 = 2*blockxpad;
const int jjs3 = 3*blockxpad;
int ijk = i +j*icells + kstart*ijcells;
double akm3, akm2, akm1, aijk, akp1, akp2, akp3;
// Read vertical stencil into variables
akm3 = a[ijk-kk3];
akm2 = a[ijk-kk2];
akm1 = a[ijk-kk1];
aijk = a[ijk ];
akp1 = a[ijk+kk1];
akp2 = a[ijk+kk2];
akp3 = a[ijk+kk3];
for (int k=kstart; k<kend; ++k)
{
const int ijk = i + j*icells + k*ijcells; // index in global memory
const int ijks = (tx+ngc) + (ty+ngc)*blockxpad; // Same location in 2d shared mem
__syncthreads();
as[ijks] = aijk;
if(ty < ngc)
as[ijks-jjs3] = a[ijk-jj3];
if(ty >= blockDim.y-ngc)
as[ijks+jjs3] = a[ijk+jj3];
if(tx < ngc)
as[ijks-ii3] = a[ijk-ii3];
if(tx >= blockDim.x-ngc)
as[ijks+ii3] = a[ijk+ii3];
__syncthreads();
at[ijk] += visc * dg4(as[ijks-ii3 ], as[ijks-ii2 ], as[ijks-ii1 ], as[ijks], as[ijks+ii1 ], as[ijks+ii2 ], as[ijks+ii3 ])*dxidxi
+ visc * dg4(as[ijks-jjs3], as[ijks-jjs2], as[ijks-jjs1], as[ijks], as[ijks+jjs1], as[ijks+jjs2], as[ijks+jjs3])*dyidyi
+ visc * dg4(akm3, akm2, akm1, aijk, akp1, akp2, akp3 )*dzidzi;
// Shift vertical stencil
akm3 = akm2;
akm2 = akm1;
akm1 = aijk;
aijk = akp1;
akp1 = akp2;
akp2 = akp3;
if(k < kend-1)
akp3 = a[ijk+kk4];
}
}
}
/*
Get max difference between two fields
*/
double maxdiff(const double * const __restrict__ a, const double * const __restrict__ b, const int n)
{
double maxdiff=0;
double diff=0;
for(int i=0; i<n; ++i)
{
diff = std::abs(a[i]-b[i]);
if(diff > maxdiff)
maxdiff = diff;
}
return maxdiff;
}
int main()
{
//
// Grid
//
const double dxi = 0.1;
const double dyi = 0.1;
const double dzi = 0.1;
const int itot = 256;
const int jtot = 256;
const int ktot = 256;
const int gc = 3;
const int iter = 50;
//
// Calculate the required variables.
//
const int ncells = (itot+2*gc)*(jtot+2*gc)*(ktot+2*gc);
const int istart = gc;
const int jstart = gc;
const int kstart = gc;
const int iend = itot+gc;
const int jend = jtot+gc;
const int kend = ktot+gc;
const int icells = itot+2*gc;
const int ijcells = (itot+2*gc)*(jtot+2*gc);
//
// Prepare fields on HOST
//
double *a = new double[ncells];
double *at = new double[ncells];
double *tmp1 = new double[ncells];
for (int n=0; n<ncells; ++n)
{
a [n] = 0.001 * (std::rand() % 1000) - 0.5;
at[n] = 0.;
tmp1[n] = 0.;
}
//
// Prepare fields on DEVICE
//
double *ad, *atd;
cudaMalloc((void **)&ad, ncells*sizeof(double));
cudaMalloc((void **)&atd, ncells*sizeof(double));
cudaMemcpy(ad, a, ncells*sizeof(double), cudaMemcpyHostToDevice);
cudaMemcpy(atd, at, ncells*sizeof(double), cudaMemcpyHostToDevice);
//
// CUDA thread blocks
//
const int blocki = 32;
const int blockj = 8;
const int gridi = itot/blocki + (itot%blocki > 0);
const int gridj = jtot/blockj + (jtot%blockj > 0);
dim3 gridGPU (gridi, gridj, ktot);
dim3 gridGPU2d(gridi, gridj, 1);
dim3 blockGPU(blocki, blockj, 1);
//
// Timer stuff
//
cudaEvent_t startEvent, stopEvent;
cudaEventCreate(&startEvent);
cudaEventCreate(&stopEvent);
float dt1, dt2;
//
// Execute kernels
//
//////////////////// CPU //////////////////////////
cudaEventRecord(startEvent, 0);
for(int n=0; n<iter; ++n)
{
diff_cpu_3d(at, a, dxi, dyi, dzi, istart, iend, jstart, jend, kstart, kend, icells, ijcells);
}
cudaEventRecord(stopEvent, 0);
cudaEventSynchronize(stopEvent);
cudaEventElapsedTime(&dt1, startEvent, stopEvent);
printf("CPU; elapsed=%f [ms]\n",dt1);
//////////////////// GPU //////////////////////////
cudaDeviceSetSharedMemConfig(cudaSharedMemBankSizeEightByte);
cudaEventRecord(startEvent, 0);
for(int n=0; n<iter; ++n)
{
diff_gpu_3d<<<gridGPU, blockGPU>>>
(atd, ad, dxi, dyi, dzi, istart, iend, jstart, jend, kstart, kend, icells, ijcells);
//diff_gpu_3d_s2d<<<gridGPU, blockGPU, (blocki+2*gc)*(blockj+2*gc)*sizeof(double)>>>
// (atd, ad, dxi, dyi, dzi, istart, iend, jstart, jend, kstart, kend, icells, ijcells, gc);
//diff_gpu_3d_s3d<<<gridGPU2d, blockGPU, (blocki+2*gc)*(blockj+2*gc)*sizeof(double)>>>
// (atd, ad, dxi, dyi, dzi, istart, iend, jstart, jend, kstart, kend, icells, ijcells, gc);
}
cudaEventRecord(stopEvent, 0);
cudaEventSynchronize(stopEvent);
cudaEventElapsedTime(&dt2, startEvent, stopEvent);
//
// Copy device field to tmp1
//
cudaMemcpy(tmp1, atd, ncells*sizeof(double), cudaMemcpyDeviceToHost);
printf("GPU; elapsed=%f [ms], speedup=%f, maxdiff=%e \n",dt2,dt1/dt2,maxdiff(at,tmp1,ncells));
return 0;
}
|
8,943 | /*
* Copyright (c) 2019 Opticks Team. All Rights Reserved.
*
* This file is part of Opticks
* (see https://bitbucket.org/simoncblyth/opticks).
*
* 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.
*/
/*
Bizarre for this test compilation fails::
nvcc fatal : redefinition of argument 'std'
when have the below include::
cmake_minimum_required(VERSION 3.5 FATAL_ERROR)
set(name CUDARapTest)
project(${name} VERSION 0.1.0)
#include(OpticksBuildOptions)
*/
#include <cstdio>
#include <cstring>
// Print device properties
void printDevProp(cudaDeviceProp devProp)
{
printf("Major revision number: %d\n", devProp.major);
printf("Minor revision number: %d\n", devProp.minor);
printf("Name: %s\n", devProp.name);
printf("Total global memory: %zu\n", devProp.totalGlobalMem);
printf("Total shared memory per block: %zu\n", devProp.sharedMemPerBlock);
printf("Total registers per block: %d\n", devProp.regsPerBlock);
printf("Warp size: %d\n", devProp.warpSize);
printf("Maximum memory pitch: %zu\n", devProp.memPitch);
printf("Maximum threads per block: %d\n", devProp.maxThreadsPerBlock);
for (int i = 0; i < 3; ++i)
printf("Maximum dimension %d of block: %d\n", i, devProp.maxThreadsDim[i]);
for (int i = 0; i < 3; ++i)
printf("Maximum dimension %d of grid: %d\n", i, devProp.maxGridSize[i]);
printf("Clock rate: %d\n", devProp.clockRate);
printf("Total constant memory: %zu\n", devProp.totalConstMem);
printf("Texture alignment: %zu\n", devProp.textureAlignment);
printf("Concurrent copy and execution: %s\n", (devProp.deviceOverlap ? "Yes" : "No"));
printf("Number of multiprocessors: %d\n", devProp.multiProcessorCount);
printf("Kernel execution timeout: %s\n", (devProp.kernelExecTimeoutEnabled ? "Yes" : "No"));
return;
}
int main(int argc, char** argv)
{
// Number of CUDA devices
int devCount;
printf( " argv[0] %s cudaGetDeviceCount START \n", argv[0] );
cudaGetDeviceCount(&devCount);
printf( " argv[0] %s cudaGetDeviceCount DONE \n", argv[0] );
bool quiet = argc > 1 && strlen(argv[1]) > 0 && argv[1][0] == 'q' ;
int target = argc > 1 && strlen(argv[1]) > 1 ? atoi(argv[1]+1) : -1 ;
if(!quiet)
{
printf("CUDA Device Query...target %d \n", target);
printf("There are %d CUDA devices.\n", devCount);
}
int compute_capability = 0 ;
// Iterate through devices
for (int i = 0; i < devCount; ++i)
{
// Get device properties
if(!quiet) printf("\nCUDA Device #%d\n", i);
cudaDeviceProp devProp;
cudaGetDeviceProperties(&devProp, i);
if(!quiet) printDevProp(devProp);
compute_capability = devProp.major*10 + devProp.minor ;
}
printf("%d\n", compute_capability);
cudaDeviceSynchronize();
return 0;
}
|
8,944 | #include "includes.h"
__global__ void extractParam ( const int d, const int n, const int Indx, const float *s, float *a ) {
int i = threadIdx.x + blockDim.x * blockIdx.x;
if ( i < n ) {
a[i] = s[Indx+i*d];
}
} |
8,945 | #include "includes.h"
extern "C" {
}
#define ROTATE_DOWN(val,MAX) ((val-1==-1)?MAX-1:val-1)
#define ROTATE_UP(val,MAX) ((val+1)%MAX)
/**
* GPU Device kernel for the for 2D stencil
* First attempt during hackaton
* M = Rows, N = Cols INCLUDING HALOS
* In this version now we replace the size of the shared memory to be just 3 rows (actually 1+HALO*2) rows
*/
__global__ void gpu_stencil2D_4pt_hack2(double * dst, double * src, int M, int N)
{
// printf("kernel begin!\n");
//Declaring the shared memory array for source
__shared__ double shared_mem[ 1 + HALO*2 ] [ GRID_TILE_X + HALO*2]; //1 is the row I am modifying
//double * shSrc = shared_mem;
//indexes
int i, j, curRow;
//Cols * numRows/Tile * tileIndex
int base_global_idx = ( N ) * ( GRID_TILE_Y * blockIdx.y ) + GRID_TILE_X*blockIdx.x;
int center = 1,north = 0,south = 2; //indexes for the current location in the shared memory
//copy the shared memory to fill the pipeline
for (i = 0 ; i < 1+HALO*2 ; i ++ )
for (j = threadIdx.x ; j < GRID_TILE_X+2*HALO ; j+=blockDim.x)
{
shared_mem [i][j] = src[base_global_idx + i*N + j];
}
__syncthreads();
//Pipelined copy one row and process it
for ( curRow = HALO; curRow < GRID_TILE_Y; curRow+=1 )
{
//Stencil computation
for (j = threadIdx.x + HALO ; j < GRID_TILE_X+HALO ; j+=blockDim.x)
{
//top + bottom + left + right
dst[base_global_idx + curRow*N + j] = (shared_mem[north][j] + shared_mem[south][j] + shared_mem[center][j-1] + shared_mem[center][j+1] )/5.5;
}
__syncthreads();
//We are copying from dst to shared memory.
for (j = threadIdx.x ; j < GRID_TILE_X+2*HALO ; j+=blockDim.x)
{
shared_mem [north][j] = src[base_global_idx + (curRow+2)*N + j];
}
center = ROTATE_UP(center,3);
south = ROTATE_UP(south,3);
north = ROTATE_UP(north,3);
__syncthreads();
}
//Dranning the pipeline
for (j = threadIdx.x + HALO ; j < GRID_TILE_X+HALO ; j+=blockDim.x)
{
//top + bottom + left + right
dst[base_global_idx + curRow*N + j] = (shared_mem[north][j] + shared_mem[south][j] + shared_mem[center][j-1] + shared_mem[center][j+1] )/5.5;
}
__syncthreads();
// printf("kernel finish!\n");
} |
8,946 | #include <stdio.h>
#include <stdlib.h>
#include <time.h>
#include <sys/time.h>
#include <cuda_runtime.h>
#define N 1000000000
#define KERNELSIZE 9
#define THREADSPERBLOCK 1024
#define BLOCKSPERGRID (N+THREADSPERBLOCK-1)/THREADSPERBLOCK
// 9 wide 1d kernel, no padding so it cuts out early
// shift by 4 to align with original data
__global__ void conv( float *data, float *kernel, float *output ){
int tid =blockIdx.x*blockDim.x+threadIdx.x;
int i;
for(i=0; i<9; i++){
output[tid] += data[tid + i] * kernel[i];
}
}
int main(){
srand(time(NULL));
struct timespec t_start, t_end;
double elapsedTimeCPU;
int pass = 1;
// gassian kernel from: http://dev.theomader.com/gaussian-kernel-calculator/
float kernel[9] = {0.000229, 0.005977, 0.060598, 0.241732, 0.382928, 0.241732, 0.060598, 0.005977, 0.000229};
// random number from python, irl this would come from lidar
float* data = (float*)malloc(N*sizeof(float));
for(int i = 0;i < N;i++){
data[i] = rand()%10+rand()/RAND_MAX;
}
// empty array to store the output
// float output[N-KERNELSIZE+1];
//CPU
clock_gettime( CLOCK_REALTIME, &t_start);
float* output = (float*)malloc((N-KERNELSIZE+1)*sizeof(float));
for (int i = 0; i < N-KERNELSIZE+1;i++){
output[i] = 0;
for (int j = 0; j < KERNELSIZE; j++){
output[i] += kernel[j] * data[i+j];
}
}
clock_gettime( CLOCK_REALTIME, &t_end);
elapsedTimeCPU = (t_end.tv_sec - t_start.tv_sec) * 1000.0;
elapsedTimeCPU += (t_end.tv_nsec - t_start.tv_nsec) / 1000000.0;
printf("CPU elapsedTime: %lf ms\n", elapsedTimeCPU);
//GPU
float *d_kernel, *d_data, *d_output;
// allocate the memory on the GPU
cudaMalloc( (void**)&d_kernel, KERNELSIZE * sizeof(float) );
cudaMalloc( (void**)&d_data, N * sizeof(float) );
cudaMalloc( (void**)&d_output, (N-KERNELSIZE+1) * sizeof(float) );
float* output_from_device = (float*)malloc((N-KERNELSIZE+1)*sizeof(float));
cudaMemcpy( d_kernel, kernel, KERNELSIZE * sizeof(float), cudaMemcpyHostToDevice );
cudaMemcpy( d_data, data, N * sizeof(float), cudaMemcpyHostToDevice );
cudaEvent_t start, stop;
cudaEventCreate(&start);
cudaEventCreate(&stop);
cudaEventRecord(start, 0);
conv<<<BLOCKSPERGRID, THREADSPERBLOCK>>>(d_data, d_kernel, d_output);
cudaEventRecord(stop, 0);
cudaEventSynchronize(stop);
cudaMemcpy(output_from_device, d_output, (N-KERNELSIZE+1) * sizeof(float), cudaMemcpyDeviceToHost );
float elapsedTime;
cudaEventElapsedTime(&elapsedTime, start, stop);
printf("GPU elapsedTime: %lf ms\n", elapsedTime);
cudaEventDestroy(start);
cudaEventDestroy(stop);
printf("speedup: %lf \n", elapsedTimeCPU/elapsedTime);
for (int i = 0; i < N-KERNELSIZE+1; i++){
if(output_from_device[i]-output[i]>0.00001){ //don't use if(output_from_device[i]!=output[i])
printf("CPU:%lf GPU:%lf\n",output[i], output_from_device[i] );
pass = 0;
}
}
if(pass == 1)
printf("Test pass!\n");
else
printf("Test fail!\n");
} |
8,947 | #include "includes.h"
# define MAX(a, b) ((a) > (b) ? (a) : (b))
# define GAUSSIAN_KERNEL_SIZE 3
# define SOBEL_KERNEL_SIZE 5
# define TILE_WIDTH 32
# define SMEM_SIZE 128
__global__ void Conv2D(float *d_image, float *kernel, float *d_result, int width, int height, int kernelSize) {
const int sharedMemWidth = TILE_WIDTH + MAX(SOBEL_KERNEL_SIZE, GAUSSIAN_KERNEL_SIZE) - 1;
__shared__ float sharedMem[sharedMemWidth][sharedMemWidth];
int dest = threadIdx.y * TILE_WIDTH + threadIdx.x;
int destY = dest / sharedMemWidth;
int destX = dest % sharedMemWidth;
int srcY = blockIdx.y * TILE_WIDTH + destY - (kernelSize / 2);
int srcX = blockIdx.x * TILE_WIDTH + destX - (kernelSize / 2);
int src = (srcY * width + srcX);
if (srcY >= 0 && srcY < height && srcX >= 0 && srcX < width)
sharedMem[destY][destX] = d_image[src];
else
sharedMem[destY][destX] = 0;
dest = threadIdx.y * TILE_WIDTH + threadIdx.x + TILE_WIDTH * TILE_WIDTH;
destY = dest / sharedMemWidth;
destX = dest % sharedMemWidth;
srcY = blockIdx.y * TILE_WIDTH + destY - (kernelSize / 2);
srcX = blockIdx.x * TILE_WIDTH + destX - (kernelSize / 2);
src = (srcY * width + srcX);
if (destY < sharedMemWidth) {
if (srcY >= 0 && srcY < height && srcX >= 0 && srcX < width)
sharedMem[destY][destX] = d_image[src];
else
sharedMem[destY][destX] = 0;
}
__syncthreads();
float accum = 0;
for (int j = 0; j < kernelSize; j++)
for (int i = 0; i < kernelSize; i++)
accum += sharedMem[threadIdx.y + j][threadIdx.x + i] * kernel[j * kernelSize + i];
int x = blockIdx.x * TILE_WIDTH + threadIdx.x;
int y = blockIdx.y * TILE_WIDTH + threadIdx.y;
if (x < width && y < height)
d_result[y * width + x] = (fminf(fmaxf((accum), 0.0), 1.0));
__syncthreads();
} |
8,948 | #include <stdio.h>
#include <stdlib.h>
void exec();
int main(int argc, char const *argv[]) {
exec();
return 0;
}
__global__ void kernel_checkvalue(){
int x = 0;
// __shared__ int x;
x = 1;
if(threadIdx.x == 0){
x++;
}
__syncthreads();
printf("id: %d x: %d addr: %p %X\n", threadIdx.x, x, &x, &x);
if(threadIdx.x == 1){
x++;
}
__syncthreads();
printf("id: %d x: %d addr: %p %X\n", threadIdx.x, x, &x, &x);
}
void exec(){
int iDev = 0;
dim3 grid, block;
cudaDeviceProp iProp;
cudaGetDeviceProperties(&iProp, iDev);
printf("Device %d: %s\n", iDev, iProp.name);
grid.x = 1;
block.x = 2;
kernel_checkvalue<<<grid, block>>>();
cudaDeviceReset();
}
|
8,949 | #include "includes.h"
#define NTHREADS 512
// Updates the column norms by subtracting the Hadamard-square of the
// Householder vector.
//
// N.B.: Overflow incurred in computing the square should already have
// been detected in the original norm construction.
__global__ void gpuSwapCol(int rows, float * dArray, int coli, int * dColj, int * dPivot)
{
int rowIndex = blockIdx.x * blockDim.x + threadIdx.x;
if(rowIndex >= rows)
return;
int colj = coli + (*dColj);
float fholder;
fholder = dArray[rowIndex+coli*rows];
dArray[rowIndex+coli*rows] = dArray[rowIndex+colj*rows];
dArray[rowIndex+colj*rows] = fholder;
if((blockIdx.x == 0) && (threadIdx.x == 0)) {
int iholder = dPivot[coli];
dPivot[coli] = dPivot[colj];
dPivot[colj] = iholder;
}
} |
8,950 | #include <stdio.h>
#include <math.h>
__device__ void somethingElse() {
printf("Hello, this is the gpu\n");
}
__global__ void add(int n, float* x, float* y) {
int index = blockIdx.x * blockDim.x + threadIdx.x;
int stride = blockDim.x * gridDim.x;
// somethingElse();
for(int i = index; i < n; i += stride) y[i] = x[i] + y[i];
}
int main() {
int N = 1<<20;
float *x, *y, *host_x, *host_y;
int blockSize = 512;
int numBlocks = (N + blockSize - 1) / blockSize;
// Allocate Unified Memory – accessible from CPU or GPU
cudaMallocManaged(&x, N*sizeof(float));
cudaMallocManaged(&y, N*sizeof(float));
host_x = (float*)malloc(sizeof(float) * N);
host_y = (float*)malloc(sizeof(float) * N);
// initialize x and y arrays on the host
for (int i = 0; i < N; i++) {
host_x[i] = 1.0f;
host_y[i] = 2.0f;
}
memcpy(x, host_x, sizeof(float) * N);
memcpy(y, host_y, sizeof(float) * N);
// Run kernel on 1M elements on the GPU
add<<<numBlocks, blockSize>>>(N, x, y);
// Wait for GPU to finish before accessing on host
cudaDeviceSynchronize();
// Check for errors (all values should be 3.0f)
float maxError = 0.0f;
for (int i = 0; i < N; i++)
maxError = fmax(maxError, fabs(y[i]-3.0f));
printf("Max error: %f\n", maxError);
// Free memory
cudaFree(x);
cudaFree(y);
} |
8,951 | //////////////////////////////////////////////////////////////////////////
////This is the code implementation for GPU Premier League Round 1
//////////////////////////////////////////////////////////////////////////
#include <iostream>
#include <fstream>
#include <vector>
#include <chrono>
#include <cuda_runtime.h>
using namespace std;
//////////////////////////////////////////////////////////////////////////
////TODO 0: Please replace the following strings with your team name and author names
////Note: Please do not use space in the string, use "_" instead
//////////////////////////////////////////////////////////////////////////
namespace name
{
std::string team="using_namespace_std;";
std::string author_1="Jeff Liu";
};
////This is a matrix class to carry out linear algebra operations on both GPU and CPU
////It is the same as the sample code I showed in class on Week 3.
////NOTICE: You do not have to change the implementation in this class.
////But if you do want to change part of it for performance reasons, please let us known by writting a submission note on Canvas.
class Matrix{
public:
int m=0; ////number of rows
int n=0; ////number of columns
vector<float> elements_on_host; ////we use a std::vector for the element array on host
float* elements_on_dev=0; ////we use a pointer for the element array on device
bool on_host=true;
////constructors
__host__ Matrix(){}
__host__ Matrix(const int _m,const int _n,bool _on_host=true)
{
on_host=_on_host;
if(on_host)Resize_On_Host(_m,_n);
else Resize_On_Device(_m,_n);
}
////destructor
__host__ ~Matrix()
{
if(!on_host&&elements_on_dev!=0) cudaFree(elements_on_dev);
}
////Resize on host or device
__host__ void Resize_On_Host(const int _m,const int _n)
{
if(m==_m&&n==_n)return;
m=_m;
n=_n;
elements_on_host.resize(m*n);
}
__host__ void Resize_On_Device(const int _m,const int _n)
{
if(m==_m&&n==_n)return;
m=_m;
n=_n;
if(elements_on_dev!=0)cudaFree(elements_on_dev);
cudaMalloc((void**)&elements_on_dev,m*n*sizeof(float));
}
////random access a matrix element
inline __host__ float& operator() (const int i,const int j)
{
return elements_on_host[i*n+j];
}
inline __host__ const float& operator() (const int i,const int j) const
{
return elements_on_host[i*n+j];
}
////copy data with four cases (CPU->CPU, GPU->CPU, GPU->GPU, CPU->GPU)
__host__ Matrix& operator= (const Matrix& mtx)
{
if(on_host&&mtx.on_host){
Resize_On_Host(mtx.m,mtx.n);
elements_on_host=mtx.elements_on_host;
}
else if(on_host&&!mtx.on_host){
Resize_On_Host(mtx.m,mtx.n);
cudaMemcpy(&elements_on_host[0],mtx.elements_on_dev,m*n*sizeof(float),cudaMemcpyDeviceToHost);
}
else if(!on_host&&!mtx.on_host){
Resize_On_Device(mtx.m,mtx.n);
cudaMemcpy(elements_on_dev,mtx.elements_on_dev,mtx.m*n*sizeof(float),cudaMemcpyDeviceToDevice);
}
else if(!on_host&&mtx.on_host){
Resize_On_Device(mtx.m,mtx.n);
cudaMemcpy(elements_on_dev,&mtx.elements_on_host[0],m*n*sizeof(float),cudaMemcpyHostToDevice);
}
return *this;
}
////print matrix elements on screen
__host__ friend ostream & operator << (ostream &out,const Matrix &mtx)
{
if(!mtx.on_host)
cout<<"Print for matrix on device is not supported."<<endl;
for(int i=0;i<mtx.m;i++){
for(int j=0;j<mtx.n;j++){
out<<mtx(i,j)<<", ";
}
out<<std::endl;
}
return out;
}
};
//////////////////////////////////////////////////////////////////////////
////Your tasks start!
////This is a sample implementation without using any memory hierarchy
////The function calculates C=A*B, with dimA=[Am,An], dimB=[Bm,Bn], dimC=[Am,bn], and An=Bm
__global__ void Matrix_Multiplication_AB_Kernel_Poorman(const float* Ae,const float* Be,float* Ce,const int Am,const int An,const int Bn)
{
int i=blockIdx.x*blockDim.x+threadIdx.x;
int j=blockIdx.y*blockDim.y+threadIdx.y;
float val=0.f;
for(int k=0;k<An;k++)
val+=Ae[i*An+k]*Be[k*Bn+j];
Ce[i*Bn+j]=val;
}
//////////////////////////////////////////////////////////////////////////
////Task 1: implement your fast matrix-matrix multiplication in the following kernel function.
////The function parameters are the same as the sample function:
////The function calculates C=A*B, with dimA=[Am,An], dimB=[Bm,Bn], dimC=[Am,bn], and An=Bm
//////////////////////////////////////////////////////////////////////////
__global__ void Matrix_Multiplication_AB_Kernel_Your_Version(const float* Ae,const float* Be,float* Ce,const int Am,const int An,const int Bn)
{
// initialize memory
const int block_size = 32;
const int num_tiles = An / block_size;
__shared__ float a_shared[block_size][block_size];
__shared__ float b_shared[block_size][block_size];
__shared__ float c_shared[block_size][block_size];
// calculate 1d index of correct item on A, B, C
int thr_per_block = blockDim.y * blockDim.x;
int c_idx = blockIdx.y * gridDim.x * thr_per_block + threadIdx.y * gridDim.x * blockDim.x + blockIdx.x * blockDim.x + threadIdx.x;
c_shared[threadIdx.y][threadIdx.x] = 0; // set everything to zero just the first time
int a_idx, b_idx;
for (int tile = 0; tile < num_tiles; ++tile) {
// want blockIdx.x to increment
a_idx = blockIdx.y * num_tiles * thr_per_block + threadIdx.y * num_tiles * blockDim.x + tile * blockDim.x + threadIdx.x;
// want blockIdx.y to increment
b_idx = tile * gridDim.x * thr_per_block + threadIdx.y * gridDim.x * blockDim.x + blockIdx.x * blockDim.x + threadIdx.x;
a_shared[threadIdx.y][threadIdx.x] = Ae[a_idx];
b_shared[threadIdx.y][threadIdx.x] = Be[b_idx];
__syncthreads();
// lmao loop unrolling time my dudes
c_shared[threadIdx.y][threadIdx.x] += a_shared[threadIdx.y][0] * b_shared[0][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += a_shared[threadIdx.y][1] * b_shared[1][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += a_shared[threadIdx.y][2] * b_shared[2][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += a_shared[threadIdx.y][3] * b_shared[3][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += a_shared[threadIdx.y][4] * b_shared[4][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += a_shared[threadIdx.y][5] * b_shared[5][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += a_shared[threadIdx.y][6] * b_shared[6][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += a_shared[threadIdx.y][7] * b_shared[7][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += a_shared[threadIdx.y][8] * b_shared[8][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += a_shared[threadIdx.y][9] * b_shared[9][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += a_shared[threadIdx.y][10] * b_shared[10][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += a_shared[threadIdx.y][11] * b_shared[11][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += a_shared[threadIdx.y][12] * b_shared[12][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += a_shared[threadIdx.y][13] * b_shared[13][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += a_shared[threadIdx.y][14] * b_shared[14][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += a_shared[threadIdx.y][15] * b_shared[15][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += a_shared[threadIdx.y][16] * b_shared[16][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += a_shared[threadIdx.y][17] * b_shared[17][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += a_shared[threadIdx.y][18] * b_shared[18][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += a_shared[threadIdx.y][19] * b_shared[19][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += a_shared[threadIdx.y][20] * b_shared[20][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += a_shared[threadIdx.y][21] * b_shared[21][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += a_shared[threadIdx.y][22] * b_shared[22][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += a_shared[threadIdx.y][23] * b_shared[23][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += a_shared[threadIdx.y][24] * b_shared[24][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += a_shared[threadIdx.y][25] * b_shared[25][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += a_shared[threadIdx.y][26] * b_shared[26][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += a_shared[threadIdx.y][27] * b_shared[27][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += a_shared[threadIdx.y][28] * b_shared[28][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += a_shared[threadIdx.y][29] * b_shared[29][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += a_shared[threadIdx.y][30] * b_shared[30][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += a_shared[threadIdx.y][31] * b_shared[31][threadIdx.x];
__syncthreads();
}
// save to global
Ce[c_idx] = c_shared[threadIdx.y][threadIdx.x];
}
////This is a sample implementation without using any memory hierarchy
////The function calculates the matrix multiplication, with C=A^T*B*A, A^T is the transpose of A, dimA=[Am,An], dimB=[Am,Am], and dimC=[An,An]
__global__ void Matrix_Multiplication_ATBA_Kernel_Poorman(const float* Ae,const float* Be,float* Ce,const int Am,const int An)
{
int i=blockIdx.x*blockDim.x+threadIdx.x;
int j=blockIdx.y*blockDim.y+threadIdx.y;
float val=0.f;
for(int l=0;l<Am;l++)
for(int k=0;k<Am;k++)
val+=Ae[l*An+i]*Be[l*Am+k]*Ae[k*An+j];
Ce[i*An+j]=val;
}
//////////////////////////////////////////////////////////////////////////
////Task 2: calculate the matrix multiplication in the following kernel function.
////The function parameters are the same as the sample function:
////The function calculates the matrix multiplication, with C=A^T*B*A, A^T is the transpose of A, dimA=[Am,An], dimB=[Am,Am], and dimC=[An,An]
//////////////////////////////////////////////////////////////////////////
__global__ void Matrix_Multiplication_ATBA_Kernel_Your_Version(const float* Ae,const float* Be,float* Ce,const int Am,const int An)
{
// memory setup
const int num_tiles = Am / 32;
__shared__ float aTT_shared[32][32];
__shared__ float b_shared[32][32];
__shared__ float a_shared[32][32];
__shared__ float accum_shared[32][32];
__shared__ float c_shared[32][32];
// coordinate setup
int thr_per_block = blockDim.y * blockDim.x;
int c_idx = blockIdx.y*gridDim.x*thr_per_block + threadIdx.y*gridDim.x*blockDim.x + blockIdx.x*blockDim.x + threadIdx.x;
int a_idx, b_idx, aTT_idx;
// initialize memory
c_shared[threadIdx.y][threadIdx.x] = 0;
// following psuedocode coordinates are (y,x)
for (int ay = 0; ay < num_tiles; ++ay) { //ay = bx
// load a(ay,blockIdx.x)
a_idx = ay*gridDim.x*thr_per_block + threadIdx.y*gridDim.x*blockDim.x + blockIdx.x*blockDim.x + threadIdx.x;
a_shared[threadIdx.y][threadIdx.x] = Ae[a_idx];
// clear accumulator
accum_shared[threadIdx.y][threadIdx.x] = 0;
__syncthreads();
for (int by = 0; by < num_tiles; ++by) { // by = aTx = aTTy
// calculate indices
b_idx = by*num_tiles*thr_per_block + threadIdx.y*num_tiles*blockDim.x + ay*blockDim.x + threadIdx.x;
aTT_idx = by*gridDim.x*thr_per_block + threadIdx.y*gridDim.x*blockDim.x + blockIdx.y*blockDim.x + threadIdx.x;
// load aTT(by, blockIdx.y) (since we load A but column access) and b(by,ay)
b_shared[threadIdx.y][threadIdx.x] = Be[b_idx];
aTT_shared[threadIdx.y][threadIdx.x] = Ae[aTT_idx];
__syncthreads();
// multiply aT x b, accumulate
accum_shared[threadIdx.y][threadIdx.x] += aTT_shared[0][threadIdx.y] * b_shared[0][threadIdx.x];
accum_shared[threadIdx.y][threadIdx.x] += aTT_shared[1][threadIdx.y] * b_shared[1][threadIdx.x];
accum_shared[threadIdx.y][threadIdx.x] += aTT_shared[2][threadIdx.y] * b_shared[2][threadIdx.x];
accum_shared[threadIdx.y][threadIdx.x] += aTT_shared[3][threadIdx.y] * b_shared[3][threadIdx.x];
accum_shared[threadIdx.y][threadIdx.x] += aTT_shared[4][threadIdx.y] * b_shared[4][threadIdx.x];
accum_shared[threadIdx.y][threadIdx.x] += aTT_shared[5][threadIdx.y] * b_shared[5][threadIdx.x];
accum_shared[threadIdx.y][threadIdx.x] += aTT_shared[6][threadIdx.y] * b_shared[6][threadIdx.x];
accum_shared[threadIdx.y][threadIdx.x] += aTT_shared[7][threadIdx.y] * b_shared[7][threadIdx.x];
accum_shared[threadIdx.y][threadIdx.x] += aTT_shared[8][threadIdx.y] * b_shared[8][threadIdx.x];
accum_shared[threadIdx.y][threadIdx.x] += aTT_shared[9][threadIdx.y] * b_shared[9][threadIdx.x];
accum_shared[threadIdx.y][threadIdx.x] += aTT_shared[10][threadIdx.y] * b_shared[10][threadIdx.x];
accum_shared[threadIdx.y][threadIdx.x] += aTT_shared[11][threadIdx.y] * b_shared[11][threadIdx.x];
accum_shared[threadIdx.y][threadIdx.x] += aTT_shared[12][threadIdx.y] * b_shared[12][threadIdx.x];
accum_shared[threadIdx.y][threadIdx.x] += aTT_shared[13][threadIdx.y] * b_shared[13][threadIdx.x];
accum_shared[threadIdx.y][threadIdx.x] += aTT_shared[14][threadIdx.y] * b_shared[14][threadIdx.x];
accum_shared[threadIdx.y][threadIdx.x] += aTT_shared[15][threadIdx.y] * b_shared[15][threadIdx.x];
accum_shared[threadIdx.y][threadIdx.x] += aTT_shared[16][threadIdx.y] * b_shared[16][threadIdx.x];
accum_shared[threadIdx.y][threadIdx.x] += aTT_shared[17][threadIdx.y] * b_shared[17][threadIdx.x];
accum_shared[threadIdx.y][threadIdx.x] += aTT_shared[18][threadIdx.y] * b_shared[18][threadIdx.x];
accum_shared[threadIdx.y][threadIdx.x] += aTT_shared[19][threadIdx.y] * b_shared[19][threadIdx.x];
accum_shared[threadIdx.y][threadIdx.x] += aTT_shared[20][threadIdx.y] * b_shared[20][threadIdx.x];
accum_shared[threadIdx.y][threadIdx.x] += aTT_shared[21][threadIdx.y] * b_shared[21][threadIdx.x];
accum_shared[threadIdx.y][threadIdx.x] += aTT_shared[22][threadIdx.y] * b_shared[22][threadIdx.x];
accum_shared[threadIdx.y][threadIdx.x] += aTT_shared[23][threadIdx.y] * b_shared[23][threadIdx.x];
accum_shared[threadIdx.y][threadIdx.x] += aTT_shared[24][threadIdx.y] * b_shared[24][threadIdx.x];
accum_shared[threadIdx.y][threadIdx.x] += aTT_shared[25][threadIdx.y] * b_shared[25][threadIdx.x];
accum_shared[threadIdx.y][threadIdx.x] += aTT_shared[26][threadIdx.y] * b_shared[26][threadIdx.x];
accum_shared[threadIdx.y][threadIdx.x] += aTT_shared[27][threadIdx.y] * b_shared[27][threadIdx.x];
accum_shared[threadIdx.y][threadIdx.x] += aTT_shared[28][threadIdx.y] * b_shared[28][threadIdx.x];
accum_shared[threadIdx.y][threadIdx.x] += aTT_shared[29][threadIdx.y] * b_shared[29][threadIdx.x];
accum_shared[threadIdx.y][threadIdx.x] += aTT_shared[30][threadIdx.y] * b_shared[30][threadIdx.x];
accum_shared[threadIdx.y][threadIdx.x] += aTT_shared[31][threadIdx.y] * b_shared[31][threadIdx.x];
__syncthreads();
}
// multiply accum x a, add to c
c_shared[threadIdx.y][threadIdx.x] += accum_shared[threadIdx.y][0] * a_shared[0][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += accum_shared[threadIdx.y][1] * a_shared[1][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += accum_shared[threadIdx.y][2] * a_shared[2][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += accum_shared[threadIdx.y][3] * a_shared[3][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += accum_shared[threadIdx.y][4] * a_shared[4][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += accum_shared[threadIdx.y][5] * a_shared[5][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += accum_shared[threadIdx.y][6] * a_shared[6][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += accum_shared[threadIdx.y][7] * a_shared[7][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += accum_shared[threadIdx.y][8] * a_shared[8][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += accum_shared[threadIdx.y][9] * a_shared[9][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += accum_shared[threadIdx.y][10] * a_shared[10][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += accum_shared[threadIdx.y][11] * a_shared[11][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += accum_shared[threadIdx.y][12] * a_shared[12][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += accum_shared[threadIdx.y][13] * a_shared[13][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += accum_shared[threadIdx.y][14] * a_shared[14][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += accum_shared[threadIdx.y][15] * a_shared[15][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += accum_shared[threadIdx.y][16] * a_shared[16][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += accum_shared[threadIdx.y][17] * a_shared[17][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += accum_shared[threadIdx.y][18] * a_shared[18][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += accum_shared[threadIdx.y][19] * a_shared[19][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += accum_shared[threadIdx.y][20] * a_shared[20][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += accum_shared[threadIdx.y][21] * a_shared[21][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += accum_shared[threadIdx.y][22] * a_shared[22][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += accum_shared[threadIdx.y][23] * a_shared[23][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += accum_shared[threadIdx.y][24] * a_shared[24][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += accum_shared[threadIdx.y][25] * a_shared[25][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += accum_shared[threadIdx.y][26] * a_shared[26][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += accum_shared[threadIdx.y][27] * a_shared[27][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += accum_shared[threadIdx.y][28] * a_shared[28][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += accum_shared[threadIdx.y][29] * a_shared[29][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += accum_shared[threadIdx.y][30] * a_shared[30][threadIdx.x];
c_shared[threadIdx.y][threadIdx.x] += accum_shared[threadIdx.y][31] * a_shared[31][threadIdx.x];
__syncthreads();
}
// save c to global
Ce[c_idx] = c_shared[threadIdx.y][threadIdx.x];
}
//////////////////////////////////////////////////////////////////////////
////Task 3: calculate the Frobenius norm of a matrix
////The definition of F-norm for a matrix is square root of (the sum of squares of all the matrix elements), i.e., F=sqrt(sum_(A_ij^2))
////See the definition: https://mathworld.wolfram.com/FrobeniusNorm.html
//////////////////////////////////////////////////////////////////////////
////Please write your own kernel function here, and call it in the function Test_F_Norm_On_GPU to test its correctness and performance
__global__ void F_Norm_On_GPU_Lazy(const float* Ae, float* sum)
{
// lazy man's method for reference
__shared__ float a_shared[16][16];
int thr_per_block = blockDim.y * blockDim.x;
int idx = blockIdx.y*gridDim.x*thr_per_block + threadIdx.y*gridDim.x*blockDim.x + blockIdx.x*blockDim.x + threadIdx.x;
float element = Ae[idx];
a_shared[threadIdx.y][threadIdx.x] = element * element;
atomicAdd(&sum[0], a_shared[threadIdx.y][threadIdx.x]);
}
__global__ void F_Norm_On_GPU(const float* Ae, float* Be, bool round1)
{
extern __shared__ float data[];
int idx = blockIdx.x*blockDim.x*2 + threadIdx.x;
// use 2 registers
float num1 = Ae[idx];
float num2 = Ae[idx + blockDim.x]; // offset by stride is better for alignment
// only square first time
if (round1) {
num1 *= num1;
num2 *= num2;
}
// add two elements into one shared index
data[threadIdx.x] = num1 + num2;
__syncthreads();
// from reduce4 in class notes
for (unsigned int s = blockDim.x/2; s > 0; s >>= 1) {
if(threadIdx.x < s){
data[threadIdx.x]+=data[threadIdx.x+s];
}
__syncthreads();
}
if (threadIdx.x == 0) Be[blockIdx.x] = data[0];
}
////Congratulations, your tasks are all finished!
//////////////////////////////////////////////////////////////////////////
////Here are the test functions for your three kernel implementations
ofstream out;
__host__ void Test_Matrix_Multiplication_AB_On_GPU(const Matrix& A,const Matrix& B,Matrix& C)
{
//// Load A and B to device memory
Matrix A_on_dev(A.m,A.n,false);
A_on_dev=A;
Matrix B_on_dev(B.m,B.n,false);
B_on_dev=B;
//// Allocate C in device memory
Matrix C_on_dev(A_on_dev.m,B_on_dev.n,false);
cudaEvent_t start,end;
cudaEventCreate(&start);
cudaEventCreate(&end);
float gpu_time=0.0f;
cudaDeviceSynchronize();
cudaEventRecord(start);
//// Invoke kernel
const int block_size=32;
const int block_num_x=C.m/block_size;
const int block_num_y=C.n/block_size;
#ifdef POORMAN
Matrix_Multiplication_AB_Kernel_Poorman<<<dim3(block_num_x,block_num_y),dim3(block_size,block_size)>>>(A_on_dev.elements_on_dev,B_on_dev.elements_on_dev,C_on_dev.elements_on_dev,A_on_dev.m,A_on_dev.n,B_on_dev.n);
#endif
#ifndef POORMAN
Matrix_Multiplication_AB_Kernel_Your_Version<<<dim3(block_num_y,block_num_x),dim3(block_size,block_size)>>>(A_on_dev.elements_on_dev,B_on_dev.elements_on_dev,C_on_dev.elements_on_dev,A_on_dev.m,A_on_dev.n,B_on_dev.n);
#endif
cudaEventRecord(end);
cudaEventSynchronize(end);
cudaEventElapsedTime(&gpu_time,start,end);
printf("\nGPU runtime for matrix multiplication AB: %.4f ms\n",gpu_time);
cudaEventDestroy(start);
cudaEventDestroy(end);
//// Transfer data back to CPU
C=C_on_dev;
out<<"T1: "<<gpu_time<<endl;
}
__host__ void Test_Matrix_Multiplication_ATBA_On_GPU(const Matrix& A,const Matrix& B,Matrix& C)
{
//// Load A and B to device memory
Matrix A_on_dev(A.m,A.n,false);
A_on_dev=A;
Matrix B_on_dev(B.m,B.n,false);
B_on_dev=B;
//// Allocate C in device memory
Matrix C_on_dev(A_on_dev.n,A_on_dev.n,false);
cudaEvent_t start,end;
cudaEventCreate(&start);
cudaEventCreate(&end);
float gpu_time=0.0f;
cudaDeviceSynchronize();
cudaEventRecord(start);
//// Invoke kernel
const int block_size=32;
const int block_num_x=C.m/block_size;
const int block_num_y=C.n/block_size;
#ifdef POORMAN
Matrix_Multiplication_ATBA_Kernel_Poorman<<<dim3(block_num_x,block_num_y),dim3(block_size,block_size)>>>(A_on_dev.elements_on_dev,B_on_dev.elements_on_dev,C_on_dev.elements_on_dev,A_on_dev.m,A_on_dev.n);
#endif
#ifndef POORMAN
////NOTICE: You do not have to use the block_size I specified here. You may customize the size of your grid and blocks for better performance.
Matrix_Multiplication_ATBA_Kernel_Your_Version<<<dim3(block_num_y,block_num_x),dim3(block_size,block_size)>>>(A_on_dev.elements_on_dev,B_on_dev.elements_on_dev,C_on_dev.elements_on_dev,A_on_dev.m,A_on_dev.n);
#endif
cudaEventRecord(end);
cudaEventSynchronize(end);
cudaEventElapsedTime(&gpu_time,start,end);
printf("\nGPU runtime for matrix multiplication ATBA: %.4f ms\n",gpu_time);
cudaEventDestroy(start);
cudaEventDestroy(end);
//// Transfer data back to CPU
C=C_on_dev;
out<<"T2: "<<gpu_time<<endl;
}
__host__ void Test_Matrix_F_Norm_On_GPU(const Matrix& A, float& norm)
{
//// Load A and B to device memory
Matrix A_on_dev(A.m,A.n,false);
A_on_dev=A;
cudaEvent_t start,end;
cudaEventCreate(&start);
cudaEventCreate(&end);
float gpu_time=0.0f;
cudaDeviceSynchronize();
cudaEventRecord(start);
#ifdef POORMAN // atomic add
//// Invoke kernel
const int block_size=16;
const int block_num_x=A.n/block_size;
const int block_num_y=A.m/block_size;
float *sum_dev = nullptr;
cudaMalloc((void**)&sum_dev, sizeof(float));
F_Norm_On_GPU_Lazy<<<dim3(block_num_x,block_num_y), dim3(block_size,block_size)>>>(A_on_dev.elements_on_dev, sum_dev);
float *sum_host = (float *)malloc(4);
cudaMemcpy(sum_host, sum_dev, sizeof(float), cudaMemcpyDeviceToHost);
cudaFree(sum_dev);
norm = sqrt(*sum_host);
free(sum_host);
#endif // ifdef
#ifndef POORMAN // parallel reduction
const int r1_blocks = A.m;
const int r1_threads = A.n / 2;
const int r2_threads = A.m / 2;
float *B_dev = nullptr;
cudaMalloc((void**)&B_dev, A.m * sizeof(float));
F_Norm_On_GPU<<<r1_blocks, r1_threads, r1_threads*sizeof(float)>>>(A_on_dev.elements_on_dev, B_dev, true);
F_Norm_On_GPU<<<1, r2_threads, r2_threads*sizeof(float)>>>(B_dev, B_dev, false);
float result = 0;
cudaMemcpy(&result,B_dev,sizeof(float),cudaMemcpyDeviceToHost);
norm = sqrt(result);
cudaFree(B_dev);
#endif // ifndef
cudaEventRecord(end);
cudaEventSynchronize(end);
cudaEventElapsedTime(&gpu_time,start,end);
printf("\nGPU runtime for F norm: %.4f ms\n",gpu_time);
cudaEventDestroy(start);
cudaEventDestroy(end);
out<<"T3: "<<gpu_time<<endl;
}
int main()
{
if(name::team=="Team_X"){
printf("\nPlease specify your team name and team member names in name::team and name::author to start.\n");
return 0;
}
std::string file_name=name::team+"_competition_1_matrix.dat";
out.open(file_name.c_str());
if(out.fail()){
printf("\ncannot open file %s to record results\n",file_name.c_str());
return 0;
}
//////////////////////////////////////////////////////////////////////////
////NOTICE: We may use a different set of parameters to evaluate your code.
////So please test your functions with different size and initial values.
//////////////////////////////////////////////////////////////////////////
const int m=512;
const int n=2048;
const int p=1024;
Matrix h_A(m,n);
for(int i=0;i<m;i++){
for(int j=0;j<n;j++){
h_A(i,j) = 1;
}
}
Matrix h_B(n,p);
for(int i=0;i<n;i++){
for(int j=0;j<p;j++){
h_B(i,j) = 1;
}
}
Matrix h_C(m,p);
Matrix h_B2(m,m);
for(int i=0;i<m;i++){
for(int j=0;j<m;j++){
h_B2(i,j) = 1;
}
}
Matrix h_C2(n,n);
Test_Matrix_Multiplication_AB_On_GPU(h_A,h_B,h_C);
cout<<"AB result: "<<h_C(h_C.m/2,h_C.n/2)<<endl;
out<<"R1: "<<h_C(h_C.m/2,h_C.n/2)<<endl;
Test_Matrix_Multiplication_ATBA_On_GPU(h_A,h_B2,h_C2);
cout<<"ATBA result: "<<h_C2(h_C2.m/3,h_C2.n/3)<<endl;
out<<"R2: "<<h_C2(h_C2.m/3,h_C2.n/3)<<endl;
float f_norm=0.f;
Test_Matrix_F_Norm_On_GPU(h_A,f_norm);
cout<<"F-norm result: "<<f_norm<<endl;
out<<"R3: "<<f_norm<<endl;
return 0;
}
|
8,952 | #include "includes.h"
__global__ void block_sum(const int *input, int *per_block_results, const size_t n)
{
extern __shared__ int sdata[];
unsigned int i = blockIdx.x * blockDim.x + threadIdx.x;
// load input into __shared__ memory
int x = 0;
if(i < n)
{
x = input[i];
}
sdata[threadIdx.x] = x;
__syncthreads();
// contiguous range pattern
for(int offset = blockDim.x / 2;
offset > 0;
offset >>= 1)
{
if(threadIdx.x < offset)
{
// add a partial sum upstream to our own
sdata[threadIdx.x] += sdata[threadIdx.x + offset];
}
// wait until all threads in the block have
// updated their partial sums
__syncthreads();
}
// thread 0 writes the final result
if(threadIdx.x == 0)
{
per_block_results[blockIdx.x] = sdata[0];
}
} |
8,953 | #include <stdio.h>
#include <stdlib.h>
__global__ void add1(int *A, int *B, int *C, int n){
int id = threadIdx.x, i;
for(i=0;i<n;i++){
C[id*n+i] = A[id*n+i] + B[id*n+i];
}
}
__global__ void add2(int *A, int *B, int *C, int m){
int id = threadIdx.x, i, n = blockDim.x;
for(i=0;i<m;i++)
C[i*n+id] = A[i*n+id] + B[i*n+id];
}
__global__ void add3(int *A, int *B, int *C){
int i = blockIdx.x, j = threadIdx.x, n = blockDim.x;
C[i*n+j] = A[i*n+j] + B[i*n+j];
}
int main(){
int *a,*b,*c,*da,*db,*dc,m,n,i,j;
printf("Enter m: ");
scanf("%d",&m);
printf("Enter n: ");
scanf("%d",&n);
int size = sizeof(int)*m*n;
a = (int *)malloc(size);
b = (int *)malloc(size);
c = (int *)malloc(size);
printf("Enter first matrix:\n");
for(i=0;i<m*n;i++)
scanf("%d",&a[i]);
printf("Enter second matrix:\n");
for(i=0;i<m*n;i++)
scanf("%d",&b[i]);
cudaMalloc((void **)&da,size);
cudaMalloc((void **)&db,size);
cudaMalloc((void **)&dc,size);
cudaMemcpy(da,a,size,cudaMemcpyHostToDevice);
cudaMemcpy(db,b,size,cudaMemcpyHostToDevice);
printf("Result 1)Thread per row:\n");
add1<<<1,m>>>(da,db,dc,n);
cudaMemcpy(c,dc,size,cudaMemcpyDeviceToHost);
for(i=0;i<m;i++){
for(j=0;j<n;j++)
printf("%d ",c[i*n+j]);
printf("\n");
}
printf("Result 2)Thread per column:\n");
add2<<<1,n>>>(da,db,dc,m);
cudaMemcpy(c,dc,size,cudaMemcpyDeviceToHost);
for(i=0;i<m;i++){
for(j=0;j<n;j++)
printf("%d ",c[i*n+j]);
printf("\n");
}
printf("Result 3)Thread per element:\n");
add3<<<m,n>>>(da,db,dc);
cudaMemcpy(c,dc,size,cudaMemcpyDeviceToHost);
for(i=0;i<m;i++){
for(j=0;j<n;j++)
printf("%d ",c[i*n+j]);
printf("\n");
}
cudaFree(da);
cudaFree(db);
cudaFree(dc);
return 0;
}
|
8,954 | #include<stdio.h>
__global__
void mallocTest()
{
size_t size =123;
char* ptr = (char*)malloc(size);
memset(ptr,0,size);
printf("Thread %d got pointer: %p\n", threadIdx.x, ptr);
free(ptr);
}
int main()
{
cudaDeviceSetLimit(cudaLimitMallocHeapSize,128*1024*1024);
mallocTest<<<1,5>>>();
cudaDeviceSynchronize();
return 0;
}
|
8,955 | /*
**********************************************
* CS314 Principles of Programming Languages *
* Spring 2020 *
**********************************************
*/
#include <stdio.h>
#include <stdlib.h>
__global__ void check_handshaking_gpu(int * strongNeighbor, int * matches, int numNodes) {
/*YOUR CODE HERE*/
int tid = blockIdx.x * blockDim.x + threadIdx.x;//this is the thread id and will be used as index
while( tid < numNodes )//as long as thread id is within numNodes(array bounds)
{
if( tid == strongNeighbor[strongNeighbor[tid]] )
{
if( matches[tid] == -1 && matches[strongNeighbor[tid]] == -1 )//both need to equal -1, both nodes are unmatched
{
matches[tid] = strongNeighbor[tid];
matches[strongNeighbor[tid]] = strongNeighbor[strongNeighbor[tid]];
}
}
tid += ( blockDim.x * gridDim.x );
}
return;
}
|
8,956 | #include <stdio.h>
#include "kernels.cuh"
__global__ void build_binary_tree(int *x, int *child, int *root, unsigned int n)
{
//Instantiate variables
unsigned int bodyIndex = threadIdx.x + blockIdx.x*blockDim.x;
unsigned int stride = blockDim.x*gridDim.x;
unsigned int offset = 0;
bool newBody = true;
int rootValue = *root;
// build binary tree
int childPath;
int temp;
offset = 0;
while((bodyIndex + offset) < n){
if(newBody){
newBody = false;
temp = 0;
childPath = 0;
if(x[bodyIndex + offset] > rootValue){
childPath = 1;
}
}
int childIndex = child[temp*2 + childPath];
// traverse tree until we hit leaf node
while(childIndex >= 0){
temp = childIndex;
childPath = 0;
if(x[bodyIndex + offset] > temp){
childPath = 1;
}
childIndex = child[2*temp + childPath];
}
if(childIndex != -2){
int locked = temp*2 + childPath;
if(atomicCAS(&child[locked], childIndex, -2) == childIndex){
if(childIndex == -1){
child[locked] = x[bodyIndex + offset];
}
offset += stride;
newBody = true;
}
}
__syncthreads(); // not strictly needed
}
} |
8,957 |
#include "cuda_runtime.h"
#include "device_launch_parameters.h"
#include <stdlib.h>
#include <stdio.h>
#include <time.h>
#define SIZE_OF_PATTERN 8192
#define SIZE_OF_TARGET 58280548
#define threadNum 8
#define blockNum 256
char Pat[SIZE_OF_PATTERN + 1];
char Tar[SIZE_OF_TARGET + 1];
int Skipping[SIZE_OF_PATTERN + 2][7] = { 0 };
//__constant__ int d_Skipping[(SIZE_OF_PATTERN+2)*7];
void Build_Map(){
// init Skipping array
for (int i = SIZE_OF_PATTERN - 1; i >= 0; i--){
Skipping[SIZE_OF_PATTERN - i][0] = Pat[i];
Skipping[SIZE_OF_PATTERN - i - 1][(Pat[i])%5+1] = SIZE_OF_PATTERN - i;
}
//bool flag = false;
int temporary_root;
int current_processing;
for (int i = 1; i <= SIZE_OF_PATTERN; i++){
temporary_root = 0;
//flag = false;
for(current_processing = i;current_processing <= SIZE_OF_PATTERN;current_processing ++){
if (Skipping[temporary_root][((char)Skipping[current_processing][0])%5+1] != 0){
temporary_root = Skipping[temporary_root][((char)Skipping[current_processing][0])%5+1];
if (current_processing == SIZE_OF_PATTERN){
Skipping[temporary_root][6] = 1;
break;
}
}
else{
Skipping[temporary_root][((char)Skipping[current_processing][0])%5+1] = current_processing;
break;
}
}
}
Skipping[SIZE_OF_PATTERN][6] = 1;
}
__global__ void MyMethod(char *Tar,int* d_Skipping, int *Output){
int thd = blockIdx.x*blockDim.x+threadIdx.x;
int thx = threadIdx.x;
//int index_in_tar=thx*SIZE_OF_PATTERN;
int index_in_tar=thd*SIZE_OF_PATTERN;
int Skip[20];
for (int i = 0; i < 20; i++){
Skip[i] = -1;
}
//Start searching
int index_in_pat = 0;
int index_in_skip = 0;
int possible_start = 0;
int tail_Node = 0;
int test_index = 0;
int temp_Node = 0;
if (thd <= SIZE_OF_TARGET/SIZE_OF_PATTERN-1){
for (index_in_pat = SIZE_OF_PATTERN - 1;index_in_pat >= 0;index_in_pat--){
//detect skipping number
if (d_Skipping[index_in_skip*7+(Tar[index_in_tar+index_in_pat])%5+1] != 0){
index_in_skip = d_Skipping[index_in_skip*7+(Tar[index_in_tar+index_in_pat])%5+1];
possible_start++;
if (d_Skipping[index_in_skip*7+6] == 1){
Skip[tail_Node] = possible_start;
tail_Node ++;
}
}
else break;
}
while(Skip[temp_Node] != -1){
if(Tar[index_in_tar+SIZE_OF_PATTERN + test_index]!=d_Skipping[(SIZE_OF_PATTERN - Skip[temp_Node] - test_index)*7+0]){
Skip[temp_Node++]=-1;
test_index = 0;
}
else{
if (Skip[temp_Node] + test_index == SIZE_OF_PATTERN-1){
//printf("Found it! Start from : %d\n",index_in_tar + 5 - possible_matching[0] );
Output[thd]=(thd+1)*SIZE_OF_PATTERN - Skip[temp_Node];
Skip[temp_Node++]=-1;
test_index = 0;
}
else
test_index++;
}
}
}
}
int main (){
FILE * fp1 = fopen("60.txt", "r");
FILE * fp2 = fopen("8192.txt", "r");
fscanf(fp1, "%s", Tar);
fscanf(fp2, "%s", Pat);
fclose(fp1);
fclose(fp2);
Build_Map();
int Tar_Size =(SIZE_OF_TARGET + 1)*sizeof(char);
int Skip_Size = ((SIZE_OF_PATTERN + 2)*7)*sizeof(int);
int Output[threadNum*blockNum] = {0};
int Output_Size = threadNum*blockNum*sizeof(int);
char *d_Tar;
int *d_Skip;
int *d_output;
cudaMalloc((void**)&d_Tar,Tar_Size);
cudaMemcpy(d_Tar,Tar,Tar_Size,cudaMemcpyHostToDevice);
cudaMalloc((void**)&d_Skip,Skip_Size);
cudaMemcpy(d_Skip,Skipping,Skip_Size,cudaMemcpyHostToDevice);
//cudaMemcpyToSymbol(d_Skipping,Skipping,Skip_Size,0U,cudaMemcpyHostToDevice);
cudaMalloc((void**)&d_output,Output_Size);
dim3 dimgrid(blockNum,1,1);
dim3 dimblock(threadNum,1,1);
float time=0;
cudaEvent_t start,stop;
cudaEventCreate(&start);
cudaEventCreate(&stop);
cudaEventRecord(start,0);
MyMethod<<<dimgrid,dimblock>>>(d_Tar,d_Skip,d_output);
cudaEventRecord(stop,0);
cudaEventSynchronize(start);
cudaEventSynchronize(stop);
cudaEventElapsedTime(&time,start,stop);
printf("time is %f(ms)\n",time/1000);
cudaMemcpy(Output,d_output,Output_Size,cudaMemcpyDeviceToHost);
cudaFree(d_Tar);
//cudaFree(d_Skip);
cudaFree(d_output);
for(int i = 0;i<threadNum*blockNum;i++)
if(Output[i]>0)
printf("Find it by GPU.%d\n",Output[i]);
return 0;
}
|
8,958 | #include <cuda_fp16.h>
__global__ void
cudaProcessHalf0(half *dst, half *gain, half *src, int imgW)
{
int tx = threadIdx.x;
int ty = threadIdx.y;
int bw = blockDim.x;
int bh = blockDim.y;
int x = blockIdx.x*bw + tx;
int y = blockIdx.y*bh + ty;
int px = y*imgW+x;
half g = gain[px];
half i = src[px];
dst[px] = __hmul(g, i);
}
__global__ void
cudaProcessFloat0(float *dst, float *gain, float *src, int imgW)
{
int tx = threadIdx.x;
int ty = threadIdx.y;
int bw = blockDim.x;
int bh = blockDim.y;
int x = blockIdx.x*bw + tx;
int y = blockIdx.y*bh + ty;
int px = y*imgW+x;
float g = gain[px];
float i = src[px];
dst[px] = g*i;
}
__global__ void
cudaProcessHalf1(half2 *dst, half2 *gain, half2 *src, int imgW)
{
int tx = threadIdx.x;
int ty = threadIdx.y;
int bw = blockDim.x;
int bh = blockDim.y;
int x = blockIdx.x*bw + tx;
int y = blockIdx.y*bh + ty;
int px = (y*imgW/2)+x;
half2 g = gain[px];
half2 i = src[px];
dst[px] = __hmul2(g, i);
}
extern "C" void
launchCudaProcessHalf0(dim3 grid, dim3 block,
short *gain, short *imageInput, short *imageOutput, int imgW)
{
cudaProcessHalf0<<< grid, block, 0 >>>((half*)imageOutput, (half*)gain, (half*)imageInput, imgW);
}
extern "C" void
launchCudaProcessFloat0(dim3 grid, dim3 block,
float *gain, float *imageInput, float *imageOutput, int imgW)
{
cudaProcessFloat0<<< grid, block, 0 >>>(imageOutput, gain, imageInput, imgW);
}
extern "C" void
launchCudaProcessHalf1(dim3 grid, dim3 block,
short *gain, short *imageInput, short *imageOutput, int imgW)
{
cudaProcessHalf1<<< grid, block, 0 >>>((half2*)imageOutput, (half2*)gain, (half2*)imageInput, imgW);
}
|
8,959 | //--------------------------------------------------------------------------
// Project:
// Read GPU temepratures on a CUDA-enabled system.
// Bypass the need for 3rd party libraries.
// Insert into your code as desired.
//
// Prerequisites:
// Must have installed the CUDA toolkit.
// Must be running on a UNIX machine
//
// Independent testing info:
// Compile on commandline: nvcc read_temps.cu -o test
// run on commandline: ./test
//
// Author: Jordan Bonilla
// Date : April 2016
// License: All rights Reserved. See LICENSE.txt
//--------------------------------------------------------------------------
#include <cstdio> // printf
#include <stdlib.h> // popen, pclose, atoi, fread
#include <cuda_runtime.h> // cudaGetDeviceCount
// Read temperatures of all connected NVIDIA GPUs
void read_temps()
{
// Get the number of GPUs on this machine
int num_devices;
cudaGetDeviceCount(&num_devices);
if(num_devices == 0) {
printf("No NVIDIA GPUs detected\n");
return;
}
// Read GPU info into buffer "output" using the "nvidia-smi" command
const unsigned int MAX_BYTES = 10000;
char output[MAX_BYTES];
FILE *fp = popen("nvidia-smi &> /dev/null", "r");
fread(output, sizeof(char), MAX_BYTES, fp);
pclose(fp);
// array to hold GPU temperatures
int * temperatures = new int[num_devices];
// parse output for temperatures using knowledge of "nvidia-smi" output format
int i = 0;
unsigned int num_temps_parsed = 0;
while(output[i] != '\0') {
if(output[i] == '%') {
unsigned int temp_begin = i + 1;
while(output[i] != 'C') {
++i;
}
unsigned int temp_end = i;
char this_temperature[32];
// Read in the characters cooresponding to this temperature
for(int j = 0; j < temp_end - temp_begin; ++j) {
this_temperature[j] = output[temp_begin + j];
}
this_temperature[temp_end - temp_begin + 1] = '\0';
// Convert the string representation to an int
temperatures[num_temps_parsed] = atoi(this_temperature);
num_temps_parsed++;
}
++i;
}
for (int i = 0; i < num_devices; i++)
{
printf("GPU %d temperature: %d C\n", i, temperatures[i]);
}
// Free memory and return
delete(temperatures);
return;
}
int main(int argc, char **argv) {
read_temps();
return 0;
}
|
8,960 | #include <iostream>
#include "../include/gpu_stack.h"
#include <thrust/device_vector.h>
#define def_dvec(t) thrust::device_vector<t>
#define to_ptr(x) thrust::raw_pointer_cast(&x[0])
using namespace std;
const int STACK_SIZE = 100;
__global__ void test(float *output){
gpu_stack<float, STACK_SIZE> stk;
for(int i=1;i<=STACK_SIZE;++i){
stk.push(1.5*i);
}
int idx = 0, k = 0;
while(!stk.empty()){
stk.pop_k(k);
if(stk.empty()) return;
output[idx] = stk.top();
idx += 1;
output[idx] = (float)stk.size();
k += 1;
idx += 1;
}
}
int main(){
def_dvec(float) dev_out(40, 0);
test<<<1, 1>>>(to_ptr(dev_out));
for(auto k:dev_out) cout<<k<<' ';
cout<<endl;
return 0;
} |
8,961 | //======================================================================
/*
get_block, assign threads into a 3D block.
input:
nthreads, number of threads.
block_limit, max dimension of the block.
output:
block_size, size of the block.
return value, 0 for all threads are assigned to the block;
1 for part of the threads are assigned.
get_grid, assign threads into a 3D grid, which consists of blocks.
input:
nthreads, number of threads to assign.
nthreads_max_per_block, max threads per block.
grid_limit, max dimension of the grid.
block_limit, max dimension of the block in the grid.
output:
grid_size, size of the grid.
block_size, size of the block.
return value, 0 for all threads are assigned to the grid;
1 for part of the threads are assigned.
*/
//======================================================================
//#include <cstddef>
//#include <cmath>
#include "cuda_runtime.h"
//#include "cublas_v2.h"
//// head;
//int get_block( const unsigned long nthreads, const dim3 block_limit, dim3 *block_size );
//int get_grid( const unsigned long nthreads, const unsigned int nthreads_max_per_block, const dim3 grid_limit, const dim3 block_limit, dim3 *grid_size, dim3 *block_size );
int get_block( const unsigned long nthreads, const dim3 block_limit, dim3 *block_size )
{
unsigned long v, v_xy, v_xyz;
unsigned int zlimit, ylimit, z, y, x;
int block_status(1);
unsigned long nthreads_max(0);
dim3 max_size(0,0,0);
v = (unsigned long)block_limit.x * (unsigned long)block_limit.y * (unsigned long)block_limit.z;
if ( v > nthreads )
v = nthreads;
zlimit = ( v - 1 ) / ( (unsigned long)block_limit.x * (unsigned long)block_limit.y ) + 1;
for ( z = ( ( 1 > zlimit ) ? 1 : zlimit ); z <= block_limit.z; z++ )
{
v_xy = v / z;
ylimit = ( v_xy - 1 ) / (unsigned long)block_limit.x + 1;
for ( y = ( ( 1 > ylimit ) ? 1 : ylimit ); y <= block_limit.y; y++ )
{
x = v_xy / y;
if ( x < 1 ) continue;
v_xyz = (unsigned long)x * (unsigned long)y * (unsigned long)z;
if ( v_xyz > nthreads_max )
{
nthreads_max = v_xyz;
max_size.x = x;
max_size.y = y;
max_size.z = z;
if ( v_xyz == v )
{
block_status = 0;
break;
}
}
}
if ( block_status == 0 )
break;
}
if ( nthreads_max == nthreads )
block_status = 0;
else
block_status = 1;
(*block_size) = max_size;
return block_status;
}
int get_grid( const unsigned long nthreads, const unsigned int nthreads_max_per_block, const dim3 grid_limit, const dim3 block_limit, dim3 *grid_size, dim3 *block_size )
{
unsigned int nthreads_per_block_limit, nthreads_per_block;
unsigned long nblocks;
int grid_status(1);
dim3 bdsize(0,0,0), gdsize(0,0,0);
unsigned int nt;
nthreads_per_block_limit = block_limit.x * block_limit.y * block_limit.z;
if ( nthreads_per_block_limit > nthreads_max_per_block )
nthreads_per_block_limit = nthreads_max_per_block;
for ( nt = nthreads_per_block_limit; nt >= 1; nt-- )
{
get_block( nt, block_limit, &bdsize );
nthreads_per_block = bdsize.x * bdsize.y * bdsize.z;
if ( ( nthreads % (unsigned long)nthreads_per_block ) != 0 ) continue;
nblocks = nthreads / (unsigned long)nthreads_per_block;
grid_status = get_block( nblocks, grid_limit, &gdsize );
if ( grid_status == 0 ) break;
}
if ( grid_status == 0 )
{
(*grid_size) = gdsize;
(*block_size) = bdsize;
}
return grid_status;
}
//#include <cstddef>
//#include <cmath>
//#include "cuda_runtime.h"
//#include "cublas_v2.h"
//// head;
//int get_block( const size_t *nthreads, const dim3 *block_limit, dim3 *block_size );
//int get_grid( const size_t *nthreads, const size_t *nthreads_max_per_block, const dim3 *grid_limit, const dim3 *block_limit, dim3 *grid_size, dim3 *block_size );
//int get_block( const size_t *nthreads, const dim3 *block_limit, dim3 *block_size )
//{
// size_t v, x, y, z, v_xy, v_xyz;
// size_t zlimit, ylimit;
//
// int block_status(1);
// size_t nthreads_max(0);
// dim3 max_size(0,0,0);
//
// v = (*block_limit).x * (*block_limit).y * (*block_limit).z;
// if ( v > *nthreads )
// v = *nthreads;
//
// zlimit = ( v - 1 ) / ( (*block_limit).x * (*block_limit).y ) + 1;
// for ( z = ( ( 1 > zlimit ) ? 1 : zlimit ); z <= (*block_limit).z; z++ )
// {
// v_xy = v / z;
// ylimit = ( v_xy - 1 ) / (*block_limit).x + 1;
// for ( y = ( ( 1 > ylimit ) ? 1 : ylimit ); y <= (*block_limit).y; y++ )
// {
// x = v_xy / y;
// if ( x < 1 ) continue;
//
// v_xyz = x * y * z;
// if ( v_xyz > nthreads_max )
// {
// nthreads_max = v_xyz;
// max_size.x = x;
// max_size.y = y;
// max_size.z = z;
//
// if ( v_xyz == v )
// {
// block_status = 0;
// break;
// }
// }
// }
// if ( block_status == 0 )
// break;
// }
//
// if ( nthreads_max == *nthreads )
// block_status = 0;
// else
// block_status = 1;
// (*block_size) = max_size;
//
// return block_status;
//}
//int get_grid( const size_t *nthreads, const size_t *nthreads_max_per_block, const dim3 *grid_limit, const dim3 *block_limit, dim3 *grid_size, dim3 *block_size )
//{
// size_t nthreads_per_block_limit, nthreads_per_block, nblocks;
//
// int grid_status(1);
// dim3 bdsize(0,0,0), gdsize(0,0,0);
// size_t nt;
//
// nthreads_per_block_limit = (*block_limit).x * (*block_limit).y * (*block_limit).z;
// if ( nthreads_per_block_limit > *nthreads_max_per_block )
// nthreads_per_block_limit = *nthreads_max_per_block;
//
// for ( nt = nthreads_per_block_limit; nt >= 1; nt-- )
// {
// get_block( &nt, block_limit, &bdsize );
// nthreads_per_block = bdsize.x * bdsize.y * bdsize.z;
// if ( ( *nthreads % nthreads_per_block ) != 0 ) continue;
//
// nblocks = *nthreads / nthreads_per_block;
// grid_status = get_block( &nblocks, grid_limit, &gdsize );
// if ( grid_status == 0 ) break;
// }
//
// if ( grid_status == 0 )
// {
// (*grid_size) = gdsize;
// (*block_size) = bdsize;
// }
//
// return grid_status;
//}
|
8,962 | #define d_vx(z,x) d_vx[(x)*(nz)+(z)]
#define d_vy(z,x) d_vy[(x)*(nz)+(z)]
#define d_vz(z,x) d_vz[(x)*(nz)+(z)]
#define d_szz(z,x) d_szz[(x)*(nz)+(z)] // Pressure
#define d_mem_dszz_dz(z,x) d_mem_dszz_dz[(x)*(nz)+(z)]
#define d_mem_dsxx_dx(z,x) d_mem_dsxx_dx[(x)*(nz)+(z)]
#define d_mem_dvz_dz(z,x) d_mem_dvz_dz[(x)*(nz)+(z)]
#define d_mem_dvx_dx(z,x) d_mem_dvx_dx[(x)*(nz)+(z)]
#define d_Lambda(z,x) d_Lambda[(x)*(nz)+(z)]
#define d_Den(z,x) d_Den[(x)*(nz)+(z)]
#define d_ave_Byc_a(z,x) d_ave_Byc_a[(x)*(nz)+(z)]
#define d_ave_Byc_b(z,x) d_ave_Byc_b[(x)*(nz)+(z)]
#include<stdio.h>
__global__ void ac_velocity_adj(float *d_vz, float *d_vx, float *d_szz, \
float *d_mem_dvz_dz, float *d_mem_dvx_dx, float *d_mem_dszz_dz, float *d_mem_dsxx_dx, \
float *d_Lambda, float *d_Den, float *d_ave_Byc_a, float *d_ave_Byc_b, \
float *d_K_z_half, float *d_a_z_half, float *d_b_z_half, \
float *d_K_x_half, float *d_a_x_half, float *d_b_x_half, \
float *d_K_z, float *d_a_z, float *d_b_z, \
float *d_K_x, float *d_a_x, float *d_b_x, \
int nz, int nx, float dt, float dz, float dx, int nPml, int nPad){
int gidz = blockIdx.x*blockDim.x + threadIdx.x;
int gidx = blockIdx.y*blockDim.y + threadIdx.y;
float dszz_dz = 0.0;
float dsxx_dx = 0.0;
float dpsiz_dz = 0.0;
float dpsix_dx = 0.0;
float c1 = 9.0/8.0;
float c2 = 1.0/24.0;
if(gidz>=2 && gidz<=nz-nPad-3 && gidx>=2 && gidx<=nx-3) {
// update vx
// if (gidx == 2) {
// dsxx_dx = -c1*(d_szz(gidz,3)-d_szz(gidz,2)) + c2*(d_szz(gidz,4));
// dpsix_dx = -c1*(d_mem_dvx_dx(gidz,3)-d_mem_dvx_dx(gidz,2)) + c2*(d_mem_dvx_dx(gidz,4));
// }
// else if (gidx == nx-3) {
// dsxx_dx = c1*d_szz(gidz,nx-3) - c2*d_szz(gidz,nx-4);
// dpsix_dx = c1*d_mem_dvx_dx(gidz,nx-3) - c2*d_mem_dvx_dx(gidz,nx-4);
// }
// else if (gidx == nx-4) {
// dsxx_dx = -c1*(d_szz(gidz,gidx+1)-d_szz(gidz,gidx)) - c2*d_szz(gidz,gidx-1);
// dpsix_dx = -c1*(d_mem_dvx_dx(gidz,gidx+1)-d_mem_dvx_dx(gidz,gidx)) - c2*d_mem_dvx_dx(gidz,gidx-1);
// }
// else {
dsxx_dx = (-c1*(d_szz(gidz,gidx+1)-d_szz(gidz,gidx)) + c2*(d_szz(gidz,gidx+2)-d_szz(gidz,gidx-1)))/dx;
dpsix_dx = (-c1*(d_mem_dvx_dx(gidz,gidx+1)-d_mem_dvx_dx(gidz,gidx)) + \
c2*(d_mem_dvx_dx(gidz,gidx+2)-d_mem_dvx_dx(gidz,gidx-1)))/dx;
// }
d_vx(gidz, gidx) += (d_a_x[gidx]*dpsix_dx + d_Lambda(gidz, gidx)*dsxx_dx/d_K_x[gidx]*dt);
// update vz
// if (gidz == 2) {
// dszz_dz = -c1*d_szz(gidz,gidx) + c2*d_szz(gidz+1,gidx);
// dpsiz_dz = -c1*d_mem_dvz_dz(gidz,gidx) + c2*d_mem_dvz_dz(gidz+1,gidx);
// }
// if (gidz == 3) {
// dszz_dz = -c1*(d_szz(gidz,gidx)-d_szz(gidz-1,gidx)) + c2*d_szz(gidz+1,gidx);
// dpsiz_dz = -c1*(d_mem_dvz_dz(gidz,gidx)-d_mem_dvz_dz(gidz-1,gidx)) + \
// c2*d_mem_dvz_dz(gidz+1,gidx);
// }
// else if (gidz == nz-nPad-3) {
// dszz_dz = c1*(d_szz(gidz-1,gidx)-d_szz(gidz,gidx)) - c2*d_szz(gidz-2,gidx);
// dpsiz_dz = c1*(d_mem_dvz_dz(gidz-1,gidx)-d_mem_dvz_dz(gidz,gidx)) - c2*d_mem_dvz_dz(gidz-2,gidx);
// } else {
dszz_dz = (-c1*(d_szz(gidz,gidx)-d_szz(gidz-1,gidx)) + c2*(d_szz(gidz+1,gidx)-d_szz(gidz-2,gidx)))/dz;
dpsiz_dz = (-c1*(d_mem_dvz_dz(gidz,gidx)-d_mem_dvz_dz(gidz-1,gidx)) + \
c2*(d_mem_dvz_dz(gidz+1,gidx)-d_mem_dvz_dz(gidz-2,gidx)))/dz;
// }
d_vz(gidz, gidx) += (d_a_z_half[gidz]*dpsiz_dz + d_Lambda(gidz, gidx)*dszz_dz/d_K_z_half[gidz]*dt);
//update psiz and psix
if(gidx<=nPml || gidx>=nx-nPml-1){
d_mem_dsxx_dx(gidz, gidx) = d_b_x_half[gidx]*d_mem_dsxx_dx(gidz, gidx) + d_ave_Byc_b(gidz, gidx)*d_vx(gidz, gidx)*dt;
}
if(gidz<=nPml || (gidz>=nz-nPml-nPad-1)){
d_mem_dszz_dz(gidz, gidx) = d_b_z[gidz]*d_mem_dszz_dz(gidz, gidx) + d_ave_Byc_a(gidz, gidx)*d_vz(gidz, gidx)*dt;
}
}
else {
return;
}
} |
8,963 | /*
It is instructive to compare zero-copy and unified memory. For the former, the memory is allocated in
page-locked fashion on the host. A device thread has to reach out to get the data. No guarantee of
coherence is provided as, for instance, the host could change the content of the pinned memory while the
device reads its content. For UM, the memory is allocated on the device and transparently made available
where needed. Specifically, upon a call to
cudaError_t cudaMallocManaged(void** devPtr, size_t size, unsigned int flag);
the user has, in devPtr, a pointer to an address of a chunk of device memory. This address can be
equally well manipulated on the device and the host (although, as illustrated below, not simultaneously).
Note that cudaMallocManaged and cudaMalloc are semantically identical; in fact, the former can be
used anywhere the latter is used.
UM enables a “single-pointer-to-data” memory model. For instance, the same pointer can be used on the
host in a memcpy operation to copy a set of integers to an array mA, and then on the device to alter, just
like in the code snippet above, the value of each entry in mA. The data in mA will be coherent as long as
the host does not touch entries in mA when the GPU executes a kernel. The host can safely operate
with/on mA only after a cudaDeviceSynchronize call. Failure to obey this rule will lead to a segfault,
as illustrated in the following example lifted from the CUDA Programming guide.
*/
#include <iostream>
#include <cmath>
const int ARRAY_SIZE = 1000;
__global__ void increment(double* aArray, double val, unsigned int sz) {
unsigned int indx = blockIdx.x * blockDim.x + threadIdx.x;
if (indx < sz)
aArray[indx] += val;
}
int main() {
double* mA;
cudaMallocManaged(&mA, ARRAY_SIZE * sizeof(double));
for (int i = 0; i < ARRAY_SIZE; i++)
mA[i] = 1.*i;
double inc_val = 2.0;
increment<<<2, 512>>>(mA, inc_val, ARRAY_SIZE);
cudaDeviceSynchronize();
double error = 0.;
for (int i = 0; i < ARRAY_SIZE; i++)
error += std::fabs(mA[i] - (i + inc_val));
for (int i=0;i<ARRAY_SIZE;++i){
std::cout<<mA[i]<<' ';
}
std::cout<<'\n';
std::cout << "Test: " << (error < 1.E-9 ? "Passed" : "Failed") << std::endl;
cudaFree(mA);
return 0;
} |
8,964 | #define EIGEN_USE_GPU
#include "cuda.h"
#include <stdio.h>
#define vx(i,j) vx[(i)*(NY+2)+(j)]
#define vy(i,j) vy[(i)*(NY+2)+(j)]
#define vx_(i,j) vx_[(i)*(NY+2)+(j)]
#define vy_(i,j) vy_[(i)*(NY+2)+(j)]
#define sigmaxx(i,j) sigmaxx[(i)*(NY+2)+(j)]
#define sigmaxx_(i,j) sigmaxx_[(i)*(NY+2)+(j)]
#define sigmayy(i,j) sigmayy[(i)*(NY+2)+(j)]
#define sigmayy_(i,j) sigmayy_[(i)*(NY+2)+(j)]
#define sigmaxy(i,j) sigmaxy[(i)*(NY+2)+(j)]
#define sigmaxy_(i,j) sigmaxy_[(i)*(NY+2)+(j)]
#define g_vx(i,j) g_vx[(i)*(NY+2)+(j)]
#define g_vy(i,j) g_vy[(i)*(NY+2)+(j)]
#define g_vx_(i,j) g_vx_[(i)*(NY+2)+(j)]
#define g_vy_(i,j) g_vy_[(i)*(NY+2)+(j)]
#define g_sigmaxx(i,j) g_sigmaxx[(i)*(NY+2)+(j)]
#define g_sigmaxx_(i,j) g_sigmaxx_[(i)*(NY+2)+(j)]
#define g_sigmayy(i,j) g_sigmayy[(i)*(NY+2)+(j)]
#define g_sigmayy_(i,j) g_sigmayy_[(i)*(NY+2)+(j)]
#define g_sigmaxy(i,j) g_sigmaxy[(i)*(NY+2)+(j)]
#define g_sigmaxy_(i,j) g_sigmaxy_[(i)*(NY+2)+(j)]
__global__ void Init(const long long size, const double* in, double* out) {
int i = blockIdx.x*blockDim.x + threadIdx.x;
if(i<size) out[i] = in[i];
}
__global__ void AddSource(
double * vx_,
double * vy_,
double * sigmaxx_,
double * sigmayy_,
double * sigmaxy_,
const long long *srci, const long long *srcj, const double *srcv, const long long *src_type, const int nsrc,
long long NX, long long NY) {
int i = blockIdx.x*blockDim.x + threadIdx.x;
// printf("%d\n", i);
if (i<nsrc){
switch (src_type[i])
{
case 0: // vx
vx_(srci[i]-1, srcj[i]-1) = srcv[i];
break;
case 1: // vy
vy_(srci[i]-1, srcj[i]-1) = srcv[i];
break;
case 2:
sigmaxx_(srci[i]-1, srcj[i]-1) = srcv[i];
// printf("add source to xx, %d\n", i);
break;
case 3:
sigmayy_(srci[i]-1, srcj[i]-1) = srcv[i];
// printf("add source to yy, %d\n", i);
break;
case 4:
sigmaxy_(srci[i]-1, srcj[i]-1) = srcv[i];
break;
default:
break;
}
}
}
__global__ void SetSourceGrad(
double * g_vx_,
double * g_vy_,
double * g_sigmaxx_,
double * g_sigmayy_,
double * g_sigmaxy_,
double * grad_srcv,
const long long *srci, const long long *srcj, const double *srcv, const long long *src_type, const int nsrc,
long long NX, long long NY) {
int i = blockIdx.x*blockDim.x + threadIdx.x;
// printf("%d\n", i);
if (i<nsrc){
switch (src_type[i])
{
case 0: // vx
grad_srcv[i] = g_vx_(srci[i]-1, srcj[i]-1);
break;
case 1: // vy
grad_srcv[i] = g_vy_(srci[i]-1, srcj[i]-1);
break;
case 2:
grad_srcv[i] = g_sigmaxx_(srci[i]-1, srcj[i]-1);
break;
case 3:
grad_srcv[i] = g_sigmayy_(srci[i]-1, srcj[i]-1);
break;
case 4:
grad_srcv[i] = g_sigmaxy_(srci[i]-1, srcj[i]-1);
break;
default:
break;
}
}
}
void forwardGPU(
double * vx_,
double * vy_,
double * sigmaxx_,
double * sigmayy_,
double * sigmaxy_,
const double * vx,
const double * vy,
const double * sigmaxx,
const double * sigmayy,
const double * sigmaxy,
const long long * srci, const long long *srcj, const double *srcv, const long long *src_type, long long nsrc,
const long long * nx, const long long * ny
){
// printf("FORWARD GPU\n");
long long NX, NY;
cudaMemcpy(&NX, nx, sizeof(long long), cudaMemcpyDeviceToHost);
cudaMemcpy(&NY, ny, sizeof(long long), cudaMemcpyDeviceToHost);
cudaDeviceSynchronize();
// printf("Running on the GPU\n");
// printf("%d\n",__LINE__);
Init<<<((NX+2)*(NY+2)+255)/256, 256>>>((NX+2)*(NY+2), vx, vx_);
// printf("%d\n",__LINE__);
Init<<<((NX+2)*(NY+2)+255)/256, 256>>>((NX+2)*(NY+2), vy, vy_);
// printf("%d\n",__LINE__);
Init<<<((NX+2)*(NY+2)+255)/256, 256>>>((NX+2)*(NY+2), sigmaxx, sigmaxx_);
// printf("%d\n",__LINE__);
Init<<<((NX+2)*(NY+2)+255)/256, 256>>>((NX+2)*(NY+2), sigmayy, sigmayy_);
// printf("%d\n",__LINE__);
Init<<<((NX+2)*(NY+2)+255)/256, 256>>>((NX+2)*(NY+2), sigmaxy, sigmaxy_);
// printf("%d\n",__LINE__);
// cudaError_t cudaerr = cudaDeviceSynchronize();
// if (cudaerr != cudaSuccess)
// {
// printf("kernel launch failed with error \"%s\".\n", cudaGetErrorString(cudaerr));
// }
AddSource<<<(nsrc+255)/256, 256>>>(vx_, vy_, sigmaxx_, sigmayy_, sigmaxy_, srci, srcj, srcv, src_type, nsrc, NX, NY);
// printf("%d\n",__LINE__);
// cudaerr = cudaDeviceSynchronize();
// if (cudaerr != cudaSuccess)
// {
// printf("kernel launch failed with error \"%s\".\n", cudaGetErrorString(cudaerr));
// }
}
void backwardGPU(
double * g_vx,
double * g_vy,
double * g_sigmaxx,
double * g_sigmayy,
double * g_sigmaxy,
double * grad_srcv,
const double * g_vx_,
const double * g_vy_,
const double * g_sigmaxx_,
const double * g_sigmayy_,
const double * g_sigmaxy_,
const long long * srci, const long long *srcj, const double *srcv, const long long *src_type, long long nsrc,
const long long * nx, const long long * ny
){
// printf("BACKWARD GPU\n");
long long NX, NY;
cudaMemcpy(&NX, nx, sizeof(long long), cudaMemcpyDeviceToHost);
cudaMemcpy(&NY, ny, sizeof(long long), cudaMemcpyDeviceToHost);
cudaDeviceSynchronize();
Init<<<((NX+2)*(NY+2)+255)/256, 256>>>((NX+2)*(NY+2), g_sigmaxx_, g_sigmaxx);
Init<<<((NX+2)*(NY+2)+255)/256, 256>>>((NX+2)*(NY+2), g_sigmaxy_, g_sigmaxy);
Init<<<((NX+2)*(NY+2)+255)/256, 256>>>((NX+2)*(NY+2), g_sigmayy_, g_sigmayy);
Init<<<((NX+2)*(NY+2)+255)/256, 256>>>((NX+2)*(NY+2), g_vx_, g_vx);
Init<<<((NX+2)*(NY+2)+255)/256, 256>>>((NX+2)*(NY+2), g_vy_, g_vy);
SetSourceGrad<<<nsrc/256, 256>>>(g_vx, g_vy, g_sigmaxx, g_sigmayy, g_sigmaxy, grad_srcv,
srci, srcj, srcv, src_type, nsrc, NX, NY);
}
|
8,965 | #define TILE_DIM 1024
//template<typename T, typename R>
//__device__ void common_math_std(const T* vector, R* result, const int length) {
//
// __shared__ R threadSum[TILE_DIM];
// __shared__ R threadSquareSum[TILE_DIM];
//
// int index = threadIdx.x;
//
// int partLength = (length + TILE_DIM - 1) / TILE_DIM;
//
// R sum = 0;
// R squareSum = 0;
// for (int i = 0; i < partLength; i++) {
// int valueIndex = i * TILE_DIM + index;
// if (valueIndex < length) {
// T value = vector[valueIndex];
// sum += value;
// squareSum += value * value;
// }
// }
// threadSum[index] = sum;
// threadSquareSum[index] = squareSum;
//
// for (int d = 1; d < TILE_DIM && d < length; d <<= 1) {
// __syncthreads();
// if (index % (d << 1) == 0) {
// int valueIndex = index + d;
// if (valueIndex < TILE_DIM) {
// R value = threadSum[valueIndex];
// R square = threadSquareSum[valueIndex];
// sum += value;
// squareSum += square;
// threadSum[index] = sum;
// threadSquareSum[index] = squareSum;
// }
// }
// }
//
// if (index == 0) {
// result[0] = sqrt((squareSum - (sum * sum) / length) / length);
// }
//
//}
template<typename T>
__device__ void math_std(const T* vector, float* result, const int length) {
__shared__ float threadSum[TILE_DIM];
__shared__ float threadSquareSum[TILE_DIM];
int index = threadIdx.x;
int partLength = (length + TILE_DIM - 1) / TILE_DIM;
float sum = 0;
float squareSum = 0;
for (int i = 0; i < partLength; i++) {
int valueIndex = i * TILE_DIM + index;
if (valueIndex < length) {
float value = vector[valueIndex];
sum += value;
squareSum += value * value;
}
}
threadSum[index] = sum;
threadSquareSum[index] = squareSum;
for (int d = 1; d < TILE_DIM && d < length; d <<= 1) {
__syncthreads();
if (index % (d << 1) == 0) {
int valueIndex = index + d;
if (valueIndex < TILE_DIM) {
float value = threadSum[valueIndex];
float square = threadSquareSum[valueIndex];
sum += value;
squareSum += square;
threadSum[index] = sum;
threadSquareSum[index] = squareSum;
}
}
}
if (index == 0) {
result[0] = sqrt((squareSum - (sum * sum) / length) / length);
}
}
|
8,966 | #include <stdio.h>
#include <stdint.h>
#include <stdlib.h>
#include <math.h>
#include <time.h>
#include <string.h>
char buffer[1024];
const int MAX_DIGITS = 50;
int i,j = 0;
struct public_key_class{
long long modulus;
long long exponent;
};
struct private_key_class{
long long modulus;
long long exponent;
};
// This should totally be in the math library.
long long gcd(long long a, long long b)
{
long long c;
while ( a != 0 ) {
c = a; a = b%a; b = c;
}
return b;
}
long long ExtEuclid(long long a, long long b)
{
long long x = 0, y = 1, u = 1, v = 0, gcd = b, m, n, q, r;
while (a!=0) {
q = gcd/a; r = gcd % a;
m = x-u*q; n = y-v*q;
gcd = a; a = r; x = u; y = v; u = m; v = n;
}
return y;
}
__global__ void rsa_modExp(long long b, long long e, long long m, long long* array)
{
if (b < 0 || e < 0 || m <= 0){
printf("error arguments.\n");
}
int index = blockDim.x * blockIdx.x + threadIdx.x;
int thread_nums = gridDim.x * blockDim.x;
long long en_result = 1;
long long i;
for(i = index; i < e ; i+=thread_nums){
//t_result = en_result % m;
en_result = (en_result * b)% m;
}
if (index < e){
array[index] = en_result;
}
else {
array[index] = 0;
}
//return en_result;
}
// Calling this function will generate a public and private key and store them in the pointers
// it is given.
void rsa_gen_keys(struct public_key_class *pub, struct private_key_class *priv, char *PRIME_SOURCE_FILE)
{
FILE *primes_list;
if(!(primes_list = fopen(PRIME_SOURCE_FILE, "r"))){
fprintf(stderr, "Problem reading %s\n", PRIME_SOURCE_FILE);
exit(1);
}
// count number of primes in the list
long long prime_count = 0;
do{
int bytes_read = fread(buffer,1,sizeof(buffer)-1, primes_list);
buffer[bytes_read] = '\0';
for (i=0 ; buffer[i]; i++){
if (buffer[i] == '\n'){
prime_count++;
}
}
}
while(feof(primes_list) == 0);
// choose random primes from the list, store them as p,q
long long p = 0;
long long q = 0;
long long e = powl(2, 8) + 1;
long long d = 0;
char prime_buffer[MAX_DIGITS];
long long max = 0;
long long phi_max = 0;
srand(time(NULL));
do{
// a and b are the positions of p and q in the list
int a = (double)rand() * (prime_count+1) / (RAND_MAX+1.0);
int b = (double)rand() * (prime_count+1) / (RAND_MAX+1.0);
// here we find the prime at position a, store it as p
rewind(primes_list);
for(i=0; i < a + 1; i++){
// for(j=0; j < MAX_DIGITS; j++){
// prime_buffer[j] = 0;
// }
fgets(prime_buffer,sizeof(prime_buffer)-1, primes_list);
}
p = atol(prime_buffer);
// here we find the prime at position b, store it as q
rewind(primes_list);
for(i=0; i < b + 1; i++){
for(j=0; j < MAX_DIGITS; j++){
prime_buffer[j] = 0;
}
fgets(prime_buffer,sizeof(prime_buffer)-1, primes_list);
}
q = atol(prime_buffer);
//here
p = 8011;
q = 8521;
max = p*q;
phi_max = (p-1)*(q-1);
}
while(!(p && q) || (p == q) || (gcd(phi_max, e) != 1));
// Next, we need to choose a,b, so that a*max+b*e = gcd(max,e). We actually only need b
// here, and in keeping with the usual notation of RSA we'll call it d. We'd also like
// to make sure we get a representation of d as positive, hence the while loop.
d = ExtEuclid(phi_max,e);
while(d < 0){
d = d+phi_max;
}
printf("primes are %lld and %lld\n",(long long)p, (long long )q);
// We now store the public / private keys in the appropriate structs
//here
d = 41956193;
pub->modulus = max;
//pub->modulus = 2936519639;
pub->exponent = e;
//pub->exponent = 257;
priv->modulus = max;
//priv->modulus = 2936519639;
priv->exponent = d;
//priv->exponent = 1988060033;
}
long long *rsa_encrypt(const char *message, const unsigned long message_size,
const struct public_key_class *pub)
{
long long *encrypted = (long long *)malloc(sizeof(long long)*message_size);
if(encrypted == NULL){
fprintf(stderr,
"Error: Heap allocation failed.\n");
return NULL;
}
long long i = 0;
long long j = 0;
dim3 dimBlock(512);
dim3 dimGrid(16);
int size = 512 * 16 * sizeof(long long);
long long *array;
long long host_array[size];
cudaMalloc((void**)&array, size);
long long result = 1;
for(i=0; i < message_size; i++){
rsa_modExp<<<dimGrid, dimBlock>>>(message[i], pub->exponent, pub->modulus, array);
cudaMemcpy(host_array, array, size, cudaMemcpyDeviceToHost);
result = 1;
for(j=0; j < 512 * 16; j++){
if (j < pub->exponent) {
result = (result * host_array[j]) % pub->modulus;
}
}
encrypted[i] = result;
}
return encrypted;
}
char *rsa_decrypt(const long long *message,
const unsigned long message_size,
const struct private_key_class *priv)
{
if(message_size % sizeof(long long) != 0){
fprintf(stderr,
"Error: message_size is not divisible by %d, so cannot be output of rsa_encrypt\n", (int)sizeof(long long));
return NULL;
}
// We allocate space to do the decryption (temp) and space for the output as a char array
// (decrypted)
char *decrypted = (char *)malloc(message_size/sizeof(long long));
char *temp = (char *)malloc(message_size);
if((decrypted == NULL) || (temp == NULL)){
fprintf(stderr,
"Error: Heap allocation failed.\n");
return NULL;
}
// Now we go through each 8-byte chunk and decrypt it.
long long i = 0;
long long j = 0;
dim3 dimBlock(512);
dim3 dimGrid(16);
int size = 512 * 16 * sizeof(long long);
long long *array;
long long host_array[size];
cudaMalloc((void**)&array, size);
long long result = 1;
for(i=0; i < message_size/8; i++){
rsa_modExp<<<dimGrid, dimBlock>>>(message[i], priv->exponent, priv->modulus, array);
cudaMemcpy(host_array, array, size, cudaMemcpyDeviceToHost);
result = 1;
for(j=0; j < 512 * 16 ; j++){
if (j < priv->exponent) {
result = (result * host_array[j]) % priv->modulus;
}
}
temp[i] = result;
}
// The result should be a number in the char range, which gives back the original byte.
// We put that into decrypted, then return.
for(i=0; i < message_size/8; i++){
decrypted[i] = temp[i];
}
free(temp);
return decrypted;
}
int main(int argc, char **argv)
{
char *PRIME_SOURCE_FILE = "primes.txt";
struct public_key_class pub[1];
struct private_key_class priv[1];
rsa_gen_keys(pub, priv, PRIME_SOURCE_FILE);
printf("Private Key:\n Modulus: %lld\n Exponent: %lld\n", (long long)priv->modulus, (long long) priv->exponent);
printf("Public Key:\n Modulus: %lld\n Exponent: %lld\n", (long long)pub->modulus, (long long) pub->exponent);
FILE* fptr = fopen("test.txt", "r");
if(fptr == NULL){
printf("e1\n");
}
int filesize = fseek(fptr, 0, SEEK_END);
char* buff = (char*)malloc(100 * sizeof(char));
fseek(fptr, 0, SEEK_SET);
int n = fread(buff, 100, 1, fptr);
char message[101];
strncpy(message, buff, sizeof(message)-1);
message[100] = '\0';
int i;
printf("Original:\n");
//for(i=0; i < strlen(message); i++){
//printf("%lld\n", (long long)message[i]);
printf("%s\n", message);
//}
long long *encrypted = rsa_encrypt(message, sizeof(message), pub);
if (!encrypted){
fprintf(stderr, "Error in encryption!\n");
return 1;
}
printf("Encrypted:\n");
for(i=0; i < strlen(message); i++){
printf("%lld\n", (long long)encrypted[i]);
}
char *decrypted = rsa_decrypt(encrypted, 8*sizeof(message), priv);
if (!decrypted){
fprintf(stderr, "Error in decryption!\n");
return 1;
}
printf("Decrypted:\n");
//for(i=0; i < strlen(message); i++){
//printf("%lld\n", i, (long long)decrypted[i]);
//printf("%s\n", decrypted);
//}
FILE* fptr1 = fopen(argv[argc - 1], "w");
fwrite(decrypted, 100, 1, fptr1);
printf("\n");
free(encrypted);
free(decrypted);
free(buff);
fclose(fptr1);
fclose(fptr);
return 0;
}
|
8,967 | #include <stdlib.h>
#include <stdio.h>
#include <vector>
#include <numeric>
#include <iostream>
#define MYDEVICE 0
#define NUM_BINS 4096
__global__ void computeHistogram(int *input, unsigned int *histogram, int dim)
{
int index = threadIdx.x + blockDim.x * blockIdx.x;
if(index < dim){
int number = input[index];
atomicAdd(&histogram[number], 1);
if(histogram[number] > 127)
histogram[number] = 127;
}
}
int main(void){
// create array of input elements
const int num_elements = 1 << 19;
srand(time(NULL));
// generate random input on the host
std::vector<int> h_input;
for(int i = 0; i < num_elements; i++)
h_input.push_back(rand() % NUM_BINS);
int inputSize = num_elements * sizeof(int);
int *d_input = 0;
cudaMalloc(&d_input, inputSize);
cudaMemcpy(d_input, &h_input[0], inputSize, cudaMemcpyHostToDevice);
int histSize = NUM_BINS * sizeof(unsigned int);
unsigned int *h_hist = 0;
unsigned int *d_hist = 0;
cudaMallocHost(&h_hist, histSize);
cudaMalloc(&d_hist, histSize);
int block_size = 1024;
int num_blocks = (num_elements + block_size - 1)/block_size;
computeHistogram<<<num_blocks, block_size>>>(d_input, d_hist, num_elements);
cudaMemcpy(h_hist, d_hist, histSize, cudaMemcpyHostToDevice);
for (int i = 0; i < NUM_BINS; i++)
std::cout << "Bin: " << i << " Elements: " << h_hist[i] << '\n';
cudaFree(d_input);
cudaFree(h_hist);
cudaFree(d_hist);
return 0;
}
|
8,968 | #include <stdlib.h>
#include <stdio.h>
#include <string.h>
#include <time.h>
#include <stdint.h>
#include <sys/mman.h>
#define ELAPSED_NS(start,stop) \
(((int64_t)stop.tv_sec-start.tv_sec)*1000*1000*1000+(stop.tv_nsec-start.tv_nsec))
#define USE_MUTLI_THREAD
#define gpuErrchk(ans) { gpuAssert((ans), __FILE__, __LINE__); }
typedef struct
{
size_t ntime;
size_t obsnchan;
size_t nbits;
size_t ndim;
size_t npol;
size_t piperblk;
size_t itime_packets;
size_t istride;
size_t tstride;
size_t ostride;
} db_transpose_t;
__global__
void transpose(db_transpose_t * ctx, const void* in, void* out)
{
// To be used in pointer arithmetic
const char* inbuf;
char* outbuf;
const char* baseinbuf = (const char*) in;
char* baseoutbuf = (char*) out;
//size_t itime_packets = ctx->itime_packets;
size_t istride = ctx->istride;
size_t tstride = ctx->tstride;
size_t ostride = ctx->ostride;
size_t ichan;
size_t iptime = blockIdx.x;
size_t nchans = ctx->obsnchan;
size_t nloops = (ctx->obsnchan + blockDim.x - 1)/blockDim.x;
for (int igrid=0; igrid < nloops; igrid++)
{
ichan = threadIdx.x + blockDim.x * igrid;
if (ichan < nchans)
{
inbuf = baseinbuf + iptime*tstride + ichan*istride;
outbuf = baseoutbuf + iptime*istride + ichan*ostride;
memcpy(outbuf, inbuf, istride);
}
}
/*
// Loop over entire spectrum-packets over all the chans
//#pragma omp parallel for private (inbuf, outbuf)
for (size_t iptime=0; iptime < itime_packets; iptime++)
{
inbuf = baseinbuf + iptime*tstride;
outbuf = baseoutbuf + iptime*istride;
for (size_t ichan=0; ichan < ctx->obsnchan; ichan++)
{
memcpy(outbuf, inbuf, istride);
inbuf += istride;
outbuf += ostride;
}
}
*/
}
int test_buf(char* outbuf, size_t nsamps)
{
for (size_t i=0; i< nsamps; i++)
{
if ( outbuf[i] != 10 )
{
fprintf(stderr, "Test failed at sample: %li, value: %i\n", i, outbuf[i]);
return EXIT_FAILURE;
}
}
return 0;
}
int main(int argc, char* argv[])
{
size_t NTIME = 16; //ntime samples per packet
size_t OBSNCHAN = 2048; //total number of channels (all the antennas)
size_t NBITS = 4; //Number of bits
size_t NDIM = 2; //i.e. complex
size_t NPOL = 2; //Number of polarisations
size_t PIPERBLK = 8192*8; // Number of time samples in a block
//size_t NTHREADS = 1;
//omp_set_num_threads(NTHREADS);
// create context
db_transpose_t* ctx;
cudaMallocManaged((void**)&ctx, sizeof(*ctx) );
ctx->ntime = NTIME;
ctx->obsnchan = OBSNCHAN;
ctx->nbits = NBITS;
ctx->ndim = NDIM;
ctx->npol = NPOL;
ctx->piperblk = PIPERBLK;
// number of packets that span the entire data block, in time
ctx->itime_packets = ctx->piperblk / ctx->ntime;
// bytes to stride within a packet in input buffer
// and also amount to copy at a time
ctx->istride = (ctx->npol * ctx->ndim * ctx->nbits * ctx->ntime)/8;
ctx->tstride = ctx->obsnchan * ctx->istride;
ctx->ostride = ctx->itime_packets * ctx->istride;
fprintf(stderr, "itime packets: %li, obsnchan: %li\n",
ctx->itime_packets, ctx->obsnchan);
//Create input and output buffers, same size
size_t buffsize = (NPOL * NDIM * NBITS * PIPERBLK * OBSNCHAN)/8; // Bytes
fprintf(stderr, "BUFFSIZE: %li\n", buffsize);
char* outbuf = (char*) malloc(buffsize);
char* inbuf = (char*) malloc(buffsize);
for (size_t i=0; i<buffsize; i++)
{
outbuf[i] = 0;
inbuf[i] = 10;
}
// GPU memory
char *d_inbuf, *d_outbuf;
if (cudaMalloc((void**) &d_inbuf, buffsize) != cudaSuccess)
{
fprintf(stderr, "Couldn't allocate inbuf\n");
return -1;
}
if (cudaMalloc((void**) &d_outbuf, buffsize) != cudaSuccess)
{
fprintf(stderr, "Couldn't allocate outbuf\n");
return -1;
}
struct timespec start, stop;
// Time the function
clock_gettime(CLOCK_MONOTONIC, &start);
int nloops = 60;
for (size_t i = 0; i<nloops; i++)
{
if (cudaMemcpy(d_inbuf, inbuf, buffsize, cudaMemcpyHostToDevice) != cudaSuccess)
{
fprintf(stderr, "Couldn't move data to device\n");
return -1;
}
//transpose <<<ctx->itime_packets, 512>>> (ctx, d_inbuf, d_outbuf);
transpose <<<ctx->itime_packets, 1024>>> (ctx, d_inbuf, d_outbuf);
//cudaMemcpy(d_outbuf, d_inbuf, buffsize, cudaMemcpyDeviceToDevice);
cudaDeviceSynchronize();
cudaError_t error = cudaGetLastError();
if (error != cudaSuccess)
{
fprintf(stderr, "Couldn't move data back to host, retval: %s\n", cudaGetErrorString(error));
return -1;
}
cudaMemcpy(outbuf, d_outbuf, buffsize, cudaMemcpyDeviceToHost);
}
clock_gettime(CLOCK_MONOTONIC, &stop);
uint64_t elapsed_ns = ELAPSED_NS(start, stop);
fprintf(stdout, "Fluffed %.1f MBytes in %.2f ms (%.2f Gb/s)\n", buffsize*nloops/1.0e6, elapsed_ns / 1.0e6, (8 * (float)buffsize*nloops / elapsed_ns));
test_buf(outbuf, buffsize);
free(inbuf);
free(outbuf);
cudaFree(d_inbuf);
cudaFree(d_outbuf);
return EXIT_SUCCESS;
}
|
8,969 | // From PTT
// (多區塊, 多執行緒) 不使用迴圈，用網格與區塊設定代替
#include <cuda.h>
#include <time.h>
#include <stdio.h>
#include <stdlib.h>
#include <math.h>
////////////////////////////////////////
// 向量加法的運算核心 (GPU)
// 函式前加 __global__ 即為核心
// 核心只傳回 void
////////////////////////////////////////
__global__ void gpu_add(float* c, float* a, float* b, int n){
int j = blockIdx.x*blockDim.x+threadIdx.x;
c[j] = a[j]+b[j];
}
////////////////////////////////////////
// 向量加法的一般函式 (Host)
////////////////////////////////////////
void host_add(float* c, float* a, float* b, int n){
for (int k=0; k<n; k++) {
c[k] = a[k]+b[k];
}
}
////////////////////////////////////////
// 計算誤差用的函式
////////////////////////////////////////
double diff(float* a, float* b, int n){
double s=0, r=0;
for (int k=0; k<n; k++) {
double w=a[k]-b[k];
s += w*w;
r += a[k]*a[k];
}
return sqrt(s/r); //相對誤差
}
////////////////////////////////////////
// 時間函數 (傳回單位:千分之一秒)
////////////////////////////////////////
double ms_time(){
return (double)clock()/CLOCKS_PER_SEC*1000.0;
}
////////////////////////////////////////
// 主程式
////////////////////////////////////////
int main(){
// 設定向量大小
int n = 1024*1024;
int size = n*sizeof(float);
// 網格與區塊設定
int block = 512; // blockDim (每個區塊具有的執行緒數)
int grid = n/block; // gridDim (每個網格具有的區塊數)
// 設定呼叫次數 (測量平均效能)
int loop=100;
// 配置主機記憶體
float *a,*b,*c,*d;
a = (float*)malloc(size);
b = (float*)malloc(size);
c = (float*)malloc(size);
d = (float*)malloc(size);
// 設定亂數的輸入向量
srand(time(0));
for (int k=0; k<n; k++) {
a[k] = (float)rand()/RAND_MAX*2-1;
b[k] = (float)rand()/RAND_MAX*2-1;
}
// 配置顯示卡記憶體
float *ga,*gb,*gc;
cudaMalloc((void**)&ga, size);
cudaMalloc((void**)&gb, size);
cudaMalloc((void**)&gc, size);
// 載入向量 a,b 到顯示卡記憶體中
cudaMemcpy(ga, a, size, cudaMemcpyHostToDevice);
cudaMemcpy(gb, b, size, cudaMemcpyHostToDevice);
////////////////////////////////////////
// part 1 : 測量精確度
////////////////////////////////////////
// 呼叫核心來運算 (GPU)
gpu_add<<<grid, block>>>(gc, ga, gb, n);
// 呼叫一般函數來運算 (Host)
host_add(d, a, b, n);
// 把計算結果存回主機
cudaMemcpy(c, gc, size, cudaMemcpyDeviceToHost);
// 比較兩者差異
printf("vector add N(%d) elements, diff = %g\n", n, diff(c,d,n));
////////////////////////////////////////
// part 2 : 測量效能
////////////////////////////////////////
// 測量 GPU 核心效能
double gpu_dt = ms_time();
for (int w=0; w<loop; w++) {
gpu_add<<<grid, block>>>(gc, ga, gb, n);
cudaThreadSynchronize(); //避免核心執行不完全
}
gpu_dt = (ms_time()-gpu_dt)/loop; //平均時間
// 測量 Host 函數效能
double host_dt = ms_time();
for (int w=0; w<loop; w++) {
host_add(d, a, b, n);
}
host_dt = (ms_time()-host_dt)/loop; //平均時間
// 輸出平均執行時間
printf("host time: %g ms\n", host_dt);
printf("gpu time: %g ms\n", gpu_dt);
// 釋放主機記憶體
free(a);
free(b);
free(c);
free(d);
// 釋放顯示卡記憶體
cudaFree(ga);
cudaFree(gb);
cudaFree(gc);
return 0;
}
// vector add N(1048576) elements, diff = 0
// host time: 3.37028 ms
// gpu time: 0.51496 ms
|
8,970 | #include <stdio.h>
typedef float (*op_func_t) (float, float);
__device__ float add_func (float x, float y)
{
return x + y;
}
__device__ float mul_func (float x, float y)
{
return x * y;
}
// Static pointers to device functions
__device__ op_func_t p_add_func = add_func;
__device__ op_func_t p_mul_func = mul_func;
__global__ void kernel( op_func_t op )
{
printf("Result: %f\n", ( *op )( 1.0, 2.0 ) );
}
int main()
{
op_func_t h_add_func;
op_func_t h_mul_func;
// Copy device function pointer to host side
cudaMemcpyFromSymbol( &h_mul_func, p_mul_func, sizeof( op_func_t ) );
cudaMemcpyFromSymbol( &h_add_func, p_add_func, sizeof( op_func_t ) );
op_func_t d_myfunc = h_mul_func;
kernel<<<1,1>>>( d_myfunc );
cudaThreadSynchronize();
return EXIT_SUCCESS;
} |
8,971 | #include "assignmentHPC1.cuh"
#include <iostream>
#include <cstdlib>
#include <chrono>
using namespace std;
using namespace std::chrono;
__global__ void reduce(float *input, float *output, unsigned int n) {
unsigned int block_size = blockDim.x;
unsigned int thread_id = threadIdx.x;
unsigned int block_id = blockIdx.x;
unsigned int block_start = block_id * block_size * 2 + thread_id;
for (unsigned int stride = block_size; stride > 0; stride /= 2) {
if (thread_id < stride && block_start + stride < n) {
input[block_start] += input[block_start + stride];
}
__syncthreads();
}
if (!thread_id) {
output[block_id] = input[block_start];
}
}
double find_sum_cpu(double *arr_host, unsigned int N) {
double result = 0.0f;
cout<<"N : "<<N<<endl;
for(unsigned int i = 0; i < N; i++) {
result += arr_host[i];
}
return result;
}
void find_sum(double *arr_host, unsigned int N) {
// ----------------------------------------- CPU Code -------------------------------------------------
auto startCPU = high_resolution_clock::now();
double result = find_sum_cpu(arr_host, N);
auto stopCPU = high_resolution_clock::now();
cout<<"\n\n--------------- CPU ---------------\n"<<endl;
cout<<"Answer CPU : "<<result<<endl;
cout<<"\nTime on CPU : "<<duration_cast<microseconds>(stopCPU - startCPU).count()/1000<<" milli seconds\n\n"<<endl;
// ----------------------------------------- GPU Code -------------------------------------------------
} |
8,972 | #include<stdio.h>
#include<stdlib.h>
#include "error.cuh"
__global__ void addArrays(float *a, float *b, float *c, int N);
int main(){
const int N = 100000;
const int M = sizeof(float) * N;
float *h_a, *h_b, *h_c;
float value_a = 1.11, value_b = 2.22;
int i;
h_a = (float*)malloc(M);
h_b = (float*)malloc(M);
h_c = (float*)malloc(M);
for(i = 0; i < N; i++)
h_a[i] = value_a;
for(i = 0; i < N; i++)
h_b[i] = value_b;
float *d_a, *d_b, *d_c;
cudaMalloc((void**)&d_a, M);
cudaMalloc((void**)&d_b, M);
cudaMalloc((void**)&d_c, M);
cudaMemcpy(d_a, h_a, M, cudaMemcpyHostToDevice);
cudaMemcpy(d_b, h_b, M, cudaMemcpyHostToDevice);
int block_size = 64;
int grid_size = (N + block_size - 1) / block_size;
cudaEvent_t start, end;
cudaEventCreate(&start);
cudaEventCreate(&end);
cudaEventRecord(start);
cudaEventQuery(start);
addArrays<<<grid_size, block_size>>>(d_a, d_b, d_c, N);
cudaEventRecord(end);
cudaEventSynchronize(end);
cudaMemcpy(h_c, d_c, M, cudaMemcpyDeviceToHost);
float time_passed;
cudaEventElapsedTime(&time_passed, start, end);
printf("Time passed %f ms.\n", time_passed);
cudaEventDestroy(start);
cudaEventDestroy(end);
free(h_a);
free(h_b);
free(h_c);
cudaFree(d_a);
cudaFree(d_b);
cudaFree(d_c);
return 0;
}
__global__ void addArrays(float *a, float *b, float *c, int N){
int index = blockIdx.x * blockDim.x + threadIdx.x;
if(index < N)
c[index] = a[index] + b[index];
} |
8,973 | #include <cuda.h>
#include <stdio.h>
#define DIM 1
#define PARTICLE_COUNT 512
#define W 2.0
#define C1 1.0
#define C2 1.0
typedef struct {
float pos[DIM];
float del[DIM];
float bsf[DIM];
} particle;
typedef struct {
particle s[PARTICLE_COUNT];
particle d[PARTICLE_COUNT];
} blockData;
__device__ void init(particle * s, particle * d, unsigned int index) {
for(unsigned int i = 0; i < DIM; i++) {
d[index].pos[i] = s[index].pos[i];
d[index].del[i] = s[index].del[i];
d[index].bsf[i] = s[index].bsf[i];
}
}
__device__ float global(particle * s, unsigned int i, unsigned int d) {
unsigned int pu, pd;
pu = (i + 1) % DIM;
pd = (i - 1) % DIM;
float a = s[i].bsf[d];
float b = s[pu].bsf[d];
float c = s[pd].bsf[d];
return (a > b) ? (a > c ? a : c) : ( b > c ? b : c);
}
__device__ void inertial(particle * s, particle * d, unsigned int index) {
for(unsigned int i = 0; i < DIM; i++) {
d[index].del[i] += s[index].del[i] * W;
}
}
__device__ void cognitive(particle * s, particle * d, unsigned int index) {
for(unsigned int i = 0; i < DIM; i++) {
d[index].del[i] += C1 * (s[index].bsf[i] - s[index].pos[i]);
}
}
__device__ void social(particle * s, particle * d, unsigned int index) {
for(unsigned int i = 0; i < DIM; i++) {
d[index].del[i] += C2 * (global(s, index, i) - s[index].pos[i]);
}
//GLOBAL BEST
}
__global__ void pso(blockData * p, float w, float c1, float c2, bool sw) {
unsigned int x_i = threadIdx.x + blockIdx.x * blockDim.x;
unsigned int y_i = threadIdx.y + blockIdx.y * blockDim.y;
unsigned index = x_i + y_i * blockDim.x * gridDim.x;
particle * s = sw ? (particle *)p->s : (particle *)p->d;
particle * d = sw ? (particle *)p->d : (particle *)p->s;
if (index < PARTICLE_COUNT) {
init(s, d, index);
inertial(s, d, index);
cognitive(s, d, index);
social(s, d, index);
}
}
int main() {
return 0;
}
|
8,974 | #include <stdio.h>
#include <stdlib.h>
#include <malloc.h>
#include <time.h>
#define MATRIX_SIZE 1024
int main(int argc, char** argv){
unsigned int col_idx, row_idx, scan_idx;
int* matA;
int* matB;
int* matC;
time_t Start, Stop;
matA = (int*)malloc(sizeof(int) * MATRIX_SIZE * MATRIX_SIZE);
matB = (int*)malloc(sizeof(int) * MATRIX_SIZE * MATRIX_SIZE);
matC = (int*)malloc(sizeof(int) * MATRIX_SIZE * MATRIX_SIZE);
for (col_idx = 0; col_idx < MATRIX_SIZE; col_idx++) {
for (row_idx = 0; row_idx < MATRIX_SIZE; row_idx++) {
matA[col_idx * MATRIX_SIZE + row_idx] = rand() % (MATRIX_SIZE * MATRIX_SIZE);
matB[col_idx * MATRIX_SIZE + row_idx] = rand() % (MATRIX_SIZE * MATRIX_SIZE);
matC[col_idx * MATRIX_SIZE + row_idx] = 0;
}
}
time(&Start);
for (col_idx = 0; col_idx < MATRIX_SIZE; col_idx++) {
for (row_idx = 0; row_idx < MATRIX_SIZE; row_idx++) {
for (scan_idx = 0; scan_idx < MATRIX_SIZE; scan_idx++) {
matC[col_idx * MATRIX_SIZE + row_idx] += matA[col_idx * MATRIX_SIZE + scan_idx] *
matB[scan_idx * MATRIX_SIZE + row_idx];
}
}
}
time(&Stop);
printf("Processing time: %d (sec)\n", Stop - Start);
free(matA);
free(matB);
free(matC);
return 0;
}
|
8,975 | #include "includes.h"
__global__ void kernel_convert(uchar3* d_Iin, float4* d_Iout, int numel) {
size_t col = threadIdx.x + blockIdx.x * blockDim.x;
if (col >= numel) { return; }
uchar3 val = d_Iin[col];
d_Iout[col] = make_float4(
val.x / 255.0f,
val.y / 255.0f,
val.z / 255.0f,
1.0f
);
} |
8,976 | #include <errno.h>
#include <limits.h>
#include <math.h>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
typedef unsigned uint;
typedef float flt;
#define exit_if(cnd_value, msg) \
do { \
if (cnd_value) { \
if (errno) \
perror(msg); \
else \
fprintf(stderr, "error: %s\n", msg); \
exit(EXIT_FAILURE); \
} \
} while (0)
#define cudaErrorCheck(error) \
do { \
cudaError_t res = error; \
if (res != cudaSuccess) { \
fprintf(stderr, "cuda %s:%d error: %s\n", __FILE__, __LINE__, \
cudaGetErrorString(res)); \
exit(EXIT_FAILURE); \
} \
} while(0)
#define MU_COUNT (3U)
__device__ __constant__ int3 deviceMu[MU_COUNT];
__global__ static void classify(uchar4 * __restrict__, uint, uint);
__host__ static uchar4 *read_file(const char *, uint *, uint *);
__host__ static void write_file(
const char *, const uchar4 * __restrict__, uint, uint
);
int main(void) {
char fileIn[FILENAME_MAX], fileOut[FILENAME_MAX];
scanf("%s%s", fileIn, fileOut);
uint w, h;
uchar4 * const __restrict__ data = read_file(fileIn, &w, &h);
const uint size = sizeof(uchar4) * w * h;
uchar4 *deviceData;
cudaErrorCheck(cudaMalloc(&deviceData, size));
cudaErrorCheck(cudaMemcpy(deviceData, data, size, cudaMemcpyHostToDevice));
int3 hostMu[MU_COUNT] = {
make_int3(255, 0, 0),
make_int3(0, 255, 0),
make_int3(0, 0, 255)
};
cudaErrorCheck(cudaMemcpyToSymbol(deviceMu, hostMu,
sizeof(int3) * MU_COUNT
));
classify<<<dim3(16U, 16U), dim3(16U, 16U)>>>(deviceData, w, h);
cudaErrorCheck(cudaGetLastError());
cudaErrorCheck(cudaMemcpy(data, deviceData, size, cudaMemcpyDeviceToHost));
cudaErrorCheck(cudaFree(deviceData));
write_file(fileOut, data, w, h);
free(data);
return 0;
}
__global__ static void classify(
uchar4 * const __restrict__ data,
const uint w, const uint h
) {
const uint
idxX = threadIdx.x + blockDim.x * blockIdx.x,
idxY = threadIdx.y + blockDim.y * blockIdx.y,
offsetX = blockDim.x * gridDim.x,
offsetY = blockDim.y * gridDim.y;
for (uint j = idxY; j < h; j += offsetY) {
for (uint i = idxX; i < w; i += offsetX) {
int min_distance = INT_MAX;
const uint index = j * w + i;
const uchar4 data_i_j = data[index];
for (uint idx = 0; idx < MU_COUNT; ++idx) {
const int distance =
(data_i_j.x - deviceMu[idx].x) * (data_i_j.x - deviceMu[idx].x) +
(data_i_j.y - deviceMu[idx].y) * (data_i_j.y - deviceMu[idx].y) +
(data_i_j.z - deviceMu[idx].z) * (data_i_j.z - deviceMu[idx].z);
if (distance < min_distance) {
data[index].w = idx;
min_distance = distance;
}
}
}
}
}
__host__ static uchar4 *read_file(
const char * const file, uint * const w, uint * const h
) {
FILE * const stream = fopen(file, "rb");
exit_if(stream == NULL, "fopen()");
exit_if(fread(w, sizeof(uint), 1, stream) != 1, "fread()");
exit_if(fread(h, sizeof(uint), 1, stream) != 1, "fread()");
const uint count = (*w) * (*h);
uchar4 * const data = (uchar4 *) malloc(sizeof(uchar4) * count);
exit_if(data == NULL, "malloc()");
exit_if(fread(data, sizeof(uchar4), count, stream) != count, "fread()");
exit_if(fclose(stream) != 0, "close()");
return data;
}
__host__ static void write_file(
const char * const file, const uchar4 * const __restrict__ data,
const uint w, const uint h
) {
FILE * const stream = fopen(file, "wb");
exit_if(stream == NULL, "fopen()");
const uint count = w * h;
exit_if(fwrite(&w, sizeof(uint), 1, stream) != 1, "fwrite()");
exit_if(fwrite(&h, sizeof(uint), 1, stream) != 1, "fwrite()");
exit_if(fwrite(data, sizeof(uchar4), count, stream) != count, "fwrite()");
exit_if(fclose(stream) != 0, "fclose()");
}
|
8,977 | #include "includes.h"
__global__ void __word2vecPos(int nrows, int ncols, int *W, int *LB, int *UB, float *A, float *B, float lrate, float vexp) {} |
8,978 | #include <stdio.h>
#include <stdlib.h>
#include <cuda_runtime_api.h>
#include <math.h>
#include "link.h"
using namespace std;
__global__ void link(float **var, int **intVar){
const int npcn = 2000;
int nseg = *intVar[7];
int *bin = intVar[12];
int *list = intVar[13];
int *bnei = intVar[14];
int nxbin = *intVar[15];
int nybin = *intVar[16];
int nzbin = *intVar[17];
int *bnum = intVar[31];
int *potCon = intVar[32];
int *potConSize = intVar[33];
int mi = blockIdx.x;
int tid = threadIdx.x;
int miBin = bnum[mi];
int nextBin = bnei[miBin + tid*nxbin*nybin*nzbin];
int nextTot = bin[nextBin];
int nj, i, pos;
if (tid == 0){
potConSize[mi] = 0;
}
__syncthreads();
for (i = 0; i < nextTot; i++){
nj = list[nextBin + i*nxbin*nybin*nzbin];
// skip when segments are connected
if (mi >= nj){
continue;
}
if ((mi - (mi / nseg)*nseg) != 0 && nj == mi - 1){
continue;
}
if ((nj - (nj / nseg)*nseg) != 0 && mi == nj - 1){
continue;
}
if ((mi - (mi / nseg)*nseg) != nseg - 1 && nj == mi + 1){
continue;
}
if ((nj - (nj / nseg)*nseg) != nseg - 1 && mi == nj + 1){
continue;
}
//printf("link mi nj %4d %4d\n", mi, nj);
pos = atomicAdd(potConSize + mi, 1);
if (pos >= npcn - 1) printf("allocate more space for potCon pos %4d\n", pos);
potCon[mi * npcn + pos] = nj;
}
}
|
8,979 | #include "includes.h"
__device__ void get_conflict_edge(bool *dl_matrix, short *deleted_rows, int *row_group, const int conflict_node_id, const int search_depth, int *conflict_edge, const int vertex_num, const int total_dl_matrix_row_num, const int total_dl_matrix_col_num) {
//*conflict_col_id = 0;
// int idxa = 0;
// int idxb = 0;
for (int i = threadIdx.x; i < total_dl_matrix_row_num; i = i + blockDim.x) {
// find the conflict edge that connects current node and the most closest
// node.
if (deleted_rows[i] == -conflict_node_id) {
atomicMax(conflict_edge, i);
}
if (row_group[i] == search_depth + 1 &&
deleted_rows[i] == conflict_node_id) {
atomicMax(conflict_edge + 1, i);
}
}
}
__global__ void get_conflict_edge(int *dl_matrix, int *deleted_rows, int *deleted_cols, int *row_group, const int conflict_node_id, const int search_depth, int *conflict_edge, const int vertex_num, const int total_dl_matrix_row_num, const int total_dl_matrix_col_num) {
//*conflict_col_id = 0;
//int idxa = 0;
//int idxb = 0;
for (int i = threadIdx.x; i < total_dl_matrix_row_num; i = i + blockDim.x) {
// find the conflict edge that connects current node and the most closest
// node.
if (deleted_rows[i] == -conflict_node_id) {
atomicMax(conflict_edge, i);
}
if (row_group[i] == search_depth + 1 &&
deleted_rows[i] == conflict_node_id) {
atomicMax(conflict_edge+1, i);
}
}
__syncthreads();
} |
8,980 | #include<bits/stdc++.h>
#include<cuda.h>
using namespace std;
#define CEIL(a, b) ((a-1)/b +1)
__global__ void Multiply(int* d_a,int* d_b,int* d_c, int N)
{
int x=blockIdx.x*blockDim.x + threadIdx.x;
int y=blockIdx.y*blockDim.y + threadIdx.y;
int index=x*N+y;
if(x<N && y<N)
{
int res=0;
for(int i=0;i<N;i++)
res += (d_a[x*N+i] * d_b[i*N+y]);
d_c[index]=res;
}
}
int main()
{
int N;
cout<<"enter size : ";
cin>>N;
int h_a[N][N], h_b[N][N], h_c[N][N], h_d[N][N];
int bytes=N*N*sizeof(int);
for(int i=0;i<N;i++)
{
for(int j=0;j<N;j++)
{
h_a[i][j]= rand()%10 ;
h_b[i][j]= rand()%10 ;
}
}
int *d_a, *d_b, *d_c;
cudaMalloc((void**)&d_b, bytes);
cudaMalloc((void**)&d_a, bytes);
cudaMalloc((void**)&d_c, bytes);
cudaMemcpy(d_b, h_b, bytes, cudaMemcpyHostToDevice);
cudaMemcpy(d_a, h_a, bytes, cudaMemcpyHostToDevice);
dim3 block(32, 32, 1);
dim3 grid(CEIL(N, 32), CEIL(N, 32), 1);
Multiply<<<grid, block>>>(d_a,d_b,d_c,N);
cudaMemcpy(h_c, d_c, bytes, cudaMemcpyDeviceToHost);
for(int i=0;i<N;i++)
{
for(int j=0;j<N;j++)
{
int res=0;
for(int k=0;k<N;k++)
res += (h_a[i][k]*h_b[k][j]);
h_d[i][j]=res;
}
}
bool verify=true;
for(int i=0;i<N;i++)
{
for(int j=0;j<N;j++)
{
if(h_c[i][j]!=h_d[i][j])
verify=false;
}
}
if(verify)
cout<<"Result is Correct";
else
cout<<"Incorrect Result";
cudaFree(d_a);
cudaFree(d_b);
cudaFree(d_c);
} |
8,981 | #include "includes.h"
__global__ void THCudaTensor_kernel_addcdiv(float *data, float value, float *src1, float *src2, long size)
{
long k = (((blockIdx.y * gridDim.x) + blockIdx.x) * blockDim.x) + threadIdx.x;
if(k < size)
data[k] += value*src1[k]/src2[k];
} |
8,982 | #include<stdio.h>
__global__ void VecAdd(float* A, float* B, float *C)
{
int idx = blockIdx.x*blockDim.x + threadIdx.x;
C[idx] = A[idx] + B[idx];
}
int main()
{
int N=16*16*16;
float *A=0, *B=0, *C=0;
float *Ad=0, *Bd=0, *Cd=0;
A = (float*)malloc(N*sizeof(float));
B = (float*)malloc(N*sizeof(float));
C = (float*)malloc(N*sizeof(float));
if(0==A||0==B||0==C){
printf("Could not allocate host memory\n");
return 1;
}
for(int i=0; i<N; i++)
{
A[i] = i;
B[i] = i;
}
cudaMalloc( (void**)&Ad, N*sizeof(float) );
cudaMalloc( (void**)&Bd, N*sizeof(float) );
cudaMalloc( (void**)&Cd, N*sizeof(float) );
if(0==Ad||0==Bd||0==Cd){
printf("Could not allocate device memory\n");
return 2;
}
cudaMemcpy(Ad, A, N*sizeof(float), cudaMemcpyHostToDevice);
cudaMemcpy(Bd, B, N*sizeof(float), cudaMemcpyHostToDevice);
dim3 grid, block;
block.x = 1;
grid.x = N/block.x;
VecAdd<<<grid, block>>>(Ad, Bd, Cd);
cudaMemcpy(C, Cd, N*sizeof(float), cudaMemcpyDeviceToHost);
for(int i=0; i<N; i++)
printf("%d %e %e %e\n", i, A[i], B[i], C[i]);
free(A); free(B); free(C);
cudaFree(Ad); cudaFree(Bd); cudaFree(Cd);
return 0;
}
|
8,983 | #include "includes.h"
__global__ void rdiv(float * res, const unsigned int * fsum, const float * csum) {
int idx = threadIdx.x + blockIdx.x*blockDim.x;
res[idx] = (float)fsum[idx] / csum[idx];
} |
8,984 | #include <iostream>
#include <math.h>
__global__
void s_scal(int n, float *alpha, float *vector) {
int index = blockIdx.x * blockDim.x + threadIdx.x;
if (index < n) {
vector[index] = vector[index] * (*alpha);
}
}
int main() {
int N = 2000000;
int threads_per_block = 256;
int blocks_per_grid = (N + 255) / threads_per_block;
float alpha, *vector, *d_alpha, *d_vector;
alpha = 12.0;
vector = new float[N];
for (int i = 0; i < N; i += 1) {
vector[i] = 1.0f;
}
cudaMalloc(&d_alpha, sizeof(float));
cudaMalloc(&d_vector, N * sizeof(float));
cudaMemcpy(d_alpha, &alpha, sizeof(float), cudaMemcpyHostToDevice);
cudaMemcpy(d_vector, vector, N * sizeof(float), cudaMemcpyHostToDevice);
s_scal<<<blocks_per_grid, threads_per_block>>>(N, d_alpha, d_vector);
cudaMemcpy(vector, d_vector, N * sizeof(float), cudaMemcpyDeviceToHost);
float maxError = 0.0f;
for (int i = 0; i < N; i++)
maxError = fmax(maxError, fabs(vector[i]-alpha));
std::cout << "Max error: " << maxError << std::endl;
cudaFree(d_alpha);
cudaFree(d_vector);
free(vector);
cudaDeviceReset();
return 0;
}
|
8,985 | // fermi
/*
* Copyright 2018 Vrije Universiteit Amsterdam, The Netherlands
*
* 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.
*/
extern "C" {
__global__ void sumDoublesKernel(const int n, double* result, const double* input);
}
__global__ void sumDoublesKernel(const int n, double* result, const double* input) {
const int wti = threadIdx.y;
const int tti = threadIdx.x;
const int nrThreads = 256;
const int nrThreadsNrThreads = min(32, nrThreads);
__shared__ double reduceMem[256];
const int ti = wti * (1 * nrThreadsNrThreads) + tti;
if (ti < nrThreads) {
if (ti < n) {
double sum = 0.0;
for (int i = ti; i < n; i += nrThreads) {
sum += input[i];
}
reduceMem[ti] = sum;
__syncthreads();
for (int i = nrThreads / 2; i > 0; i >>= 1) {
if (ti < i) {
reduceMem[ti] += reduceMem[ti + i];
}
__syncthreads();
}
if (ti == 0) {
*result = reduceMem[0];
}
}
}
}
|
8,986 | #ifndef M_PI
#define M_PI 3.14159265358979323846F /* pi */
#endif
struct point3d
{
float x=0, y=0, z=0;
};
// database: B*N*3
// query: B*M*3
// nnIndex: B*M*nnSample
// nnCount: B*M
// nnDist: B*M*nnSample
__global__ void cal_nnidx_sphere(int B, int N, int M, int nnSample, float radius,
const float* database, const float* query,
int* nnIndex, int* nnCount, float* nnDist)
{
// get the neighbor indices
point3d ptQuery, pt, delta;
for(int i=blockIdx.x;i<B;i+=gridDim.x)
{
for(int j=threadIdx.x;j<M;j+=blockDim.x)
{
ptQuery.x = query[i*M*3+j*3];
ptQuery.y = query[i*M*3+j*3+1];
ptQuery.z = query[i*M*3+j*3+2];
int s=0; // to count the number of neighbors
while(s==0) //require a minimum of 1 neighbor point
{
//re-initialziation
s = 0;
for(int k=0;k<N;k++)
{
pt.x = database[i*N*3+k*3];
pt.y = database[i*N*3+k*3+1];
pt.z = database[i*N*3+k*3+2];
delta.x = pt.x - ptQuery.x;
delta.y = pt.y - ptQuery.y;
delta.z = pt.z - ptQuery.z;
float dist3D = delta.x*delta.x + delta.y*delta.y + delta.z*delta.z; // squared 3D
dist3D = sqrtf(dist3D); //sqrt
if (dist3D<radius && fabs(dist3D-radius)>1e-6) // find a neighbor in range
{
if (s<nnSample) // sample NO=nnSample neighbor points, requires shuffling of points order in every epoch
{
nnIndex[i*M*nnSample+j*nnSample+s] = k;
nnDist[i*M*nnSample+j*nnSample+s] = dist3D; // sqrt, not the squared one
}
s++;
}
}
radius += 0.05;
}
nnCount[i*M+j] = s<nnSample?s:nnSample;
}
}
}
// database: B*N*3
// query: B*M*3
// nnIndex: B*M*nnSample*2
// nnCount: B*M
__global__ void cal_nnidx_cube(int B, int N, int M, int gridSize, int nnSample, float length,
const float* database, const float* query, int* nnIndex, int* nnCount)
{
// get the neighbor indices, and compute their indices in the filter/kernel bins
point3d ptQuery, pt, delta;
for(int i=blockIdx.x;i<B;i+=gridDim.x)
{
for(int j=threadIdx.x;j<M;j+=blockDim.x)
{
ptQuery.x = query[i*M*3+j*3];
ptQuery.y = query[i*M*3+j*3+1];
ptQuery.z = query[i*M*3+j*3+2];
int s=0; // to count the number of neighbors
while(s==0) //require a minimum of 1 neighbor point
{
//re-initialziation
s = 0; // to count the number of neighbors
for(int k=0;k<N;k++)
{
pt.x = database[i*N*3+k*3];
pt.y = database[i*N*3+k*3+1];
pt.z = database[i*N*3+k*3+2];
delta.x = pt.x - ptQuery.x;
delta.y = pt.y - ptQuery.y;
delta.z = pt.z - ptQuery.z;
if (abs(delta.x)<length/2 && abs(delta.y)<length/2 && abs(delta.z)<length/2 && s<nnSample)
{
// calculate bin index in the cubic filter/kernel
int xId = (delta.x + length/2)/(length/gridSize); //[0, gridSize)
int yId = (delta.y + length/2)/(length/gridSize); //[0, gridSize)
int zId = (delta.z + length/2)/(length/gridSize); //[0, gridSize)
// float dist3D = delta.x*delta.x + delta.y*delta.y + delta.z*delta.z; // squared 3D
// int binID;
// if (dist3D<1e-6)
// binID = 0;
// else
// binID = xId*gridSize*gridSize + yId*gridSize + zId + 1;
int binID = xId*gridSize*gridSize + yId*gridSize + zId;
nnIndex[i*M*nnSample*2+j*nnSample*2+s*2] = k;
nnIndex[i*M*nnSample*2+j*nnSample*2+s*2+1] = binID;
s++;
}
}
length += 0.1;
}
nnCount[i*M+j] = s<nnSample?s:nnSample;
}
}
}
/* This part's code is based on the 3nn weighted interpolation of PointNet++
of Charles R. Qi.
*/
// database: B*N*3
// query: B*M*3
// nnIndex: B*M*nnOut
// nnDist: B*M*nnOut
__global__ void cal_nnidx(int B, int N, int M, const float* database,
const float* query, int* nnIndex, float* nnDist)
{
// get the neighbor indices
point3d ptQuery, pt, delta;
for(int i=blockIdx.x;i<B;i+=gridDim.x)
{
for(int j=threadIdx.x;j<M;j+=blockDim.x)
{
ptQuery.x = query[i*M*3+j*3];
ptQuery.y = query[i*M*3+j*3+1];
ptQuery.z = query[i*M*3+j*3+2];
float best1=1e40, best2=1e40, best3=1e40, best4=1e40;
int besti1=0, besti2=0, besti3=0, besti4=0;
for(int k=0;k<N;k++)
{
pt.x = database[i*N*3+k*3];
pt.y = database[i*N*3+k*3+1];
pt.z = database[i*N*3+k*3+2];
delta.x = pt.x - ptQuery.x;
delta.y = pt.y - ptQuery.y;
delta.z = pt.z - ptQuery.z;
float dist3D = delta.x*delta.x + delta.y*delta.y + delta.z*delta.z; // squared 3D
if (dist3D<best1) { // This is from PointNet++
best4=best3;
besti4=besti3;
best3=best2;
besti3=besti2;
best2=best1;
besti2=besti1;
best1=dist3D;
besti1=k;
} else if (dist3D<best2) {
best4=best3;
besti4=besti3;
best3=best2;
besti3=besti2;
best2=dist3D;
besti2=k;
} else if (dist3D<best3) {
best4=best3;
besti4=besti3;
best3=dist3D;
besti3=k;
} else if (dist3D<best4) {
best4=dist3D;
besti4=k;
}
nnIndex[i*M*3+j*3] = besti1;
nnIndex[i*M*3+j*3+1] = besti2;
nnIndex[i*M*3+j*3+2] = besti3;
nnIndex[i*M*3+j*3+3] = besti4;
nnDist[i*M*3+j*3] = sqrtf(best1); // sqrt, not the squared one
nnDist[i*M*3+j*3+1] = sqrtf(best2); // sqrt, not the squared one
nnDist[i*M*3+j*3+2] = sqrtf(best3); // sqrt, not the squared one
nnDist[i*M*3+j*3+3] = sqrtf(best4); // sqrt, not the squared one
}
}
}
}
void buildSphereNeighborLauncher(int B, int N, int M, int nnSample, float radius,
const float* database, const float* query, int* nnIndex,
int* nnCount, float* nnDist)
{
cal_nnidx_sphere<<<B,1024>>>(B, N, M, nnSample, radius,
database, query, nnIndex, nnCount, nnDist);
}
void buildCubeNeighborLauncher(int B, int N, int M, int gridSize, int nnSample, float length,
const float* database, const float* query, int* nnIndex, int* nnCount)
{
cal_nnidx_cube<<<B,1024>>>(B, N, M, gridSize, nnSample, length, database, query, nnIndex, nnCount);
}
void buildNearestNeighborLauncher(int B, int N, int M, const float* database,
const float* query, int* nnIndex, float* nnDist)
{
cal_nnidx<<<B,1024>>>(B, N, M, database, query, nnIndex, nnDist);
} |
8,987 | #include <stdio.h>
#include <stdlib.h>
#include <fcntl.h>
#include <unistd.h>
#include "string.h"
#include "cuda.h"
#define DEFAULT_THRESHOLD 4000
#define DEFAULT_FILENAME "images/BWstop-sign.ppm"
unsigned int *read_ppm( char *filename, int & xsize, int & ysize, int & maxval ) {
if ( !filename || filename[0] == '\0') {
fprintf(stderr, "read_ppm but no file name\n");
return NULL; // fail
}
fprintf(stderr, "read_ppm( %s )\n", filename);
int fd = open( filename, O_RDONLY);
if (fd == -1) {
fprintf(stderr, "read_ppm() ERROR file '%s' cannot be opened for reading\n", filename);
return NULL; // fail
}
char chars[1024];
int num = read(fd, chars, 1000);
if (chars[0] != 'P' || chars[1] != '6') {
fprintf(stderr, "Texture::Texture() ERROR file '%s' does not start with \"P6\" I am expecting a binary PPM file\n", filename);
return NULL;
}
unsigned int width, height, maxvalue;
char *ptr = chars+3; // P 6 newline
if (*ptr == '#') { // comment line!
ptr = 1 + strstr(ptr, "\n");
}
num = sscanf(ptr, "%d\n%d\n%d", &width, &height, &maxvalue);
fprintf(stderr, "read %d things width %d height %d maxval %d\n", num, width, height, maxvalue);
xsize = width;
ysize = height;
maxval = maxvalue;
unsigned int *pic = (unsigned int *)malloc( width * height * sizeof(unsigned int));
if (!pic) {
fprintf(stderr, "read_ppm() unable to allocate %d x %d unsigned ints for the picture\n", width, height);
return NULL; // fail but return
}
// allocate buffer to read the rest of the file into
int bufsize = 3 * width * height * sizeof(unsigned char);
if (maxval > 255) bufsize *= 2;
unsigned char *buf = (unsigned char *)malloc( bufsize );
if (!buf) {
fprintf(stderr, "read_ppm() unable to allocate %d bytes of read buffer\n", bufsize);
return NULL; // fail but return
}
// TODO really read
char duh[80];
char *line = chars;
// find the start of the pixel data. no doubt stupid
sprintf(duh, "%d\0", xsize);
line = strstr(line, duh);
//fprintf(stderr, "%s found at offset %d\n", duh, line-chars);
line += strlen(duh) + 1;
sprintf(duh, "%d\0", ysize);
line = strstr(line, duh);
//fprintf(stderr, "%s found at offset %d\n", duh, line-chars);
line += strlen(duh) + 1;
sprintf(duh, "%d\0", maxval);
line = strstr(line, duh);
fprintf(stderr, "%s found at offset %d\n", duh, line - chars);
line += strlen(duh) + 1;
long offset = line - chars;
lseek(fd, offset, SEEK_SET); // move to the correct offset
long numread = read(fd, buf, bufsize);
fprintf(stderr, "Texture %s read %ld of %ld bytes\n", filename, numread, bufsize);
close(fd);
int pixels = xsize * ysize;
for (int i=0; i<pixels; i++) pic[i] = (int) buf[3*i]; // red channel
return pic; // success
}
void write_ppm( char *filename, int xsize, int ysize, int maxval, int *pic) {
FILE *fp;
fp = fopen(filename, "w");
if (!fp) {
fprintf(stderr, "FAILED TO OPEN FILE '%s' for writing\n");
exit(-1);
}
// int x,y;
fprintf(fp, "P6\n");
fprintf(fp,"%d %d\n%d\n", xsize, ysize, maxval);
int numpix = xsize * ysize;
for (int i=0; i<numpix; i++) {
unsigned char uc = (unsigned char) pic[i];
fprintf(fp, "%c%c%c", uc, uc, uc);
}
fclose(fp);
}
// ======================================== SOBEL ========================================
__device__ void sobel(int offset, int thresh, int *result,
unsigned int i0j0, unsigned int i0j1, unsigned int i0j2,
unsigned int i1j0, unsigned int i1j1, unsigned int i1j2,
unsigned int i2j0, unsigned int i2j1, unsigned int i2j2) {
int sum1 = i0j2 - i0j0 + 2*i1j2 - 2*i1j0 + i2j2 - i2j0;
int sum2 = i0j0 + 2*i0j1 + i0j2 - i2j0 - 2*i2j1 - i2j2;
int magnitude = sum1*sum1 + sum2*sum2;
if (magnitude > thresh) {
result[offset] = 255;
}
}
/*
Naive solution
Converts the outer loop of the sequential code into blocks, and the inner loop into threads
*/
__global__ void sobel_naive(unsigned int *pic, int *result, int thresh,
int ysize, int xsize, int ythreads, int xthreads, int yelems, int xelems) {
int i, j, offset, sum1, sum2, magnitude;
for (i = blockIdx.x + 1; i < ysize - 1; i += gridDim.x) {
for (j = threadIdx.x + 1; j < xsize - 1; j += xthreads) {
offset = i * xsize + j;
sum1 = pic[xsize*(i-1) + j+1] - pic[xsize*(i-1) + j-1]
+ 2*pic[xsize* i + j+1] - 2*pic[xsize* i + j-1]
+ pic[xsize*(i+1) + j+1] - pic[xsize*(i+1) + j-1];
sum2 = pic[xsize*(i-1) + j-1] + 2*pic[xsize*(i-1) + j] + pic[xsize*(i-1) + j+1]
- pic[xsize*(i+1) + j-1] - 2*pic[xsize*(i+1) + j] - pic[xsize*(i+1) + j+1];
magnitude = sum1*sum1 + sum2*sum2;
if (magnitude > thresh) {
result[offset] = 255;
}
}
}
}
/*
Shared solution
Each thread in a block brings one element into shared memory, with the perimeter threads bringing
additional halo elements (divergent threads). Then each thread computes sobel for its element.
*/
__global__ void sobel_shared(unsigned int *pic, int *result, int thresh,
int ysize, int xsize, int ythreads, int xthreads, int yelems, int xelems) {
__shared__ unsigned int tile[1156];
int y = threadIdx.y;
int x = threadIdx.x;
int rowsize = xthreads+2;
int min_y = blockIdx.y*ythreads+1;
int min_x = blockIdx.x*xthreads+1;
int max_y = min(ysize-1, min_y+ythreads-1);
int max_x = min(xsize-1, min_x+xthreads-1);
// Load into shared memory
if (y == 0) {
// Top-left corner
if (x == 0) {
tile[0] = pic[xsize*(min_y-1) + (min_x-1)];
}
// Bring in first row
tile[x+1] = pic[xsize*(min_y-1) + (min_x+x)];
} else if (y == ythreads-1) {
// Bottom-right corner
if (x == xthreads-1) {
tile[rowsize*(y+2) + x+2] = pic[xsize*(max_y+1) + (max_x+1)];
}
// Bring in last row
tile[rowsize*(y+2) + x+1] = pic[xsize*(max_y+1) + (min_x+x)];
}
if (x == 0) {
// Bottom-left corner
if (y == ythreads-1) {
tile[rowsize*(y+2)] = pic[xsize*(max_y+1) + (min_x-1)];
}
// Bring in first column
tile[rowsize*(y+1)] = pic[xsize*(min_y+y) + (min_x-1)];
} else if (x == xthreads-1) {
// Top-right corner
if (y == 0) {
tile[x+2] = pic[xsize*(min_y-1) + (max_x+1)];
}
// Bring in last column
tile[rowsize*(y+1) + x+2] = pic[xsize*(min_y+y) + (max_x+1)];
}
tile[rowsize*(y+1) + (x+1)] = pic[xsize*(min_y+y) + (min_x+x)];
// Sync the threads
__syncthreads();
// Each thread computes sobel
int sum1 = tile[rowsize* y + (x+2)] - tile[rowsize* y + x]
+ 2*tile[rowsize*(y+1) + (x+2)] - 2*tile[rowsize*(y+1) + x]
+ tile[rowsize*(y+2) + (x+2)] - tile[rowsize*(y+2) + x];
int sum2 = tile[rowsize* y + x] + 2*tile[rowsize* y + (x+1)] + tile[rowsize* y + (x+2)]
- tile[rowsize*(y+2) + x] - 2*tile[rowsize*(y+2) + (x+1)] - tile[rowsize*(y+2) + (x+2)];
int magnitude = sum1*sum1 + sum2*sum2;
if (magnitude > thresh) {
result[xsize*(min_y+y) + (min_x+x)] = 255;
}
}
/*
Shared overlapping solution
Each thread in a block brings one element into shared memory. Then the interior threads compute
sobel for each of their elements. Blocks must overlap to compute sobel for all elements.
*/
__global__ void sobel_shared_overlap(unsigned int *pic, int *result, int thresh,
int ysize, int xsize, int ythreads, int xthreads, int yelems, int xelems) {
__shared__ unsigned int tile[1024];
int y = threadIdx.y;
int x = threadIdx.x;
int min_y = blockIdx.y*(ythreads-2);
int min_x = blockIdx.x*(xthreads-2);
// Load into shared memory
tile[xthreads*y + x] = pic[xsize*(min_y+y) + (min_x+x)];
// Sync the threads
__syncthreads();
// Each interior thread computes sobel
if (y > 0 && y < ythreads-1 && x > 0 && x < xthreads-1) {
int sum1 = tile[xthreads*(y-1) + (x+1)] - tile[xthreads*(y-1) + (x-1)]
+ 2*tile[xthreads* y + (x+1)] - 2*tile[xthreads* y + (x-1)]
+ tile[xthreads*(y+1) + (x+1)] - tile[xthreads*(y+1) + (x-1)];
int sum2 = tile[xthreads*(y-1) + (x-1)] + 2*tile[xthreads*(y-1) + x] + tile[xthreads*(y-1) + (x+1)]
- tile[xthreads*(y+1) + (x-1)] - 2*tile[xthreads*(y+1) + x] - tile[xthreads*(y+1) + (x+1)];
int magnitude = sum1*sum1 + sum2*sum2;
if (magnitude > thresh) {
result[xsize*(min_y+y) + (min_x+x)] = 255;
}
}
}
/*
Unrolled solution
Each thread loads a 6x6 grid into registers, then computes sobel for each of the 4x4 interior elements
*/
__global__ void sobel_unrolled(unsigned int *pic, int *result, int thresh,
int ysize, int xsize, int ythreads, int xthreads, int yelems, int xelems) {
// Get bounds
int min_y = blockIdx.y * ythreads * yelems + 1;
int min_x = blockIdx.x * xthreads * xelems + 1;
// Put elements into registers
int i = min_y + threadIdx.y * yelems;
int j = min_x + threadIdx.x * xelems;
unsigned int i0j0 = pic[xsize*(i-1) + (j-1)];
unsigned int i0j1 = pic[xsize*(i-1) + j];
unsigned int i0j2 = pic[xsize*(i-1) + (j+1)];
unsigned int i0j3 = pic[xsize*(i-1) + (j+2)];
unsigned int i0j4 = pic[xsize*(i-1) + (j+3)];
unsigned int i0j5 = pic[xsize*(i-1) + (j+4)];
unsigned int i1j0 = pic[xsize* i + (j-1)];
unsigned int i1j1 = pic[xsize* i + j];
unsigned int i1j2 = pic[xsize* i + (j+1)];
unsigned int i1j3 = pic[xsize* i + (j+2)];
unsigned int i1j4 = pic[xsize* i + (j+3)];
unsigned int i1j5 = pic[xsize* i + (j+4)];
unsigned int i2j0 = pic[xsize*(i+1) + (j-1)];
unsigned int i2j1 = pic[xsize*(i+1) + j];
unsigned int i2j2 = pic[xsize*(i+1) + (j+1)];
unsigned int i2j3 = pic[xsize*(i+1) + (j+2)];
unsigned int i2j4 = pic[xsize*(i+1) + (j+3)];
unsigned int i2j5 = pic[xsize*(i+1) + (j+4)];
unsigned int i3j0 = pic[xsize*(i+2) + (j-1)];
unsigned int i3j1 = pic[xsize*(i+2) + j];
unsigned int i3j2 = pic[xsize*(i+2) + (j+1)];
unsigned int i3j3 = pic[xsize*(i+2) + (j+2)];
unsigned int i3j4 = pic[xsize*(i+2) + (j+3)];
unsigned int i3j5 = pic[xsize*(i+2) + (j+4)];
unsigned int i4j0 = pic[xsize*(i+3) + (j-1)];
unsigned int i4j1 = pic[xsize*(i+3) + j];
unsigned int i4j2 = pic[xsize*(i+3) + (j+1)];
unsigned int i4j3 = pic[xsize*(i+3) + (j+2)];
unsigned int i4j4 = pic[xsize*(i+3) + (j+3)];
unsigned int i4j5 = pic[xsize*(i+3) + (j+4)];
unsigned int i5j0 = pic[xsize*(i+4) + (j-1)];
unsigned int i5j1 = pic[xsize*(i+4) + j];
unsigned int i5j2 = pic[xsize*(i+4) + (j+1)];
unsigned int i5j3 = pic[xsize*(i+4) + (j+2)];
unsigned int i5j4 = pic[xsize*(i+4) + (j+3)];
unsigned int i5j5 = pic[xsize*(i+4) + (j+4)];
sobel(i * xsize + j, thresh, result,
i0j0, i0j1, i0j2, i1j0, i1j1, i1j2, i2j0, i2j1, i2j2);
sobel(i * xsize + (j+1), thresh, result,
i0j1, i0j2, i0j3, i1j1, i1j2, i1j3, i2j1, i2j2, i2j3);
sobel(i * xsize + (j+2), thresh, result,
i0j2, i0j3, i0j4, i1j2, i1j3, i1j4, i2j2, i2j3, i2j4);
sobel(i * xsize + (j+3), thresh, result,
i0j3, i0j4, i0j5, i1j3, i1j4, i1j5, i2j3, i2j4, i2j5);
sobel((i+1) * xsize + j, thresh, result,
i1j0, i1j1, i1j2, i2j0, i2j1, i2j2, i3j0, i3j1, i3j2);
sobel((i+1) * xsize + (j+1), thresh, result,
i1j1, i1j2, i1j3, i2j1, i2j2, i2j3, i3j1, i3j2, i3j3);
sobel((i+1) * xsize + (j+2), thresh, result,
i1j2, i1j3, i1j4, i2j2, i2j3, i2j4, i3j2, i3j3, i3j4);
sobel((i+1) * xsize + (j+3), thresh, result,
i1j3, i1j4, i1j5, i2j3, i2j4, i2j5, i3j3, i3j4, i3j5);
sobel((i+2) * xsize + j, thresh, result,
i2j0, i2j1, i2j2, i3j0, i3j1, i3j2, i4j0, i4j1, i4j2);
sobel((i+2) * xsize + (j+1), thresh, result,
i2j1, i2j2, i2j3, i3j1, i3j2, i3j3, i4j1, i4j2, i4j3);
sobel((i+2) * xsize + (j+2), thresh, result,
i2j2, i2j3, i2j4, i3j2, i3j3, i3j4, i4j2, i4j3, i4j4);
sobel((i+2) * xsize + (j+3), thresh, result,
i2j3, i2j4, i2j5, i3j3, i3j4, i3j5, i4j3, i4j4, i4j5);
sobel((i+3) * xsize + j, thresh, result,
i3j0, i3j1, i3j2, i4j0, i4j1, i4j2, i5j0, i5j1, i5j2);
sobel((i+3) * xsize + (j+1), thresh, result,
i3j1, i3j2, i3j3, i4j1, i4j2, i4j3, i5j1, i5j2, i5j3);
sobel((i+3) * xsize + (j+2), thresh, result,
i3j2, i3j3, i3j4, i4j2, i4j3, i4j4, i5j2, i5j3, i5j4);
sobel((i+3) * xsize + (j+3), thresh, result,
i3j3, i3j4, i3j5, i4j3, i4j4, i4j5, i5j3, i5j4, i5j5);
}
int main( int argc, char **argv ) {
int thresh = DEFAULT_THRESHOLD;
char *filename;
filename = strdup( DEFAULT_FILENAME);
if (argc > 1) {
if (argc == 3) { // filename AND threshold
filename = strdup( argv[1]);
thresh = atoi( argv[2] );
}
if (argc == 2) { // default file but specified threshhold
thresh = atoi( argv[1] );
}
fprintf(stderr, "file %s threshold %d\n", filename, thresh);
}
int xsize, ysize, maxval;
unsigned int *pic = read_ppm( filename, xsize, ysize, maxval );
int numbytes = xsize * ysize * 3 * sizeof( int );
int *result = (int *) malloc( numbytes );
if (!result) {
fprintf(stderr, "sobel() unable to malloc %d bytes\n", numbytes);
exit(-1); // fail
}
int i, j, magnitude, sum1, sum2;
int *out = result;
for (int col=0; col<ysize; col++) {
for (int row=0; row<xsize; row++) {
*out++ = 0;
}
}
for (i = 1; i < ysize - 1; i++) {
for (j = 1; j < xsize -1; j++) {
int offset = i*xsize + j;
sum1 = pic[ xsize * (i-1) + j+1 ] - pic[ xsize*(i-1) + j-1 ]
+ 2 * pic[ xsize * (i) + j+1 ] - 2 * pic[ xsize*(i) + j-1 ]
+ pic[ xsize * (i+1) + j+1 ] - pic[ xsize*(i+1) + j-1 ];
sum2 = pic[ xsize * (i-1) + j-1 ] + 2 * pic[ xsize * (i-1) + j ] + pic[ xsize * (i-1) + j+1 ]
- pic[xsize * (i+1) + j-1 ] - 2 * pic[ xsize * (i+1) + j ] - pic[ xsize * (i+1) + j+1 ];
magnitude = sum1*sum1 + sum2*sum2;
if (magnitude > thresh)
result[offset] = 255;
else
result[offset] = 0;
}
}
write_ppm( "result.ppm", xsize, ysize, 255, result);
fprintf(stderr, "sobel done\n");
// ==================== GPU IMPLEMENTATION ====================
char* strategy = "unrolled";
int yround = ysize;
int xround = xsize;
int yblocks, xblocks, ymult, xmult, ythreads, xthreads, yelems, xelems;
if (strategy == "naive") {
yblocks = 1;
ythreads = 1;
xblocks = ysize;
xthreads = xsize;
if (xblocks > 1024) {
xblocks = 1024;
}
if (xthreads > 1024) {
xthreads = 1024;
}
} else {
ythreads = 32;
xthreads = 32;
if (strategy == "shared") {
ymult = ythreads;
xmult = xthreads;
} else if (strategy == "shared_overlap") {
ymult = ythreads-2;
xmult = xthreads-2;
} else if (strategy == "unrolled") {
yelems = 4;
xelems = 4;
ymult = ythreads*yelems;
xmult = xthreads*xelems;
}
// For simplicity, have exactly the number of blocks and threads needed
if (yround % ymult) {
yround = yround/ymult*ymult + ymult;
}
if (xround % xmult) {
xround = xround/xmult*xmult + xmult;
}
yblocks = yround / ymult;
xblocks = xround / xmult;
}
dim3 blocks(xblocks, yblocks);
dim3 threads(xthreads, ythreads);
// Allocate memory
unsigned int *dPic;
int *dResult;
int *resultGPU = (int *) malloc(numbytes);
if (!resultGPU) {
fprintf(stderr, "sobel() unable to malloc %d bytes\n", numbytes);
exit(-1); // fail
}
cudaMalloc((unsigned int **) &dPic, yround*xround*sizeof(unsigned int));
cudaMalloc((int **) &dResult, numbytes);
cudaMemcpy(dPic, pic, ysize*xsize*sizeof(unsigned int), cudaMemcpyHostToDevice);
cudaMemset(dResult, 0, numbytes);
float elapsed_time;
cudaEvent_t start,stop;
// Execute the kernel
if (strategy == "naive") {
cudaEventCreate(&start);
cudaEventCreate(&stop);
cudaEventRecord(start,0);
sobel_naive<<<blocks, threads>>>(dPic, dResult, thresh, ysize, xsize, ythreads, xthreads, yelems, xelems);
cudaDeviceSynchronize();
cudaEventRecord(stop);
cudaEventSynchronize(stop);
cudaEventElapsedTime(&elapsed_time,start, stop);
} else if (strategy == "shared") {
cudaEventCreate(&start);
cudaEventCreate(&stop);
cudaEventRecord(start,0);
sobel_shared<<<blocks, threads>>>(dPic, dResult, thresh, ysize, xsize, ythreads, xthreads, yelems, xelems);
cudaDeviceSynchronize();
cudaEventRecord(stop);
cudaEventSynchronize(stop);
cudaEventElapsedTime(&elapsed_time,start, stop);
} else if (strategy == "shared_overlap") {
cudaEventCreate(&start);
cudaEventCreate(&stop);
cudaEventRecord(start,0);
sobel_shared_overlap<<<blocks, threads>>>(dPic, dResult, thresh, ysize, xsize, ythreads, xthreads, yelems, xelems);
cudaDeviceSynchronize();
cudaEventRecord(stop);
cudaEventSynchronize(stop);
cudaEventElapsedTime(&elapsed_time,start, stop);
} else if (strategy == "unrolled") {
cudaEventCreate(&start);
cudaEventCreate(&stop);
cudaEventRecord(start,0);
sobel_unrolled<<<blocks, threads>>>(dPic, dResult, thresh, ysize, xsize, ythreads, xthreads, yelems, xelems);
cudaDeviceSynchronize();
cudaEventRecord(stop);
cudaEventSynchronize(stop);
cudaEventElapsedTime(&elapsed_time,start, stop);
}
// Copy the result
cudaMemcpy(resultGPU, dResult, numbytes, cudaMemcpyDeviceToHost);
for (i = 1; i < ysize - 1; i++) {
for (j = 1; j < xsize - 1; j++) {
if (result[i*xsize + j] != resultGPU[i*xsize + j]) {
//fprintf(stderr, "RESULTS NOT EQUAL %i %i\n", i, j);
}
}
}
// Write the ppm file
char* name = (char*) malloc(strlen(strategy) + 5);
if (!name) {
fprintf(stderr, "sobel() unable to malloc %d bytes\n", strlen(strategy) + 5);
exit(-1); // fail
}
strcpy(name, strategy);
strcat(name, ".ppm");
write_ppm(name, xsize, ysize, 255, resultGPU);
fprintf(stderr, "%4.4f\n", elapsed_time);
// Free memory
cudaFree(dPic);
cudaFree(dResult);
free(pic);
free(result);
free(resultGPU);
free(name);
}
|
8,988 | #include "includes.h"
__device__ bool checkBoundary(int blockIdx, int blockDim, int threadIdx){
int x = threadIdx;
int y = blockIdx;
return (x == 0 || x == (blockDim-1) || y == 0 || y == 479);
}
__global__ void mAdvect(float *new_data, float *old_data, float *xv, float *yv, float t_step, float s_stepX, float s_stepY) {
if(checkBoundary(blockIdx.x, blockDim.x, threadIdx.x)) return;
int Idx = blockIdx.x * blockDim.x + threadIdx.x;
float curr_x = (float)threadIdx.x;
float curr_y = (float)blockIdx.x;
float last_x = curr_x - t_step*s_stepX*xv[Idx];
float last_y = curr_y - t_step*s_stepY*yv[Idx];
if(last_x < 1.5) last_x = 1.5;
if(last_x > 637.5) last_x = 637.5;
if(last_y < 1.5) last_y = 1.5;
if(last_y > 477.5) last_y = 477.5;
// Bilinear Interpolation
float xDiff = last_x - (int)last_x;
float yDiff = last_y - (int)last_y;
int LeftTopX = (int)last_x;
int LeftTopY = (int)last_y;
int LeftTopIdx = LeftTopY * blockDim.x + LeftTopX;
new_data[Idx] = (xDiff*yDiff)*old_data[LeftTopIdx+blockDim.x+1]
+(xDiff*(1.f-yDiff))*old_data[LeftTopIdx+1]
+((1.f-xDiff)*yDiff)*old_data[LeftTopIdx+blockDim.x]
+((1.f-xDiff)*(1.f-yDiff))*old_data[LeftTopIdx];
} |
8,989 | // #include "vec.cuh"
// template <>
// template <> __device__ void Vector_gmem<char>::CleanData<ExecutionPolicy::WC>() {
// for (size_t i = LTID; i < *size; i += blockDim.x) {
// data[i] = 0;
// }
// }
// template <>
// template <> __device__ void Vector_gmem<char>::CleanData<ExecutionPolicy::BC>() {
// for (size_t i = LTID; i < *size; i += blockDim.x) {
// data[i] = 0;
// }
// } |
8,990 | #include "includes.h"
__global__ void computeNormsAndCenter( float *norms, float *center, float *masses, float4 *positions, int *blocknums, int *blocksizes ) {
int blockNum = blockIdx.x * blockDim.x + threadIdx.x;
float totalmass = 0.0;
for( int j = blocknums[blockNum]; j <= blocknums[blockNum] + blocksizes[blockNum] - 1; j += 3 ) {
float mass = masses[ j / 3 ];
center[blockNum * 3 + 0] = positions[j / 3].x * mass;
center[blockNum * 3 + 1] = positions[j / 3].y * mass;
center[blockNum * 3 + 2] = positions[j / 3].z * mass;
totalmass += mass;
}
norms[blockNum] = sqrt( totalmass );
center[blockNum * 3 + 0] /= totalmass;
center[blockNum * 3 + 1] /= totalmass;
center[blockNum * 3 + 2] /= totalmass;
} |
8,991 | /**
* Configuration indexes.
*/
#define Y_IMAGE_SIZE conf[0]
#define Y_FEATURE_SIZE conf[1]
#define Y_ROW_SIZE conf[5]
#define Y_0 conf[2]
#define Y_1 conf[3]
#define Y_2 conf[4]
#define Y_3 conf[5]
#define STRIDES_0 conf[6]
#define STRIDES_1 conf[7]
#define W_0 conf[8]
#define W_1 conf[9]
#define W_2 conf[10]
#define W_3 conf[11]
#define X_IMAGE_SIZE conf[12]
#define X_CHANNEL_SIZE conf[13]
#define X_ROW_SIZE conf[14]
#define X_0 conf[15]
/**
* The memory shared between the threads of each block.
*/
extern __shared__ float sdata[];
/**
* Compute the sum of the array's elements.
* @param sdata the array.
* @return the sum.
*/
__device__ float reduce_sum(float *sdata) {
for (int i = 1; i < blockDim.x * blockDim.y * blockDim.z; i++) {
sdata[0] += sdata[i];
}
return sdata[0];
}
/**
* Compute the CPCA gradients.
* @param conf is the kernel' configuration.
* @param x the input activation.
* @param w the weights.
* @param y the output activation.
* @param r the gradients, i.e. the output buffer.
* @return nothing.
*/
extern "C"
__global__ void weights_gradients(int *conf, float *x, float *w, float *y, float *r)
{
int bid = blockIdx.x * gridDim.y * gridDim.z + blockIdx.y * gridDim.z + blockIdx.z;
int tid = threadIdx.x * blockDim.y * blockDim.z + threadIdx.y * blockDim.z + threadIdx.z;
int fi = blockIdx.x / W_1;
int4 w_pos = make_int4(fi, blockIdx.x - fi * W_1, blockIdx.y, blockIdx.z);
int4 y_pos = make_int4(threadIdx.x, fi, threadIdx.y, threadIdx.z);
sdata[tid] = 0;
for (int i = y_pos.x; i < Y_0; i += blockDim.x) {
for (int r = y_pos.z; r < Y_2; r += blockDim.y) {
for (int c = y_pos.w; c < Y_3; c += blockDim.z) {
int rx = r * STRIDES_0 + w_pos.z;
int cx = c * STRIDES_1 + w_pos.w;
int y_index = i * Y_IMAGE_SIZE + w_pos.x * Y_FEATURE_SIZE + r * Y_ROW_SIZE + c;
for (int ii = 0; ii < X_0; ii++) {
int x_index = ii * X_IMAGE_SIZE + w_pos.y * X_CHANNEL_SIZE + rx * X_ROW_SIZE + cx;
sdata[tid] += min(y[y_index], (float)1) * (x[x_index] - w[bid]);
}
}
}
}
__syncthreads();
if (tid == 0) {
r[bid] = reduce_sum(sdata);
}
}
/**
* Count the patterns.
* @param conf is the kernel' configuration.
* @param y the output activation.
* @param r the count, i.e. the output buffer.
* @return nothing.
*/
extern "C"
__global__ void count_patterns(int *conf, float *y, float *r)
{
int tid = threadIdx.x * blockDim.y * blockDim.z + threadIdx.y * blockDim.z + threadIdx.z;
sdata[tid] = 0;
for (int ii = threadIdx.x; threadIdx.x + ii < X_0; ii += blockDim.x) {
int index = ii * Y_IMAGE_SIZE + blockIdx.x * Y_FEATURE_SIZE + threadIdx.y * Y_ROW_SIZE + threadIdx.z;
for (int vo = 0; threadIdx.y + vo < Y_2; vo += blockDim.y) {
for (int ho = 0; threadIdx.z + ho < Y_3; ho += blockDim.z) {
int y_index = index + vo * Y_3 + ho;
if (y[y_index] != 0)
sdata[tid] += 1;
}
}
}
__syncthreads();
if (tid == 0) {
r[blockIdx.x] = reduce_sum(sdata);
}
}
|
8,992 | #include <stdio.h>
__global__
void saxpy(int n, float a, float* __restrict__ x, float* __restrict__ y)
{
int i = blockIdx.x*blockDim.x + threadIdx.x;
if (i < n) y[i] = a*x[i] + y[i];
}
|
8,993 | #include <stdio.h>
#include <math.h>
#define N 1200
#define THREADS 1024
__global__ void matrixMultKernel (double *a, double *b, double *c, int n)
{
int row = blockIdx.y * blockDim.y + threadIdx.y;
int col = blockIdx.x * blockDim.x + threadIdx.x;
if((row < n) && (col < n)){
double v = 0;
for(int k = 0; k < n; k++){
v += a[row * n + k] * b[k * n + col];
}
c[row * n + col] = v;
}
}
int main(){
double *a, *b, *c;
double *d_a, *d_b, *d_c;
double size = N * N * sizeof(double);
cudaMalloc((void**) &d_a, size);
cudaMalloc((void**) &d_b, size);
cudaMalloc((void**) &d_c, size);
a = (double*)malloc(size);
b = (double*)malloc(size);
c = (double*)malloc(size);
for(int i = 0; i < N * N; i++){
a[i] = b[i] = i;
c[i] = 0;
}
cudaMemcpy(d_a, a, size, cudaMemcpyHostToDevice);
cudaMemcpy(d_b, b, size, cudaMemcpyHostToDevice);
matrixMultKernel<<<(int)ceil(N / THREADS), THREADS>>> (d_a, d_b, d_c, N);
cudaMemcpy(c, d_c, size, cudaMemcpyDeviceToHost);
printf("c[0] = %lf\n", c[0]);
printf("c[%d] = %lf\n", N-1, c[N-1]);
free(a);
free(b);
free(c);
cudaFree(d_a);
cudaFree(d_b);
cudaFree(d_c);
return 0;
} |
8,994 |
#include "cuda_runtime.h"
#include "device_launch_parameters.h"
#include <ctime>
#include <stdio.h>
#include "stdlib.h"
cudaError_t launchCuda(int *c, const int *a, const int *b, size_t size);
void algorithm(int *c, const int *a, const int *b, size_t size);
int initTime = 0;
__global__ void Bl1(int *X, int *A, int *B)
{
int i = threadIdx.x;
X[i] = 100500;
}
__global__ void Bl2(float **X, float **A, float *B)
{
int i = threadIdx.x;
// c[i] = a[i] + b[i];
}
__global__ void helpBl(float **X, float **A, float *B)
{
}
void TestFunc()
{
printf("blah-blah\n");
}
int cudaTest(const int &size, float &time, float *answer)
{
srand((unsigned)std::time(NULL));
time = initTime;
// answer = new float[size];
for (int i = 0; i < size; ++i)
answer[i] = rand();
return 0;
}
void cudaSetInitTime(int t)
{
initTime = t;
}
int cudaMain(const int &size, float &time, float *answer)
{
const int arraySize = 5;
const int *a = new int[size];
const int *b = new int[size];
int *c = new int[size];
// Add vectors in parallel.
cudaError_t cudaStatus = launchCuda(c, a, b, size);
if (cudaStatus != cudaSuccess) {
fprintf(stderr, "addWithCuda failed!");
return 1;
}
for (int i = 0; i < size; ++i)
{
answer[i] = c[i];
}
//printf("{1,2,3,4,5} + {10,20,30,40,50} = {%d,%d,%d,%d,%d}\n",
// c[0], c[1], c[2], c[3], c[4]);
// cudaDeviceReset must be called before exiting in order for profiling and
// tracing tools such as Nsight and Visual Profiler to show complete traces.
cudaStatus = cudaDeviceReset();
if (cudaStatus != cudaSuccess) {
fprintf(stderr, "cudaDeviceReset failed!");
return 1;
}
return 0;
}
bool loadInput(char *path, float **A, float *B, int &size)
{
return true;
}
void algorithm(int *c, int *a, int *b, size_t size)
{
Bl1<<<1, size>>>(c, a, b);
}
// Helper function for using CUDA to add vectors in parallel.
cudaError_t launchCuda(int *c, const int *a, const int *b, size_t size)
{
int *dev_a = 0;
int *dev_b = 0;
int *dev_c = 0;
cudaError_t cudaStatus;
// Choose which GPU to run on, change this on a multi-GPU system.
cudaStatus = cudaSetDevice(0);
if (cudaStatus != cudaSuccess) {
fprintf(stderr, "cudaSetDevice failed! Do you have a CUDA-capable GPU installed?");
goto Error;
}
// Allocate GPU buffers for three vectors (two input, one output) .
cudaStatus = cudaMalloc((void**)&dev_c, size * sizeof(int));
if (cudaStatus != cudaSuccess) {
fprintf(stderr, "cudaMalloc failed!");
goto Error;
}
cudaStatus = cudaMalloc((void**)&dev_a, size * sizeof(int));
if (cudaStatus != cudaSuccess) {
fprintf(stderr, "cudaMalloc failed!");
goto Error;
}
cudaStatus = cudaMalloc((void**)&dev_b, size * sizeof(int));
if (cudaStatus != cudaSuccess) {
fprintf(stderr, "cudaMalloc failed!");
goto Error;
}
// Copy input vectors from host memory to GPU buffers.
cudaStatus = cudaMemcpy(dev_a, a, size * sizeof(int), cudaMemcpyHostToDevice);
if (cudaStatus != cudaSuccess) {
fprintf(stderr, "cudaMemcpy failed!");
goto Error;
}
cudaStatus = cudaMemcpy(dev_b, b, size * sizeof(int), cudaMemcpyHostToDevice);
if (cudaStatus != cudaSuccess) {
fprintf(stderr, "cudaMemcpy failed!");
goto Error;
}
// Launch a kernel on the GPU with one thread for each element.
algorithm(dev_c, dev_a, dev_b, size);
// cudaDeviceSynchronize waits for the kernel to finish, and returns
// any errors encountered during the launch.
cudaStatus = cudaDeviceSynchronize();
if (cudaStatus != cudaSuccess) {
fprintf(stderr, "cudaDeviceSynchronize returned error code %d after launching addKernel!\n", cudaStatus);
goto Error;
}
// Copy output vector from GPU buffer to host memory.
cudaStatus = cudaMemcpy(c, dev_c, size * sizeof(int), cudaMemcpyDeviceToHost);
if (cudaStatus != cudaSuccess) {
fprintf(stderr, "cudaMemcpy failed!");
goto Error;
}
Error:
cudaFree(dev_c);
cudaFree(dev_a);
cudaFree(dev_b);
return cudaStatus;
}
|
8,995 |
#include <stdio.h>
#include <cuda_runtime.h>
__global__ void add (int a, int b, int *c) {
*c = a + b;
printf("into add");
}
int main(int argv, char** argc ) {
printf( "Hello, World!\n" );
int c;
int *device_c;
cudaMalloc((void**)&device_c, sizeof(int));
add<<<1, 1>>>(2, 7, device_c);
cudaMemcpy(&c, device_c, sizeof(int),
cudaMemcpyDeviceToHost);
printf("2 + 7 = %d\n", c);
cudaFree(device_c);
return 0;
}
|
8,996 | #include <stdio.h>
#include <limits.h>
__device__ static inline unsigned int argmin(unsigned int a, unsigned int b, unsigned int c)
{
if (a < b)
{
if (a < c)
return 0;
else
return 2;
}
if (b < c)
return 1;
else return 2;
}
__global__ void matching(int *D, unsigned int *phi, int m, int n)
{
// matrix m x n
int pnt = 2;
const int tid = threadIdx.x;// + blockDim.x * blockIdx.x;
if (tid < m)
{
int j = 0;
int reserve = -threadIdx.x + 1;
for (j = reserve; j < n; j++)
{
if (j >= 1){
int tmp[3] = {D[(tid * (n+1)) + j], D[(tid * (n+1)) + j + 1]+pnt, D[(tid+1)*(n+1)+j]+pnt};
int arg = argmin(tmp[0], tmp[1], tmp[2]);
int dmin = tmp[arg];
D[(tid+1)*(n+1)+j+1] = D[(tid+1)*(n+1)+j+1] + dmin;
phi[tid * n + j] = arg + 1;
}
__syncthreads();
}
}
}
// if (tid == 2){
// printf("j: %d\n", j);
// printf("idx: %d %d %d %d\n",(tid * (n+1)) + j + 1, (tid * (n+1)) + j + 2, (tid+1)*(n+1)+j+1, (tid+1)*(n+1)+j+2);
// printf("tmp: %d %d %d\n",D[(tid * (n+1)) + j], D[(tid * (n+1)) + j + 1], D[(tid+1)*(n+1)+j]);
// // printf("min: %d\n", tmp[arg]);
// printf("D[i+1][j+1]: %d\n", D[(tid+1)*(n+1)+j+1]);
// } |
8,997 | #include <stdio.h>
#include <math.h>
#include <stdlib.h>
#define MAX_ELEM_VALUE 10
#define N 8192
#define BLOCK_X 32
#define BLOCK_Y 32
int n_threads = 1024;
__global__ void transpose(float* mat, float *transp){
int index = threadIdx.x + blockIdx.x*blockDim.x;
int x = index%N;
int y = index/N;
transp[y*N+x] = mat[x*N+y];
}
__global__ void shared_transpose(float* mat, float *transp){
__shared__ double temp[BLOCK_X][BLOCK_Y+1];
int index_x = blockIdx.x * blockDim.x + threadIdx.x;
int index_y = blockIdx.y * blockDim.y + threadIdx.y;
temp[threadIdx.x][threadIdx.y] = mat[index_y * N + index_x];
__syncthreads();
transp[index_x * N + index_y] = temp[threadIdx.x][threadIdx.y];
}
void print_mat(float* mat){
int i, j;
for(i = 0; i < N; i++){
for(j = 0; j < N; j++)
printf("%f ",mat[i*N + j]);
printf("\n");
}
}
void randomly_fill_matrix(float *A)
{
for (unsigned int i = 0; i < N; i++)
{
for (unsigned int j = 0; j < N; j++)
{
A[i*N + j] = rand() % (2 * MAX_ELEM_VALUE) - MAX_ELEM_VALUE;
}
}
}
void normal_transpose(float *mat, float *transp)
{
for (unsigned int i = 0; i < N; i++)
for (unsigned int j = 0; j < N; j++)
transp[i +j*N] = mat[i*N + j];
}
int test(float *a, float *b)
{
for (unsigned int i = 0; i < N; i++){
for (unsigned int j = 0; j < N; j++){
if(b[i*N + j] != a[i*N + j])
return 0;
}
}
return 1;
}
int main(void){
float *mat, *transp1, *transp2, *test_mat;
float *dev_mat, *dev_transp1, *dev_transp2;
int size = N*N*sizeof(double);
cudaEvent_t start, stop;
dim3 grid, block;
block.x = BLOCK_X;
block.y = BLOCK_Y;
grid.x = N/BLOCK_X;
grid.y = N/BLOCK_Y;
cudaMalloc( (void**)&dev_mat, size );
cudaMalloc( (void**)&dev_transp1, size );
cudaMalloc( (void**)&dev_transp2, size );
mat = (float*)malloc(size);
transp1 = (float*)malloc(size);
transp2 = (float*)malloc(size);
test_mat = (float*)malloc(size);
randomly_fill_matrix(mat);
//print_mat(mat);
normal_transpose(mat, test_mat);
//----------//
cudaEventCreate(&start);
cudaEventCreate(&stop);
cudaMemcpy(dev_mat, mat, size, cudaMemcpyHostToDevice );
//-------------//
cudaEventRecord(start);
transpose<<< (N*N)/n_threads, n_threads >>>(dev_mat, dev_transp1);
cudaEventRecord(stop);
cudaEventSynchronize(stop);
float time = 0;
cudaEventElapsedTime(&time, start, stop);
cudaMemcpy(transp1, dev_transp1, size, cudaMemcpyDeviceToHost);
printf("%d %f ", n_threads, time);
//-------------//
cudaEventRecord(start);
shared_transpose<<< grid , block >>>(dev_mat, dev_transp2);
cudaEventRecord(stop);
cudaEventSynchronize(stop);
time = 0;
cudaEventElapsedTime(&time, start, stop);
cudaMemcpy(transp2, dev_transp2, size, cudaMemcpyDeviceToHost);
printf("%f ", n_threads, time);
if(test(transp1, test_mat)) printf("correct naive ");
else printf("not correct naive ");
if(test(transp2, test_mat)) printf("correct shared\n");
else printf("not correct shared\n");
//-------------//
free(transp1); cudaFree(dev_transp1);
free(transp2); cudaFree(dev_transp2);
free(mat); cudaFree(dev_mat);
return 0;
}
|
8,998 | float h_A[]= {
0.9216671137735739, 0.9259668865552235, 0.529123634423551, 0.8139788790699016, 0.7667188580252835, 0.6234550692398635, 0.955397987834083, 0.820606072273355, 0.9747061244685017, 0.5449702555130261, 0.6805020971641711, 0.9497025422008357, 0.916780885019636, 0.8645539840766937, 0.8372153538679408, 0.9210798097887585, 0.6595966859568572, 0.7438568195279243, 0.6568512551894685, 0.8097578195479649, 0.9271535983770643, 0.6225497080406767, 0.6873301194093778, 0.6165056765248539, 0.8847068122982977, 0.7582141469711399, 0.7395767647465418, 0.6611136441137175, 0.9321300700185404, 0.6419739391654381, 0.5436808070646744, 0.5257441567517374, 0.6706684093062416, 0.7943614601884345, 0.9445448811114667, 0.5312288371931326, 0.8973316812303838, 0.8285475251020219, 0.7693197108835361, 0.7692744370710647, 0.8397756880782328, 0.9703134985681496, 0.8687405941754177, 0.9363545857880495, 0.9971404633836063, 0.9207732759728204, 0.8356686979855378, 0.8314220262500929, 0.547744432464938, 0.7759442960879432, 0.5263370782925765, 0.6803881976025952, 0.627475904047562, 0.7064388760240781, 0.6000810643243775, 0.9265503671339475, 0.5531206395588608, 0.887921048121384, 0.9010937444937734, 0.5222886419208206, 0.5408002622709964, 0.7157656389351329, 0.5534566516358301, 0.9874200627165446, 0.902134078950197, 0.9810895696041988, 0.5049801008537993, 0.8630281218547906, 0.5553828576975883, 0.7370295178258517, 0.9717126354169827, 0.6784222509046566, 0.6606141613167389, 0.7945288835244577, 0.5932746738017876, 0.579526427543219, 0.545635777066586, 0.821650045836283, 0.5878948697864732, 0.878825744943236, 0.7025796047455404, 0.661734297988421, 0.7242959957669841, 0.9445216605562303, 0.5862038606389584, 0.989491515003887, 0.5468072240497905, 0.9108474255881974, 0.9183192993991219, 0.8776473473897614, 0.8945740763574814, 0.8603233887156332, 0.5112918003847812, 0.7260404448534639, 0.9591112748672374, 0.5204596294799271, 0.7100385315722304, 0.5875454200982264, 0.520802987034169, 0.8215246387542896, 0.8684118875071221, 0.6509443952099467, 0.8134680830432439, 0.8291182949363824, 0.5415536691807257, 0.9293060891204017, 0.7357379484063507, 0.5134029010619998, 0.9065767834173741, 0.8889754524883648, 0.885554902534046, 0.8135773114746045, 0.7507035933733358, 0.5284169643697278, 0.7187493248530583, 0.7424576920280601, 0.5450304533254877, 0.5216399995240176, 0.7265275079522786, 0.9692646488347687, 0.5140448906837614, 0.6930188605704032, 0.5555224592587304, 0.6196737179149066, 0.7195427098268359, 0.7265524586466348, 0.875509488610236, 0.8716799654144672, 0.6937948496109221, 0.6092611535767769, 0.9575060269956277, 0.7930928096830722, 0.7430820800080244, 0.5648397020331211, 0.8163789560504975, 0.6536467088410594, 0.5667497711557377, 0.7536364909472333, 0.5092390071313797, 0.9782514793147645, 0.87301224200337, 0.6829247934029222, 0.9875506720579211, 0.7800669791854336, 0.5798425246214773, 0.6191230385752904, 0.787236650392571, 0.7164397555074665, 0.6677423724617377, 0.6634329991787249, 0.8789784075550298, 0.9692840871528745, 0.8109734658789058, 0.7401964749116179, 0.7134218759037075, 0.9764613662058619, 0.5297657139330443, 0.843031744454393, 0.7699392321560388, 0.9583443082091971, 0.7210666788283511, 0.5945747308328897, 0.7655611313797848, 0.8449268833421848, 0.7998900801072616, 0.9830499597490183, 0.6036895091322468, 0.738989585187496, 0.5895632014670855, 0.8613121714427324, 0.9919103539094855, 0.593438313175546, 0.7431973473569677, 0.5103158472741681, 0.8427014740106553, 0.7620666948473269, 0.5799523202442651, 0.6042796044936183, 0.9946302252046653, 0.501587392583402, 0.8471604574733634, 0.782111312383675, 0.7952005764441605, 0.6795735350900232, 0.8648981997895826, 0.7865921304660962, 0.5583183347803565, 0.7905854430937097, 0.5882550932626784, 0.8994313977567083, 0.5609909688264463, 0.7922913314087107, 0.7859382327481339, 0.6717845610807968, 0.5424367397651949, 0.7164827557302551, 0.8335159492427666, 0.9585170430237094, 0.9293006772505201, 0.9817072734800205, 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0.8708221800568803, 0.5972919627664417, 0.9691132990283955, 0.695485429463514, 0.7640371125167134, 0.9072009780844209, 0.5718691359262729, 0.7867451976664088, 0.721095040313823, 0.8369326333072787, 0.6380336990196198, 0.7399092576875842, 0.6736624729894246, 0.7924547270226392, 0.55868469076503, 0.9591190933591147, 0.6714667829676866, 0.9842869874592254, 0.5411637199805095, 0.6568275721223935, 0.7474251946105642, 0.7572459610394608, 0.9817734897169774, 0.810208117235583, 0.8408891288269975, 0.8249510961398214, 0.7396111830302783, 0.680272212771687, 0.7442733965418862, 0.5788584482993259, 0.7273229060598572, 0.8161104312641383, 0.7903584006399587, 50000.0, 50000.0, 50000.0, 50000.0, 50000.0, 50000.0, 50000.0, 50000.0, 50000.0, 50000.0, 50000.0, 50000.0, 50000.0, 50000.0, 50000.0};
int h_B[]= {
0, 2, 4, 6, 8, 10, 12, 14, 18, 20, 22, 24, 26, 28, 30, 32, 34, 36, 38, 40, 42, 44, 47, 49, 51, 53, 56, 58, 60, 62, 64, 66, 68, 70, 73, 75, 77, 79, 81, 83, 85, 87, 93, 95, 97, 99, 101, 103, 105, 107, 109, 111, 113, 115, 117, 119, 121, 123, 125, 127, 129, 131, 133, 135, 137, 139, 141, 143, 145, 147, 149, 151, 153, 155, 157, 159, 161, 163, 165, 167, 170, 172, 174, 176, 178, 180, 182, 184, 186, 188, 190, 192, 194, 196, 198, 200, 203, 205, 207, 209, 211, 213, 215, 217, 219, 221, 223, 225, 227, 229, 231, 233, 235, 237, 239, 241, 243, 245, 247, 249, 251, 253, 255, 257, 259, 261, 263, 265, 267, 269, 271, 273, 275, 277, 279, 281, 283, 285, 287, 289, 291, 293, 296, 298, 300, 302, 304, 306, 308, 310, 312, 314, 316, 318, 320, 322, 324, 326, 328, 330, 332, 334, 336, 338, 340, 342, 344, 346, 348, 350, 352, 354, 356, 358, 360, 362, 364, 366, 368, 370, 372, 374, 376, 378, 380, 382, 384, 386, 388, 390, 392, 394, 397, 399, 401, 403, 405, 407, 409, 411, 413, 415, 417, 419, 421, 423, 425, 427, 429, 431, 433, 435, 437, 439, 441, 443, 445, 447, 449, 451, 453, 455, 457, 459, 461, 463, 465, 467, 469, 471, 473, 475, 477, 479, 481, 483, 486, 488, 491, 493, 495, 497, 499, 501, 503, 505, 507, 509, 512, 514, 516, 518, 521, 523, 525, 527, 529, 531, 533, 535, 537, 539, 541, 543, 545, 547, 549, 551, 553, 555, 557, 559, 561, 563, 565, 567, 569, 571, 573, 575, 577, 579, 581, 583, 585, 587, 589, 591, 593, 595, 597, 599, 601, 603, 605, 607, 609, 611, 614, 616, 618, 620, 622, 624, 626, 628, 630, 632, 634, 636, 638, 640, 642, 644, 648, 650, 652, 654, 656, 658, 660, 662, 664, 666, 668, 670, 672, 674, 676, 678, 682, 684, 686, 688, 691, 693, 695, 697, 699, 701, 703, 705, 707, 709, 711, 713, 715, 717, 719, 721, 723, 725, 727, 729, 731, 733, 735, 737, 739, 741, 743, 745, 747, 749, 751, 753, 755, 757, 759, 761, 763, 765, 767, 769, 771, 773, 775, 777, 779, 781, 783, 785, 787, 789, 791, 793, 795, 797, 799, 801, 803, 805, 807, 809, 811, 813, 817, 819, 821, 823, 825, 827, 829, 831, 833, 835, 837, 839, 841, 843, 845, 847, 849, 851, 853, 855, 857, 859, 861, 863, 865, 867, 869, 871, 873, 875, 877, 879, 881, 883, 885, 887, 889, 891, 893, 895, 897, 899, 901, 903, 905, 907, 909, 911, 913, 915, 917, 919, 921, 923, 925, 927, 929, 931, 933, 935, 937, 939, 941, 943, 947, 949, 951, 953, 955, 957, 959, 961, 963, 965, 967, 969, 972, 974, 976, 978, 980, 982, 984, 986, 988, 990, 992, 994, 996, 998, 1000, 1002, 1004, 1006, 1008, 1010, 1018, 1020, 1022, 1024, 1026, 1028, 1030, 1032, 1034, 1036, 1038, 1040, 1045, 1047, 1050, 1052, 1054, 1056, 1059, 1061, 1064, 1066, 1068, 1070, 1072, 1074, 1076, 1078, 1080, 1082, 1084, 1086, 1088, 1090, 1092, 1094, 1096, 1098, 1100, 1102, 1104, 1106, 1108, 1110, 1112, 1114, 1116, 1118, 1120, 1122, 1124, 1126, 1128, 1130, 1132, 1134, 1137, 1139, 1141, 1143, 1145, 1147, 1149, 1151, 1153, 1155, 1158, 1160, 1163, 1165, 1167, 1169, 1172, 1174, 1176, 1178, 1180, 1182, 1184, 1186, 1188, 1190, 1192, 1194, 1196, 1198, 1200, 1202, 1205, 1207, 1210, 1212, 1214, 1216, 1219, 1221, 1223, 1225, 1227, 1229, 1231, 1233, 1235, 1237, 1239, 1241, 1244, 1246, 1248, 1250, 1253, 1255, 1258, 1260, 1263, 1265, 1268, 1270, 1273, 1275, 1277, 1279, 1281, 1283, 1286, 1288, 1291, 1293, 1296, 1298, 1301, 1303, 1306, 1308, 1311, 1313, 1316, 1318, 1321, 1323, 1326, 1328, 1331, 1333, 1335, 1337, 1339, 1341, 1343, 1345, 1348, 1350, 1353, 1355, 1361, 1363, 1365, 1367, 1369, 1371, 1374, 1376, 1378, 1380, 1382, 1384, 1387, 1389, 1391, 1393, 1396, 1398, 1401, 1403, 1409, 1411, 1413, 1415, 1417, 1419, 1421, 1423, 1425, 1427, 1430, 1432, 1435, 1437, 1439, 1441, 1443, 1445, 1448, 1450, 1453, 1455, 1457, 1459, 1461, 1463, 1466, 1468, 1471, 1473, 1476, 1478, 1481, 1483, 1486, 1488, 1491, 1493, 1496, 1498, 1501, 1503, 1506, 1508, 1511, 1513, 1516, 1518, 1520, 1522, 1525, 1527, 1530, 1532, 1538, 1540, 1542, 1544, 1546, 1548, 1551, 1553, 1556, 1558, 1561, 1563, 1566, 1568, 1570, 1572, 1574, 1576, 1578, 1580, 1582, 1584, 1586, 1588, 1590, 1592, 1594, 1596, 1598, 1600, 1602, 1604, 1606, 1608, 1610, 1612, 1614, 1616, 1618, 1620, 1622, 1624, 1626, 1628, 1630, 1632, 1634, 1636, 1639, 1641, 1643, 1645, 1648, 1650, 1652, 1654, 1656, 1658, 1660, 1662, 1664, 1666, 1668, 1670, 1672, 1674, 1676, 1678, 1680, 1682, 1684, 1686, 1688, 1690, 1692, 1694, 1696, 1698, 1700, 1702, 1704, 1706, 1708, 1710, 1712, 1714, 1716, 1718, 1720, 1722, 1724, 1726, 1728, 1730, 1732, 1734, 1736, 1738, 1740, 1742, 1744, 1746, 1748, 1750, 1752, 1754, 1756, 1758, 1760, 1762, 1764, 1766, 1768, 1770, 1772, 1774, 1776, 1778, 1780, 1782, 1784, 1786, 1788, 1790, 1792, 1794, 1796, 1798, 1800, 1802, 1804, 1806, 1809, 1811, 1813, 1815, 1817, 1819, 1821, 1823, 1825, 1827, 1829, 1831, 1833, 1835, 1839, 1841, 1843, 1845, 1847, 1849, 1851, 1853, 1855, 1857, 1859, 1861, 1863, 1865, 1867, 1869, 1871, 1873, 1875, 1877, 1880, 1882, 1884, 1886, 1888, 1890, 1893, 1895, 1898, 1900, 1903, 1905, 1908, 1910, 1912, 1914, 1917, 1919, 1921, 1923, 1926, 1928, 1932, 1934, 1936, 1938, 1940, 1942, 1944, 1946, 1948, 1950, 1952, 1954, 1956, 1958, 1960, 1962, 1964, 1966, 1968, 1970, 1973, 1975, 1978, 1980, 1983, 1985, 1988, 1990, 1993, 1995, 1997, 1999, 2002, 2004, 2007, 2009, 2014, 2016, 2019, 2021, 2024, 2026, 2029, 2031, 2034, 2036, 2039, 2041, 2044, 2046, 2048, 2050, 2052, 2054, 2057, 2059, 2062, 2064, 2066, 2068, 2071, 2073, 2075, 2077, 2079, 2081, 2083, 2085, 2087, 2089, 2092, 2094, 2099, 2101, 2104, 2106, 2109, 2111, 2113, 2115, 2117, 2119, 2121, 2123, 2125, 2127, 2129, 2131, 2133, 2135, 2137, 2139, 2141, 2143, 2145, 2147, 2149, 2151, 2153, 2155, 2157, 2159, 2161, 2163, 2165, 2167, 2170, 2172, 2174, 2176, 2179, 2181, 2184, 2186, 2192, 2194, 2196, 2198, 2200, 2202, 2205, 2207, 2210, 2212, 2215, 2217, 2220, 2222, 2224, 2226, 2228, 2230, 2233, 2235, 2238, 2240, 2243, 2245, 2248, 2250, 2253, 2255, 2262, 2264, 2266, 2268, 2270, 2272, 2274, 2276, 2279, 2281, 2284, 2286, 2292, 2294, 2296, 2298, 2301, 2303, 2306, 2308, 2317, 2319, 2322, 2324, 2327, 2329, 2332, 2334, 2337, 2339, 2343, 2345, 2347, 2349, 2352, 2354, 2356, 2358, 2360, 2362, 2364, 2366, 2368, 2370, 2372, 2374, 2376, 2378, 2380, 2382, 2384, 2386, 2388, 2390, 2392, 2394, 2396, 2398, 2400, 2402, 2404, 2406, 2408, 2410, 2412, 2414, 2416, 2418, 2420, 2422, 2424, 2426, 2428, 2430, 2432, 2434, 2436, 2438, 2441, 2443, 2445, 2447, 2450, 2452, 2454, 2456, 2458, 2460, 2462, 2464, 2466, 2468, 2470, 2472, 2474, 2476, 2479, 2481, 2483, 2485, 2487, 2489, 2491, 2493, 2495, 2497, 2499, 2501, 2503, 2505, 2507, 2509, 2512, 2514, 2516, 2518, 2520, 2522, 2524, 2526, 2528, 2530, 2533, 2535, 2537, 2539, 2541, 2543, 2545, 2547, 2549, 2551, 2553, 2555, 2557, 2559, 2561, 2563, 2566, 2568, 2570, 2572, 2574, 2576, 2578, 2580, 2582, 2584, 2586, 2588, 2590, 2592, 2594, 2596, 2598, 2600, 2602, 2604, 2606, 2608, 2610, 2612, 2614, 2616, 2618, 2620, 2622, 2624, 2626, 2628, 2630, 2632, 2634, 2636, 2638, 2640, 2642, 2644, 2646, 2648, 2650, 2652, 2654, 2656, 2658, 2660, 2662, 2664, 2666, 2668, 2670, 2672, 2674, 2676, 2678, 2680, 2682, 2684, 2686, 2688, 2690, 2692, 2694, 2696, 2699, 2701, 2703, 2705, 2708, 2710, 2712, 2714, 2716, 2718, 2720, 2722, 2724, 2726, 2729, 2731, 2734, 2736, 2738, 2740, 2742, 2744, 2746, 2748, 2750, 2752, 2754, 2756, 2759, 2761, 2763, 2765, 2767, 2769, 2771, 2773, 2776, 2778, 2780, 2782, 2785, 2787, 2789, 2791, 2793, 2795, 2797, 2799, 2801, 2803, 2805, 2807, 2810, 2812, 2814, 2816, 2819, 2821, 2823, 2825, 2827, 2829, 2831, 2833, 2835, 2837, 2840, 2842, 2844, 2846, 2848, 2850, 2852, 2854, 2856, 2858, 2861, 2863, 2865, 2867, 2869, 2871, 2873, 2875, 2877, 2879, 2881, 2883, 2885, 2887, 2889, 2891, 2893, 2895, 2898, 2900, 2903, 2905, 2908, 2910, 2913, 2915, 2917, 2919, 2921, 2923, 2926, 2928, 2931, 2933, 2935, 2937, 2940, 2942, 2945, 2947, 2950, 2952, 2954, 2956, 2958, 2960, 2963, 2965, 2967, 2969, 2971, 2973, 2976, 2978, 2980, 2982, 2984, 2986, 2989, 2991, 2994, 2996, 2999, 3001, 3005, 3007, 3009, 3011, 3015, 3017, 3019, 3021, 3023, 3025, 3028, 3030, 3033, 3035, 3038, 3040, 3043, 3045, 3048, 3050, 3053, 3055, 3061, 3063, 3065, 3067, 3069, 3071, 3073, 3075, 3077, 3079, 3081, 3083, 3085, 3087, 3089, 3091, 3093, 3095, 3097, 3099, 3101, 3103, 3105, 3107, 3109, 3111, 3114, 3116, 3118, 3120, 3122, 3124, 3126, 3128, 3130, 3132, 3134, 3136, 3139, 3141, 3145, 3147, 3150, 3152, 3155, 3157, 3160, 3162, 3165, 3167, 3170, 3172, 3175, 3177, 3180, 3182, 3184, 3186, 3188, 3190, 3193, 3195, 3198, 3200, 3203, 3205, 3208, 3210, 3212, 3214, 3216, 3218, 3221, 3223, 3226, 3228, 3231, 3233, 3236, 3238, 3241, 3243, 3246, 3248, 3251, 3253, 3256, 3258, 3261, 3263, 3269, 3271, 3274, 3276, 3279, 3281, 3284, 3286, 3291, 3293, 3295, 3297, 3299, 3301, 3303, 3305, 3307, 3309, 3311, 3313, 3316, 3318, 3320, 3322, 3325, 3327, 3329, 3331, 3333, 3335, 3337, 3339, 3341, 3343, 3345, 3347, 3350, 3352, 3355, 3357, 3359, 3361, 3364, 3366, 3369, 3371, 3374, 3376, 3379, 3381, 3384, 3386, 3389, 3391, 3394, 3396, 3399, 3401, 3404, 3406, 3409, 3411, 3414, 3416, 3419, 3421, 3424, 3426, 3428, 3430, 3433, 3435, 3437, 3439, 3442, 3444, 3448, 3450, 3452, 3454, 3456, 3458, 3460, 3462, 3464, 3466, 3469, 3471, 3473, 3475, 3480, 3482, 3484, 3486, 3488, 3490, 3493, 3495, 3498, 3500, 3503, 3505, 3508, 3510, 3512, 3514, 3516, 3518, 3521, 3523, 3525, 3527, 3530, 3532, 3535, 3537, 3542, 3544, 3546, 3548, 3554, 3556, 3558, 3560, 3562, 3564, 3566, 3568, 3570, 3572, 3574, 3576, 3580, 3582, 3584, 3586, 3588, 3590, 3592, 3594, 3596, 3598, 3601, 3603, 3605, 3607, 3609, 3611, 3613, 3615, 3617, 3619, 3623, 3625, 3628, 3630, 3632, 3634, 3637, 3639, 3641, 3643, 3647, 3649, 3651, 3653, 3656, 3658, 3660, 3662, 3665, 3667, 3670, 3672, 3674, 3676, 3678, 3680, 3682, 3684, 3686, 3688, 3690, 3692, 3694, 3696, 3698, 3700, 3702, 3704, 3706, 3708, 3710, 3712, 3714, 3716, 3719, 3721, 3723, 3725, 3727, 3729, 3731, 3733, 3735, 3737, 3739, 3741, 3743, 3745, 3747, 3749, 3752, 3754, 3757, 3759, 3762, 3764, 3767, 3769, 3772, 3774, 3777, 3779, 3782, 3784, 3787, 3789, 3792, 3794, 3797, 3799, 3802, 3804, 3808, 3810, 3812, 3814, 3817, 3819, 3822, 3824, 3827, 3829, 3832, 3834, 3837, 3839, 3841, 3843, 3845, 3847, 3849, 3851, 3854, 3856, 3858, 3860, 3863, 3865, 3869, 3871, 3873, 3875, 3878, 3880, 3883, 3885, 3888, 3890, 3893, 3895, 3897, 3899, 3901, 3903, 3905, 3907, 3909, 3911, 3913, 3915, 3917, 3919, 3921, 3923, 3925, 3927, 3929, 3931, 3933, 3935, 3937, 3939, 3941, 3943, 3945, 3947, 3949, 3951, 3953, 3955, 3958, 3960, 3963, 3965, 3967, 3969, 3971, 3973, 3975, 3977, 3979, 3981, 3983, 3985, 3987, 3989, 3991, 3993, 3995, 3997, 3999, 4001, 4003, 4005, 4007, 4009, 4011, 4013, 4016, 4018, 4020, 4022, 4024, 4026, 4028, 4030, 4032, 4034, 4036, 4038, 4040, 4042, 4044, 4046, 4048, 4050, 4052, 4054, 4056, 4058, 4060, 4062, 4064, 4066, 4068, 4070, 4072, 4074, 4076, 4078, 4080, 4082, 4084, 4086, 4088, 4090, 4092, 4094, 4096, 4098, 4100, 4102, 4104, 4106, 4108, 4110, 4112, 4114, 4116, 4118, 4120, 4122, 4124, 4126, 4128, 4130, 4132, 4134, 4136, 4138, 4140, 4142, 4144, 4146, 4148, 4150, 4152, 4154, 4156, 4158, 4160, 4162, 4164, 4166, 4168, 4170, 4172, 4174, 4176, 4178, 4181, 4183, 4185, 4187, 4189, 4191, 4193, 4195, 4197, 4199, 4201, 4203, 4205, 4207, 4209, 4211, 4213, 4215, 4217, 4219, 4221, 4223, 4225, 4227, 4229, 4231, 4233, 4235, 4237, 4239, 4241, 4243, 4246, 4248, 4250, 4252, 4254, 4256, 4258, 4260, 4262, 4264, 4266, 4268, 4270, 4272, 4274, 4276, 4278, 4280, 4282, 4284, 4286, 4288, 4290, 4292, 4294, 4296, 4298, 4300, 4302, 4304, 4306, 4308, 4310, 4312, 4314, 4316, 4318, 4320, 4322, 4324, 4326, 4328, 4330, 4332, 4335, 4337, 4339, 4341, 4344, 4346, 4348, 4350, 4353, 4355, 4357, 4359, 4361, 4363, 4366, 4368, 4371, 4373, 4376, 4378, 4380, 4382, 4384, 4386, 4389, 4391, 4393, 4395, 4397, 4399, 4402, 4404, 4407, 4409, 4412, 4414, 4417, 4419, 4421, 4423, 4433, 4435, 4438, 4440, 4446, 4448, 4450, 4452, 4454, 4456, 4459, 4461, 4464, 4466, 4469, 4471, 4474, 4476, 4479, 4481, 4484, 4486, 4489, 4491, 4494, 4496, 4499, 4501, 4504, 4506, 4509, 4511, 4514, 4516, 4518, 4520, 4522, 4524, 4527, 4529, 4532, 4534, 4537, 4539, 4542, 4544, 4546, 4548, 4550, 4552, 4554, 4556, 4558, 4560, 4562, 4564, 4566, 4568, 4570, 4572, 4574, 4576, 4578, 4580, 4582, 4584, 4586, 4588, 4590, 4592, 4594, 4596, 4598, 4600, 4602, 4604, 4607, 4609, 4611, 4613, 4615, 4617, 4619, 4621, 4624, 4626, 4628, 4630, 4632, 4634, 4636, 4638, 4642, 4644, 4646, 4648, 4651, 4653, 4656, 4658, 4664, 4666, 4669, 4671, 4677, 4679, 4682, 4684, 4690, 4692, 4694, 4696, 4699, 4701, 4703, 4705, 4709, 4711, 4713, 4715, 4717, 4719, 4721, 4723, 4725, 4727, 4729, 4731, 4734, 4736, 4738, 4740, 4742, 4744, 4746, 4748, 4752, 4754, 4756, 4758, 4760, 4762, 4764, 4766, 4768, 4770, 4772, 4774, 4778, 4780, 4782, 4784, 4787, 4789, 4792, 4794, 4800, 4802, 4805, 4807, 4810, 4812, 4815, 4817, 4819, 4821, 4823, 4825, 4828, 4830, 4832, 4834, 4836, 4838, 4841, 4843, 4846, 4848, 4851, 4853, 4856, 4858, 4860, 4862, 4864, 4866, 4869, 4871, 4873, 4875, 4877, 4879, 4881, 4883, 4885, 4887, 4890, 4892, 4895, 4897, 4900, 4902, 4904, 4906, 4908, 4910, 4912, 4914, 4916, 4918, 4920, 4922, 4924, 4926, 4928, 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20915, 20913, 23202, 20958, 19390, 19389, 19388, 20958, 19390, 19389, 20973, 20974, 8430, 23347, 20982, 8485, 8485, 23334, 20993, 8430, 23268, 23278, 23290, 24289, 24290, 23291, 23301, 8430, 23316, 23322, 23334, 23353, 8485, 23721, 23719, 23676, 23738, 19546, 19545, 19544, 19543, 19546, 19545, 19544, 19543, 19546, 19545, 21250, 21248, 19560, 19559, 23391, 19638, 23404, 23410, 19638, 24053, 24051, 24059, 21250, 21248, 19560, 19559, 19560, 19559, 23472, 23470, 23691, 23695, 23711, 23713, 23712, 23480, 23478, 23498, 23496, 19546, 19545, 21250, 21248, 23822, 23543, 23547, 23545, 23552, 23556, 23554, 23565, 23580, 24291, 24292, 24293, 24294, 19480, 19479, 24295, 24296, 19506, 19505, 24297, 24298, 23668, 23666, 23673, 23691, 23695, 23711, 23713, 23712, 23676, 23738, 19546, 19545, 23691, 23695, 23711, 23713, 23712, 23721, 23719, 23738, 23736, 19546, 19545, 21533, 21531, 19560, 19559, 23777, 23803, 19560, 19559, 23822, 21625, 21623, 23843, 19619, 19619, 24201, 23884, 24219, 24216, 24299, 24201, 23884, 24219, 24216, 24302, 24304, 24306, 24308, 23892, 19638, 23908, 21733, 19600, 19599, 24120, 24117, 24127, 24125, 21760, 21758, 24120, 24117, 21782, 21780, 24127, 23970, 23972, 23989, 23987, 24008, 24012, 24010, 24014, 24017, 24015, 24311, 24313, 24315, 24317, 24319, 24023, 19638, 24037, 19638, 24053, 24051, 24059, 24095, 24094, 24127, 24125, 24133, 24160, 24323, 24325, 24327, 24165, 24180, 24178, 24203, 24207, 24205, 24227, 24331, 24333, 24335, 24337, 24339, 24340, 24341, 24342, 24343, 24344, 24345, 24348, 24349, 24350, 24351, 22114, 22112, 24352, 24353, 22114, 22112, 24354, 24355, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 25092, 22725, 22728, 24576, 24578, 22144, 20435, 19729, 22749, 22147, 19054, 19735, 19057, 25093, 25094, 25095, 25096, 25097, 24463, 23381, 22150, 25098, 24849, 19544, 19543, 19065, 19557, 22155, 19065, 19557, 22155, 24463, 19067, 19558, 22158, 24849, 19067, 19558, 22159, 25099, 25100, 19752, 19753, 22164, 19757, 22183, 22167, 22170, 22173, 19658, 19657, 22183, 22180, 22186, 22192, 22189, 22195, 22198, 25101, 25102, 25103, 25104, 24470, 22202, 22201, 25106, 25107, 25108, 25109, 25110, 25111, 25112, 25113, 25114, 25115, 25116, 25117, 25118, 24387, 20817, 24722, 19377, 19376, 24478, 23179, 23182, 23155, 23188, 23191, 22212, 22209, 24513, 24508, 22546, 22543, 23122, 22969, 24673, 25121, 25122, 25123, 25124, 25125, 25126, 25127, 19372, 25128, 22216, 22215, 25129, 25130, 25131, 22523, 22520, 25132, 20786, 20783, 19377, 19376, 24478, 23179, 23182, 23185, 23188, 22222, 24512, 19092, 22535, 22532, 24516, 24478, 23182, 23185, 23188, 22222, 19093, 22223, 22222, 25133, 24672, 24726, 23179, 20786, 20783, 23185, 23182, 25134, 25135, 23083, 23002, 20915, 20715, 24735, 23122, 22224, 25136, 25137, 25138, 25139, 25140, 25141, 25142, 25143, 25144, 25145, 25146, 24672, 20685, 25147, 25148, 25149, 20786, 20783, 19376, 19377, 24726, 23179, 23182, 23077, 25150, 25151, 23086, 23083, 20915, 20715, 24735, 20786, 20783, 19376, 19377, 23185, 23182, 25153, 25154, 23086, 23083, 20915, 20715, 24735, 24392, 22233, 24394, 22239, 24396, 24398, 19096, 19096, 19096, 19096, 24136, 24145, 22246, 24210, 24400, 22255, 25156, 19860, 19637, 24405, 22268, 25157, 19874, 25158, 24409, 22277, 19884, 22282, 19107, 19107, 19107, 19107, 25163, 22316, 24413, 24863, 22289, 24416, 25164, 22316, 24879, 25165, 25168, 25171, 21408, 19916, 19913, 25173, 25174, 24832, 24834, 23468, 19478, 19445, 25175, 21420, 19508, 19507, 21427, 21424, 21434, 21431, 19524, 21442, 21439, 23664, 25178, 25179, 25180, 23671, 25181, 22316, 24420, 24421, 25182, 22316, 24424, 24425, 25183, 25185, 25187, 24832, 25189, 19508, 19507, 20019, 25190, 25191, 25192, 23541, 25193, 25194, 25195, 23550, 25196, 25197, 24426, 24427, 25200, 23563, 23571, 23568, 24867, 24868, 25201, 23578, 23586, 23583, 25202, 24436, 23593, 24429, 24431, 23456, 23459, 25204, 23541, 25205, 25206, 25207, 23550, 25208, 25209, 25210, 24433, 24434, 23563, 25211, 25212, 23571, 23568, 24867, 24868, 25213, 23578, 23586, 23583, 25214, 24436, 23596, 24439, 24441, 22369, 22368, 21389, 21386, 21397, 21394, 21405, 21402, 21408, 21411, 21284, 25218, 25219, 24832, 24444, 19478, 19445, 23468, 25220, 19507, 19178, 19178, 19507, 19178, 19507, 19524, 19178, 19507, 23664, 25222, 25223, 25224, 23671, 24832, 24444, 19508, 19179, 19179, 19508, 19179, 19508, 19179, 19508, 25225, 25226, 21389, 21386, 21397, 21394, 21405, 21402, 21408, 21411, 21284, 25229, 25230, 24832, 24834, 23468, 19478, 19445, 25231, 19508, 19507, 20019, 21427, 21424, 21434, 21431, 19524, 21442, 21439, 23664, 25234, 25235, 25236, 23671, 25237, 25238, 23513, 19552, 19551, 20033, 20030, 22394, 22401, 19558, 19557, 19560, 19559, 22408, 22411, 22414, 24459, 22420, 24461, 22426, 24463, 24465, 25239, 24466, 25240, 24467, 25241, 25242, 23752, 19552, 19551, 24849, 19560, 19559, 23822, 24470, 24851, 19560, 19559, 23822, 22782, 22848, 22854, 22750, 22860, 19303, 19302, 19309, 19308, 24630, 19311, 19310, 24586, 25243, 24594, 24474, 22782, 22848, 22764, 22763, 22860, 19303, 19302, 19309, 19308, 24593, 25244, 24639, 24476, 22782, 22848, 22764, 22854, 19303, 19302, 22860, 19309, 19308, 24630, 19311, 19310, 24586, 25245, 24594, 24476, 19202, 19363, 20786, 20783, 19377, 19376, 24726, 23179, 23185, 23182, 19207, 19364, 24512, 22462, 22535, 22465, 25246, 20786, 20783, 19377, 19376, 24478, 23179, 23182, 23185, 19364, 19207, 24512, 22468, 22535, 22532, 24516, 24743, 20928, 20925, 24747, 23234, 23231, 25248, 25249, 23243, 23211, 19394, 19393, 23246, 25250, 19387, 24480, 20925, 20928, 24483, 23234, 23231, 25251, 25252, 22484, 22481, 23246, 19394, 19393, 25253, 19387, 24787, 24789, 23347, 24792, 24487, 24489, 25254, 20150, 20147, 25255, 20156, 21061, 24787, 21034, 20159, 23347, 24792, 22848, 22845, 22764, 22854, 24630, 19311, 19310, 22860, 19303, 19302, 19309, 19308, 24586, 25256, 24593, 25257, 24594, 24640, 22510, 22507, 24689, 24673, 25258, 25259, 25260, 19372, 24498, 20173, 22523, 22520, 20182, 19377, 19376, 23191, 23188, 24512, 24504, 22535, 22532, 24516, 24512, 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19302, 19309, 19308, 24630, 19311, 19310, 24593, 25303, 24594, 24640, 22782, 22848, 22854, 22787, 22860, 22857, 19309, 19308, 24630, 19311, 19310, 24634, 22879, 24637, 24638, 22848, 22782, 22787, 22854, 22860, 22857, 19309, 19308, 24630, 19311, 19310, 24634, 22879, 24637, 24638, 24599, 24601, 24603, 24605, 25304, 22811, 22808, 25305, 24609, 24611, 24613, 25306, 22831, 22828, 25307, 22848, 22845, 22854, 22851, 22860, 22857, 19309, 19308, 24630, 19311, 19310, 24634, 22879, 24637, 24638, 24639, 24640, 22848, 22845, 22854, 22851, 22860, 22857, 19309, 19308, 24630, 19311, 19310, 24634, 22879, 24637, 24638, 24639, 24640, 22896, 22893, 24643, 25308, 25309, 20598, 20604, 20601, 22915, 22912, 22920, 25310, 20618, 20625, 19337, 19336, 20631, 20628, 24656, 24657, 20641, 19337, 19336, 20647, 20644, 24662, 24663, 20659, 19337, 19336, 20665, 20662, 24669, 24670, 23122, 22969, 25311, 25312, 25313, 25314, 24672, 20768, 23108, 23105, 24707, 25315, 25316, 25317, 25318, 23122, 22969, 24673, 25319, 25320, 25321, 25322, 25323, 25324, 25325, 25326, 24672, 20685, 23122, 23125, 24673, 25327, 25328, 23125, 22982, 25329, 25330, 25331, 25332, 25333, 24722, 19376, 19377, 24726, 23179, 23182, 23077, 25334, 25335, 25336, 25337, 20715, 20915, 24682, 25338, 19376, 19377, 23179, 23182, 23077, 25339, 25340, 20715, 20915, 24682, 25341, 24722, 19376, 19377, 24726, 23179, 23182, 23185, 25342, 25343, 25344, 25345, 20715, 20915, 24682, 25346, 19377, 19376, 25347, 25348, 23083, 23086, 20915, 20913, 24682, 25349, 23023, 23020, 24710, 25350, 25351, 25352, 25353, 25354, 25355, 25356, 25357, 24686, 24688, 25358, 24689, 23108, 23105, 24707, 25359, 25360, 25361, 25362, 23122, 23125, 25363, 25364, 25365, 25366, 25367, 25368, 25369, 25370, 25371, 25372, 25373, 23054, 23051, 20768, 25374, 25375, 25376, 25377, 24695, 20866, 20786, 20783, 19377, 19376, 24726, 23179, 23182, 23077, 25378, 25379, 25380, 23086, 23083, 20915, 20913, 24735, 25381, 23092, 23091, 25382, 25383, 25384, 25385, 25386, 25387, 25388, 25389, 25390, 25391, 25392, 25393, 25394, 24714, 20817, 23108, 23105, 24707, 25395, 25396, 25397, 25398, 23125, 23122, 24710, 25399, 25400, 25401, 25402, 24711, 25403, 25404, 19372, 24714, 20866, 24722, 19377, 19376, 24726, 23179, 23182, 23155, 23191, 23160, 25405, 25406, 24722, 19377, 19376, 24726, 23179, 23185, 23182, 23191, 23188, 24733, 25407, 25408, 24735, 25409, 24743, 20928, 20925, 24747, 23234, 23231, 25410, 25411, 25412, 23243, 23211, 23246, 19394, 19393, 25413, 19387, 24743, 24745, 24747, 23234, 23231, 25414, 25415, 25416, 23243, 23240, 19394, 19393, 23246, 25417, 23309, 23306, 23359, 25418, 25419, 24787, 24789, 25420, 20981, 20978, 25421, 23359, 23356, 24758, 25422, 24760, 25423, 24782, 24784, 25424, 21074, 24787, 24789, 23347, 24792, 23309, 23306, 23359, 25425, 25426, 25427, 24762, 21005, 21002, 25428, 24766, 24768, 21018, 21031, 25429, 25430, 24782, 24784, 25432, 21074, 24771, 21034, 21031, 25433, 24774, 23309, 23306, 23310, 24777, 25434, 25435, 24779, 25436, 21061, 24782, 24784, 25437, 21074, 24787, 24789, 23347, 24792, 25438, 23359, 23356, 24796, 25439, 24921, 25440, 25441, 24797, 19544, 19543, 23734, 23731, 25442, 25443, 24798, 25444, 25445, 25446, 25447, 25448, 25449, 25450, 25451, 25452, 25453, 19557, 19557, 19557, 19558, 19558, 19558, 19429, 19551, 23774, 19551, 19429, 23381, 23382, 25454, 25455, 19430, 19552, 24849, 24851, 25456, 25457, 19552, 19430, 24802, 25458, 23389, 24805, 25459, 19637, 24808, 25460, 24810, 23413, 25461, 24813, 19637, 25462, 21164, 21161, 25463, 25464, 24818, 25465, 24820, 23435, 21178, 23440, 24825, 23447, 25466, 25467, 23513, 19552, 19551, 24849, 24827, 21554, 21551, 23767, 23774, 19558, 19557, 25468, 25469, 25470, 25471, 23459, 23456, 21411, 21284, 24832, 24834, 23468, 19478, 19445, 25472, 25473, 23686, 19532, 19531, 23689, 25474, 24912, 25475, 24913, 24915, 24916, 24918, 24919, 25476, 25477, 25478, 24836, 25479, 25480, 24838, 19544, 19543, 23494, 23491, 25481, 25482, 24844, 25483, 25484, 25485, 25486, 23513, 19552, 19551, 24849, 24851, 25487, 21269, 24854, 24856, 19446, 19445, 21284, 25488, 23541, 25489, 25490, 25491, 23550, 25492, 25493, 24862, 24863, 25494, 23563, 23571, 23568, 24867, 24868, 25495, 23578, 23586, 23583, 25496, 21343, 25498, 21350, 23596, 23593, 24877, 24879, 23610, 23607, 24883, 24884, 19478, 19477, 25500, 25501, 21389, 21386, 21397, 21394, 21405, 21402, 21408, 21411, 25504, 25505, 21420, 19508, 19507, 21427, 21424, 21434, 21431, 19524, 21442, 21439, 23664, 25508, 25509, 25510, 23671, 23686, 19532, 19531, 23689, 25511, 24912, 25512, 24913, 24915, 24916, 24918, 24919, 25513, 25514, 25515, 23675, 23734, 23731, 25516, 25517, 23679, 25518, 25519, 23686, 19532, 19531, 23689, 25520, 24912, 25521, 24913, 24915, 24916, 24918, 24919, 25522, 25523, 25524, 24921, 25525, 25526, 23724, 19544, 19543, 23734, 23731, 25527, 25528, 23741, 25529, 25530, 25531, 25532, 23752, 19552, 19551, 24932, 24934, 21554, 21551, 23767, 23774, 19558, 19557, 25533, 25534, 23814, 25535, 23820, 24941, 23783, 24943, 23789, 24946, 24948, 24950, 25536, 23809, 23806, 25537, 25538, 23814, 23817, 23820, 25539, 21618, 21615, 24958, 25540, 25541, 24959, 23838, 23835, 23841, 23846, 25542, 24965, 25543, 21653, 21650, 23861, 23858, 24971, 25544, 24973, 25545, 25546, 25547, 25548, 21675, 24976, 23881, 23957, 23960, 25550, 25551, 25552, 25553, 24979, 23895, 25558, 24982, 25559, 19637, 21707, 21704, 25560, 24987, 23915, 21719, 23920, 21906, 25046, 21728, 21725, 24999, 25561, 25562, 25563, 25000, 23933, 23930, 23936, 24114, 25564, 25565, 25059, 25566, 25567, 21753, 21750, 24999, 25568, 25569, 25000, 23957, 23954, 23960, 25005, 25570, 25571, 25572, 25573, 25574, 25575, 23975, 25576, 25008, 19619, 25011, 25577, 25578, 25013, 19620, 25016, 24002, 25019, 25579, 25580, 25581, 25582, 25583, 25584, 25021, 24026, 25590, 21843, 25591, 19637, 25026, 24040, 25592, 21858, 25593, 19637, 25031, 25594, 25595, 21875, 21872, 25596, 25035, 24066, 21887, 24071, 21893, 24076, 25042, 24083, 21906, 25046, 25048, 25597, 25598, 25049, 25050, 24107, 19656, 19655, 25055, 24114, 24120, 24117, 25059, 25599, 25600, 25061, 25601, 24139, 24136, 24142, 24148, 24145, 24151, 24154, 25602, 19658, 19657, 25606, 24163, 25073, 24172, 25076, 25607, 25608, 25078, 24187, 25081, 25083, 24201, 24198, 25609, 25610, 25611, 24213, 24210, 24219, 24216, 24222, 25612, 24225, 25275, 25275, 25617, 25619, 25621, 19691, 19692, 25623, 19692, 19691, 19681, 19682, 19682, 19681, 19691, 19692, 25160, 25624, 25162, 25626, 19692, 19691, 25275, 25277, 25549, 25554, 22083, 25557, 25585, 22093, 25588, 25589, 25628, 25629, 22117, 22120, 25605, 25630, 25632, 25633, 22120, 22117, 25616, 25634, 15, 25649, 25650, 25651, 25652, 25653, 25654, 25655, 25656, 25657, 25658, 25659, 25660, 25666, 25667, 25668, 25670, 25671, 25672, 25673, 25674, 25675, 25676, 25677, 25678, 25679, 25680, 25681, 25682, 25683, 25684, 25685, 25686, 25689, 25690, 25691, 25692, 25693, 25694, 25695, 25696, 25697, 25698, 25699, 25700, 25701, 25702, 25703, 25704, 25705, 25710, 25711, 25712, 25713, 25716, 25718, 25720, 25723, 25726, 25727, 25728, 25729, 25730, 25731, 25732, 25733, 25734, 25735, 25736, 25737, 25738, 25739, 25740, 25741, 25742, 25743, 25744, 25745, 25746, 25748, 25753, 25751, 25755, 25756, 25760, 25761, 25763, 25764, 25765, 25766, 25767, 25768, 25769, 25770, 25771, 25772, 25773, 25774, 25775, 25776, 25777, 25778, 25779, 25780, 25781, 25782, 25783, 25784, 25785, 25787, 25788, 25789, 25790, 25791, 25792, 25793, 25794, 25796, 25797, 25798, 25799, 25800, 25801, 25802, 25803, 25806, 25808, 25811, 25814, 25815, 25816, 25819, 25820, 25821, 25822, 25823, 25824, 25825, 25826, 25827, 25829, 25830, 25831, 25832, 25833, 25834, 25835, 25836, 25837, 25838, 25839, 25840, 25842, 25843, 25844, 25845, 25846, 25847, 25848, 25849, 25850, 25851, 25852, 25853, 25854, 25855, 25856, 25857, 25858, 25859, 25860, 25861, 25862, 25864, 25865, 25866, 25867, 25869, 25871, 25872, 25873, 25874, 25875, 25876, 25877, 25878, 25880, 25881, 25882, 25883, 25884, 25886, 25887, 25891, 25892, 25893, 25894, 25896, 25897, 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26078, 26079, 26080, 26081, 26082, 26083, 26084, 26085, 26086, 26087, 26089, 26091, 26092, 26094, 26095, 26096, 26097, 26098, 26099, 26100, 26101, 26102, 26103, 26104, 26105, 26106, 26107, 26108, 26109, 26110, 26111, 26112, 26113, 26114, 26115, 26116, 26117, 26118, 26120, 26121, 26122, 26123, 26124, 26125, 26126, 26127, 26128, 26129, 26130, 26131, 26133, 26134, 26135, 26136, 26137, 26138, 26139, 26140, 26141, 26142, 26143, 26144, 26145, 26146, 26147, 26149, 26150, 26151, 26152, 26153, 26154, 26155, 26156, 26157, 26158, 26159, 26160, 26161, 26162, 26163, 26164, 26165, 26166, 26168, 26169, 26170, 26171, 26172, 26173, 26174, 26175, 26176, 26177, 26178, 26179, 26180, 26181, 26182, 26183, 26184, 26185, 26186, 26187, 26188, 26189, 26191, 26192, 26193, 26194, 26195, 26197, 26198, 26199, 26200, 26201, 26202, 26203, 26204, 26206, 26207, 26208, 26209, 26210, 26212, 26213, 26214, 26215, 26216, 26217, 26218, 26220, 26221, 26223, 26224, 26225, 26226, 26227, 26228, 26229, 26230, 26231, 26232, 26233, 26234, 26235, 26236, 26237, 26238, 26239, 26240, 26241, 26242, 26244, 26246, 26247, 26248, 26249, 26250, 26251, 26255, 26253, 26256, 26257, 26258, 26259, 26260, 26261, 26262, 26263, 26264, 26265, 26266, 26267, 26268, 26269, 26270, 26271, 26272, 26273, 26274, 26275, 26276, 26277, 26278, 26279, 26280, 26281, 26282, 26283, 26284, 26285, 26288, 26289, 26290, 26291, 26292, 26294, 26295, 26296, 26297, 26298, 26299, 26300, 26303, 26304, 26305, 26306, 26307, 26309, 26310, 26312, 26313, 26314, 26315, 26316, 26318, 26320, 26321, 26322, 26323, 26325, 26326, 26328, 26329, 26330, 26331, 26332, 26333, 26335, 26336, 26337, 26338, 26340, 26341, 26342, 26343, 26345, 26346, 26347, 26348, 26350, 26352, 26353, 26354, 26355, 26356, 26358, 26359, 26361, 26362, 26363, 26365, 26366, 26367, 26369, 26371, 26373, 26374, 26375, 26376, 26377, 26378, 26380, 26381, 26383, 26384, 26385, 26386, 26387, 26388, 26389, 26390, 26391, 26392, 26393, 26394, 26395, 26396, 26397, 26398, 26399, 26400, 26401, 26402, 26403, 26404, 26406, 26407, 26408, 26409, 26410, 26411, 26412, 26413, 26414, 26415, 26416, 26417, 26418, 26419, 26420, 26422, 26423, 26424, 26425, 26426, 26427, 26428, 26429, 26430, 26431, 26432, 26433, 26434, 26435, 26436, 26437, 26438, 26439, 26440, 26441, 26442, 26443, 26444, 26445, 26446, 26447, 26448, 26449, 26450, 26451, 26452, 26453, 26454, 26455, 26456, 26457, 26459, 26460, 26462, 26463, 26464, 26466, 26467, 26469, 26470, 26471, 26472, 26473, 26474, 26475, 26476, 26477, 26478, 26479, 26480, 26481, 26482, 26483, 26484, 26485, 26486, 26487, 26488, 26489, 26490, 26491, 26492, 26493, 26494, 26495, 26496, 26497, 26498, 26499, 26500, 26501, 26502, 26503, 26504, 26505, 26506, 26508, 26509, 26510, 26511, 26512, 26513, 26515, 26516, 26517, 26518, 26519, 26520, 26521, 26522, 26523, 26524, 26525, 26526, 26527, 26528, 26529, 26530, 26531, 26532, 26533, 26534, 26535, 26536, 26537, 26538, 26540, 26543, 26544, 26545, 26546, 26547, 26548, 26550, 26552, 26553, 26554, 26555, 26557, 26560, 26563, 26564, 26565, 26566, 26567, 26568, 26570, 26571, 26572, 26575, 26577, 26578, 26579, 26580, 26581, 26582, 26583, 26584, 26586, 26588, 26589, 26590, 26592, 26593, 26594, 26595, 26596, 26597, 26599, 26600, 26601, 26603, 26604, 26605, 26606, 26607, 26608, 26609, 26610, 26612, 26614, 26615, 26616, 26618, 26619, 26620, 26622, 26623, 26624, 26625, 26626, 26628, 26629, 26630, 26631, 26633, 26636, 26639, 26640, 26642, 26643, 26644, 26645, 26646, 26648, 26650, 26651, 26652, 26655, 26657, 26660, 26663, 26664, 26665, 26667, 26670, 26671, 26672, 26673, 26674, 26675, 26676, 26677, 26678, 26679, 26680, 26683, 26684, 26685, 26686, 26687, 26689, 26690, 26691, 26694, 26696, 26698, 26701, 26704, 26705, 26706, 26707, 26708, 26709, 26711, 26713, 26714, 26715, 26716, 26718, 26720, 26723, 26721, 26724, 26725, 26726, 26727, 26728, 26729, 26730, 26731, 26732, 26733, 26734, 26735, 26737, 26738, 26739, 26740, 26741, 26742, 26743, 26744, 26745, 26746, 26747, 26749, 26751, 26752, 26753, 26754, 26755, 26756, 26757, 26760, 26761, 26762, 26763, 26764, 26766, 26767, 26768, 26769, 26770, 26771, 26772, 26775, 26776, 26777, 26778, 26779, 26781, 26782, 26783, 26786, 26787, 26789, 26790, 26792, 26793, 26794, 26796, 26798, 26799, 26801, 26802, 26803, 26804, 26805, 26806, 26807, 26808, 26812, 26813, 26814, 26816, 26817, 26818, 26819, 26822, 26823, 26825, 26826, 26827, 26828, 26830, 26831, 26832, 26833, 26834, 26837, 26839, 26840, 26841, 26843, 26844, 26845, 26846, 26847, 26849, 26850, 26851, 26853, 26854, 26856, 26857, 26858, 26859, 26860, 26861, 26863, 26864, 26866, 26868, 26870, 26872, 26874, 26875, 26876, 26877, 26878, 26879, 26880, 26881, 26882, 26883, 26884, 26885, 26886, 26887, 26889, 26890, 26891, 26892, 26893, 26895, 26896, 26897, 26899, 26900, 26902, 26903, 26905, 26906, 26908, 26909, 26911, 26912, 26913, 26915, 26917, 26918, 26919, 26920, 26921, 26922, 26923, 26925, 26926, 26927, 26928, 26929, 26930, 26931, 26932, 26933, 26934, 26935, 26936, 26938, 26940, 26941, 26942, 26943, 26944, 26945, 26946, 26947, 26948, 26949, 26951, 26952, 26953, 26954, 26956, 26958, 26959, 26960, 26961, 26962, 26964, 26966, 26967, 26969, 26970, 26971, 26972, 26973, 26974, 26976, 26977, 26979, 26981, 26982, 26983, 26984, 26985, 26987, 26988, 26989, 26990, 26991, 26992, 26994, 26995, 26998, 26999, 27001, 27002, 27004, 27005, 27006, 27007, 27008, 27010, 27011, 27012, 27014, 27016, 27017, 27018, 27019, 27020, 27021, 27022, 27023, 27024, 27025, 27026, 27027, 27029, 27030, 27031, 27032, 27033, 27034, 27035, 27036, 27037, 27039, 27040, 27041, 27042, 27043, 27044, 27045, 27046, 27047, 27048, 27049, 27050, 27053, 27054, 27055, 27056, 27057, 27059, 27061, 27062, 27063, 27064, 27065, 27067, 27069, 27070, 27071, 27072, 27074, 27075, 27077, 27078, 27079, 27080, 27082, 27084, 27085, 27086, 27087, 27088, 27090, 27092, 27093, 27095, 27096, 27097, 27098, 27099, 27100, 27102, 27103, 27105, 27107, 27108, 27109, 27110, 27111, 27112, 27113, 27114, 27115, 27116, 27117, 27118, 27120, 27122, 27123, 27124, 27125, 27126, 27127, 27128, 27129, 27131, 27132, 27133, 27135, 27136, 27137, 27139, 27140, 27141, 27142, 27144, 27145, 27146, 27147, 27148, 27150, 27152, 27153, 27154, 27155, 27156, 27158, 27159, 27161, 27163, 27164, 27165, 27166, 27167, 27168, 27170, 27172, 27173, 27175, 27177, 27178, 27179, 27181, 27182, 27183, 27184, 27185, 27186, 27187, 27188, 27189, 27190, 27193, 27194, 27195, 27196, 27197, 27198, 27200, 27201, 27203, 27204, 27205, 27206, 27208, 27209, 27210, 27211, 27212, 27213, 27215, 27217, 27219, 27221, 27222, 27223, 27224, 27226, 27227, 27228, 27229, 27230, 27232, 27235, 27237, 27238, 27240, 27242, 27243, 27244, 27246, 27248, 27249, 27250, 27252, 27253, 27255, 27256, 27257, 27258, 27259, 27260, 27261, 27262, 27263, 27264, 27265, 27266, 27268, 27269, 27270, 27271, 27272, 27273, 27274, 27275, 27276, 27277, 27278, 27280, 27282, 27283, 27284, 27285, 27286, 27287, 27288, 27290, 27291, 27293, 27294, 27295, 27296, 27297, 27299, 27300, 27301, 27302, 27303, 27304, 27306, 27308, 27309, 27310, 27311, 27312, 27314, 27315, 27316, 27320, 27321, 27322, 27323, 27324, 27325, 27326, 27327, 27328, 27329, 27330, 27331, 27333, 27335, 27336, 25170, 25167, 25503, 25502, 27337, 27338, 26785, 26810, 26821, 27339, 27340, 27341, 27342, 27343, 27344, 27345, 27346, 27347, 27349, 27350, 27351, 27353, 27355, 27356, 27357, 7, 8, 9, 10, 11, 12, 13, 14, 15, 27365, 27367, 27373, 27376, 27378, 27381, 27385, 27389, 27396, 27400, 27402, 27405, 27410, 27412, 27415, 27416, 27420, 27424, 27426, 27428, 27432, 27434, 27440, 27441, 27443, 27445, 27447, 27451, 27453, 27457, 27461, 27463, 27466, 27471, 27473, 27476, 27478, 27481, 27483, 27486, 27489, 27490, 27492, 27496, 27499, 27501, 27504, 27506, 27508, 27511, 27513, 27531, 27535, 25879, 25885, 27553, 27558, 27561, 27564, 27566, 27569, 25915, 25917, 25921, 27581, 25935, 25939, 25945, 27592, 25951, 27597, 27603, 25962, 25966, 27608, 27611, 27612, 25980, 27617, 27623, 27625, 27627, 27629, 27632, 27637, 27640, 27642, 27644, 27647, 26020, 27654, 27656, 27658, 27660, 27663, 27665, 27667, 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28167, 28170, 28173, 28175, 28178, 28183, 28187, 28192, 28194, 28197, 28198, 28201, 28204, 28206, 28210, 28212, 28213, 28215, 28218, 28220, 28223, 28224, 28227, 28232, 28239, 28243, 28247, 28249, 28253, 28257, 28259, 28265, 28268, 28270, 28271, 28273, 26765, 28280, 28282, 28283, 28285, 28288, 28293, 28295, 28306, 28310, 28314, 28320, 28323, 28336, 28342, 28344, 28359, 28367, 26898, 26901, 28380, 28382, 28383, 28394, 28399, 28402, 28407, 28409, 28413, 28417, 28431, 28433, 28439, 28447, 26993, 26997, 27003, 28457, 27009, 28462, 28466, 28470, 28474, 28477, 28479, 28481, 28486, 28489, 28491, 28494, 27052, 28499, 28511, 28516, 28530, 28532, 28538, 28543, 28546, 28559, 28565, 28570, 28573, 28575, 28577, 28585, 28591, 27176, 28594, 28602, 28605, 28607, 28614, 28619, 28626, 28639, 27241, 28643, 27247, 28648, 28664, 28669, 28674, 28677, 27289, 27292, 28692, 28695, 28697, 27313, 27360, 27362, 27364, 26319, 26364, 26372, 26324, 27921, 26372, 26327, 27924, 25283, 25289, 27941, 27965, 27967, 27369, 26319, 26364, 26372, 26324, 27921, 26372, 26327, 27924, 25283, 25289, 27370, 27965, 27967, 27371, 27711, 28340, 27708, 27706, 27710, 28563, 27725, 27708, 27706, 27710, 27725, 28370, 27711, 28426, 28424, 27712, 28340, 28348, 27708, 27706, 27710, 27130, 28563, 27725, 27720, 27711, 28426, 28424, 27712, 28340, 28348, 27708, 27706, 27710, 27130, 28563, 27725, 28370, 27720, 28673, 28686, 28690, 26916, 28388, 28390, 28392, 28601, 28663, 28661, 28672, 26916, 28388, 28390, 28392, 28601, 28663, 28661, 28672, 28673, 28690, 25706, 28703, 28686, 28690, 28706, 28370, 27722, 27414, 27418, 27423, 25119, 27438, 25754, 25759, 27450, 27456, 28151, 27465, 27775, 27781, 28185, 28200, 27470, 26627, 27485, 27488, 28182, 28185, 27495, 25152, 28256, 25155, 27519, 27517, 27521, 28708, 28710, 28679, 28676, 28679, 28676, 27533, 25870, 27538, 27540, 28679, 28676, 28712, 28716, 27547, 27595, 27599, 27578, 27610, 27615, 27619, 27621, 27552, 28718, 28719, 27557, 27576, 27595, 27599, 27578, 27610, 27615, 27619, 27579, 28483, 28720, 28721, 28412, 25199, 25198, 27595, 27599, 27601, 27610, 27615, 27619, 27621, 27636, 27653, 27674, 27711, 27712, 27121, 27704, 27708, 27706, 27710, 27711, 27712, 28370, 27720, 27722, 27725, 26119, 27740, 26132, 27752, 26148, 27767, 28182, 27858, 28191, 28196, 27863, 27775, 27781, 27789, 27795, 28136, 27858, 28191, 28196, 27863, 27775, 27781, 27789, 27795, 27826, 27828, 27830, 28327, 27839, 26245, 26243, 27855, 28136, 27858, 28196, 28191, 27863, 28209, 27872, 27877, 25261, 27882, 27884, 27899, 27910, 27911, 26317, 26319, 26364, 25278, 27919, 26372, 26324, 27921, 26372, 26327, 27924, 25283, 25286, 25289, 27941, 27965, 27967, 27944, 26372, 27950, 26372, 26364, 27953, 26372, 26370, 26368, 27958, 27965, 27967, 27969, 26405, 27988, 26421, 28003, 28016, 28018, 28031, 28033, 28083, 28036, 26458, 28041, 26465, 28057, 28061, 28059, 28074, 28078, 28076, 28083, 28096, 28103, 28110, 28115, 28120, 28125, 28128, 28236, 28136, 28185, 28141, 26591, 28151, 26602, 28162, 26617, 28256, 26627, 28182, 28185, 28186, 28191, 28196, 28203, 28209, 26688, 28222, 28226, 28231, 28236, 28241, 28246, 28251, 28256, 28262, 26750, 28278, 28724, 28292, 26797, 26795, 28300, 28301, 28303, 28305, 28725, 28312, 28726, 28317, 28318, 28322, 26835, 28327, 28328, 28330, 28331, 28333, 28335, 26852, 28340, 28348, 28349, 28350, 28351, 28352, 28371, 28406, 26986, 28371, 28406, 26986, 28371, 28363, 28362, 28406, 26986, 28370, 28373, 28372, 26904, 26916, 28388, 28390, 28392, 28473, 28398, 28455, 28460, 28444, 28465, 28412, 28422, 28421, 28426, 28424, 28427, 28429, 28437, 28443, 26986, 26986, 28455, 28460, 28444, 28465, 28473, 28485, 28455, 28460, 28465, 28464, 28473, 28485, 28504, 28503, 28508, 28506, 28509, 28515, 28521, 28520, 28525, 28523, 28526, 28528, 28536, 28542, 27121, 27138, 28555, 28553, 28557, 27130, 28563, 27138, 28569, 28580, 28581, 28584, 28588, 28597, 28599, 28601, 28611, 28613, 28618, 28623, 28625, 28629, 28631, 28633, 28686, 28637, 28636, 28647, 28651, 28653, 28655, 28657, 28659, 28663, 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31359, 31360, 31361, 31362, 31238, 31365, 31367, 31240, 31368, 31370, 31371, 31372, 31373, 31374, 31375, 31376, 31238, 31379, 31381, 31240, 31382, 31384, 31385, 31386, 31387, 31388, 31389, 31390, 31391, 31238, 31394, 31396, 31240, 31397, 31399, 31400, 31401, 31402, 31403, 29851, 31404, 31405, 29861, 29860, 31406, 31145, 30612, 31407, 31408, 29875, 31409, 31410, 29885, 29884, 31411, 31152, 30630, 31171, 31413, 31414, 31415, 30639, 31416, 31417, 29910, 29909, 31418, 31159, 31165, 31165, 31419, 29940, 31420, 31421, 29950, 31169, 31423, 31425, 31426, 29948, 31427, 31428, 29950, 31171, 31430, 31432, 31436, 31437, 31438, 31439, 31440, 31175, 30696, 31441, 30699, 31442, 31443, 31444, 31445, 31446, 31447, 31178, 30708, 31448, 30711, 31449, 31450, 31181, 31451, 31182, 31453, 31454, 31456, 31457, 31458, 31459, 31460, 31461, 31462, 31184, 30735, 31463, 31186, 31465, 31187, 31466, 31188, 31467, 31469, 31471, 31472, 31474, 31475, 31476, 31477, 31478, 31479, 31480, 31481, 31482, 31483, 31485, 30091, 31486, 31487, 31489, 31193, 31194, 31494, 31495, 31196, 31195, 31197, 31496, 31198, 31497, 31498, 31499, 30144, 30143, 30142, 31500, 31501, 31502, 31503, 31504, 31505, 31506, 31507, 31508, 31509, 31510, 31511, 30801, 31512, 30804, 31513, 30807, 31514, 30810, 31515, 31516, 31517, 31518, 31519, 31520, 31521, 31522, 31523, 30821, 31524, 31525, 31526, 31527, 31528, 31529, 31530, 30829, 30831, 31533, 31209, 31534, 31210, 31535, 31536, 31539, 31540, 31543, 31544, 31545, 31547, 31549, 31550, 31551, 31554, 31555, 31556, 30293, 31557, 31217, 31558, 30884, 31559, 31560, 31561, 31562, 30293, 31563, 31217, 31564, 30884, 31565, 31567, 31568, 31570, 31573, 31574, 31577, 31578, 31580, 31582, 31583, 31584, 31217, 31586, 31211, 31588, 31590, 31212, 31591, 30951, 31593, 31595, 31597, 31598, 31599, 31601, 31602, 30293, 31603, 31217, 31604, 30884, 31605, 31606, 30288, 31214, 31607, 31608, 31609, 31610, 30293, 31611, 31217, 31612, 30884, 31613, 31614, 30319, 31616, 31618, 31619, 30324, 31620, 31621, 31622, 31623, 30344, 31624, 31625, 31626, 30922, 31627, 31628, 31629, 30927, 31630, 31631, 30379, 31233, 31633, 31635, 31235, 31636, 30937, 30942, 31640, 31642, 31643, 31644, 31645, 31235, 31646, 30942, 30951, 31650, 31652, 31653, 31654, 31235, 31655, 30949, 30951, 31659, 31661, 31662, 31663, 31664, 31665, 31666, 31667, 31238, 31670, 31672, 31240, 31673, 31675, 31676, 31677, 31678, 31679, 31680, 31681, 31682, 31683, 31684, 31685, 31686, 31687, 31688, 31689, 31690, 31691, 31696, 31697, 31701, 31702, 8, 9, 10, 11, 12, 13, 14, 15, 31147, 31154, 31167, 31219, 31225, 31229, 31733, 31735, 31737, 31739, 31741, 31744, 31746, 31748, 31750, 31752, 31756, 31757, 31271, 31761, 31762, 31276, 31766, 31767, 31769, 31770, 31283, 31285, 31776, 31777, 31291, 31781, 31293, 31295, 31784, 31298, 31787, 31790, 31305, 31794, 31795, 31308, 31797, 31799, 31802, 31804, 31807, 31322, 31811, 31812, 31325, 31814, 31816, 31818, 31820, 31823, 31824, 31825, 31827, 31828, 31829, 31831, 31833, 31835, 31838, 31840, 31842, 31845, 31847, 31850, 31852, 31855, 31857, 31859, 31862, 31863, 31366, 31866, 31369, 31869, 31871, 31874, 31875, 31380, 31878, 31383, 31881, 31883, 31885, 31887, 31888, 31395, 31891, 31398, 31894, 31898, 31896, 31901, 31902, 31904, 31905, 31908, 31906, 31911, 31912, 31914, 31915, 31916, 31920, 31918, 31923, 31924, 31926, 30651, 30657, 31927, 30666, 30662, 31928, 30666, 31930, 31931, 31933, 31934, 31424, 31938, 31939, 31941, 31942, 31431, 31719, 31720, 31721, 31945, 31948, 31950, 31951, 31953, 31955, 31958, 31960, 31961, 31963, 31966, 31968, 31969, 31722, 31973, 31976, 31978, 31979, 31981, 31983, 31985, 31990, 31992, 31994, 31996, 31998, 32001, 30084, 31724, 31725, 32005, 32006, 32007, 32009, 32010, 32011, 32013, 32015, 32017, 32018, 32019, 32020, 32023, 32026, 32029, 32032, 32034, 32036, 32038, 32040, 32044, 32046, 32048, 32050, 32053, 32056, 32057, 32059, 32061, 32063, 32065, 32068, 32069, 32072, 32076, 32074, 30876, 32078, 32080, 32081, 32085, 32083, 30876, 32087, 32089, 32090, 32093, 31572, 31576, 31581, 30876, 32102, 32104, 31589, 32107, 32109, 32112, 32117, 32115, 30876, 32119, 32121, 32122, 32124, 32125, 32130, 32128, 32132, 30876, 32134, 32135, 32137, 32141, 32139, 30337, 32146, 32144, 30357, 32150, 32151, 32154, 32155, 32157, 32158, 31634, 32161, 32163, 32164, 32165, 32166, 32168, 32170, 32172, 32173, 32174, 32176, 32178, 32180, 32181, 32182, 32184, 32186, 32189, 32190, 31671, 32193, 31674, 32196, 31732, 31743, 31754, 32000, 32004, 32071, 31988, 32067, 32073, 32000, 32004, 32067, 32073, 32071, 31988, 32064, 32000, 32004, 32092, 32095, 32097, 32101, 32127, 31617, 7, 8, 9, 10, 11, 12, 13, 14, 15, 32230, 32233, 32235, 32238, 31755, 31278, 31768, 31775, 32258, 31793, 31810, 32295, 32297, 32301, 32304, 32308, 32311, 32316, 32320, 31900, 32323, 30618, 32326, 31910, 32329, 30636, 31412, 32333, 31922, 32337, 32338, 32340, 32341, 32343, 30672, 31929, 31422, 31937, 31429, 32354, 32355, 32356, 32370, 32378, 32381, 32384, 32383, 32385, 32386, 32390, 32395, 32416, 32418, 32422, 32423, 30882, 32079, 32428, 32429, 30882, 32088, 32437, 31587, 32445, 32446, 30882, 32120, 32453, 32455, 30882, 32133, 32460, 32461, 30904, 32463, 32464, 30920, 32149, 32153, 31632, 32475, 32481, 32486, 32488, 32492, 32495, 32496, 32497, 32242, 32245, 32251, 32250, 32256, 32254, 32266, 31789, 31791, 32266, 31801, 31803, 31806, 31808, 32275, 32348, 32353, 32055, 31822, 31464, 32280, 32043, 31975, 32283, 32282, 31834, 31832, 31830, 32288, 32043, 31837, 31841, 32043, 31849, 32028, 31844, 31853, 31851, 32348, 32296, 31864, 32303, 31876, 32310, 31889, 32318, 32348, 32179, 31658, 31657, 32162, 31639, 31638, 32348, 32353, 32498, 32499, 31493, 31492, 32014, 32012, 32359, 32043, 31947, 31954, 31952, 32364, 32043, 31957, 31964, 31962, 32055, 32052, 31464, 32375, 32377, 32368, 32367, 32500, 32501, 32502, 32503, 32064, 32504, 32505, 31493, 31492, 32014, 32012, 32373, 32043, 31975, 31980, 31464, 32375, 32377, 32376, 32506, 32507, 32508, 32509, 32510, 32511, 32512, 31493, 31492, 32014, 32012, 32043, 32022, 32025, 32028, 32031, 32039, 32037, 32035, 32033, 32408, 32043, 32042, 32049, 32055, 32052, 31532, 31531, 32415, 32414, 32066, 32067, 32062, 32073, 32471, 32513, 32434, 32514, 32434, 32515, 32435, 32516, 32436, 32440, 32108, 31638, 31639, 32110, 32111, 31658, 31657, 32114, 32191, 32494, 32517, 32451, 32518, 31615, 32471, 32162, 31639, 31638, 32171, 31649, 31648, 32179, 31658, 31657, 32191, 32494, 15, 32528, 32530, 32537, 32538, 32547, 32549, 32551, 32553, 32556, 32336, 32339, 32342, 32562, 32571, 32574, 32578, 32580, 32582, 32583, 32586, 32587, 32589, 32592, 32593, 32454, 32597, 32600, 32601, 32603, 32604, 32241, 32533, 32616, 32244, 32533, 32617, 32249, 32618, 32619, 32253, 32620, 32621, 32536, 32536, 32622, 32623, 32624, 32625, 32626, 32627, 32628, 32629, 32630, 31899, 31909, 32345, 32631, 32564, 32632, 32566, 32633, 32634, 32635, 32636, 32637, 32638, 32639, 32640, 32641, 32642, 32643, 32644, 32645, 32646, 32647, 32648, 32649, 32650, 32651, 32652, 32653, 31899, 31909, 32345, 32554, 32654, 32539, 32655, 32298, 32656, 32541, 32657, 32305, 32658, 32543, 32659, 32313, 32660, 32545, 32661, 31899, 31909, 32345, 32662, 32554, 32663, 32664, 32665, 32487, 32666, 32667, 32668, 32477, 31921, 32345, 32669, 32564, 32350, 32670, 32566, 31433, 31434, 32673, 32674, 31435, 32577, 32675, 32676, 32677, 32678, 32679, 32680, 32681, 32682, 32683, 32684, 32685, 32686, 32687, 32688, 32689, 32690, 32691, 32692, 32693, 32698, 32694, 32696, 31972, 32701, 32702, 32577, 32703, 32704, 32705, 32706, 32707, 32708, 32709, 32710, 32711, 32712, 32713, 32715, 32720, 32721, 31491, 31490, 32577, 32722, 32723, 32724, 32725, 32726, 32727, 32728, 32729, 32730, 32731, 32732, 32733, 32734, 32735, 32736, 32737, 32738, 32739, 32740, 32741, 32742, 32743, 32744, 32745, 32064, 32746, 32077, 32426, 32747, 32607, 32086, 32432, 32749, 32433, 32751, 32753, 32755, 32756, 32590, 32757, 32758, 32759, 32477, 32760, 32761, 32762, 32763, 32487, 32764, 32765, 32612, 32766, 32118, 32449, 32768, 32131, 32457, 32770, 32142, 32147, 32468, 32466, 32771, 32607, 32772, 32773, 32774, 32477, 32775, 32776, 32777, 32482, 32778, 32779, 32780, 32487, 32489, 32781, 32612, 32782, 9, 10, 11, 12, 13, 14, 15, 32529, 32531, 32814, 32815, 32817, 32818, 32820, 32821, 32823, 32824, 32826, 32827, 32786, 32787, 31903, 32837, 32789, 31913, 32838, 32791, 32839, 32841, 32843, 32844, 32846, 32848, 32850, 32852, 32855, 32859, 32861, 32863, 31903, 32865, 32789, 31913, 32866, 32791, 32867, 32868, 32870, 32872, 32874, 32876, 32878, 32880, 32882, 31903, 32884, 32789, 31913, 32885, 32791, 32886, 32888, 32890, 32892, 32894, 32896, 31925, 32897, 32796, 32560, 32558, 32898, 32900, 32901, 32903, 32572, 32003, 32904, 32905, 32908, 32906, 32909, 32910, 32799, 32912, 32915, 32917, 32920, 32922, 32924, 32926, 32930, 32572, 32003, 32932, 32935, 32936, 32799, 32938, 32942, 32944, 32946, 32572, 32003, 32950, 32951, 32948, 32952, 32953, 32799, 32955, 32957, 32960, 32962, 32964, 32968, 32970, 32972, 32071, 32977, 32975, 32979, 32802, 32980, 32982, 32983, 32804, 32984, 32748, 32986, 32750, 32752, 32754, 32809, 32991, 32993, 32995, 32998, 33000, 33003, 33005, 32807, 33006, 32767, 33008, 32809, 33009, 32769, 33011, 32811, 33012, 32813, 33013, 33014, 33016, 33018, 33020, 33022, 33024, 33026, 33028, 33029, 33031, 32199, 32207, 32835, 32830, 32201, 32835, 32833, 32203, 32215, 32205, 32207, 32209, 32211, 33002, 32213, 33002, 32213, 32215, 14, 15, 33040, 33041, 33043, 33045, 33052, 33053, 33054, 33056, 33057, 33059, 32840, 32842, 33065, 33067, 33068, 33069, 33072, 33074, 33075, 33077, 33079, 33087, 33089, 33090, 33092, 32887, 33099, 33101, 33102, 33103, 32899, 32902, 33108, 33109, 33110, 33116, 33117, 33119, 33123, 33124, 33125, 33126, 33127, 33130, 33131, 33134, 33135, 33136, 33137, 33142, 33143, 33145, 33147, 33151, 33152, 33155, 32981, 33159, 33166, 32990, 33174, 33178, 33182, 33184, 33185, 33015, 33064, 33149, 33049, 33047, 33168, 31694, 33196, 32198, 33197, 32206, 33170, 31695, 33198, 33199, 33200, 33201, 33202, 33203, 33188, 31698, 33192, 31700, 33030, 33204, 32214, 33064, 33149, 33205, 32204, 32873, 33206, 32206, 32877, 33207, 32208, 32881, 33208, 32210, 33095, 31692, 33097, 31693, 33168, 31694, 33170, 31695, 33209, 33210, 32212, 33122, 33132, 33149, 33161, 33163, 33164, 33165, 33168, 31694, 33190, 33170, 31695, 33211, 33212, 32212, 33176, 33180, 33188, 31698, 33190, 31699, 33192, 31700, 33030, 33213, 32214, 13, 14, 15, 33222, 33224, 33232, 33234, 33237, 33239, 33242, 33243, 33250, 33258, 33139, 33266, 33269, 32672, 32613, 33251, 33229, 33282, 33255, 32719, 32615, 32614, 33265, 33283, 33071, 32858, 33284, 33285, 33219, 33218, 33286, 33287, 33289, 33291, 33292, 33293, 33294, 32200, 33297, 32202, 33226, 33227, 33300, 33301, 33302, 33303, 33304, 33306, 32672, 32671, 33251, 33229, 33307, 33255, 32719, 32718, 33265, 33308, 33071, 32858, 33236, 33310, 33311, 33313, 33314, 33316, 33317, 33319, 33241, 33320, 33321, 33322, 33323, 33246, 33247, 33324, 33325, 33326, 33327, 33330, 32672, 32671, 33251, 33331, 33120, 33118, 33255, 32700, 32699, 33259, 33332, 32941, 33261, 32719, 32718, 33265, 33333, 32967, 33271, 33272, 33273, 33334, 33335, 33336, 33337, 33274, 33275, 33338, 33339, 33340, 33341, 33342, 33345, 33276, 33346, 33277, 33347, 33279, 33278, 33281, 33348, 33349, 33350, 33351, 33352, 33353, 33354, 33356, 33367, 33368, 33372, 33373, 33374, 33375, 33376, 33378, 33379, 33380, 33381, 33382, 33140, 33267, 33384, 33385, 33388, 33389, 33386, 33288, 33290, 33397, 33399, 33225, 33223, 33400, 33401, 33305, 33408, 33409, 33410, 33411, 33413, 33414, 33415, 33416, 33140, 33267, 33418, 33419, 33235, 33233, 33420, 33309, 33312, 33315, 33318, 33240, 33238, 33428, 33433, 33434, 33329, 33440, 33441, 33442, 33444, 33445, 33446, 33447, 33448, 33449, 33128, 33451, 33452, 33453, 33454, 33455, 33140, 33457, 33267, 33458, 33459, 33460, 33465, 33466, 33344, 33473, 33475, 33477, 33478, 33479, 33355, 33483, 33391, 33395, 33405, 33483, 33403, 33483, 33432, 33430, 33438, 33483, 33436, 33471, 33483, 33468, 33485, 33483, 33481, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 33490, 33491, 33114, 33494, 33496, 33500, 33501, 33502, 33488, 33504, 33296, 33299, 33511, 33512, 33516, 33114, 33519, 33521, 33524, 33525, 33526, 33528, 33529, 33535, 33536, 33488, 33541, 33114, 33443, 33547, 33550, 33450, 33553, 33556, 33558, 33456, 33567, 33514, 33571, 33572, 33508, 33507, 33573, 33514, 33515, 33574, 33575, 33576, 33539, 33534, 33533, 33532, 33531, 33539, 33577, 33578, 33579, 33539, 33540, 33580, 33581, 33582, 33462, 33461, 33560, 33463, 33563, 33464, 33564, 33583, 33584, 33585, 33476, 33474, 33570, 33586, 33587, 33588, 14, 15, 33602, 33604, 33499, 33383, 33600, 33608, 33506, 33612, 33615, 33523, 33417, 33600, 33621, 33623, 33625, 33627, 33628, 33549, 33555, 33635, 33600, 33495, 33637, 33610, 33640, 33641, 33611, 33643, 33644, 33646, 33520, 33648, 33649, 33650, 33651, 33652, 33653, 33654, 33657, 33658, 33660, 33552, 33662, 33663, 33664, 33665, 33666, 33667, 33668, 33670, 33569, 33672, 33673, 33674, 33676, 7, 8, 9, 10, 11, 12, 13, 14, 15, 33493, 33683, 33684, 33518, 33690, 33691, 33543, 33700, 33701, 33682, 33686, 33703, 33706, 33639, 33513, 33708, 33710, 33689, 33530, 33712, 33714, 33537, 33717, 33538, 33719, 33546, 33697, 33721, 33698, 33722, 33724, 33726, 33728, 33730, 33733, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 33744, 33753, 33746, 33754, 33755, 33705, 33758, 33759, 33747, 33761, 33749, 33762, 33763, 33765, 33767, 33768, 33750, 33769, 33770, 33772, 33751, 33773, 33776, 33777, 33778, 9, 10, 11, 12, 13, 14, 15, 33792, 33794, 33702, 33796, 33797, 33707, 33800, 33802, 33711, 33716, 33718, 33808, 33812, 33813, 33815, 33771, 33771, 33771, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 33827, 33825, 33839, 33752, 33799, 33831, 33840, 33760, 33807, 33766, 33804, 33836, 33841, 33809, 33816, 33814, 33857, 33859, 33860, 33856, 33861, 33863, 33864, 33865, 33866, 33867, 33869, 33870, 33871, 13, 14, 15, 33872, 33875, 33876, 33878, 33881, 33883, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 33888, 33874, 33890, 33891, 33892, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 33893, 33907, 33905, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 33920, 33921, 33922, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 33936, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 33952, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15};
int h_C[]= {
1, 3, 5, 7, 9, 11, 13, 15, 19, 21, 23, 25, 27, 29, 31, 33, 35, 37, 39, 41, 43, 45, 48, 50, 52, 54, 57, 59, 61, 63, 65, 67, 69, 71, 74, 76, 78, 80, 82, 84, 86, 88, 94, 96, 98, 100, 102, 104, 106, 108, 110, 112, 114, 116, 118, 120, 122, 124, 126, 128, 130, 132, 134, 136, 138, 140, 142, 144, 146, 148, 150, 152, 154, 156, 158, 160, 162, 164, 166, 168, 171, 173, 175, 177, 179, 181, 183, 185, 187, 189, 191, 193, 195, 197, 199, 201, 204, 206, 208, 210, 212, 214, 216, 218, 220, 222, 224, 226, 228, 230, 232, 234, 236, 238, 240, 242, 244, 246, 248, 250, 252, 254, 256, 258, 260, 262, 264, 266, 268, 270, 272, 274, 276, 278, 280, 282, 284, 286, 288, 290, 292, 294, 297, 299, 301, 303, 305, 307, 309, 311, 313, 315, 317, 319, 321, 323, 325, 327, 329, 331, 333, 335, 337, 339, 341, 343, 345, 347, 349, 351, 353, 355, 357, 359, 361, 363, 365, 367, 369, 371, 373, 375, 377, 379, 381, 383, 385, 387, 389, 391, 393, 395, 398, 400, 402, 404, 406, 408, 410, 412, 414, 416, 418, 420, 422, 424, 426, 428, 430, 432, 434, 436, 438, 440, 442, 444, 446, 448, 450, 452, 454, 456, 458, 460, 462, 464, 466, 468, 470, 472, 474, 476, 478, 480, 482, 484, 487, 489, 492, 494, 496, 498, 500, 502, 504, 506, 508, 510, 513, 515, 517, 519, 522, 524, 526, 528, 530, 532, 534, 536, 538, 540, 542, 544, 546, 548, 550, 552, 554, 556, 558, 560, 562, 564, 566, 568, 570, 572, 574, 576, 578, 580, 582, 584, 586, 588, 590, 592, 594, 596, 598, 600, 602, 604, 606, 608, 610, 612, 615, 617, 619, 621, 623, 625, 627, 629, 631, 633, 635, 637, 639, 641, 643, 645, 649, 651, 653, 655, 657, 659, 661, 663, 665, 667, 669, 671, 673, 675, 677, 679, 683, 685, 687, 689, 692, 694, 696, 698, 700, 702, 704, 706, 708, 710, 712, 714, 716, 718, 720, 722, 724, 726, 728, 730, 732, 734, 736, 738, 740, 742, 744, 746, 748, 750, 752, 754, 756, 758, 760, 762, 764, 766, 768, 770, 772, 774, 776, 778, 780, 782, 784, 786, 788, 790, 792, 794, 796, 798, 800, 802, 804, 806, 808, 810, 812, 814, 818, 820, 822, 824, 826, 828, 830, 832, 834, 836, 838, 840, 842, 844, 846, 848, 850, 852, 854, 856, 858, 860, 862, 864, 866, 868, 870, 872, 874, 876, 878, 880, 882, 884, 886, 888, 890, 892, 894, 896, 898, 900, 902, 904, 906, 908, 910, 912, 914, 916, 918, 920, 922, 924, 926, 928, 930, 932, 934, 936, 938, 940, 942, 944, 948, 950, 952, 954, 956, 958, 960, 962, 964, 966, 968, 970, 973, 975, 977, 979, 981, 983, 985, 987, 989, 991, 993, 995, 997, 999, 1001, 1003, 1005, 1007, 1009, 1011, 1019, 1021, 1023, 1025, 1027, 1029, 1031, 1033, 1035, 1037, 1039, 1041, 1046, 1048, 1051, 1053, 1055, 1057, 1060, 1062, 1065, 1067, 1069, 1071, 1073, 1075, 1077, 1079, 1081, 1083, 1085, 1087, 1089, 1091, 1093, 1095, 1097, 1099, 1101, 1103, 1105, 1107, 1109, 1111, 1113, 1115, 1117, 1119, 1121, 1123, 1125, 1127, 1129, 1131, 1133, 1135, 1138, 1140, 1142, 1144, 1146, 1148, 1150, 1152, 1154, 1156, 1159, 1161, 1164, 1166, 1168, 1170, 1173, 1175, 1177, 1179, 1181, 1183, 1185, 1187, 1189, 1191, 1193, 1195, 1197, 1199, 1201, 1203, 1206, 1208, 1211, 1213, 1215, 1217, 1220, 1222, 1224, 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8981, 8983, 8986, 8989, 8990, 8992, 8993, 8995, 8996, 8997, 8998, 8999, 9000, 9001, 9002, 9003, 9004, 9005, 9006, 9007, 9010, 9011, 9014, 9015, 9016, 9017, 9018, 9020, 9021, 9023, 9024, 9025, 9026, 9027, 9028, 9029, 9030, 9031, 9032, 9033, 9034, 9035, 9036, 9037, 9038, 9039, 9040, 9041, 9042, 9043, 9044, 9045, 9046, 9047, 9048, 9049, 9050, 9051, 9052, 9053, 9054, 9055, 9056, 9057, 9058, 9059, 9060, 9061, 9063, 9065, 9066, 9067, 9068, 9069, 9070, 9071, 9072, 9073, 9074, 9075, 9076, 9077, 9080, 9081, 9086, 9087, 9088, 9091, 9096, 9097, 9098, 9099, 9100, 9101, 9102, 9103, 9104, 9105, 9106, 9107, 9108, 9109, 9110, 9111, 9112, 9113, 9114, 9115, 9116, 9117, 9118, 9121, 9122, 9125, 9126, 9127, 9128, 9129, 9130, 9131, 9132, 9133, 9134, 9135, 9136, 9137, 9138, 9139, 9140, 9141, 9142, 9143, 9152, 9153, 9156, 9157, 9158, 9159, 9160, 9161, 9162, 9163, 9164, 9165, 9190, 9191, 9192, 9193, 9194, 9195, 9196, 9197, 9198, 9199, 9200, 9201, 9202, 9203, 9204, 9205, 9206, 9207, 9210, 9211, 9214, 9215, 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9475, 9476, 9477, 9478, 9479, 9480, 9481, 9482, 9483, 9484, 9485, 9488, 9489, 9490, 9491, 9492, 9493, 9494, 9495, 9498, 9501, 9502, 9503, 9504, 9507, 9508, 9509, 9510, 9512, 9513, 9515, 9516, 9517, 9518, 9519, 9520, 9521, 9522, 9523, 9524, 9525, 9526, 9527, 9528, 9529, 9530, 9531, 9532, 9533, 9534, 9535, 9536, 9537, 9538, 9539, 9540, 9541, 9542, 9543, 9544, 9545, 9546, 9547, 9548, 9549, 9550, 9551, 9552, 9553, 9554, 9555, 9556, 9557, 9558, 9559, 9560, 9561, 9562, 9563, 9564, 9565, 9566, 9568, 9569, 9571, 9572, 9598, 9599, 9600, 9601, 9602, 9603, 9604, 9605, 9606, 9607, 9608, 9609, 9610, 9611, 9612, 9613, 9614, 9615, 9616, 9617, 9618, 9619, 9620, 9621, 9622, 9623, 9624, 9625, 9626, 9627, 9628, 9629, 9630, 9631, 9632, 9633, 9634, 9635, 9636, 9637, 9638, 9639, 9640, 9641, 9642, 9643, 9644, 9645, 9646, 9647, 9648, 9649, 9650, 9651, 9652, 9653, 9654, 9655, 9656, 9657, 9658, 9659, 9660, 9661, 9662, 9663, 9664, 19798, 19796, 9827, 9828, 9831, 9832, 9924, 9925, 9939, 9940, 9973, 9974, 9975, 9976, 9980, 9981, 9982, 9983, 19904, 19903, 19905, 19908, 19907, 21398, 19910, 19909, 19922, 21428, 19947, 19946, 19948, 19949, 19950, 19949, 19959, 19964, 19988, 19986, 19988, 19986, 21390, 21398, 21421, 21390, 21398, 21421, 21428, 19224, 19224, 10409, 10410, 10413, 10414, 19240, 20232, 19240, 20235, 20236, 20272, 20287, 20302, 21022, 21021, 21339, 21337, 21346, 21344, 21390, 21398, 21421, 21428, 11320, 11321, 11331, 11332, 11333, 11334, 11335, 11338, 11339, 11340, 11341, 11407, 11408, 11409, 11410, 11411, 11414, 11415, 11416, 11417, 11420, 11421, 11477, 11478, 11479, 11480, 11481, 11482, 11483, 11484, 11512, 11515, 11518, 11519, 11522, 11523, 11526, 11527, 11528, 11529, 19675, 19675, 19676, 19676, 19677, 19677, 19680, 11684, 11685, 19685, 19685, 19688, 19688, 22127, 22109, 22127, 22125, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 22146, 22149, 22152, 22154, 22157, 22161, 22163, 22166, 22169, 22172, 22175, 22177, 22179, 22182, 22185, 22188, 22191, 22194, 22197, 22204, 22206, 22208, 22211, 22221, 22230, 22232, 22236, 22238, 22241, 22243, 22245, 22248, 22250, 22254, 22257, 22259, 22261, 22263, 22267, 22270, 22272, 22274, 22276, 22279, 22281, 22286, 22288, 22291, 22293, 22297, 22299, 22303, 22311, 22313, 22315, 22320, 22322, 22324, 22330, 22332, 22334, 22336, 22338, 22340, 22342, 22347, 22349, 22353, 22355, 22357, 22359, 22361, 22363, 22365, 22367, 22371, 22373, 22379, 22381, 22383, 22389, 22391, 22393, 22396, 22398, 22400, 22403, 22405, 22407, 22410, 22413, 22417, 22419, 22423, 22425, 22428, 22430, 22432, 22436, 22439, 22443, 22445, 22447, 22449, 22451, 22453, 22456, 22458, 22461, 22464, 22467, 22470, 22472, 22474, 22476, 22478, 22480, 22483, 22486, 22488, 22490, 22492, 22495, 22497, 22500, 22502, 22504, 22506, 22509, 22513, 22515, 22517, 22519, 22522, 22525, 22527, 22529, 22531, 22534, 22538, 22540, 22542, 22545, 22548, 22550, 22553, 22555, 22557, 22559, 22561, 22563, 22565, 22567, 22569, 22571, 22575, 22577, 22581, 22583, 22585, 22587, 22592, 22594, 22596, 22599, 22601, 22606, 22609, 22611, 22617, 22620, 22622, 22628, 22630, 22632, 22634, 22640, 22644, 22647, 22649, 22651, 22654, 22656, 22660, 22662, 22667, 22669, 22671, 22673, 22678, 22680, 22682, 22684, 22688, 22690, 22694, 22696, 22701, 22703, 22705, 22707, 22710, 22712, 22718, 22720, 22724, 22727, 22730, 22732, 22734, 22736, 22738, 22741, 22743, 22745, 22748, 22752, 22754, 22756, 22760, 22762, 22766, 22768, 22770, 22772, 22774, 22778, 22781, 22784, 22786, 22789, 22792, 22794, 22796, 22798, 22800, 22802, 22804, 22807, 22810, 22814, 22816, 22818, 22820, 22822, 22824, 22827, 22830, 22834, 22836, 22838, 22840, 22842, 22844, 22847, 22850, 22853, 22856, 22859, 22862, 22864, 22866, 22868, 22870, 22872, 22874, 22876, 22878, 22881, 22883, 22885, 22888, 22890, 22892, 22895, 22899, 22905, 22907, 22909, 22911, 22914, 22919, 22922, 22924, 22926, 22928, 22930, 22932, 22934, 22937, 22939, 22941, 22943, 22945, 22947, 22950, 22952, 22954, 22956, 22958, 22960, 22962, 22965, 22976, 22978, 22981, 22994, 22996, 22998, 23000, 23005, 23010, 23012, 23014, 23016, 23019, 23022, 23026, 23028, 23030, 23032, 23036, 23038, 23050, 23053, 23056, 23064, 23066, 23068, 23070, 23072, 23074, 23076, 23082, 23085, 23088, 23090, 23104, 23107, 23111, 23121, 23124, 23128, 23139, 23141, 23146, 23148, 23150, 23152, 23154, 23157, 23159, 23162, 23166, 23168, 23170, 23172, 23174, 23176, 23178, 23181, 23184, 23187, 23190, 23193, 23195, 23199, 23201, 23204, 23206, 23208, 23210, 23213, 23215, 23218, 23220, 23222, 23224, 23226, 23228, 23230, 23233, 23239, 23242, 23245, 23248, 23250, 23254, 23256, 23258, 23260, 23263, 23265, 23270, 23272, 23274, 23276, 23280, 23282, 23284, 23286, 23288, 23293, 23295, 23297, 23299, 23303, 23305, 23308, 23313, 23318, 23320, 23324, 23326, 23328, 23330, 23332, 23336, 23338, 23340, 23342, 23344, 23346, 23349, 23351, 23355, 23358, 23361, 23363, 23366, 23368, 23378, 23380, 23384, 23386, 23388, 23393, 23395, 23397, 23400, 23402, 23406, 23408, 23412, 23415, 23417, 23420, 23422, 23424, 23426, 23428, 23430, 23432, 23434, 23437, 23439, 23442, 23444, 23446, 23449, 23451, 23455, 23458, 23461, 23463, 23465, 23467, 23474, 23476, 23482, 23484, 23486, 23488, 23490, 23493, 23500, 23502, 23508, 23510, 23512, 23515, 23517, 23519, 23521, 23524, 23526, 23528, 23530, 23532, 23534, 23536, 23538, 23540, 23549, 23558, 23560, 23562, 23567, 23570, 23573, 23575, 23577, 23582, 23585, 23588, 23590, 23592, 23595, 23598, 23600, 23602, 23604, 23606, 23609, 23612, 23614, 23617, 23619, 23621, 23625, 23627, 23629, 23631, 23633, 23635, 23637, 23639, 23643, 23645, 23647, 23649, 23651, 23653, 23655, 23657, 23659, 23661, 23663, 23670, 23678, 23681, 23683, 23685, 23688, 23693, 23697, 23699, 23701, 23703, 23705, 23707, 23709, 23715, 23717, 23723, 23726, 23728, 23730, 23733, 23740, 23747, 23749, 23751, 23754, 23756, 23758, 23760, 23762, 23764, 23766, 23769, 23771, 23773, 23780, 23782, 23786, 23788, 23791, 23793, 23795, 23797, 23799, 23801, 23805, 23808, 23813, 23816, 23819, 23824, 23826, 23828, 23832, 23834, 23837, 23840, 23845, 23848, 23850, 23853, 23855, 23857, 23860, 23863, 23865, 23868, 23870, 23876, 23878, 23880, 23883, 23888, 23890, 23894, 23897, 23899, 23901, 23904, 23906, 23910, 23912, 23914, 23917, 23919, 23922, 23924, 23929, 23932, 23935, 23938, 23943, 23945, 23947, 23951, 23953, 23956, 23959, 23962, 23964, 23974, 23977, 23979, 23981, 23983, 23985, 23991, 23993, 23995, 23997, 23999, 24001, 24004, 24006, 24019, 24021, 24025, 24028, 24030, 24033, 24035, 24039, 24042, 24044, 24047, 24049, 24055, 24057, 24061, 24063, 24065, 24068, 24070, 24073, 24075, 24078, 24080, 24082, 24085, 24087, 24089, 24091, 24093, 24098, 24100, 24102, 24104, 24106, 24109, 24111, 24113, 24116, 24119, 24123, 24129, 24131, 24135, 24138, 24141, 24144, 24147, 24150, 24153, 24156, 24158, 24162, 24167, 24169, 24171, 24174, 24176, 24182, 24184, 24186, 24189, 24191, 24193, 24195, 24197, 24200, 24209, 24212, 24215, 24218, 24221, 24224, 22641, 22415, 22421, 23505, 22415, 22421, 23506, 19749, 19749, 22199, 19794, 19795, 9794, 9795, 23095, 23094, 23093, 23131, 23129, 23135, 23133, 23100, 23099, 23098, 23143, 23142, 23102, 24231, 24233, 23131, 23129, 23135, 23133, 23137, 23143, 23142, 22214, 22217, 23137, 22218, 22219, 22970, 22226, 23078, 23041, 23040, 23039, 23131, 23129, 23135, 23133, 22970, 23047, 23046, 23045, 23041, 23040, 23039, 22226, 23078, 24235, 22226, 23078, 24237, 22251, 22264, 23398, 24239, 24241, 24243, 24245, 22283, 22294, 10002, 10003, 10004, 10005, 10006, 10007, 10008, 10009, 22301, 22300, 22377, 10024, 10027, 22306, 22304, 23672, 22308, 22317, 10046, 10047, 10048, 10049, 10050, 10051, 22377, 22327, 22325, 23542, 23546, 23544, 23551, 23555, 23553, 10068, 10070, 23564, 23579, 10081, 10082, 23542, 23546, 23544, 23551, 23553, 22345, 22344, 22351, 22350, 23579, 10111, 10112, 10121, 10124, 23641, 23640, 22377, 10140, 22376, 22374, 23672, 22376, 22374, 10167, 10170, 23641, 23640, 22377, 10187, 10190, 22385, 22384, 23672, 22386, 22387, 22433, 22437, 22441, 22440, 22757, 22775, 22757, 10302, 10303, 23237, 23235, 23216, 23237, 23236, 23216, 22493, 22498, 22757, 22775, 23137, 23143, 23142, 24278, 24280, 23237, 23236, 23235, 23216, 23237, 23236, 23235, 23251, 23333, 23314, 22572, 10460, 10461, 10462, 10463, 10465, 22578, 22588, 22604, 22602, 10480, 22614, 22612, 10486, 22625, 22623, 10492, 22637, 22635, 22641, 22657, 22663, 22674, 22685, 22691, 22697, 22715, 22713, 22721, 22757, 22775, 19304, 19305, 19304, 19305, 22902, 22900, 22916, 22970, 22968, 22967, 22966, 23114, 23112, 23118, 23116, 23131, 23129, 23135, 23133, 22970, 22974, 22973, 22972, 23131, 23129, 22985, 22984, 22983, 22989, 22987, 23008, 23007, 22992, 22991, 19365, 22992, 22991, 19365, 23008, 23007, 23003, 23001, 19365, 23008, 23007, 19365, 23131, 23129, 23135, 23133, 23024, 23143, 23142, 23102, 23033, 23114, 23112, 23118, 23116, 23041, 23040, 23039, 23131, 23129, 23135, 23133, 23043, 23047, 23046, 23045, 23057, 23061, 23060, 23059, 23080, 23079, 23078, 19365, 23095, 23094, 23093, 23131, 23129, 23135, 23133, 23100, 23099, 23098, 23143, 23142, 23102, 23114, 23112, 23118, 23116, 23131, 23129, 23135, 23133, 23143, 23142, 23164, 23163, 23197, 23196, 19382, 23237, 23236, 23235, 23216, 23237, 23236, 23235, 23251, 23311, 23314, 23252, 23267, 23261, 23266, 23333, 23311, 23314, 23267, 23277, 23289, 10969, 10970, 23333, 23300, 23314, 23315, 23321, 23333, 23352, 23364, 23720, 23718, 23735, 23737, 23743, 23742, 23370, 23369, 23372, 23371, 23374, 23373, 23376, 23375, 23506, 23505, 23453, 23452, 23390, 23398, 23403, 23409, 23418, 24052, 24050, 24058, 23506, 23505, 23453, 23452, 23453, 23452, 23471, 23469, 23690, 23694, 23710, 21498, 21496, 23479, 23477, 23497, 23495, 23504, 23503, 23506, 23505, 23522, 23542, 23546, 23544, 23551, 23555, 23553, 23564, 23579, 11162, 11163, 11165, 11166, 23623, 23622, 11182, 11185, 23641, 23640, 11195, 11198, 23667, 23665, 23672, 23690, 23674, 23710, 21498, 21496, 23735, 23737, 23743, 23742, 23690, 23694, 23710, 21498, 21496, 23720, 23718, 23737, 23735, 23743, 23742, 23745, 23744, 23811, 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32060, 32058, 32417, 32420, 32420, 32420, 32159, 13331, 32098, 13334, 32098, 13336, 32098, 13338, 32098, 32105, 32441, 32442, 32474, 32478, 32483, 32485, 32484, 32443, 32490, 32493, 13363, 32450, 13368, 32458, 32159, 32472, 32474, 32473, 32478, 32480, 32479, 32483, 32485, 32484, 32490, 32493, 15, 32232, 32237, 32264, 32273, 32322, 12703, 32328, 12714, 32335, 32557, 32559, 32561, 12734, 32380, 32573, 32397, 32070, 32424, 12922, 32430, 12933, 32438, 32447, 12983, 32596, 12998, 32143, 13013, 32148, 13020, 32532, 32243, 13105, 32535, 32246, 13108, 32534, 13110, 13111, 32535, 13113, 13114, 32262, 32257, 13119, 13120, 13121, 13124, 13126, 13127, 13128, 13129, 13132, 32546, 32550, 32563, 13141, 32276, 13143, 32277, 13145, 13146, 13147, 13148, 13149, 13150, 13151, 13152, 13153, 13154, 13155, 13156, 13157, 13158, 13159, 13160, 13161, 13162, 13163, 13164, 13165, 32546, 32550, 32563, 32346, 13174, 32300, 13177, 32540, 13180, 32300, 13183, 32542, 13186, 32307, 13189, 32544, 13192, 32315, 13195, 32546, 32550, 32563, 13204, 32346, 13206, 13207, 13208, 32610, 13211, 13212, 13213, 32608, 32555, 32563, 13222, 32346, 32565, 13225, 32351, 32567, 32568, 13233, 13234, 32569, 32389, 13237, 13238, 13240, 13241, 13242, 13243, 13244, 13245, 13246, 13247, 13248, 13249, 13250, 13251, 13252, 13253, 13254, 13255, 13256, 13261, 32695, 32697, 32570, 13267, 13268, 32389, 13270, 13271, 13273, 13274, 13275, 13276, 13277, 13278, 13279, 13280, 32714, 32716, 13290, 13291, 32576, 32575, 32389, 13295, 13296, 13298, 13299, 13300, 13301, 13302, 13303, 13304, 13305, 13306, 13307, 13308, 13309, 13310, 13311, 13312, 13313, 13314, 13315, 13316, 13318, 13319, 13320, 32579, 13322, 32581, 32584, 13326, 32469, 32585, 32588, 13332, 32598, 13335, 13337, 13339, 13341, 32103, 13343, 13344, 13345, 32608, 13348, 13349, 13350, 13351, 32610, 13354, 13355, 32491, 13358, 32591, 32594, 13364, 32595, 32598, 13369, 32599, 32602, 32606, 32605, 13376, 32469, 13378, 13379, 13380, 32608, 13383, 13384, 13385, 32609, 13388, 13389, 13390, 32610, 32611, 13394, 32491, 13397, 9, 10, 11, 12, 13, 14, 15, 32784, 32785, 13103, 13104, 13106, 13107, 13109, 32822, 13112, 32825, 13115, 13118, 32262, 32271, 32788, 13135, 32548, 32790, 13138, 32552, 13140, 13142, 13144, 32845, 32847, 32849, 32851, 32853, 32856, 32860, 32862, 32864, 32788, 13167, 32548, 32790, 13170, 32552, 13172, 13173, 13175, 13179, 13181, 13185, 13187, 13191, 13193, 32788, 13198, 32548, 32790, 13201, 32552, 13203, 13205, 32891, 13209, 32895, 13214, 32792, 13217, 32795, 32794, 32793, 13221, 13223, 13224, 13226, 32797, 32798, 13231, 13232, 13235, 32907, 13236, 32911, 32394, 32913, 32916, 32918, 32921, 32923, 32925, 32927, 32931, 32797, 32798, 13266, 13269, 32937, 32394, 32939, 32943, 32945, 32947, 32797, 32798, 13292, 13293, 32949, 13294, 32954, 32394, 32956, 32958, 32961, 32963, 32965, 32969, 32971, 32973, 32800, 13321, 32976, 13323, 32801, 13325, 13327, 13328, 32803, 13330, 32985, 13333, 32987, 32988, 32989, 32805, 13342, 32994, 13346, 32999, 13352, 13356, 13360, 32806, 13362, 33007, 13365, 32808, 13367, 33010, 13370, 32810, 13372, 32812, 13374, 13375, 13377, 33019, 13381, 33023, 13386, 33027, 13391, 13393, 13395, 32831, 32828, 32834, 32829, 32831, 32834, 32832, 32836, 33032, 32871, 32875, 32879, 32883, 33001, 33004, 33001, 33004, 33032, 14, 15, 13099, 13101, 32816, 32819, 13122, 13130, 13134, 13136, 13137, 13139, 33061, 33062, 33066, 32854, 32857, 33070, 13166, 13168, 13169, 13171, 32869, 13197, 13199, 13200, 13202, 33094, 13216, 13218, 13219, 13220, 33105, 33107, 13227, 13229, 33111, 13239, 32914, 32919, 32928, 32929, 13262, 13264, 32933, 13272, 32940, 32717, 13286, 13288, 33138, 13297, 33144, 33146, 32966, 13317, 32978, 13324, 33157, 13329, 13340, 33167, 13361, 13366, 13371, 13373, 33186, 33187, 33121, 33148, 33048, 33046, 32992, 33169, 13423, 33050, 13425, 33051, 32997, 33171, 13429, 13430, 13431, 13433, 13434, 13435, 33017, 33189, 33025, 33193, 33194, 13446, 33195, 33063, 33148, 13467, 33080, 33081, 13470, 33082, 33083, 13473, 33084, 33085, 13476, 33086, 32889, 33096, 32893, 33098, 32992, 33169, 32997, 33171, 13492, 13493, 33172, 33121, 33148, 33148, 33160, 33162, 33179, 33179, 32992, 33169, 32996, 32997, 33171, 13532, 13533, 33172, 33175, 33179, 33017, 33189, 33021, 33191, 33025, 33193, 33194, 13549, 33195, 13, 14, 15, 33055, 33058, 33073, 33076, 33088, 33091, 33100, 33244, 33113, 32934, 33264, 32959, 32974, 33249, 33248, 33115, 33228, 13404, 33254, 33263, 33217, 33216, 33141, 13411, 33231, 33230, 13417, 13418, 33044, 33042, 13421, 13422, 13424, 13426, 13427, 13428, 33295, 33220, 33298, 33221, 33060, 33106, 13441, 13442, 13443, 13444, 13445, 13447, 33249, 33248, 33115, 33228, 13453, 33254, 33263, 33262, 33141, 13459, 33231, 33230, 33078, 13468, 13469, 13471, 13472, 13474, 13475, 13477, 33093, 13481, 13482, 13483, 13484, 33104, 33106, 13488, 13489, 13490, 13491, 13494, 33249, 33248, 33115, 13499, 33253, 33252, 33254, 33257, 33256, 33129, 13507, 33260, 33133, 33263, 33262, 33141, 13514, 33268, 33154, 33156, 33158, 13521, 13522, 13523, 13524, 33177, 33179, 13527, 13528, 13529, 13530, 13531, 13534, 33173, 13536, 33177, 13538, 33183, 33181, 33280, 13542, 13543, 13544, 13545, 13546, 13547, 13548, 13550, 33245, 33112, 33153, 13399, 13400, 13401, 13403, 13405, 13406, 13407, 13408, 13409, 33370, 33371, 13413, 13414, 13419, 13420, 33387, 33392, 33393, 13432, 13436, 33361, 33360, 13439, 13440, 33407, 13448, 13449, 13450, 13452, 13454, 13455, 13456, 13457, 33370, 33371, 13461, 13462, 33363, 33362, 13466, 33421, 33423, 33425, 33427, 33365, 33364, 13480, 13486, 13487, 33439, 13495, 13496, 13497, 13500, 13501, 13502, 13503, 13504, 13505, 33369, 13508, 13509, 13510, 13511, 13512, 33370, 13515, 33371, 13518, 13519, 13520, 13525, 13526, 33472, 13535, 13537, 13539, 13540, 13541, 33487, 33469, 33390, 33394, 33404, 33482, 33402, 33482, 33431, 33429, 33437, 33469, 33435, 33470, 33469, 33467, 33484, 33482, 33480, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 33270, 33492, 33489, 33377, 33497, 13410, 13412, 33503, 33366, 33505, 33509, 33510, 13437, 13438, 33517, 33489, 33412, 33522, 13458, 13460, 33527, 13464, 13465, 13478, 13479, 33366, 33542, 33489, 33544, 33548, 13506, 33551, 33554, 13513, 13516, 33557, 33568, 33566, 13558, 13559, 33396, 33396, 13563, 33566, 33406, 13567, 13568, 13569, 33566, 33426, 33424, 33422, 33422, 33566, 13582, 13583, 13584, 33566, 33328, 13588, 13589, 13590, 33562, 33561, 33559, 33562, 33562, 33562, 33343, 13604, 13605, 13606, 33566, 33565, 33486, 13611, 13612, 13613, 14, 15, 13402, 33498, 33605, 33606, 33150, 13416, 33609, 33613, 13451, 33618, 33619, 33150, 33622, 33624, 13485, 13498, 33545, 33630, 33633, 33634, 33150, 33603, 13555, 33396, 13560, 13561, 33398, 13564, 13566, 33647, 33616, 13574, 13576, 13577, 13578, 13579, 13580, 33655, 13585, 13587, 33661, 33631, 13597, 13598, 13599, 13600, 13601, 13602, 13603, 33671, 33636, 13608, 13609, 13610, 33677, 7, 8, 9, 10, 11, 12, 13, 14, 15, 33680, 33607, 13415, 33688, 33620, 13463, 33695, 13517, 13552, 33681, 33685, 13557, 13562, 33704, 33687, 33645, 13571, 33617, 33692, 33713, 33715, 33693, 33656, 33694, 33659, 33696, 33629, 13594, 33632, 33723, 33725, 33727, 33669, 13607, 33675, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 33601, 13553, 33745, 13556, 33638, 33756, 13565, 33709, 33614, 13572, 33748, 13575, 33764, 13581, 13586, 33720, 33626, 13592, 13593, 13595, 33699, 33774, 33729, 33731, 33734, 9, 10, 11, 12, 13, 14, 15, 13551, 13554, 33795, 33757, 33642, 33798, 13570, 13573, 33803, 33805, 33806, 13591, 13596, 33775, 33732, 33810, 33810, 33810, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 33828, 33793, 13615, 33824, 33829, 33801, 13620, 33830, 33834, 33833, 33832, 33811, 13626, 33835, 33838, 33837, 13614, 13616, 13617, 33826, 13619, 13621, 13622, 13623, 13624, 13625, 13627, 13628, 13629, 13, 14, 15, 33858, 13618, 33862, 33879, 33868, 33884, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 33873, 33889, 33877, 33880, 33882, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 33908, 33906, 33904, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 13630, 13631, 13632, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 33937, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 33938, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15};
bool h_Op[]= {
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 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1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 1, 1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 1, 1, 0, 0, 0, 1, 0, 1, 0, 1, 1, 0, 0, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 0, 1, 1, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 0, 1, 1, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 0, 1, 0, 0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1, 0, 1, 1, 1, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 1, 1, 0, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 0, 1, 1, 0, 1, 1, 0, 1, 0, 1, 1, 0, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 1, 0, 0, 0, 0, 1, 1, 1, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 1, 1, 0, 1, 0, 0, 1, 1, 0, 1, 0, 0, 0, 1, 0, 1, 0, 1, 1, 0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 0, 1, 0, 0, 0, 1, 1, 0, 1, 0, 0, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 0, 0, 1, 0, 0, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 1, 0, 0, 1, 0, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 1, 0, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 1, 1, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0};
#define THREADS_PER_BLOCK 16
#define BLOCKS_PER_GRID 1
#define SIZE_OF_IN 13648
#define SIZE_OF_AC 20336
__device__ void
ac(float *A, const int *B, const int *C, const bool *Op, int n_iter) {
int i= blockDim.x * blockIdx.x + threadIdx.x;
__shared__ float R[2124*THREADS_PER_BLOCK];
const int t= THREADS_PER_BLOCK;
__shared__ float final;
final=0;
R[i + 0*t] = A[i + 0*t];
R[i + 1*t] = A[i + 1*t];
R[i + 2*t] = A[i + 2*t];
R[i + 3*t] = A[i + 3*t];
R[i + 4*t] = A[i + 4*t];
R[i + 5*t] = A[i + 5*t];
R[i + 6*t] = A[i + 6*t];
R[i + 7*t] = A[i + 7*t];
R[i + 8*t] = A[i + 8*t];
R[i + 9*t] = A[i + 9*t];
R[i + 10*t] = A[i + 10*t];
R[i + 11*t] = A[i + 11*t];
R[i + 12*t] = A[i + 12*t];
R[i + 13*t] = A[i + 13*t];
R[i + 14*t] = A[i + 14*t];
R[i + 15*t] = A[i + 15*t];
R[i + 16*t] = A[i + 16*t];
R[i + 17*t] = A[i + 17*t];
R[i + 18*t] = A[i + 18*t];
R[i + 19*t] = A[i + 19*t];
R[i + 20*t] = A[i + 20*t];
R[i + 21*t] = A[i + 21*t];
R[i + 22*t] = A[i + 22*t];
R[i + 23*t] = A[i + 23*t];
R[i + 24*t] = A[i + 24*t];
R[i + 25*t] = A[i + 25*t];
R[i + 26*t] = A[i + 26*t];
R[i + 27*t] = A[i + 27*t];
R[i + 28*t] = A[i + 28*t];
R[i + 29*t] = A[i + 29*t];
R[i + 30*t] = A[i + 30*t];
R[i + 31*t] = A[i + 31*t];
R[i + 32*t] = A[i + 32*t];
R[i + 33*t] = A[i + 33*t];
R[i + 34*t] = A[i + 34*t];
R[i + 35*t] = A[i + 35*t];
R[i + 36*t] = A[i + 36*t];
R[i + 37*t] = A[i + 37*t];
R[i + 38*t] = A[i + 38*t];
R[i + 39*t] = A[i + 39*t];
R[i + 40*t] = A[i + 40*t];
R[i + 41*t] = A[i + 41*t];
R[i + 42*t] = A[i + 42*t];
R[i + 43*t] = A[i + 43*t];
R[i + 44*t] = A[i + 44*t];
R[i + 45*t] = A[i + 45*t];
R[i + 46*t] = A[i + 46*t];
R[i + 47*t] = A[i + 47*t];
R[i + 48*t] = A[i + 48*t];
R[i + 49*t] = A[i + 49*t];
R[i + 50*t] = A[i + 50*t];
R[i + 51*t] = A[i + 51*t];
R[i + 52*t] = A[i + 52*t];
R[i + 53*t] = A[i + 53*t];
R[i + 54*t] = A[i + 54*t];
R[i + 55*t] = A[i + 55*t];
R[i + 56*t] = A[i + 56*t];
R[i + 57*t] = A[i + 57*t];
R[i + 58*t] = A[i + 58*t];
R[i + 59*t] = A[i + 59*t];
R[i + 60*t] = A[i + 60*t];
R[i + 61*t] = A[i + 61*t];
R[i + 62*t] = A[i + 62*t];
R[i + 63*t] = A[i + 63*t];
R[i + 64*t] = A[i + 64*t];
R[i + 65*t] = A[i + 65*t];
R[i + 66*t] = A[i + 66*t];
R[i + 67*t] = A[i + 67*t];
R[i + 68*t] = A[i + 68*t];
R[i + 69*t] = A[i + 69*t];
R[i + 70*t] = A[i + 70*t];
R[i + 71*t] = A[i + 71*t];
R[i + 72*t] = A[i + 72*t];
R[i + 73*t] = A[i + 73*t];
R[i + 74*t] = A[i + 74*t];
R[i + 75*t] = A[i + 75*t];
R[i + 76*t] = A[i + 76*t];
R[i + 77*t] = A[i + 77*t];
R[i + 78*t] = A[i + 78*t];
R[i + 79*t] = A[i + 79*t];
R[i + 80*t] = A[i + 80*t];
R[i + 81*t] = A[i + 81*t];
R[i + 82*t] = A[i + 82*t];
R[i + 83*t] = A[i + 83*t];
R[i + 84*t] = A[i + 84*t];
R[i + 85*t] = A[i + 85*t];
R[i + 86*t] = A[i + 86*t];
R[i + 87*t] = A[i + 87*t];
R[i + 88*t] = A[i + 88*t];
R[i + 89*t] = A[i + 89*t];
R[i + 90*t] = A[i + 90*t];
R[i + 91*t] = A[i + 91*t];
R[i + 92*t] = A[i + 92*t];
R[i + 93*t] = A[i + 93*t];
R[i + 94*t] = A[i + 94*t];
R[i + 95*t] = A[i + 95*t];
R[i + 96*t] = A[i + 96*t];
R[i + 97*t] = A[i + 97*t];
R[i + 98*t] = A[i + 98*t];
R[i + 99*t] = A[i + 99*t];
R[i + 100*t] = A[i + 100*t];
R[i + 101*t] = A[i + 101*t];
R[i + 102*t] = A[i + 102*t];
R[i + 103*t] = A[i + 103*t];
R[i + 104*t] = A[i + 104*t];
R[i + 105*t] = A[i + 105*t];
R[i + 106*t] = A[i + 106*t];
R[i + 107*t] = A[i + 107*t];
R[i + 108*t] = A[i + 108*t];
R[i + 109*t] = A[i + 109*t];
R[i + 110*t] = A[i + 110*t];
R[i + 111*t] = A[i + 111*t];
R[i + 112*t] = A[i + 112*t];
R[i + 113*t] = A[i + 113*t];
R[i + 114*t] = A[i + 114*t];
R[i + 115*t] = A[i + 115*t];
R[i + 116*t] = A[i + 116*t];
R[i + 117*t] = A[i + 117*t];
R[i + 118*t] = A[i + 118*t];
R[i + 119*t] = A[i + 119*t];
R[i + 120*t] = A[i + 120*t];
R[i + 121*t] = A[i + 121*t];
R[i + 122*t] = A[i + 122*t];
R[i + 123*t] = A[i + 123*t];
R[i + 124*t] = A[i + 124*t];
R[i + 125*t] = A[i + 125*t];
R[i + 126*t] = A[i + 126*t];
R[i + 127*t] = A[i + 127*t];
R[i + 128*t] = A[i + 128*t];
R[i + 129*t] = A[i + 129*t];
R[i + 130*t] = A[i + 130*t];
R[i + 131*t] = A[i + 131*t];
R[i + 132*t] = A[i + 132*t];
R[i + 133*t] = A[i + 133*t];
R[i + 134*t] = A[i + 134*t];
R[i + 135*t] = A[i + 135*t];
R[i + 136*t] = A[i + 136*t];
R[i + 137*t] = A[i + 137*t];
R[i + 138*t] = A[i + 138*t];
R[i + 139*t] = A[i + 139*t];
R[i + 140*t] = A[i + 140*t];
R[i + 141*t] = A[i + 141*t];
R[i + 142*t] = A[i + 142*t];
R[i + 143*t] = A[i + 143*t];
R[i + 144*t] = A[i + 144*t];
R[i + 145*t] = A[i + 145*t];
R[i + 146*t] = A[i + 146*t];
R[i + 147*t] = A[i + 147*t];
R[i + 148*t] = A[i + 148*t];
R[i + 149*t] = A[i + 149*t];
R[i + 150*t] = A[i + 150*t];
R[i + 151*t] = A[i + 151*t];
R[i + 152*t] = A[i + 152*t];
R[i + 153*t] = A[i + 153*t];
R[i + 154*t] = A[i + 154*t];
R[i + 155*t] = A[i + 155*t];
R[i + 156*t] = A[i + 156*t];
R[i + 157*t] = A[i + 157*t];
R[i + 158*t] = A[i + 158*t];
R[i + 159*t] = A[i + 159*t];
R[i + 160*t] = A[i + 160*t];
R[i + 161*t] = A[i + 161*t];
R[i + 162*t] = A[i + 162*t];
R[i + 163*t] = A[i + 163*t];
R[i + 164*t] = A[i + 164*t];
R[i + 165*t] = A[i + 165*t];
R[i + 166*t] = A[i + 166*t];
R[i + 167*t] = A[i + 167*t];
R[i + 168*t] = A[i + 168*t];
R[i + 169*t] = A[i + 169*t];
R[i + 170*t] = A[i + 170*t];
R[i + 171*t] = A[i + 171*t];
R[i + 172*t] = A[i + 172*t];
R[i + 173*t] = A[i + 173*t];
R[i + 174*t] = A[i + 174*t];
R[i + 175*t] = A[i + 175*t];
R[i + 176*t] = A[i + 176*t];
R[i + 177*t] = A[i + 177*t];
R[i + 178*t] = A[i + 178*t];
R[i + 179*t] = A[i + 179*t];
R[i + 180*t] = A[i + 180*t];
R[i + 181*t] = A[i + 181*t];
R[i + 182*t] = A[i + 182*t];
R[i + 183*t] = A[i + 183*t];
R[i + 184*t] = A[i + 184*t];
R[i + 185*t] = A[i + 185*t];
R[i + 186*t] = A[i + 186*t];
R[i + 187*t] = A[i + 187*t];
R[i + 188*t] = A[i + 188*t];
R[i + 189*t] = A[i + 189*t];
R[i + 190*t] = A[i + 190*t];
R[i + 191*t] = A[i + 191*t];
R[i + 192*t] = A[i + 192*t];
R[i + 193*t] = A[i + 193*t];
R[i + 194*t] = A[i + 194*t];
R[i + 195*t] = A[i + 195*t];
R[i + 196*t] = A[i + 196*t];
R[i + 197*t] = A[i + 197*t];
R[i + 198*t] = A[i + 198*t];
R[i + 199*t] = A[i + 199*t];
R[i + 200*t] = A[i + 200*t];
R[i + 201*t] = A[i + 201*t];
R[i + 202*t] = A[i + 202*t];
R[i + 203*t] = A[i + 203*t];
R[i + 204*t] = A[i + 204*t];
R[i + 205*t] = A[i + 205*t];
R[i + 206*t] = A[i + 206*t];
R[i + 207*t] = A[i + 207*t];
R[i + 208*t] = A[i + 208*t];
R[i + 209*t] = A[i + 209*t];
R[i + 210*t] = A[i + 210*t];
R[i + 211*t] = A[i + 211*t];
R[i + 212*t] = A[i + 212*t];
R[i + 213*t] = A[i + 213*t];
R[i + 214*t] = A[i + 214*t];
R[i + 215*t] = A[i + 215*t];
R[i + 216*t] = A[i + 216*t];
R[i + 217*t] = A[i + 217*t];
R[i + 218*t] = A[i + 218*t];
R[i + 219*t] = A[i + 219*t];
R[i + 220*t] = A[i + 220*t];
R[i + 221*t] = A[i + 221*t];
R[i + 222*t] = A[i + 222*t];
R[i + 223*t] = A[i + 223*t];
R[i + 224*t] = A[i + 224*t];
R[i + 225*t] = A[i + 225*t];
R[i + 226*t] = A[i + 226*t];
R[i + 227*t] = A[i + 227*t];
R[i + 228*t] = A[i + 228*t];
R[i + 229*t] = A[i + 229*t];
R[i + 230*t] = A[i + 230*t];
R[i + 231*t] = A[i + 231*t];
R[i + 232*t] = A[i + 232*t];
R[i + 233*t] = A[i + 233*t];
R[i + 234*t] = A[i + 234*t];
R[i + 235*t] = A[i + 235*t];
R[i + 236*t] = A[i + 236*t];
R[i + 237*t] = A[i + 237*t];
R[i + 238*t] = A[i + 238*t];
R[i + 239*t] = A[i + 239*t];
R[i + 240*t] = A[i + 240*t];
R[i + 241*t] = A[i + 241*t];
R[i + 242*t] = A[i + 242*t];
R[i + 243*t] = A[i + 243*t];
R[i + 244*t] = A[i + 244*t];
R[i + 245*t] = A[i + 245*t];
R[i + 246*t] = A[i + 246*t];
R[i + 247*t] = A[i + 247*t];
R[i + 248*t] = A[i + 248*t];
R[i + 249*t] = A[i + 249*t];
R[i + 250*t] = A[i + 250*t];
R[i + 251*t] = A[i + 251*t];
R[i + 252*t] = A[i + 252*t];
R[i + 253*t] = A[i + 253*t];
R[i + 254*t] = A[i + 254*t];
R[i + 255*t] = A[i + 255*t];
R[i + 256*t] = A[i + 256*t];
R[i + 257*t] = A[i + 257*t];
R[i + 258*t] = A[i + 258*t];
R[i + 259*t] = A[i + 259*t];
R[i + 260*t] = A[i + 260*t];
R[i + 261*t] = A[i + 261*t];
R[i + 262*t] = A[i + 262*t];
R[i + 263*t] = A[i + 263*t];
R[i + 264*t] = A[i + 264*t];
R[i + 265*t] = A[i + 265*t];
R[i + 266*t] = A[i + 266*t];
R[i + 267*t] = A[i + 267*t];
R[i + 268*t] = A[i + 268*t];
R[i + 269*t] = A[i + 269*t];
R[i + 270*t] = A[i + 270*t];
R[i + 271*t] = A[i + 271*t];
R[i + 272*t] = A[i + 272*t];
R[i + 273*t] = A[i + 273*t];
R[i + 274*t] = A[i + 274*t];
R[i + 275*t] = A[i + 275*t];
R[i + 276*t] = A[i + 276*t];
R[i + 277*t] = A[i + 277*t];
R[i + 278*t] = A[i + 278*t];
R[i + 279*t] = A[i + 279*t];
R[i + 280*t] = A[i + 280*t];
R[i + 281*t] = A[i + 281*t];
R[i + 282*t] = A[i + 282*t];
R[i + 283*t] = A[i + 283*t];
R[i + 284*t] = A[i + 284*t];
R[i + 285*t] = A[i + 285*t];
R[i + 286*t] = A[i + 286*t];
R[i + 287*t] = A[i + 287*t];
R[i + 288*t] = A[i + 288*t];
R[i + 289*t] = A[i + 289*t];
R[i + 290*t] = A[i + 290*t];
R[i + 291*t] = A[i + 291*t];
R[i + 292*t] = A[i + 292*t];
R[i + 293*t] = A[i + 293*t];
R[i + 294*t] = A[i + 294*t];
R[i + 295*t] = A[i + 295*t];
R[i + 296*t] = A[i + 296*t];
R[i + 297*t] = A[i + 297*t];
R[i + 298*t] = A[i + 298*t];
R[i + 299*t] = A[i + 299*t];
R[i + 300*t] = A[i + 300*t];
R[i + 301*t] = A[i + 301*t];
R[i + 302*t] = A[i + 302*t];
R[i + 303*t] = A[i + 303*t];
R[i + 304*t] = A[i + 304*t];
R[i + 305*t] = A[i + 305*t];
R[i + 306*t] = A[i + 306*t];
R[i + 307*t] = A[i + 307*t];
R[i + 308*t] = A[i + 308*t];
R[i + 309*t] = A[i + 309*t];
R[i + 310*t] = A[i + 310*t];
R[i + 311*t] = A[i + 311*t];
R[i + 312*t] = A[i + 312*t];
R[i + 313*t] = A[i + 313*t];
R[i + 314*t] = A[i + 314*t];
R[i + 315*t] = A[i + 315*t];
R[i + 316*t] = A[i + 316*t];
R[i + 317*t] = A[i + 317*t];
R[i + 318*t] = A[i + 318*t];
R[i + 319*t] = A[i + 319*t];
R[i + 320*t] = A[i + 320*t];
R[i + 321*t] = A[i + 321*t];
R[i + 322*t] = A[i + 322*t];
R[i + 323*t] = A[i + 323*t];
R[i + 324*t] = A[i + 324*t];
R[i + 325*t] = A[i + 325*t];
R[i + 326*t] = A[i + 326*t];
R[i + 327*t] = A[i + 327*t];
R[i + 328*t] = A[i + 328*t];
R[i + 329*t] = A[i + 329*t];
R[i + 330*t] = A[i + 330*t];
R[i + 331*t] = A[i + 331*t];
R[i + 332*t] = A[i + 332*t];
R[i + 333*t] = A[i + 333*t];
R[i + 334*t] = A[i + 334*t];
R[i + 335*t] = A[i + 335*t];
R[i + 336*t] = A[i + 336*t];
R[i + 337*t] = A[i + 337*t];
R[i + 338*t] = A[i + 338*t];
R[i + 339*t] = A[i + 339*t];
R[i + 340*t] = A[i + 340*t];
R[i + 341*t] = A[i + 341*t];
R[i + 342*t] = A[i + 342*t];
R[i + 343*t] = A[i + 343*t];
R[i + 344*t] = A[i + 344*t];
R[i + 345*t] = A[i + 345*t];
R[i + 346*t] = A[i + 346*t];
R[i + 347*t] = A[i + 347*t];
R[i + 348*t] = A[i + 348*t];
R[i + 349*t] = A[i + 349*t];
R[i + 350*t] = A[i + 350*t];
R[i + 351*t] = A[i + 351*t];
R[i + 352*t] = A[i + 352*t];
R[i + 353*t] = A[i + 353*t];
R[i + 354*t] = A[i + 354*t];
R[i + 355*t] = A[i + 355*t];
R[i + 356*t] = A[i + 356*t];
R[i + 357*t] = A[i + 357*t];
R[i + 358*t] = A[i + 358*t];
R[i + 359*t] = A[i + 359*t];
R[i + 360*t] = A[i + 360*t];
R[i + 361*t] = A[i + 361*t];
R[i + 362*t] = A[i + 362*t];
R[i + 363*t] = A[i + 363*t];
R[i + 364*t] = A[i + 364*t];
R[i + 365*t] = A[i + 365*t];
R[i + 366*t] = A[i + 366*t];
R[i + 367*t] = A[i + 367*t];
R[i + 368*t] = A[i + 368*t];
R[i + 369*t] = A[i + 369*t];
R[i + 370*t] = A[i + 370*t];
R[i + 371*t] = A[i + 371*t];
R[i + 372*t] = A[i + 372*t];
R[i + 373*t] = A[i + 373*t];
R[i + 374*t] = A[i + 374*t];
R[i + 375*t] = A[i + 375*t];
R[i + 376*t] = A[i + 376*t];
R[i + 377*t] = A[i + 377*t];
R[i + 378*t] = A[i + 378*t];
R[i + 379*t] = A[i + 379*t];
R[i + 380*t] = A[i + 380*t];
R[i + 381*t] = A[i + 381*t];
R[i + 382*t] = A[i + 382*t];
R[i + 383*t] = A[i + 383*t];
R[i + 384*t] = A[i + 384*t];
R[i + 385*t] = A[i + 385*t];
R[i + 386*t] = A[i + 386*t];
R[i + 387*t] = A[i + 387*t];
R[i + 388*t] = A[i + 388*t];
R[i + 389*t] = A[i + 389*t];
R[i + 390*t] = A[i + 390*t];
R[i + 391*t] = A[i + 391*t];
R[i + 392*t] = A[i + 392*t];
R[i + 393*t] = A[i + 393*t];
R[i + 394*t] = A[i + 394*t];
R[i + 395*t] = A[i + 395*t];
R[i + 396*t] = A[i + 396*t];
R[i + 397*t] = A[i + 397*t];
R[i + 398*t] = A[i + 398*t];
R[i + 399*t] = A[i + 399*t];
R[i + 400*t] = A[i + 400*t];
R[i + 401*t] = A[i + 401*t];
R[i + 402*t] = A[i + 402*t];
R[i + 403*t] = A[i + 403*t];
R[i + 404*t] = A[i + 404*t];
R[i + 405*t] = A[i + 405*t];
R[i + 406*t] = A[i + 406*t];
R[i + 407*t] = A[i + 407*t];
R[i + 408*t] = A[i + 408*t];
R[i + 409*t] = A[i + 409*t];
R[i + 410*t] = A[i + 410*t];
R[i + 411*t] = A[i + 411*t];
R[i + 412*t] = A[i + 412*t];
R[i + 413*t] = A[i + 413*t];
R[i + 414*t] = A[i + 414*t];
R[i + 415*t] = A[i + 415*t];
R[i + 416*t] = A[i + 416*t];
R[i + 417*t] = A[i + 417*t];
R[i + 418*t] = A[i + 418*t];
R[i + 419*t] = A[i + 419*t];
R[i + 420*t] = A[i + 420*t];
R[i + 421*t] = A[i + 421*t];
R[i + 422*t] = A[i + 422*t];
R[i + 423*t] = A[i + 423*t];
R[i + 424*t] = A[i + 424*t];
R[i + 425*t] = A[i + 425*t];
R[i + 426*t] = A[i + 426*t];
R[i + 427*t] = A[i + 427*t];
R[i + 428*t] = A[i + 428*t];
R[i + 429*t] = A[i + 429*t];
R[i + 430*t] = A[i + 430*t];
R[i + 431*t] = A[i + 431*t];
R[i + 432*t] = A[i + 432*t];
R[i + 433*t] = A[i + 433*t];
R[i + 434*t] = A[i + 434*t];
R[i + 435*t] = A[i + 435*t];
R[i + 436*t] = A[i + 436*t];
R[i + 437*t] = A[i + 437*t];
R[i + 438*t] = A[i + 438*t];
R[i + 439*t] = A[i + 439*t];
R[i + 440*t] = A[i + 440*t];
R[i + 441*t] = A[i + 441*t];
R[i + 442*t] = A[i + 442*t];
R[i + 443*t] = A[i + 443*t];
R[i + 444*t] = A[i + 444*t];
R[i + 445*t] = A[i + 445*t];
R[i + 446*t] = A[i + 446*t];
R[i + 447*t] = A[i + 447*t];
R[i + 448*t] = A[i + 448*t];
R[i + 449*t] = A[i + 449*t];
R[i + 450*t] = A[i + 450*t];
R[i + 451*t] = A[i + 451*t];
R[i + 452*t] = A[i + 452*t];
R[i + 453*t] = A[i + 453*t];
R[i + 454*t] = A[i + 454*t];
R[i + 455*t] = A[i + 455*t];
R[i + 456*t] = A[i + 456*t];
R[i + 457*t] = A[i + 457*t];
R[i + 458*t] = A[i + 458*t];
R[i + 459*t] = A[i + 459*t];
R[i + 460*t] = A[i + 460*t];
R[i + 461*t] = A[i + 461*t];
R[i + 462*t] = A[i + 462*t];
R[i + 463*t] = A[i + 463*t];
R[i + 464*t] = A[i + 464*t];
R[i + 465*t] = A[i + 465*t];
R[i + 466*t] = A[i + 466*t];
R[i + 467*t] = A[i + 467*t];
R[i + 468*t] = A[i + 468*t];
R[i + 469*t] = A[i + 469*t];
R[i + 470*t] = A[i + 470*t];
R[i + 471*t] = A[i + 471*t];
R[i + 472*t] = A[i + 472*t];
R[i + 473*t] = A[i + 473*t];
R[i + 474*t] = A[i + 474*t];
R[i + 475*t] = A[i + 475*t];
R[i + 476*t] = A[i + 476*t];
R[i + 477*t] = A[i + 477*t];
R[i + 478*t] = A[i + 478*t];
R[i + 479*t] = A[i + 479*t];
R[i + 480*t] = A[i + 480*t];
R[i + 481*t] = A[i + 481*t];
R[i + 482*t] = A[i + 482*t];
R[i + 483*t] = A[i + 483*t];
R[i + 484*t] = A[i + 484*t];
R[i + 485*t] = A[i + 485*t];
R[i + 486*t] = A[i + 486*t];
R[i + 487*t] = A[i + 487*t];
R[i + 488*t] = A[i + 488*t];
R[i + 489*t] = A[i + 489*t];
R[i + 490*t] = A[i + 490*t];
R[i + 491*t] = A[i + 491*t];
R[i + 492*t] = A[i + 492*t];
R[i + 493*t] = A[i + 493*t];
R[i + 494*t] = A[i + 494*t];
R[i + 495*t] = A[i + 495*t];
R[i + 496*t] = A[i + 496*t];
R[i + 497*t] = A[i + 497*t];
R[i + 498*t] = A[i + 498*t];
R[i + 499*t] = A[i + 499*t];
R[i + 500*t] = A[i + 500*t];
R[i + 501*t] = A[i + 501*t];
R[i + 502*t] = A[i + 502*t];
R[i + 503*t] = A[i + 503*t];
R[i + 504*t] = A[i + 504*t];
R[i + 505*t] = A[i + 505*t];
R[i + 506*t] = A[i + 506*t];
R[i + 507*t] = A[i + 507*t];
R[i + 508*t] = A[i + 508*t];
R[i + 509*t] = A[i + 509*t];
R[i + 510*t] = A[i + 510*t];
R[i + 511*t] = A[i + 511*t];
R[i + 512*t] = A[i + 512*t];
R[i + 513*t] = A[i + 513*t];
R[i + 514*t] = A[i + 514*t];
R[i + 515*t] = A[i + 515*t];
R[i + 516*t] = A[i + 516*t];
R[i + 517*t] = A[i + 517*t];
R[i + 518*t] = A[i + 518*t];
R[i + 519*t] = A[i + 519*t];
R[i + 520*t] = A[i + 520*t];
R[i + 521*t] = A[i + 521*t];
R[i + 522*t] = A[i + 522*t];
R[i + 523*t] = A[i + 523*t];
R[i + 524*t] = A[i + 524*t];
R[i + 525*t] = A[i + 525*t];
R[i + 526*t] = A[i + 526*t];
R[i + 527*t] = A[i + 527*t];
R[i + 528*t] = A[i + 528*t];
R[i + 529*t] = A[i + 529*t];
R[i + 530*t] = A[i + 530*t];
R[i + 531*t] = A[i + 531*t];
R[i + 532*t] = A[i + 532*t];
R[i + 533*t] = A[i + 533*t];
R[i + 534*t] = A[i + 534*t];
R[i + 535*t] = A[i + 535*t];
R[i + 536*t] = A[i + 536*t];
R[i + 537*t] = A[i + 537*t];
R[i + 538*t] = A[i + 538*t];
R[i + 539*t] = A[i + 539*t];
R[i + 540*t] = A[i + 540*t];
R[i + 541*t] = A[i + 541*t];
R[i + 542*t] = A[i + 542*t];
R[i + 543*t] = A[i + 543*t];
R[i + 544*t] = A[i + 544*t];
R[i + 545*t] = A[i + 545*t];
R[i + 546*t] = A[i + 546*t];
R[i + 547*t] = A[i + 547*t];
R[i + 548*t] = A[i + 548*t];
R[i + 549*t] = A[i + 549*t];
R[i + 550*t] = A[i + 550*t];
R[i + 551*t] = A[i + 551*t];
R[i + 552*t] = A[i + 552*t];
R[i + 553*t] = A[i + 553*t];
R[i + 554*t] = A[i + 554*t];
R[i + 555*t] = A[i + 555*t];
R[i + 556*t] = A[i + 556*t];
R[i + 557*t] = A[i + 557*t];
R[i + 558*t] = A[i + 558*t];
R[i + 559*t] = A[i + 559*t];
R[i + 560*t] = A[i + 560*t];
R[i + 561*t] = A[i + 561*t];
R[i + 562*t] = A[i + 562*t];
R[i + 563*t] = A[i + 563*t];
R[i + 564*t] = A[i + 564*t];
R[i + 565*t] = A[i + 565*t];
R[i + 566*t] = A[i + 566*t];
R[i + 567*t] = A[i + 567*t];
R[i + 568*t] = A[i + 568*t];
R[i + 569*t] = A[i + 569*t];
R[i + 570*t] = A[i + 570*t];
R[i + 571*t] = A[i + 571*t];
R[i + 572*t] = A[i + 572*t];
R[i + 573*t] = A[i + 573*t];
R[i + 574*t] = A[i + 574*t];
R[i + 575*t] = A[i + 575*t];
R[i + 576*t] = A[i + 576*t];
R[i + 577*t] = A[i + 577*t];
R[i + 578*t] = A[i + 578*t];
R[i + 579*t] = A[i + 579*t];
R[i + 580*t] = A[i + 580*t];
R[i + 581*t] = A[i + 581*t];
R[i + 582*t] = A[i + 582*t];
R[i + 583*t] = A[i + 583*t];
R[i + 584*t] = A[i + 584*t];
R[i + 585*t] = A[i + 585*t];
R[i + 586*t] = A[i + 586*t];
R[i + 587*t] = A[i + 587*t];
R[i + 588*t] = A[i + 588*t];
R[i + 589*t] = A[i + 589*t];
R[i + 590*t] = A[i + 590*t];
R[i + 591*t] = A[i + 591*t];
R[i + 592*t] = A[i + 592*t];
R[i + 593*t] = A[i + 593*t];
R[i + 594*t] = A[i + 594*t];
R[i + 595*t] = A[i + 595*t];
R[i + 596*t] = A[i + 596*t];
R[i + 597*t] = A[i + 597*t];
R[i + 598*t] = A[i + 598*t];
R[i + 599*t] = A[i + 599*t];
R[i + 600*t] = A[i + 600*t];
R[i + 601*t] = A[i + 601*t];
R[i + 602*t] = A[i + 602*t];
R[i + 603*t] = A[i + 603*t];
R[i + 604*t] = A[i + 604*t];
R[i + 605*t] = A[i + 605*t];
R[i + 606*t] = A[i + 606*t];
R[i + 607*t] = A[i + 607*t];
R[i + 608*t] = A[i + 608*t];
R[i + 609*t] = A[i + 609*t];
R[i + 610*t] = A[i + 610*t];
R[i + 611*t] = A[i + 611*t];
R[i + 612*t] = A[i + 612*t];
R[i + 613*t] = A[i + 613*t];
R[i + 614*t] = A[i + 614*t];
R[i + 615*t] = A[i + 615*t];
R[i + 616*t] = A[i + 616*t];
R[i + 617*t] = A[i + 617*t];
R[i + 618*t] = A[i + 618*t];
R[i + 619*t] = A[i + 619*t];
R[i + 620*t] = A[i + 620*t];
R[i + 621*t] = A[i + 621*t];
R[i + 622*t] = A[i + 622*t];
R[i + 623*t] = A[i + 623*t];
R[i + 624*t] = A[i + 624*t];
R[i + 625*t] = A[i + 625*t];
R[i + 626*t] = A[i + 626*t];
R[i + 627*t] = A[i + 627*t];
R[i + 628*t] = A[i + 628*t];
R[i + 629*t] = A[i + 629*t];
R[i + 630*t] = A[i + 630*t];
R[i + 631*t] = A[i + 631*t];
R[i + 632*t] = A[i + 632*t];
R[i + 633*t] = A[i + 633*t];
R[i + 634*t] = A[i + 634*t];
R[i + 635*t] = A[i + 635*t];
R[i + 636*t] = A[i + 636*t];
R[i + 637*t] = A[i + 637*t];
R[i + 638*t] = A[i + 638*t];
R[i + 639*t] = A[i + 639*t];
R[i + 640*t] = A[i + 640*t];
R[i + 641*t] = A[i + 641*t];
R[i + 642*t] = A[i + 642*t];
R[i + 643*t] = A[i + 643*t];
R[i + 644*t] = A[i + 644*t];
R[i + 645*t] = A[i + 645*t];
R[i + 646*t] = A[i + 646*t];
R[i + 647*t] = A[i + 647*t];
R[i + 648*t] = A[i + 648*t];
R[i + 649*t] = A[i + 649*t];
R[i + 650*t] = A[i + 650*t];
R[i + 651*t] = A[i + 651*t];
R[i + 652*t] = A[i + 652*t];
R[i + 653*t] = A[i + 653*t];
R[i + 654*t] = A[i + 654*t];
R[i + 655*t] = A[i + 655*t];
R[i + 656*t] = A[i + 656*t];
R[i + 657*t] = A[i + 657*t];
R[i + 658*t] = A[i + 658*t];
R[i + 659*t] = A[i + 659*t];
R[i + 660*t] = A[i + 660*t];
R[i + 661*t] = A[i + 661*t];
R[i + 662*t] = A[i + 662*t];
R[i + 663*t] = A[i + 663*t];
R[i + 664*t] = A[i + 664*t];
R[i + 665*t] = A[i + 665*t];
R[i + 666*t] = A[i + 666*t];
R[i + 667*t] = A[i + 667*t];
R[i + 668*t] = A[i + 668*t];
R[i + 669*t] = A[i + 669*t];
R[i + 670*t] = A[i + 670*t];
R[i + 671*t] = A[i + 671*t];
R[i + 672*t] = A[i + 672*t];
R[i + 673*t] = A[i + 673*t];
R[i + 674*t] = A[i + 674*t];
R[i + 675*t] = A[i + 675*t];
R[i + 676*t] = A[i + 676*t];
R[i + 677*t] = A[i + 677*t];
R[i + 678*t] = A[i + 678*t];
R[i + 679*t] = A[i + 679*t];
R[i + 680*t] = A[i + 680*t];
R[i + 681*t] = A[i + 681*t];
R[i + 682*t] = A[i + 682*t];
R[i + 683*t] = A[i + 683*t];
R[i + 684*t] = A[i + 684*t];
R[i + 685*t] = A[i + 685*t];
R[i + 686*t] = A[i + 686*t];
R[i + 687*t] = A[i + 687*t];
R[i + 688*t] = A[i + 688*t];
R[i + 689*t] = A[i + 689*t];
R[i + 690*t] = A[i + 690*t];
R[i + 691*t] = A[i + 691*t];
R[i + 692*t] = A[i + 692*t];
R[i + 693*t] = A[i + 693*t];
R[i + 694*t] = A[i + 694*t];
R[i + 695*t] = A[i + 695*t];
R[i + 696*t] = A[i + 696*t];
R[i + 697*t] = A[i + 697*t];
R[i + 698*t] = A[i + 698*t];
R[i + 699*t] = A[i + 699*t];
R[i + 700*t] = A[i + 700*t];
R[i + 701*t] = A[i + 701*t];
R[i + 702*t] = A[i + 702*t];
R[i + 703*t] = A[i + 703*t];
R[i + 704*t] = A[i + 704*t];
R[i + 705*t] = A[i + 705*t];
R[i + 706*t] = A[i + 706*t];
R[i + 707*t] = A[i + 707*t];
R[i + 708*t] = A[i + 708*t];
R[i + 709*t] = A[i + 709*t];
R[i + 710*t] = A[i + 710*t];
R[i + 711*t] = A[i + 711*t];
R[i + 712*t] = A[i + 712*t];
R[i + 713*t] = A[i + 713*t];
R[i + 714*t] = A[i + 714*t];
R[i + 715*t] = A[i + 715*t];
R[i + 716*t] = A[i + 716*t];
R[i + 717*t] = A[i + 717*t];
R[i + 718*t] = A[i + 718*t];
R[i + 719*t] = A[i + 719*t];
R[i + 720*t] = A[i + 720*t];
R[i + 721*t] = A[i + 721*t];
R[i + 722*t] = A[i + 722*t];
R[i + 723*t] = A[i + 723*t];
R[i + 724*t] = A[i + 724*t];
R[i + 725*t] = A[i + 725*t];
R[i + 726*t] = A[i + 726*t];
R[i + 727*t] = A[i + 727*t];
R[i + 728*t] = A[i + 728*t];
R[i + 729*t] = A[i + 729*t];
R[i + 730*t] = A[i + 730*t];
R[i + 731*t] = A[i + 731*t];
R[i + 732*t] = A[i + 732*t];
R[i + 733*t] = A[i + 733*t];
R[i + 734*t] = A[i + 734*t];
R[i + 735*t] = A[i + 735*t];
R[i + 736*t] = A[i + 736*t];
R[i + 737*t] = A[i + 737*t];
R[i + 738*t] = A[i + 738*t];
R[i + 739*t] = A[i + 739*t];
R[i + 740*t] = A[i + 740*t];
R[i + 741*t] = A[i + 741*t];
R[i + 742*t] = A[i + 742*t];
R[i + 743*t] = A[i + 743*t];
R[i + 744*t] = A[i + 744*t];
R[i + 745*t] = A[i + 745*t];
R[i + 746*t] = A[i + 746*t];
R[i + 747*t] = A[i + 747*t];
R[i + 748*t] = A[i + 748*t];
R[i + 749*t] = A[i + 749*t];
R[i + 750*t] = A[i + 750*t];
R[i + 751*t] = A[i + 751*t];
R[i + 752*t] = A[i + 752*t];
R[i + 753*t] = A[i + 753*t];
R[i + 754*t] = A[i + 754*t];
R[i + 755*t] = A[i + 755*t];
R[i + 756*t] = A[i + 756*t];
R[i + 757*t] = A[i + 757*t];
R[i + 758*t] = A[i + 758*t];
R[i + 759*t] = A[i + 759*t];
R[i + 760*t] = A[i + 760*t];
R[i + 761*t] = A[i + 761*t];
R[i + 762*t] = A[i + 762*t];
R[i + 763*t] = A[i + 763*t];
R[i + 764*t] = A[i + 764*t];
R[i + 765*t] = A[i + 765*t];
R[i + 766*t] = A[i + 766*t];
R[i + 767*t] = A[i + 767*t];
R[i + 768*t] = A[i + 768*t];
R[i + 769*t] = A[i + 769*t];
R[i + 770*t] = A[i + 770*t];
R[i + 771*t] = A[i + 771*t];
R[i + 772*t] = A[i + 772*t];
R[i + 773*t] = A[i + 773*t];
R[i + 774*t] = A[i + 774*t];
R[i + 775*t] = A[i + 775*t];
R[i + 776*t] = A[i + 776*t];
R[i + 777*t] = A[i + 777*t];
R[i + 778*t] = A[i + 778*t];
R[i + 779*t] = A[i + 779*t];
R[i + 780*t] = A[i + 780*t];
R[i + 781*t] = A[i + 781*t];
R[i + 782*t] = A[i + 782*t];
R[i + 783*t] = A[i + 783*t];
R[i + 784*t] = A[i + 784*t];
R[i + 785*t] = A[i + 785*t];
R[i + 786*t] = A[i + 786*t];
R[i + 787*t] = A[i + 787*t];
R[i + 788*t] = A[i + 788*t];
R[i + 789*t] = A[i + 789*t];
R[i + 790*t] = A[i + 790*t];
R[i + 791*t] = A[i + 791*t];
R[i + 792*t] = A[i + 792*t];
R[i + 793*t] = A[i + 793*t];
R[i + 794*t] = A[i + 794*t];
R[i + 795*t] = A[i + 795*t];
R[i + 796*t] = A[i + 796*t];
R[i + 797*t] = A[i + 797*t];
R[i + 798*t] = A[i + 798*t];
R[i + 799*t] = A[i + 799*t];
R[i + 800*t] = A[i + 800*t];
R[i + 801*t] = A[i + 801*t];
R[i + 802*t] = A[i + 802*t];
R[i + 803*t] = A[i + 803*t];
R[i + 804*t] = A[i + 804*t];
R[i + 805*t] = A[i + 805*t];
R[i + 806*t] = A[i + 806*t];
R[i + 807*t] = A[i + 807*t];
R[i + 808*t] = A[i + 808*t];
R[i + 809*t] = A[i + 809*t];
R[i + 810*t] = A[i + 810*t];
R[i + 811*t] = A[i + 811*t];
R[i + 812*t] = A[i + 812*t];
R[i + 813*t] = A[i + 813*t];
R[i + 814*t] = A[i + 814*t];
R[i + 815*t] = A[i + 815*t];
R[i + 816*t] = A[i + 816*t];
R[i + 817*t] = A[i + 817*t];
R[i + 818*t] = A[i + 818*t];
R[i + 819*t] = A[i + 819*t];
R[i + 820*t] = A[i + 820*t];
R[i + 821*t] = A[i + 821*t];
R[i + 822*t] = A[i + 822*t];
R[i + 823*t] = A[i + 823*t];
R[i + 824*t] = A[i + 824*t];
R[i + 825*t] = A[i + 825*t];
R[i + 826*t] = A[i + 826*t];
R[i + 827*t] = A[i + 827*t];
R[i + 828*t] = A[i + 828*t];
R[i + 829*t] = A[i + 829*t];
R[i + 830*t] = A[i + 830*t];
R[i + 831*t] = A[i + 831*t];
R[i + 832*t] = A[i + 832*t];
R[i + 833*t] = A[i + 833*t];
R[i + 834*t] = A[i + 834*t];
R[i + 835*t] = A[i + 835*t];
R[i + 836*t] = A[i + 836*t];
R[i + 837*t] = A[i + 837*t];
R[i + 838*t] = A[i + 838*t];
R[i + 839*t] = A[i + 839*t];
R[i + 840*t] = A[i + 840*t];
R[i + 841*t] = A[i + 841*t];
R[i + 842*t] = A[i + 842*t];
R[i + 843*t] = A[i + 843*t];
R[i + 844*t] = A[i + 844*t];
R[i + 845*t] = A[i + 845*t];
R[i + 846*t] = A[i + 846*t];
R[i + 847*t] = A[i + 847*t];
R[i + 848*t] = A[i + 848*t];
R[i + 849*t] = A[i + 849*t];
R[i + 850*t] = A[i + 850*t];
R[i + 851*t] = A[i + 851*t];
R[i + 852*t] = A[i + 852*t];
__syncthreads();
for (int iter=0; iter< n_iter; iter++) {
R[i + 853*t] = Op[i + 0*t] ? R[B[i + 0*t]] * R[C[i + 0*t]] : R[B[i + 0*t]] + R[C[i + 0*t]];
R[i + 854*t] = Op[i + 1*t] ? R[B[i + 1*t]] * R[C[i + 1*t]] : R[B[i + 1*t]] + R[C[i + 1*t]];
R[i + 855*t] = Op[i + 2*t] ? R[B[i + 2*t]] * R[C[i + 2*t]] : R[B[i + 2*t]] + R[C[i + 2*t]];
R[i + 856*t] = Op[i + 3*t] ? R[B[i + 3*t]] * R[C[i + 3*t]] : R[B[i + 3*t]] + R[C[i + 3*t]];
R[i + 857*t] = Op[i + 4*t] ? R[B[i + 4*t]] * R[C[i + 4*t]] : R[B[i + 4*t]] + R[C[i + 4*t]];
R[i + 858*t] = Op[i + 5*t] ? R[B[i + 5*t]] * R[C[i + 5*t]] : R[B[i + 5*t]] + R[C[i + 5*t]];
R[i + 859*t] = Op[i + 6*t] ? R[B[i + 6*t]] * R[C[i + 6*t]] : R[B[i + 6*t]] + R[C[i + 6*t]];
R[i + 860*t] = Op[i + 7*t] ? R[B[i + 7*t]] * R[C[i + 7*t]] : R[B[i + 7*t]] + R[C[i + 7*t]];
R[i + 861*t] = Op[i + 8*t] ? R[B[i + 8*t]] * R[C[i + 8*t]] : R[B[i + 8*t]] + R[C[i + 8*t]];
R[i + 862*t] = Op[i + 9*t] ? R[B[i + 9*t]] * R[C[i + 9*t]] : R[B[i + 9*t]] + R[C[i + 9*t]];
R[i + 863*t] = Op[i + 10*t] ? R[B[i + 10*t]] * R[C[i + 10*t]] : R[B[i + 10*t]] + R[C[i + 10*t]];
R[i + 864*t] = Op[i + 11*t] ? R[B[i + 11*t]] * R[C[i + 11*t]] : R[B[i + 11*t]] + R[C[i + 11*t]];
R[i + 865*t] = Op[i + 12*t] ? R[B[i + 12*t]] * R[C[i + 12*t]] : R[B[i + 12*t]] + R[C[i + 12*t]];
R[i + 866*t] = Op[i + 13*t] ? R[B[i + 13*t]] * R[C[i + 13*t]] : R[B[i + 13*t]] + R[C[i + 13*t]];
R[i + 867*t] = Op[i + 14*t] ? R[B[i + 14*t]] * R[C[i + 14*t]] : R[B[i + 14*t]] + R[C[i + 14*t]];
R[i + 868*t] = Op[i + 15*t] ? R[B[i + 15*t]] * R[C[i + 15*t]] : R[B[i + 15*t]] + R[C[i + 15*t]];
R[i + 869*t] = Op[i + 16*t] ? R[B[i + 16*t]] * R[C[i + 16*t]] : R[B[i + 16*t]] + R[C[i + 16*t]];
R[i + 870*t] = Op[i + 17*t] ? R[B[i + 17*t]] * R[C[i + 17*t]] : R[B[i + 17*t]] + R[C[i + 17*t]];
R[i + 871*t] = Op[i + 18*t] ? R[B[i + 18*t]] * R[C[i + 18*t]] : R[B[i + 18*t]] + R[C[i + 18*t]];
R[i + 872*t] = Op[i + 19*t] ? R[B[i + 19*t]] * R[C[i + 19*t]] : R[B[i + 19*t]] + R[C[i + 19*t]];
R[i + 873*t] = Op[i + 20*t] ? R[B[i + 20*t]] * R[C[i + 20*t]] : R[B[i + 20*t]] + R[C[i + 20*t]];
R[i + 874*t] = Op[i + 21*t] ? R[B[i + 21*t]] * R[C[i + 21*t]] : R[B[i + 21*t]] + R[C[i + 21*t]];
R[i + 875*t] = Op[i + 22*t] ? R[B[i + 22*t]] * R[C[i + 22*t]] : R[B[i + 22*t]] + R[C[i + 22*t]];
R[i + 876*t] = Op[i + 23*t] ? R[B[i + 23*t]] * R[C[i + 23*t]] : R[B[i + 23*t]] + R[C[i + 23*t]];
R[i + 877*t] = Op[i + 24*t] ? R[B[i + 24*t]] * R[C[i + 24*t]] : R[B[i + 24*t]] + R[C[i + 24*t]];
R[i + 878*t] = Op[i + 25*t] ? R[B[i + 25*t]] * R[C[i + 25*t]] : R[B[i + 25*t]] + R[C[i + 25*t]];
R[i + 879*t] = Op[i + 26*t] ? R[B[i + 26*t]] * R[C[i + 26*t]] : R[B[i + 26*t]] + R[C[i + 26*t]];
R[i + 880*t] = Op[i + 27*t] ? R[B[i + 27*t]] * R[C[i + 27*t]] : R[B[i + 27*t]] + R[C[i + 27*t]];
R[i + 881*t] = Op[i + 28*t] ? R[B[i + 28*t]] * R[C[i + 28*t]] : R[B[i + 28*t]] + R[C[i + 28*t]];
R[i + 882*t] = Op[i + 29*t] ? R[B[i + 29*t]] * R[C[i + 29*t]] : R[B[i + 29*t]] + R[C[i + 29*t]];
R[i + 883*t] = Op[i + 30*t] ? R[B[i + 30*t]] * R[C[i + 30*t]] : R[B[i + 30*t]] + R[C[i + 30*t]];
R[i + 884*t] = Op[i + 31*t] ? R[B[i + 31*t]] * R[C[i + 31*t]] : R[B[i + 31*t]] + R[C[i + 31*t]];
R[i + 885*t] = Op[i + 32*t] ? R[B[i + 32*t]] * R[C[i + 32*t]] : R[B[i + 32*t]] + R[C[i + 32*t]];
R[i + 886*t] = Op[i + 33*t] ? R[B[i + 33*t]] * R[C[i + 33*t]] : R[B[i + 33*t]] + R[C[i + 33*t]];
R[i + 887*t] = Op[i + 34*t] ? R[B[i + 34*t]] * R[C[i + 34*t]] : R[B[i + 34*t]] + R[C[i + 34*t]];
R[i + 888*t] = Op[i + 35*t] ? R[B[i + 35*t]] * R[C[i + 35*t]] : R[B[i + 35*t]] + R[C[i + 35*t]];
R[i + 889*t] = Op[i + 36*t] ? R[B[i + 36*t]] * R[C[i + 36*t]] : R[B[i + 36*t]] + R[C[i + 36*t]];
R[i + 890*t] = Op[i + 37*t] ? R[B[i + 37*t]] * R[C[i + 37*t]] : R[B[i + 37*t]] + R[C[i + 37*t]];
R[i + 891*t] = Op[i + 38*t] ? R[B[i + 38*t]] * R[C[i + 38*t]] : R[B[i + 38*t]] + R[C[i + 38*t]];
R[i + 892*t] = Op[i + 39*t] ? R[B[i + 39*t]] * R[C[i + 39*t]] : R[B[i + 39*t]] + R[C[i + 39*t]];
R[i + 893*t] = Op[i + 40*t] ? R[B[i + 40*t]] * R[C[i + 40*t]] : R[B[i + 40*t]] + R[C[i + 40*t]];
R[i + 894*t] = Op[i + 41*t] ? R[B[i + 41*t]] * R[C[i + 41*t]] : R[B[i + 41*t]] + R[C[i + 41*t]];
R[i + 895*t] = Op[i + 42*t] ? R[B[i + 42*t]] * R[C[i + 42*t]] : R[B[i + 42*t]] + R[C[i + 42*t]];
R[i + 896*t] = Op[i + 43*t] ? R[B[i + 43*t]] * R[C[i + 43*t]] : R[B[i + 43*t]] + R[C[i + 43*t]];
R[i + 897*t] = Op[i + 44*t] ? R[B[i + 44*t]] * R[C[i + 44*t]] : R[B[i + 44*t]] + R[C[i + 44*t]];
R[i + 898*t] = Op[i + 45*t] ? R[B[i + 45*t]] * R[C[i + 45*t]] : R[B[i + 45*t]] + R[C[i + 45*t]];
R[i + 899*t] = Op[i + 46*t] ? R[B[i + 46*t]] * R[C[i + 46*t]] : R[B[i + 46*t]] + R[C[i + 46*t]];
R[i + 900*t] = Op[i + 47*t] ? R[B[i + 47*t]] * R[C[i + 47*t]] : R[B[i + 47*t]] + R[C[i + 47*t]];
R[i + 901*t] = Op[i + 48*t] ? R[B[i + 48*t]] * R[C[i + 48*t]] : R[B[i + 48*t]] + R[C[i + 48*t]];
R[i + 902*t] = Op[i + 49*t] ? R[B[i + 49*t]] * R[C[i + 49*t]] : R[B[i + 49*t]] + R[C[i + 49*t]];
R[i + 903*t] = Op[i + 50*t] ? R[B[i + 50*t]] * R[C[i + 50*t]] : R[B[i + 50*t]] + R[C[i + 50*t]];
R[i + 904*t] = Op[i + 51*t] ? R[B[i + 51*t]] * R[C[i + 51*t]] : R[B[i + 51*t]] + R[C[i + 51*t]];
R[i + 905*t] = Op[i + 52*t] ? R[B[i + 52*t]] * R[C[i + 52*t]] : R[B[i + 52*t]] + R[C[i + 52*t]];
R[i + 906*t] = Op[i + 53*t] ? R[B[i + 53*t]] * R[C[i + 53*t]] : R[B[i + 53*t]] + R[C[i + 53*t]];
R[i + 907*t] = Op[i + 54*t] ? R[B[i + 54*t]] * R[C[i + 54*t]] : R[B[i + 54*t]] + R[C[i + 54*t]];
R[i + 908*t] = Op[i + 55*t] ? R[B[i + 55*t]] * R[C[i + 55*t]] : R[B[i + 55*t]] + R[C[i + 55*t]];
R[i + 909*t] = Op[i + 56*t] ? R[B[i + 56*t]] * R[C[i + 56*t]] : R[B[i + 56*t]] + R[C[i + 56*t]];
R[i + 910*t] = Op[i + 57*t] ? R[B[i + 57*t]] * R[C[i + 57*t]] : R[B[i + 57*t]] + R[C[i + 57*t]];
R[i + 911*t] = Op[i + 58*t] ? R[B[i + 58*t]] * R[C[i + 58*t]] : R[B[i + 58*t]] + R[C[i + 58*t]];
R[i + 912*t] = Op[i + 59*t] ? R[B[i + 59*t]] * R[C[i + 59*t]] : R[B[i + 59*t]] + R[C[i + 59*t]];
R[i + 913*t] = Op[i + 60*t] ? R[B[i + 60*t]] * R[C[i + 60*t]] : R[B[i + 60*t]] + R[C[i + 60*t]];
R[i + 914*t] = Op[i + 61*t] ? R[B[i + 61*t]] * R[C[i + 61*t]] : R[B[i + 61*t]] + R[C[i + 61*t]];
R[i + 915*t] = Op[i + 62*t] ? R[B[i + 62*t]] * R[C[i + 62*t]] : R[B[i + 62*t]] + R[C[i + 62*t]];
R[i + 916*t] = Op[i + 63*t] ? R[B[i + 63*t]] * R[C[i + 63*t]] : R[B[i + 63*t]] + R[C[i + 63*t]];
R[i + 917*t] = Op[i + 64*t] ? R[B[i + 64*t]] * R[C[i + 64*t]] : R[B[i + 64*t]] + R[C[i + 64*t]];
R[i + 918*t] = Op[i + 65*t] ? R[B[i + 65*t]] * R[C[i + 65*t]] : R[B[i + 65*t]] + R[C[i + 65*t]];
R[i + 919*t] = Op[i + 66*t] ? R[B[i + 66*t]] * R[C[i + 66*t]] : R[B[i + 66*t]] + R[C[i + 66*t]];
R[i + 920*t] = Op[i + 67*t] ? R[B[i + 67*t]] * R[C[i + 67*t]] : R[B[i + 67*t]] + R[C[i + 67*t]];
R[i + 921*t] = Op[i + 68*t] ? R[B[i + 68*t]] * R[C[i + 68*t]] : R[B[i + 68*t]] + R[C[i + 68*t]];
R[i + 922*t] = Op[i + 69*t] ? R[B[i + 69*t]] * R[C[i + 69*t]] : R[B[i + 69*t]] + R[C[i + 69*t]];
R[i + 923*t] = Op[i + 70*t] ? R[B[i + 70*t]] * R[C[i + 70*t]] : R[B[i + 70*t]] + R[C[i + 70*t]];
R[i + 924*t] = Op[i + 71*t] ? R[B[i + 71*t]] * R[C[i + 71*t]] : R[B[i + 71*t]] + R[C[i + 71*t]];
R[i + 925*t] = Op[i + 72*t] ? R[B[i + 72*t]] * R[C[i + 72*t]] : R[B[i + 72*t]] + R[C[i + 72*t]];
R[i + 926*t] = Op[i + 73*t] ? R[B[i + 73*t]] * R[C[i + 73*t]] : R[B[i + 73*t]] + R[C[i + 73*t]];
R[i + 927*t] = Op[i + 74*t] ? R[B[i + 74*t]] * R[C[i + 74*t]] : R[B[i + 74*t]] + R[C[i + 74*t]];
R[i + 928*t] = Op[i + 75*t] ? R[B[i + 75*t]] * R[C[i + 75*t]] : R[B[i + 75*t]] + R[C[i + 75*t]];
R[i + 929*t] = Op[i + 76*t] ? R[B[i + 76*t]] * R[C[i + 76*t]] : R[B[i + 76*t]] + R[C[i + 76*t]];
R[i + 930*t] = Op[i + 77*t] ? R[B[i + 77*t]] * R[C[i + 77*t]] : R[B[i + 77*t]] + R[C[i + 77*t]];
R[i + 931*t] = Op[i + 78*t] ? R[B[i + 78*t]] * R[C[i + 78*t]] : R[B[i + 78*t]] + R[C[i + 78*t]];
R[i + 932*t] = Op[i + 79*t] ? R[B[i + 79*t]] * R[C[i + 79*t]] : R[B[i + 79*t]] + R[C[i + 79*t]];
R[i + 933*t] = Op[i + 80*t] ? R[B[i + 80*t]] * R[C[i + 80*t]] : R[B[i + 80*t]] + R[C[i + 80*t]];
R[i + 934*t] = Op[i + 81*t] ? R[B[i + 81*t]] * R[C[i + 81*t]] : R[B[i + 81*t]] + R[C[i + 81*t]];
R[i + 935*t] = Op[i + 82*t] ? R[B[i + 82*t]] * R[C[i + 82*t]] : R[B[i + 82*t]] + R[C[i + 82*t]];
R[i + 936*t] = Op[i + 83*t] ? R[B[i + 83*t]] * R[C[i + 83*t]] : R[B[i + 83*t]] + R[C[i + 83*t]];
R[i + 937*t] = Op[i + 84*t] ? R[B[i + 84*t]] * R[C[i + 84*t]] : R[B[i + 84*t]] + R[C[i + 84*t]];
R[i + 938*t] = Op[i + 85*t] ? R[B[i + 85*t]] * R[C[i + 85*t]] : R[B[i + 85*t]] + R[C[i + 85*t]];
R[i + 939*t] = Op[i + 86*t] ? R[B[i + 86*t]] * R[C[i + 86*t]] : R[B[i + 86*t]] + R[C[i + 86*t]];
R[i + 940*t] = Op[i + 87*t] ? R[B[i + 87*t]] * R[C[i + 87*t]] : R[B[i + 87*t]] + R[C[i + 87*t]];
R[i + 941*t] = Op[i + 88*t] ? R[B[i + 88*t]] * R[C[i + 88*t]] : R[B[i + 88*t]] + R[C[i + 88*t]];
R[i + 942*t] = Op[i + 89*t] ? R[B[i + 89*t]] * R[C[i + 89*t]] : R[B[i + 89*t]] + R[C[i + 89*t]];
R[i + 943*t] = Op[i + 90*t] ? R[B[i + 90*t]] * R[C[i + 90*t]] : R[B[i + 90*t]] + R[C[i + 90*t]];
R[i + 944*t] = Op[i + 91*t] ? R[B[i + 91*t]] * R[C[i + 91*t]] : R[B[i + 91*t]] + R[C[i + 91*t]];
R[i + 945*t] = Op[i + 92*t] ? R[B[i + 92*t]] * R[C[i + 92*t]] : R[B[i + 92*t]] + R[C[i + 92*t]];
R[i + 946*t] = Op[i + 93*t] ? R[B[i + 93*t]] * R[C[i + 93*t]] : R[B[i + 93*t]] + R[C[i + 93*t]];
R[i + 947*t] = Op[i + 94*t] ? R[B[i + 94*t]] * R[C[i + 94*t]] : R[B[i + 94*t]] + R[C[i + 94*t]];
R[i + 948*t] = Op[i + 95*t] ? R[B[i + 95*t]] * R[C[i + 95*t]] : R[B[i + 95*t]] + R[C[i + 95*t]];
R[i + 949*t] = Op[i + 96*t] ? R[B[i + 96*t]] * R[C[i + 96*t]] : R[B[i + 96*t]] + R[C[i + 96*t]];
R[i + 950*t] = Op[i + 97*t] ? R[B[i + 97*t]] * R[C[i + 97*t]] : R[B[i + 97*t]] + R[C[i + 97*t]];
R[i + 951*t] = Op[i + 98*t] ? R[B[i + 98*t]] * R[C[i + 98*t]] : R[B[i + 98*t]] + R[C[i + 98*t]];
R[i + 952*t] = Op[i + 99*t] ? R[B[i + 99*t]] * R[C[i + 99*t]] : R[B[i + 99*t]] + R[C[i + 99*t]];
R[i + 953*t] = Op[i + 100*t] ? R[B[i + 100*t]] * R[C[i + 100*t]] : R[B[i + 100*t]] + R[C[i + 100*t]];
R[i + 954*t] = Op[i + 101*t] ? R[B[i + 101*t]] * R[C[i + 101*t]] : R[B[i + 101*t]] + R[C[i + 101*t]];
R[i + 955*t] = Op[i + 102*t] ? R[B[i + 102*t]] * R[C[i + 102*t]] : R[B[i + 102*t]] + R[C[i + 102*t]];
R[i + 956*t] = Op[i + 103*t] ? R[B[i + 103*t]] * R[C[i + 103*t]] : R[B[i + 103*t]] + R[C[i + 103*t]];
R[i + 957*t] = Op[i + 104*t] ? R[B[i + 104*t]] * R[C[i + 104*t]] : R[B[i + 104*t]] + R[C[i + 104*t]];
R[i + 958*t] = Op[i + 105*t] ? R[B[i + 105*t]] * R[C[i + 105*t]] : R[B[i + 105*t]] + R[C[i + 105*t]];
R[i + 959*t] = Op[i + 106*t] ? R[B[i + 106*t]] * R[C[i + 106*t]] : R[B[i + 106*t]] + R[C[i + 106*t]];
R[i + 960*t] = Op[i + 107*t] ? R[B[i + 107*t]] * R[C[i + 107*t]] : R[B[i + 107*t]] + R[C[i + 107*t]];
R[i + 961*t] = Op[i + 108*t] ? R[B[i + 108*t]] * R[C[i + 108*t]] : R[B[i + 108*t]] + R[C[i + 108*t]];
R[i + 962*t] = Op[i + 109*t] ? R[B[i + 109*t]] * R[C[i + 109*t]] : R[B[i + 109*t]] + R[C[i + 109*t]];
R[i + 963*t] = Op[i + 110*t] ? R[B[i + 110*t]] * R[C[i + 110*t]] : R[B[i + 110*t]] + R[C[i + 110*t]];
R[i + 964*t] = Op[i + 111*t] ? R[B[i + 111*t]] * R[C[i + 111*t]] : R[B[i + 111*t]] + R[C[i + 111*t]];
R[i + 965*t] = Op[i + 112*t] ? R[B[i + 112*t]] * R[C[i + 112*t]] : R[B[i + 112*t]] + R[C[i + 112*t]];
R[i + 966*t] = Op[i + 113*t] ? R[B[i + 113*t]] * R[C[i + 113*t]] : R[B[i + 113*t]] + R[C[i + 113*t]];
R[i + 967*t] = Op[i + 114*t] ? R[B[i + 114*t]] * R[C[i + 114*t]] : R[B[i + 114*t]] + R[C[i + 114*t]];
R[i + 968*t] = Op[i + 115*t] ? R[B[i + 115*t]] * R[C[i + 115*t]] : R[B[i + 115*t]] + R[C[i + 115*t]];
R[i + 969*t] = Op[i + 116*t] ? R[B[i + 116*t]] * R[C[i + 116*t]] : R[B[i + 116*t]] + R[C[i + 116*t]];
R[i + 970*t] = Op[i + 117*t] ? R[B[i + 117*t]] * R[C[i + 117*t]] : R[B[i + 117*t]] + R[C[i + 117*t]];
R[i + 971*t] = Op[i + 118*t] ? R[B[i + 118*t]] * R[C[i + 118*t]] : R[B[i + 118*t]] + R[C[i + 118*t]];
R[i + 972*t] = Op[i + 119*t] ? R[B[i + 119*t]] * R[C[i + 119*t]] : R[B[i + 119*t]] + R[C[i + 119*t]];
R[i + 973*t] = Op[i + 120*t] ? R[B[i + 120*t]] * R[C[i + 120*t]] : R[B[i + 120*t]] + R[C[i + 120*t]];
R[i + 974*t] = Op[i + 121*t] ? R[B[i + 121*t]] * R[C[i + 121*t]] : R[B[i + 121*t]] + R[C[i + 121*t]];
R[i + 975*t] = Op[i + 122*t] ? R[B[i + 122*t]] * R[C[i + 122*t]] : R[B[i + 122*t]] + R[C[i + 122*t]];
R[i + 976*t] = Op[i + 123*t] ? R[B[i + 123*t]] * R[C[i + 123*t]] : R[B[i + 123*t]] + R[C[i + 123*t]];
R[i + 977*t] = Op[i + 124*t] ? R[B[i + 124*t]] * R[C[i + 124*t]] : R[B[i + 124*t]] + R[C[i + 124*t]];
R[i + 978*t] = Op[i + 125*t] ? R[B[i + 125*t]] * R[C[i + 125*t]] : R[B[i + 125*t]] + R[C[i + 125*t]];
R[i + 979*t] = Op[i + 126*t] ? R[B[i + 126*t]] * R[C[i + 126*t]] : R[B[i + 126*t]] + R[C[i + 126*t]];
R[i + 980*t] = Op[i + 127*t] ? R[B[i + 127*t]] * R[C[i + 127*t]] : R[B[i + 127*t]] + R[C[i + 127*t]];
R[i + 981*t] = Op[i + 128*t] ? R[B[i + 128*t]] * R[C[i + 128*t]] : R[B[i + 128*t]] + R[C[i + 128*t]];
R[i + 982*t] = Op[i + 129*t] ? R[B[i + 129*t]] * R[C[i + 129*t]] : R[B[i + 129*t]] + R[C[i + 129*t]];
R[i + 983*t] = Op[i + 130*t] ? R[B[i + 130*t]] * R[C[i + 130*t]] : R[B[i + 130*t]] + R[C[i + 130*t]];
R[i + 984*t] = Op[i + 131*t] ? R[B[i + 131*t]] * R[C[i + 131*t]] : R[B[i + 131*t]] + R[C[i + 131*t]];
R[i + 985*t] = Op[i + 132*t] ? R[B[i + 132*t]] * R[C[i + 132*t]] : R[B[i + 132*t]] + R[C[i + 132*t]];
R[i + 986*t] = Op[i + 133*t] ? R[B[i + 133*t]] * R[C[i + 133*t]] : R[B[i + 133*t]] + R[C[i + 133*t]];
R[i + 987*t] = Op[i + 134*t] ? R[B[i + 134*t]] * R[C[i + 134*t]] : R[B[i + 134*t]] + R[C[i + 134*t]];
R[i + 988*t] = Op[i + 135*t] ? R[B[i + 135*t]] * R[C[i + 135*t]] : R[B[i + 135*t]] + R[C[i + 135*t]];
R[i + 989*t] = Op[i + 136*t] ? R[B[i + 136*t]] * R[C[i + 136*t]] : R[B[i + 136*t]] + R[C[i + 136*t]];
R[i + 990*t] = Op[i + 137*t] ? R[B[i + 137*t]] * R[C[i + 137*t]] : R[B[i + 137*t]] + R[C[i + 137*t]];
R[i + 991*t] = Op[i + 138*t] ? R[B[i + 138*t]] * R[C[i + 138*t]] : R[B[i + 138*t]] + R[C[i + 138*t]];
R[i + 992*t] = Op[i + 139*t] ? R[B[i + 139*t]] * R[C[i + 139*t]] : R[B[i + 139*t]] + R[C[i + 139*t]];
R[i + 993*t] = Op[i + 140*t] ? R[B[i + 140*t]] * R[C[i + 140*t]] : R[B[i + 140*t]] + R[C[i + 140*t]];
R[i + 994*t] = Op[i + 141*t] ? R[B[i + 141*t]] * R[C[i + 141*t]] : R[B[i + 141*t]] + R[C[i + 141*t]];
R[i + 995*t] = Op[i + 142*t] ? R[B[i + 142*t]] * R[C[i + 142*t]] : R[B[i + 142*t]] + R[C[i + 142*t]];
R[i + 996*t] = Op[i + 143*t] ? R[B[i + 143*t]] * R[C[i + 143*t]] : R[B[i + 143*t]] + R[C[i + 143*t]];
R[i + 997*t] = Op[i + 144*t] ? R[B[i + 144*t]] * R[C[i + 144*t]] : R[B[i + 144*t]] + R[C[i + 144*t]];
R[i + 998*t] = Op[i + 145*t] ? R[B[i + 145*t]] * R[C[i + 145*t]] : R[B[i + 145*t]] + R[C[i + 145*t]];
R[i + 999*t] = Op[i + 146*t] ? R[B[i + 146*t]] * R[C[i + 146*t]] : R[B[i + 146*t]] + R[C[i + 146*t]];
R[i + 1000*t] = Op[i + 147*t] ? R[B[i + 147*t]] * R[C[i + 147*t]] : R[B[i + 147*t]] + R[C[i + 147*t]];
R[i + 1001*t] = Op[i + 148*t] ? R[B[i + 148*t]] * R[C[i + 148*t]] : R[B[i + 148*t]] + R[C[i + 148*t]];
R[i + 1002*t] = Op[i + 149*t] ? R[B[i + 149*t]] * R[C[i + 149*t]] : R[B[i + 149*t]] + R[C[i + 149*t]];
R[i + 1003*t] = Op[i + 150*t] ? R[B[i + 150*t]] * R[C[i + 150*t]] : R[B[i + 150*t]] + R[C[i + 150*t]];
R[i + 1004*t] = Op[i + 151*t] ? R[B[i + 151*t]] * R[C[i + 151*t]] : R[B[i + 151*t]] + R[C[i + 151*t]];
R[i + 1005*t] = Op[i + 152*t] ? R[B[i + 152*t]] * R[C[i + 152*t]] : R[B[i + 152*t]] + R[C[i + 152*t]];
R[i + 1006*t] = Op[i + 153*t] ? R[B[i + 153*t]] * R[C[i + 153*t]] : R[B[i + 153*t]] + R[C[i + 153*t]];
R[i + 1007*t] = Op[i + 154*t] ? R[B[i + 154*t]] * R[C[i + 154*t]] : R[B[i + 154*t]] + R[C[i + 154*t]];
R[i + 1008*t] = Op[i + 155*t] ? R[B[i + 155*t]] * R[C[i + 155*t]] : R[B[i + 155*t]] + R[C[i + 155*t]];
R[i + 1009*t] = Op[i + 156*t] ? R[B[i + 156*t]] * R[C[i + 156*t]] : R[B[i + 156*t]] + R[C[i + 156*t]];
R[i + 1010*t] = Op[i + 157*t] ? R[B[i + 157*t]] * R[C[i + 157*t]] : R[B[i + 157*t]] + R[C[i + 157*t]];
R[i + 1011*t] = Op[i + 158*t] ? R[B[i + 158*t]] * R[C[i + 158*t]] : R[B[i + 158*t]] + R[C[i + 158*t]];
R[i + 1012*t] = Op[i + 159*t] ? R[B[i + 159*t]] * R[C[i + 159*t]] : R[B[i + 159*t]] + R[C[i + 159*t]];
R[i + 1013*t] = Op[i + 160*t] ? R[B[i + 160*t]] * R[C[i + 160*t]] : R[B[i + 160*t]] + R[C[i + 160*t]];
R[i + 1014*t] = Op[i + 161*t] ? R[B[i + 161*t]] * R[C[i + 161*t]] : R[B[i + 161*t]] + R[C[i + 161*t]];
R[i + 1015*t] = Op[i + 162*t] ? R[B[i + 162*t]] * R[C[i + 162*t]] : R[B[i + 162*t]] + R[C[i + 162*t]];
R[i + 1016*t] = Op[i + 163*t] ? R[B[i + 163*t]] * R[C[i + 163*t]] : R[B[i + 163*t]] + R[C[i + 163*t]];
R[i + 1017*t] = Op[i + 164*t] ? R[B[i + 164*t]] * R[C[i + 164*t]] : R[B[i + 164*t]] + R[C[i + 164*t]];
R[i + 1018*t] = Op[i + 165*t] ? R[B[i + 165*t]] * R[C[i + 165*t]] : R[B[i + 165*t]] + R[C[i + 165*t]];
R[i + 1019*t] = Op[i + 166*t] ? R[B[i + 166*t]] * R[C[i + 166*t]] : R[B[i + 166*t]] + R[C[i + 166*t]];
R[i + 1020*t] = Op[i + 167*t] ? R[B[i + 167*t]] * R[C[i + 167*t]] : R[B[i + 167*t]] + R[C[i + 167*t]];
R[i + 1021*t] = Op[i + 168*t] ? R[B[i + 168*t]] * R[C[i + 168*t]] : R[B[i + 168*t]] + R[C[i + 168*t]];
R[i + 1022*t] = Op[i + 169*t] ? R[B[i + 169*t]] * R[C[i + 169*t]] : R[B[i + 169*t]] + R[C[i + 169*t]];
R[i + 1023*t] = Op[i + 170*t] ? R[B[i + 170*t]] * R[C[i + 170*t]] : R[B[i + 170*t]] + R[C[i + 170*t]];
R[i + 1024*t] = Op[i + 171*t] ? R[B[i + 171*t]] * R[C[i + 171*t]] : R[B[i + 171*t]] + R[C[i + 171*t]];
R[i + 1025*t] = Op[i + 172*t] ? R[B[i + 172*t]] * R[C[i + 172*t]] : R[B[i + 172*t]] + R[C[i + 172*t]];
R[i + 1026*t] = Op[i + 173*t] ? R[B[i + 173*t]] * R[C[i + 173*t]] : R[B[i + 173*t]] + R[C[i + 173*t]];
R[i + 1027*t] = Op[i + 174*t] ? R[B[i + 174*t]] * R[C[i + 174*t]] : R[B[i + 174*t]] + R[C[i + 174*t]];
R[i + 1028*t] = Op[i + 175*t] ? R[B[i + 175*t]] * R[C[i + 175*t]] : R[B[i + 175*t]] + R[C[i + 175*t]];
R[i + 1029*t] = Op[i + 176*t] ? R[B[i + 176*t]] * R[C[i + 176*t]] : R[B[i + 176*t]] + R[C[i + 176*t]];
R[i + 1030*t] = Op[i + 177*t] ? R[B[i + 177*t]] * R[C[i + 177*t]] : R[B[i + 177*t]] + R[C[i + 177*t]];
R[i + 1031*t] = Op[i + 178*t] ? R[B[i + 178*t]] * R[C[i + 178*t]] : R[B[i + 178*t]] + R[C[i + 178*t]];
R[i + 1032*t] = Op[i + 179*t] ? R[B[i + 179*t]] * R[C[i + 179*t]] : R[B[i + 179*t]] + R[C[i + 179*t]];
R[i + 1033*t] = Op[i + 180*t] ? R[B[i + 180*t]] * R[C[i + 180*t]] : R[B[i + 180*t]] + R[C[i + 180*t]];
R[i + 1034*t] = Op[i + 181*t] ? R[B[i + 181*t]] * R[C[i + 181*t]] : R[B[i + 181*t]] + R[C[i + 181*t]];
R[i + 1035*t] = Op[i + 182*t] ? R[B[i + 182*t]] * R[C[i + 182*t]] : R[B[i + 182*t]] + R[C[i + 182*t]];
R[i + 1036*t] = Op[i + 183*t] ? R[B[i + 183*t]] * R[C[i + 183*t]] : R[B[i + 183*t]] + R[C[i + 183*t]];
R[i + 1037*t] = Op[i + 184*t] ? R[B[i + 184*t]] * R[C[i + 184*t]] : R[B[i + 184*t]] + R[C[i + 184*t]];
R[i + 1038*t] = Op[i + 185*t] ? R[B[i + 185*t]] * R[C[i + 185*t]] : R[B[i + 185*t]] + R[C[i + 185*t]];
R[i + 1039*t] = Op[i + 186*t] ? R[B[i + 186*t]] * R[C[i + 186*t]] : R[B[i + 186*t]] + R[C[i + 186*t]];
R[i + 1040*t] = Op[i + 187*t] ? R[B[i + 187*t]] * R[C[i + 187*t]] : R[B[i + 187*t]] + R[C[i + 187*t]];
R[i + 1041*t] = Op[i + 188*t] ? R[B[i + 188*t]] * R[C[i + 188*t]] : R[B[i + 188*t]] + R[C[i + 188*t]];
R[i + 1042*t] = Op[i + 189*t] ? R[B[i + 189*t]] * R[C[i + 189*t]] : R[B[i + 189*t]] + R[C[i + 189*t]];
R[i + 1043*t] = Op[i + 190*t] ? R[B[i + 190*t]] * R[C[i + 190*t]] : R[B[i + 190*t]] + R[C[i + 190*t]];
R[i + 1044*t] = Op[i + 191*t] ? R[B[i + 191*t]] * R[C[i + 191*t]] : R[B[i + 191*t]] + R[C[i + 191*t]];
R[i + 1045*t] = Op[i + 192*t] ? R[B[i + 192*t]] * R[C[i + 192*t]] : R[B[i + 192*t]] + R[C[i + 192*t]];
R[i + 1046*t] = Op[i + 193*t] ? R[B[i + 193*t]] * R[C[i + 193*t]] : R[B[i + 193*t]] + R[C[i + 193*t]];
R[i + 1047*t] = Op[i + 194*t] ? R[B[i + 194*t]] * R[C[i + 194*t]] : R[B[i + 194*t]] + R[C[i + 194*t]];
R[i + 1048*t] = Op[i + 195*t] ? R[B[i + 195*t]] * R[C[i + 195*t]] : R[B[i + 195*t]] + R[C[i + 195*t]];
R[i + 1049*t] = Op[i + 196*t] ? R[B[i + 196*t]] * R[C[i + 196*t]] : R[B[i + 196*t]] + R[C[i + 196*t]];
R[i + 1050*t] = Op[i + 197*t] ? R[B[i + 197*t]] * R[C[i + 197*t]] : R[B[i + 197*t]] + R[C[i + 197*t]];
R[i + 1051*t] = Op[i + 198*t] ? R[B[i + 198*t]] * R[C[i + 198*t]] : R[B[i + 198*t]] + R[C[i + 198*t]];
R[i + 1052*t] = Op[i + 199*t] ? R[B[i + 199*t]] * R[C[i + 199*t]] : R[B[i + 199*t]] + R[C[i + 199*t]];
R[i + 1053*t] = Op[i + 200*t] ? R[B[i + 200*t]] * R[C[i + 200*t]] : R[B[i + 200*t]] + R[C[i + 200*t]];
R[i + 1054*t] = Op[i + 201*t] ? R[B[i + 201*t]] * R[C[i + 201*t]] : R[B[i + 201*t]] + R[C[i + 201*t]];
R[i + 1055*t] = Op[i + 202*t] ? R[B[i + 202*t]] * R[C[i + 202*t]] : R[B[i + 202*t]] + R[C[i + 202*t]];
R[i + 1056*t] = Op[i + 203*t] ? R[B[i + 203*t]] * R[C[i + 203*t]] : R[B[i + 203*t]] + R[C[i + 203*t]];
R[i + 1057*t] = Op[i + 204*t] ? R[B[i + 204*t]] * R[C[i + 204*t]] : R[B[i + 204*t]] + R[C[i + 204*t]];
R[i + 1058*t] = Op[i + 205*t] ? R[B[i + 205*t]] * R[C[i + 205*t]] : R[B[i + 205*t]] + R[C[i + 205*t]];
R[i + 1059*t] = Op[i + 206*t] ? R[B[i + 206*t]] * R[C[i + 206*t]] : R[B[i + 206*t]] + R[C[i + 206*t]];
R[i + 1060*t] = Op[i + 207*t] ? R[B[i + 207*t]] * R[C[i + 207*t]] : R[B[i + 207*t]] + R[C[i + 207*t]];
R[i + 1061*t] = Op[i + 208*t] ? R[B[i + 208*t]] * R[C[i + 208*t]] : R[B[i + 208*t]] + R[C[i + 208*t]];
R[i + 1062*t] = Op[i + 209*t] ? R[B[i + 209*t]] * R[C[i + 209*t]] : R[B[i + 209*t]] + R[C[i + 209*t]];
R[i + 1063*t] = Op[i + 210*t] ? R[B[i + 210*t]] * R[C[i + 210*t]] : R[B[i + 210*t]] + R[C[i + 210*t]];
R[i + 1064*t] = Op[i + 211*t] ? R[B[i + 211*t]] * R[C[i + 211*t]] : R[B[i + 211*t]] + R[C[i + 211*t]];
R[i + 1065*t] = Op[i + 212*t] ? R[B[i + 212*t]] * R[C[i + 212*t]] : R[B[i + 212*t]] + R[C[i + 212*t]];
R[i + 1066*t] = Op[i + 213*t] ? R[B[i + 213*t]] * R[C[i + 213*t]] : R[B[i + 213*t]] + R[C[i + 213*t]];
R[i + 1067*t] = Op[i + 214*t] ? R[B[i + 214*t]] * R[C[i + 214*t]] : R[B[i + 214*t]] + R[C[i + 214*t]];
R[i + 1068*t] = Op[i + 215*t] ? R[B[i + 215*t]] * R[C[i + 215*t]] : R[B[i + 215*t]] + R[C[i + 215*t]];
R[i + 1069*t] = Op[i + 216*t] ? R[B[i + 216*t]] * R[C[i + 216*t]] : R[B[i + 216*t]] + R[C[i + 216*t]];
R[i + 1070*t] = Op[i + 217*t] ? R[B[i + 217*t]] * R[C[i + 217*t]] : R[B[i + 217*t]] + R[C[i + 217*t]];
R[i + 1071*t] = Op[i + 218*t] ? R[B[i + 218*t]] * R[C[i + 218*t]] : R[B[i + 218*t]] + R[C[i + 218*t]];
R[i + 1072*t] = Op[i + 219*t] ? R[B[i + 219*t]] * R[C[i + 219*t]] : R[B[i + 219*t]] + R[C[i + 219*t]];
R[i + 1073*t] = Op[i + 220*t] ? R[B[i + 220*t]] * R[C[i + 220*t]] : R[B[i + 220*t]] + R[C[i + 220*t]];
R[i + 1074*t] = Op[i + 221*t] ? R[B[i + 221*t]] * R[C[i + 221*t]] : R[B[i + 221*t]] + R[C[i + 221*t]];
R[i + 1075*t] = Op[i + 222*t] ? R[B[i + 222*t]] * R[C[i + 222*t]] : R[B[i + 222*t]] + R[C[i + 222*t]];
R[i + 1076*t] = Op[i + 223*t] ? R[B[i + 223*t]] * R[C[i + 223*t]] : R[B[i + 223*t]] + R[C[i + 223*t]];
R[i + 1077*t] = Op[i + 224*t] ? R[B[i + 224*t]] * R[C[i + 224*t]] : R[B[i + 224*t]] + R[C[i + 224*t]];
R[i + 1078*t] = Op[i + 225*t] ? R[B[i + 225*t]] * R[C[i + 225*t]] : R[B[i + 225*t]] + R[C[i + 225*t]];
R[i + 1079*t] = Op[i + 226*t] ? R[B[i + 226*t]] * R[C[i + 226*t]] : R[B[i + 226*t]] + R[C[i + 226*t]];
R[i + 1080*t] = Op[i + 227*t] ? R[B[i + 227*t]] * R[C[i + 227*t]] : R[B[i + 227*t]] + R[C[i + 227*t]];
R[i + 1081*t] = Op[i + 228*t] ? R[B[i + 228*t]] * R[C[i + 228*t]] : R[B[i + 228*t]] + R[C[i + 228*t]];
R[i + 1082*t] = Op[i + 229*t] ? R[B[i + 229*t]] * R[C[i + 229*t]] : R[B[i + 229*t]] + R[C[i + 229*t]];
R[i + 1083*t] = Op[i + 230*t] ? R[B[i + 230*t]] * R[C[i + 230*t]] : R[B[i + 230*t]] + R[C[i + 230*t]];
R[i + 1084*t] = Op[i + 231*t] ? R[B[i + 231*t]] * R[C[i + 231*t]] : R[B[i + 231*t]] + R[C[i + 231*t]];
R[i + 1085*t] = Op[i + 232*t] ? R[B[i + 232*t]] * R[C[i + 232*t]] : R[B[i + 232*t]] + R[C[i + 232*t]];
R[i + 1086*t] = Op[i + 233*t] ? R[B[i + 233*t]] * R[C[i + 233*t]] : R[B[i + 233*t]] + R[C[i + 233*t]];
R[i + 1087*t] = Op[i + 234*t] ? R[B[i + 234*t]] * R[C[i + 234*t]] : R[B[i + 234*t]] + R[C[i + 234*t]];
R[i + 1088*t] = Op[i + 235*t] ? R[B[i + 235*t]] * R[C[i + 235*t]] : R[B[i + 235*t]] + R[C[i + 235*t]];
R[i + 1089*t] = Op[i + 236*t] ? R[B[i + 236*t]] * R[C[i + 236*t]] : R[B[i + 236*t]] + R[C[i + 236*t]];
R[i + 1090*t] = Op[i + 237*t] ? R[B[i + 237*t]] * R[C[i + 237*t]] : R[B[i + 237*t]] + R[C[i + 237*t]];
R[i + 1091*t] = Op[i + 238*t] ? R[B[i + 238*t]] * R[C[i + 238*t]] : R[B[i + 238*t]] + R[C[i + 238*t]];
R[i + 1092*t] = Op[i + 239*t] ? R[B[i + 239*t]] * R[C[i + 239*t]] : R[B[i + 239*t]] + R[C[i + 239*t]];
__syncthreads();
R[i + 1093*t] = Op[i + 240*t] ? R[B[i + 240*t]] * R[C[i + 240*t]] : R[B[i + 240*t]] + R[C[i + 240*t]];
R[i + 1094*t] = Op[i + 241*t] ? R[B[i + 241*t]] * R[C[i + 241*t]] : R[B[i + 241*t]] + R[C[i + 241*t]];
R[i + 1095*t] = Op[i + 242*t] ? R[B[i + 242*t]] * R[C[i + 242*t]] : R[B[i + 242*t]] + R[C[i + 242*t]];
R[i + 1096*t] = Op[i + 243*t] ? R[B[i + 243*t]] * R[C[i + 243*t]] : R[B[i + 243*t]] + R[C[i + 243*t]];
R[i + 1097*t] = Op[i + 244*t] ? R[B[i + 244*t]] * R[C[i + 244*t]] : R[B[i + 244*t]] + R[C[i + 244*t]];
R[i + 1098*t] = Op[i + 245*t] ? R[B[i + 245*t]] * R[C[i + 245*t]] : R[B[i + 245*t]] + R[C[i + 245*t]];
R[i + 1099*t] = Op[i + 246*t] ? R[B[i + 246*t]] * R[C[i + 246*t]] : R[B[i + 246*t]] + R[C[i + 246*t]];
R[i + 1100*t] = Op[i + 247*t] ? R[B[i + 247*t]] * R[C[i + 247*t]] : R[B[i + 247*t]] + R[C[i + 247*t]];
R[i + 1101*t] = Op[i + 248*t] ? R[B[i + 248*t]] * R[C[i + 248*t]] : R[B[i + 248*t]] + R[C[i + 248*t]];
R[i + 1102*t] = Op[i + 249*t] ? R[B[i + 249*t]] * R[C[i + 249*t]] : R[B[i + 249*t]] + R[C[i + 249*t]];
R[i + 1103*t] = Op[i + 250*t] ? R[B[i + 250*t]] * R[C[i + 250*t]] : R[B[i + 250*t]] + R[C[i + 250*t]];
R[i + 1104*t] = Op[i + 251*t] ? R[B[i + 251*t]] * R[C[i + 251*t]] : R[B[i + 251*t]] + R[C[i + 251*t]];
R[i + 1105*t] = Op[i + 252*t] ? R[B[i + 252*t]] * R[C[i + 252*t]] : R[B[i + 252*t]] + R[C[i + 252*t]];
R[i + 1106*t] = Op[i + 253*t] ? R[B[i + 253*t]] * R[C[i + 253*t]] : R[B[i + 253*t]] + R[C[i + 253*t]];
R[i + 1107*t] = Op[i + 254*t] ? R[B[i + 254*t]] * R[C[i + 254*t]] : R[B[i + 254*t]] + R[C[i + 254*t]];
R[i + 1108*t] = Op[i + 255*t] ? R[B[i + 255*t]] * R[C[i + 255*t]] : R[B[i + 255*t]] + R[C[i + 255*t]];
R[i + 1109*t] = Op[i + 256*t] ? R[B[i + 256*t]] * R[C[i + 256*t]] : R[B[i + 256*t]] + R[C[i + 256*t]];
R[i + 1110*t] = Op[i + 257*t] ? R[B[i + 257*t]] * R[C[i + 257*t]] : R[B[i + 257*t]] + R[C[i + 257*t]];
R[i + 1111*t] = Op[i + 258*t] ? R[B[i + 258*t]] * R[C[i + 258*t]] : R[B[i + 258*t]] + R[C[i + 258*t]];
R[i + 1112*t] = Op[i + 259*t] ? R[B[i + 259*t]] * R[C[i + 259*t]] : R[B[i + 259*t]] + R[C[i + 259*t]];
R[i + 1113*t] = Op[i + 260*t] ? R[B[i + 260*t]] * R[C[i + 260*t]] : R[B[i + 260*t]] + R[C[i + 260*t]];
R[i + 1114*t] = Op[i + 261*t] ? R[B[i + 261*t]] * R[C[i + 261*t]] : R[B[i + 261*t]] + R[C[i + 261*t]];
R[i + 1115*t] = Op[i + 262*t] ? R[B[i + 262*t]] * R[C[i + 262*t]] : R[B[i + 262*t]] + R[C[i + 262*t]];
R[i + 1116*t] = Op[i + 263*t] ? R[B[i + 263*t]] * R[C[i + 263*t]] : R[B[i + 263*t]] + R[C[i + 263*t]];
R[i + 1117*t] = Op[i + 264*t] ? R[B[i + 264*t]] * R[C[i + 264*t]] : R[B[i + 264*t]] + R[C[i + 264*t]];
R[i + 1118*t] = Op[i + 265*t] ? R[B[i + 265*t]] * R[C[i + 265*t]] : R[B[i + 265*t]] + R[C[i + 265*t]];
R[i + 1119*t] = Op[i + 266*t] ? R[B[i + 266*t]] * R[C[i + 266*t]] : R[B[i + 266*t]] + R[C[i + 266*t]];
R[i + 1120*t] = Op[i + 267*t] ? R[B[i + 267*t]] * R[C[i + 267*t]] : R[B[i + 267*t]] + R[C[i + 267*t]];
R[i + 1121*t] = Op[i + 268*t] ? R[B[i + 268*t]] * R[C[i + 268*t]] : R[B[i + 268*t]] + R[C[i + 268*t]];
R[i + 1122*t] = Op[i + 269*t] ? R[B[i + 269*t]] * R[C[i + 269*t]] : R[B[i + 269*t]] + R[C[i + 269*t]];
R[i + 1123*t] = Op[i + 270*t] ? R[B[i + 270*t]] * R[C[i + 270*t]] : R[B[i + 270*t]] + R[C[i + 270*t]];
R[i + 1124*t] = Op[i + 271*t] ? R[B[i + 271*t]] * R[C[i + 271*t]] : R[B[i + 271*t]] + R[C[i + 271*t]];
R[i + 1125*t] = Op[i + 272*t] ? R[B[i + 272*t]] * R[C[i + 272*t]] : R[B[i + 272*t]] + R[C[i + 272*t]];
R[i + 1126*t] = Op[i + 273*t] ? R[B[i + 273*t]] * R[C[i + 273*t]] : R[B[i + 273*t]] + R[C[i + 273*t]];
R[i + 1127*t] = Op[i + 274*t] ? R[B[i + 274*t]] * R[C[i + 274*t]] : R[B[i + 274*t]] + R[C[i + 274*t]];
R[i + 1128*t] = Op[i + 275*t] ? R[B[i + 275*t]] * R[C[i + 275*t]] : R[B[i + 275*t]] + R[C[i + 275*t]];
R[i + 1129*t] = Op[i + 276*t] ? R[B[i + 276*t]] * R[C[i + 276*t]] : R[B[i + 276*t]] + R[C[i + 276*t]];
R[i + 1130*t] = Op[i + 277*t] ? R[B[i + 277*t]] * R[C[i + 277*t]] : R[B[i + 277*t]] + R[C[i + 277*t]];
R[i + 1131*t] = Op[i + 278*t] ? R[B[i + 278*t]] * R[C[i + 278*t]] : R[B[i + 278*t]] + R[C[i + 278*t]];
R[i + 1132*t] = Op[i + 279*t] ? R[B[i + 279*t]] * R[C[i + 279*t]] : R[B[i + 279*t]] + R[C[i + 279*t]];
R[i + 1133*t] = Op[i + 280*t] ? R[B[i + 280*t]] * R[C[i + 280*t]] : R[B[i + 280*t]] + R[C[i + 280*t]];
R[i + 1134*t] = Op[i + 281*t] ? R[B[i + 281*t]] * R[C[i + 281*t]] : R[B[i + 281*t]] + R[C[i + 281*t]];
R[i + 1135*t] = Op[i + 282*t] ? R[B[i + 282*t]] * R[C[i + 282*t]] : R[B[i + 282*t]] + R[C[i + 282*t]];
R[i + 1136*t] = Op[i + 283*t] ? R[B[i + 283*t]] * R[C[i + 283*t]] : R[B[i + 283*t]] + R[C[i + 283*t]];
R[i + 1137*t] = Op[i + 284*t] ? R[B[i + 284*t]] * R[C[i + 284*t]] : R[B[i + 284*t]] + R[C[i + 284*t]];
R[i + 1138*t] = Op[i + 285*t] ? R[B[i + 285*t]] * R[C[i + 285*t]] : R[B[i + 285*t]] + R[C[i + 285*t]];
R[i + 1139*t] = Op[i + 286*t] ? R[B[i + 286*t]] * R[C[i + 286*t]] : R[B[i + 286*t]] + R[C[i + 286*t]];
R[i + 1140*t] = Op[i + 287*t] ? R[B[i + 287*t]] * R[C[i + 287*t]] : R[B[i + 287*t]] + R[C[i + 287*t]];
R[i + 1141*t] = Op[i + 288*t] ? R[B[i + 288*t]] * R[C[i + 288*t]] : R[B[i + 288*t]] + R[C[i + 288*t]];
R[i + 1142*t] = Op[i + 289*t] ? R[B[i + 289*t]] * R[C[i + 289*t]] : R[B[i + 289*t]] + R[C[i + 289*t]];
R[i + 1143*t] = Op[i + 290*t] ? R[B[i + 290*t]] * R[C[i + 290*t]] : R[B[i + 290*t]] + R[C[i + 290*t]];
R[i + 1144*t] = Op[i + 291*t] ? R[B[i + 291*t]] * R[C[i + 291*t]] : R[B[i + 291*t]] + R[C[i + 291*t]];
R[i + 1145*t] = Op[i + 292*t] ? R[B[i + 292*t]] * R[C[i + 292*t]] : R[B[i + 292*t]] + R[C[i + 292*t]];
R[i + 1146*t] = Op[i + 293*t] ? R[B[i + 293*t]] * R[C[i + 293*t]] : R[B[i + 293*t]] + R[C[i + 293*t]];
R[i + 1147*t] = Op[i + 294*t] ? R[B[i + 294*t]] * R[C[i + 294*t]] : R[B[i + 294*t]] + R[C[i + 294*t]];
R[i + 1148*t] = Op[i + 295*t] ? R[B[i + 295*t]] * R[C[i + 295*t]] : R[B[i + 295*t]] + R[C[i + 295*t]];
R[i + 1149*t] = Op[i + 296*t] ? R[B[i + 296*t]] * R[C[i + 296*t]] : R[B[i + 296*t]] + R[C[i + 296*t]];
R[i + 1150*t] = Op[i + 297*t] ? R[B[i + 297*t]] * R[C[i + 297*t]] : R[B[i + 297*t]] + R[C[i + 297*t]];
R[i + 1151*t] = Op[i + 298*t] ? R[B[i + 298*t]] * R[C[i + 298*t]] : R[B[i + 298*t]] + R[C[i + 298*t]];
R[i + 1152*t] = Op[i + 299*t] ? R[B[i + 299*t]] * R[C[i + 299*t]] : R[B[i + 299*t]] + R[C[i + 299*t]];
R[i + 1153*t] = Op[i + 300*t] ? R[B[i + 300*t]] * R[C[i + 300*t]] : R[B[i + 300*t]] + R[C[i + 300*t]];
R[i + 1154*t] = Op[i + 301*t] ? R[B[i + 301*t]] * R[C[i + 301*t]] : R[B[i + 301*t]] + R[C[i + 301*t]];
R[i + 1155*t] = Op[i + 302*t] ? R[B[i + 302*t]] * R[C[i + 302*t]] : R[B[i + 302*t]] + R[C[i + 302*t]];
R[i + 1156*t] = Op[i + 303*t] ? R[B[i + 303*t]] * R[C[i + 303*t]] : R[B[i + 303*t]] + R[C[i + 303*t]];
R[i + 1157*t] = Op[i + 304*t] ? R[B[i + 304*t]] * R[C[i + 304*t]] : R[B[i + 304*t]] + R[C[i + 304*t]];
R[i + 1158*t] = Op[i + 305*t] ? R[B[i + 305*t]] * R[C[i + 305*t]] : R[B[i + 305*t]] + R[C[i + 305*t]];
R[i + 1159*t] = Op[i + 306*t] ? R[B[i + 306*t]] * R[C[i + 306*t]] : R[B[i + 306*t]] + R[C[i + 306*t]];
R[i + 1160*t] = Op[i + 307*t] ? R[B[i + 307*t]] * R[C[i + 307*t]] : R[B[i + 307*t]] + R[C[i + 307*t]];
R[i + 1161*t] = Op[i + 308*t] ? R[B[i + 308*t]] * R[C[i + 308*t]] : R[B[i + 308*t]] + R[C[i + 308*t]];
R[i + 1162*t] = Op[i + 309*t] ? R[B[i + 309*t]] * R[C[i + 309*t]] : R[B[i + 309*t]] + R[C[i + 309*t]];
R[i + 1163*t] = Op[i + 310*t] ? R[B[i + 310*t]] * R[C[i + 310*t]] : R[B[i + 310*t]] + R[C[i + 310*t]];
R[i + 1164*t] = Op[i + 311*t] ? R[B[i + 311*t]] * R[C[i + 311*t]] : R[B[i + 311*t]] + R[C[i + 311*t]];
R[i + 1165*t] = Op[i + 312*t] ? R[B[i + 312*t]] * R[C[i + 312*t]] : R[B[i + 312*t]] + R[C[i + 312*t]];
R[i + 1166*t] = Op[i + 313*t] ? R[B[i + 313*t]] * R[C[i + 313*t]] : R[B[i + 313*t]] + R[C[i + 313*t]];
R[i + 1167*t] = Op[i + 314*t] ? R[B[i + 314*t]] * R[C[i + 314*t]] : R[B[i + 314*t]] + R[C[i + 314*t]];
R[i + 1168*t] = Op[i + 315*t] ? R[B[i + 315*t]] * R[C[i + 315*t]] : R[B[i + 315*t]] + R[C[i + 315*t]];
R[i + 1169*t] = Op[i + 316*t] ? R[B[i + 316*t]] * R[C[i + 316*t]] : R[B[i + 316*t]] + R[C[i + 316*t]];
R[i + 1170*t] = Op[i + 317*t] ? R[B[i + 317*t]] * R[C[i + 317*t]] : R[B[i + 317*t]] + R[C[i + 317*t]];
R[i + 1171*t] = Op[i + 318*t] ? R[B[i + 318*t]] * R[C[i + 318*t]] : R[B[i + 318*t]] + R[C[i + 318*t]];
R[i + 1172*t] = Op[i + 319*t] ? R[B[i + 319*t]] * R[C[i + 319*t]] : R[B[i + 319*t]] + R[C[i + 319*t]];
R[i + 1173*t] = Op[i + 320*t] ? R[B[i + 320*t]] * R[C[i + 320*t]] : R[B[i + 320*t]] + R[C[i + 320*t]];
R[i + 1174*t] = Op[i + 321*t] ? R[B[i + 321*t]] * R[C[i + 321*t]] : R[B[i + 321*t]] + R[C[i + 321*t]];
R[i + 1175*t] = Op[i + 322*t] ? R[B[i + 322*t]] * R[C[i + 322*t]] : R[B[i + 322*t]] + R[C[i + 322*t]];
R[i + 1176*t] = Op[i + 323*t] ? R[B[i + 323*t]] * R[C[i + 323*t]] : R[B[i + 323*t]] + R[C[i + 323*t]];
R[i + 1177*t] = Op[i + 324*t] ? R[B[i + 324*t]] * R[C[i + 324*t]] : R[B[i + 324*t]] + R[C[i + 324*t]];
R[i + 1178*t] = Op[i + 325*t] ? R[B[i + 325*t]] * R[C[i + 325*t]] : R[B[i + 325*t]] + R[C[i + 325*t]];
R[i + 1179*t] = Op[i + 326*t] ? R[B[i + 326*t]] * R[C[i + 326*t]] : R[B[i + 326*t]] + R[C[i + 326*t]];
R[i + 1180*t] = Op[i + 327*t] ? R[B[i + 327*t]] * R[C[i + 327*t]] : R[B[i + 327*t]] + R[C[i + 327*t]];
R[i + 1181*t] = Op[i + 328*t] ? R[B[i + 328*t]] * R[C[i + 328*t]] : R[B[i + 328*t]] + R[C[i + 328*t]];
R[i + 1182*t] = Op[i + 329*t] ? R[B[i + 329*t]] * R[C[i + 329*t]] : R[B[i + 329*t]] + R[C[i + 329*t]];
R[i + 1183*t] = Op[i + 330*t] ? R[B[i + 330*t]] * R[C[i + 330*t]] : R[B[i + 330*t]] + R[C[i + 330*t]];
R[i + 1184*t] = Op[i + 331*t] ? R[B[i + 331*t]] * R[C[i + 331*t]] : R[B[i + 331*t]] + R[C[i + 331*t]];
R[i + 1185*t] = Op[i + 332*t] ? R[B[i + 332*t]] * R[C[i + 332*t]] : R[B[i + 332*t]] + R[C[i + 332*t]];
R[i + 1186*t] = Op[i + 333*t] ? R[B[i + 333*t]] * R[C[i + 333*t]] : R[B[i + 333*t]] + R[C[i + 333*t]];
R[i + 1187*t] = Op[i + 334*t] ? R[B[i + 334*t]] * R[C[i + 334*t]] : R[B[i + 334*t]] + R[C[i + 334*t]];
R[i + 1188*t] = Op[i + 335*t] ? R[B[i + 335*t]] * R[C[i + 335*t]] : R[B[i + 335*t]] + R[C[i + 335*t]];
R[i + 1189*t] = Op[i + 336*t] ? R[B[i + 336*t]] * R[C[i + 336*t]] : R[B[i + 336*t]] + R[C[i + 336*t]];
R[i + 1190*t] = Op[i + 337*t] ? R[B[i + 337*t]] * R[C[i + 337*t]] : R[B[i + 337*t]] + R[C[i + 337*t]];
R[i + 1191*t] = Op[i + 338*t] ? R[B[i + 338*t]] * R[C[i + 338*t]] : R[B[i + 338*t]] + R[C[i + 338*t]];
R[i + 1192*t] = Op[i + 339*t] ? R[B[i + 339*t]] * R[C[i + 339*t]] : R[B[i + 339*t]] + R[C[i + 339*t]];
R[i + 1193*t] = Op[i + 340*t] ? R[B[i + 340*t]] * R[C[i + 340*t]] : R[B[i + 340*t]] + R[C[i + 340*t]];
R[i + 1194*t] = Op[i + 341*t] ? R[B[i + 341*t]] * R[C[i + 341*t]] : R[B[i + 341*t]] + R[C[i + 341*t]];
R[i + 1195*t] = Op[i + 342*t] ? R[B[i + 342*t]] * R[C[i + 342*t]] : R[B[i + 342*t]] + R[C[i + 342*t]];
R[i + 1196*t] = Op[i + 343*t] ? R[B[i + 343*t]] * R[C[i + 343*t]] : R[B[i + 343*t]] + R[C[i + 343*t]];
R[i + 1197*t] = Op[i + 344*t] ? R[B[i + 344*t]] * R[C[i + 344*t]] : R[B[i + 344*t]] + R[C[i + 344*t]];
R[i + 1198*t] = Op[i + 345*t] ? R[B[i + 345*t]] * R[C[i + 345*t]] : R[B[i + 345*t]] + R[C[i + 345*t]];
R[i + 1199*t] = Op[i + 346*t] ? R[B[i + 346*t]] * R[C[i + 346*t]] : R[B[i + 346*t]] + R[C[i + 346*t]];
R[i + 1200*t] = Op[i + 347*t] ? R[B[i + 347*t]] * R[C[i + 347*t]] : R[B[i + 347*t]] + R[C[i + 347*t]];
R[i + 1201*t] = Op[i + 348*t] ? R[B[i + 348*t]] * R[C[i + 348*t]] : R[B[i + 348*t]] + R[C[i + 348*t]];
R[i + 1202*t] = Op[i + 349*t] ? R[B[i + 349*t]] * R[C[i + 349*t]] : R[B[i + 349*t]] + R[C[i + 349*t]];
R[i + 1203*t] = Op[i + 350*t] ? R[B[i + 350*t]] * R[C[i + 350*t]] : R[B[i + 350*t]] + R[C[i + 350*t]];
R[i + 1204*t] = Op[i + 351*t] ? R[B[i + 351*t]] * R[C[i + 351*t]] : R[B[i + 351*t]] + R[C[i + 351*t]];
R[i + 1205*t] = Op[i + 352*t] ? R[B[i + 352*t]] * R[C[i + 352*t]] : R[B[i + 352*t]] + R[C[i + 352*t]];
R[i + 1206*t] = Op[i + 353*t] ? R[B[i + 353*t]] * R[C[i + 353*t]] : R[B[i + 353*t]] + R[C[i + 353*t]];
R[i + 1207*t] = Op[i + 354*t] ? R[B[i + 354*t]] * R[C[i + 354*t]] : R[B[i + 354*t]] + R[C[i + 354*t]];
R[i + 1208*t] = Op[i + 355*t] ? R[B[i + 355*t]] * R[C[i + 355*t]] : R[B[i + 355*t]] + R[C[i + 355*t]];
R[i + 1209*t] = Op[i + 356*t] ? R[B[i + 356*t]] * R[C[i + 356*t]] : R[B[i + 356*t]] + R[C[i + 356*t]];
R[i + 1210*t] = Op[i + 357*t] ? R[B[i + 357*t]] * R[C[i + 357*t]] : R[B[i + 357*t]] + R[C[i + 357*t]];
R[i + 1211*t] = Op[i + 358*t] ? R[B[i + 358*t]] * R[C[i + 358*t]] : R[B[i + 358*t]] + R[C[i + 358*t]];
R[i + 1212*t] = Op[i + 359*t] ? R[B[i + 359*t]] * R[C[i + 359*t]] : R[B[i + 359*t]] + R[C[i + 359*t]];
R[i + 1213*t] = Op[i + 360*t] ? R[B[i + 360*t]] * R[C[i + 360*t]] : R[B[i + 360*t]] + R[C[i + 360*t]];
R[i + 1214*t] = Op[i + 361*t] ? R[B[i + 361*t]] * R[C[i + 361*t]] : R[B[i + 361*t]] + R[C[i + 361*t]];
R[i + 1215*t] = Op[i + 362*t] ? R[B[i + 362*t]] * R[C[i + 362*t]] : R[B[i + 362*t]] + R[C[i + 362*t]];
R[i + 1216*t] = Op[i + 363*t] ? R[B[i + 363*t]] * R[C[i + 363*t]] : R[B[i + 363*t]] + R[C[i + 363*t]];
R[i + 1217*t] = Op[i + 364*t] ? R[B[i + 364*t]] * R[C[i + 364*t]] : R[B[i + 364*t]] + R[C[i + 364*t]];
R[i + 1218*t] = Op[i + 365*t] ? R[B[i + 365*t]] * R[C[i + 365*t]] : R[B[i + 365*t]] + R[C[i + 365*t]];
R[i + 1219*t] = Op[i + 366*t] ? R[B[i + 366*t]] * R[C[i + 366*t]] : R[B[i + 366*t]] + R[C[i + 366*t]];
R[i + 1220*t] = Op[i + 367*t] ? R[B[i + 367*t]] * R[C[i + 367*t]] : R[B[i + 367*t]] + R[C[i + 367*t]];
R[i + 1221*t] = Op[i + 368*t] ? R[B[i + 368*t]] * R[C[i + 368*t]] : R[B[i + 368*t]] + R[C[i + 368*t]];
R[i + 1222*t] = Op[i + 369*t] ? R[B[i + 369*t]] * R[C[i + 369*t]] : R[B[i + 369*t]] + R[C[i + 369*t]];
R[i + 1223*t] = Op[i + 370*t] ? R[B[i + 370*t]] * R[C[i + 370*t]] : R[B[i + 370*t]] + R[C[i + 370*t]];
R[i + 1224*t] = Op[i + 371*t] ? R[B[i + 371*t]] * R[C[i + 371*t]] : R[B[i + 371*t]] + R[C[i + 371*t]];
R[i + 1225*t] = Op[i + 372*t] ? R[B[i + 372*t]] * R[C[i + 372*t]] : R[B[i + 372*t]] + R[C[i + 372*t]];
R[i + 1226*t] = Op[i + 373*t] ? R[B[i + 373*t]] * R[C[i + 373*t]] : R[B[i + 373*t]] + R[C[i + 373*t]];
R[i + 1227*t] = Op[i + 374*t] ? R[B[i + 374*t]] * R[C[i + 374*t]] : R[B[i + 374*t]] + R[C[i + 374*t]];
R[i + 1228*t] = Op[i + 375*t] ? R[B[i + 375*t]] * R[C[i + 375*t]] : R[B[i + 375*t]] + R[C[i + 375*t]];
R[i + 1229*t] = Op[i + 376*t] ? R[B[i + 376*t]] * R[C[i + 376*t]] : R[B[i + 376*t]] + R[C[i + 376*t]];
R[i + 1230*t] = Op[i + 377*t] ? R[B[i + 377*t]] * R[C[i + 377*t]] : R[B[i + 377*t]] + R[C[i + 377*t]];
R[i + 1231*t] = Op[i + 378*t] ? R[B[i + 378*t]] * R[C[i + 378*t]] : R[B[i + 378*t]] + R[C[i + 378*t]];
R[i + 1232*t] = Op[i + 379*t] ? R[B[i + 379*t]] * R[C[i + 379*t]] : R[B[i + 379*t]] + R[C[i + 379*t]];
__syncthreads();
R[i + 1233*t] = Op[i + 380*t] ? R[B[i + 380*t]] * R[C[i + 380*t]] : R[B[i + 380*t]] + R[C[i + 380*t]];
R[i + 1234*t] = Op[i + 381*t] ? R[B[i + 381*t]] * R[C[i + 381*t]] : R[B[i + 381*t]] + R[C[i + 381*t]];
R[i + 1235*t] = Op[i + 382*t] ? R[B[i + 382*t]] * R[C[i + 382*t]] : R[B[i + 382*t]] + R[C[i + 382*t]];
R[i + 1236*t] = Op[i + 383*t] ? R[B[i + 383*t]] * R[C[i + 383*t]] : R[B[i + 383*t]] + R[C[i + 383*t]];
R[i + 1237*t] = Op[i + 384*t] ? R[B[i + 384*t]] * R[C[i + 384*t]] : R[B[i + 384*t]] + R[C[i + 384*t]];
R[i + 1238*t] = Op[i + 385*t] ? R[B[i + 385*t]] * R[C[i + 385*t]] : R[B[i + 385*t]] + R[C[i + 385*t]];
R[i + 1239*t] = Op[i + 386*t] ? R[B[i + 386*t]] * R[C[i + 386*t]] : R[B[i + 386*t]] + R[C[i + 386*t]];
R[i + 1240*t] = Op[i + 387*t] ? R[B[i + 387*t]] * R[C[i + 387*t]] : R[B[i + 387*t]] + R[C[i + 387*t]];
R[i + 1241*t] = Op[i + 388*t] ? R[B[i + 388*t]] * R[C[i + 388*t]] : R[B[i + 388*t]] + R[C[i + 388*t]];
R[i + 1242*t] = Op[i + 389*t] ? R[B[i + 389*t]] * R[C[i + 389*t]] : R[B[i + 389*t]] + R[C[i + 389*t]];
R[i + 1243*t] = Op[i + 390*t] ? R[B[i + 390*t]] * R[C[i + 390*t]] : R[B[i + 390*t]] + R[C[i + 390*t]];
R[i + 1244*t] = Op[i + 391*t] ? R[B[i + 391*t]] * R[C[i + 391*t]] : R[B[i + 391*t]] + R[C[i + 391*t]];
R[i + 1245*t] = Op[i + 392*t] ? R[B[i + 392*t]] * R[C[i + 392*t]] : R[B[i + 392*t]] + R[C[i + 392*t]];
R[i + 1246*t] = Op[i + 393*t] ? R[B[i + 393*t]] * R[C[i + 393*t]] : R[B[i + 393*t]] + R[C[i + 393*t]];
R[i + 1247*t] = Op[i + 394*t] ? R[B[i + 394*t]] * R[C[i + 394*t]] : R[B[i + 394*t]] + R[C[i + 394*t]];
R[i + 1248*t] = Op[i + 395*t] ? R[B[i + 395*t]] * R[C[i + 395*t]] : R[B[i + 395*t]] + R[C[i + 395*t]];
R[i + 1249*t] = Op[i + 396*t] ? R[B[i + 396*t]] * R[C[i + 396*t]] : R[B[i + 396*t]] + R[C[i + 396*t]];
R[i + 1250*t] = Op[i + 397*t] ? R[B[i + 397*t]] * R[C[i + 397*t]] : R[B[i + 397*t]] + R[C[i + 397*t]];
R[i + 1251*t] = Op[i + 398*t] ? R[B[i + 398*t]] * R[C[i + 398*t]] : R[B[i + 398*t]] + R[C[i + 398*t]];
R[i + 1252*t] = Op[i + 399*t] ? R[B[i + 399*t]] * R[C[i + 399*t]] : R[B[i + 399*t]] + R[C[i + 399*t]];
R[i + 1253*t] = Op[i + 400*t] ? R[B[i + 400*t]] * R[C[i + 400*t]] : R[B[i + 400*t]] + R[C[i + 400*t]];
R[i + 1254*t] = Op[i + 401*t] ? R[B[i + 401*t]] * R[C[i + 401*t]] : R[B[i + 401*t]] + R[C[i + 401*t]];
R[i + 1255*t] = Op[i + 402*t] ? R[B[i + 402*t]] * R[C[i + 402*t]] : R[B[i + 402*t]] + R[C[i + 402*t]];
R[i + 1256*t] = Op[i + 403*t] ? R[B[i + 403*t]] * R[C[i + 403*t]] : R[B[i + 403*t]] + R[C[i + 403*t]];
R[i + 1257*t] = Op[i + 404*t] ? R[B[i + 404*t]] * R[C[i + 404*t]] : R[B[i + 404*t]] + R[C[i + 404*t]];
R[i + 1258*t] = Op[i + 405*t] ? R[B[i + 405*t]] * R[C[i + 405*t]] : R[B[i + 405*t]] + R[C[i + 405*t]];
R[i + 1259*t] = Op[i + 406*t] ? R[B[i + 406*t]] * R[C[i + 406*t]] : R[B[i + 406*t]] + R[C[i + 406*t]];
R[i + 1260*t] = Op[i + 407*t] ? R[B[i + 407*t]] * R[C[i + 407*t]] : R[B[i + 407*t]] + R[C[i + 407*t]];
R[i + 1261*t] = Op[i + 408*t] ? R[B[i + 408*t]] * R[C[i + 408*t]] : R[B[i + 408*t]] + R[C[i + 408*t]];
R[i + 1262*t] = Op[i + 409*t] ? R[B[i + 409*t]] * R[C[i + 409*t]] : R[B[i + 409*t]] + R[C[i + 409*t]];
R[i + 1263*t] = Op[i + 410*t] ? R[B[i + 410*t]] * R[C[i + 410*t]] : R[B[i + 410*t]] + R[C[i + 410*t]];
R[i + 1264*t] = Op[i + 411*t] ? R[B[i + 411*t]] * R[C[i + 411*t]] : R[B[i + 411*t]] + R[C[i + 411*t]];
R[i + 1265*t] = Op[i + 412*t] ? R[B[i + 412*t]] * R[C[i + 412*t]] : R[B[i + 412*t]] + R[C[i + 412*t]];
R[i + 1266*t] = Op[i + 413*t] ? R[B[i + 413*t]] * R[C[i + 413*t]] : R[B[i + 413*t]] + R[C[i + 413*t]];
R[i + 1267*t] = Op[i + 414*t] ? R[B[i + 414*t]] * R[C[i + 414*t]] : R[B[i + 414*t]] + R[C[i + 414*t]];
R[i + 1268*t] = Op[i + 415*t] ? R[B[i + 415*t]] * R[C[i + 415*t]] : R[B[i + 415*t]] + R[C[i + 415*t]];
R[i + 1269*t] = Op[i + 416*t] ? R[B[i + 416*t]] * R[C[i + 416*t]] : R[B[i + 416*t]] + R[C[i + 416*t]];
R[i + 1270*t] = Op[i + 417*t] ? R[B[i + 417*t]] * R[C[i + 417*t]] : R[B[i + 417*t]] + R[C[i + 417*t]];
R[i + 1271*t] = Op[i + 418*t] ? R[B[i + 418*t]] * R[C[i + 418*t]] : R[B[i + 418*t]] + R[C[i + 418*t]];
R[i + 1272*t] = Op[i + 419*t] ? R[B[i + 419*t]] * R[C[i + 419*t]] : R[B[i + 419*t]] + R[C[i + 419*t]];
R[i + 1273*t] = Op[i + 420*t] ? R[B[i + 420*t]] * R[C[i + 420*t]] : R[B[i + 420*t]] + R[C[i + 420*t]];
R[i + 1274*t] = Op[i + 421*t] ? R[B[i + 421*t]] * R[C[i + 421*t]] : R[B[i + 421*t]] + R[C[i + 421*t]];
R[i + 1275*t] = Op[i + 422*t] ? R[B[i + 422*t]] * R[C[i + 422*t]] : R[B[i + 422*t]] + R[C[i + 422*t]];
R[i + 1276*t] = Op[i + 423*t] ? R[B[i + 423*t]] * R[C[i + 423*t]] : R[B[i + 423*t]] + R[C[i + 423*t]];
R[i + 1277*t] = Op[i + 424*t] ? R[B[i + 424*t]] * R[C[i + 424*t]] : R[B[i + 424*t]] + R[C[i + 424*t]];
R[i + 1278*t] = Op[i + 425*t] ? R[B[i + 425*t]] * R[C[i + 425*t]] : R[B[i + 425*t]] + R[C[i + 425*t]];
R[i + 1279*t] = Op[i + 426*t] ? R[B[i + 426*t]] * R[C[i + 426*t]] : R[B[i + 426*t]] + R[C[i + 426*t]];
R[i + 1280*t] = Op[i + 427*t] ? R[B[i + 427*t]] * R[C[i + 427*t]] : R[B[i + 427*t]] + R[C[i + 427*t]];
R[i + 1281*t] = Op[i + 428*t] ? R[B[i + 428*t]] * R[C[i + 428*t]] : R[B[i + 428*t]] + R[C[i + 428*t]];
R[i + 1282*t] = Op[i + 429*t] ? R[B[i + 429*t]] * R[C[i + 429*t]] : R[B[i + 429*t]] + R[C[i + 429*t]];
R[i + 1283*t] = Op[i + 430*t] ? R[B[i + 430*t]] * R[C[i + 430*t]] : R[B[i + 430*t]] + R[C[i + 430*t]];
R[i + 1284*t] = Op[i + 431*t] ? R[B[i + 431*t]] * R[C[i + 431*t]] : R[B[i + 431*t]] + R[C[i + 431*t]];
R[i + 1285*t] = Op[i + 432*t] ? R[B[i + 432*t]] * R[C[i + 432*t]] : R[B[i + 432*t]] + R[C[i + 432*t]];
R[i + 1286*t] = Op[i + 433*t] ? R[B[i + 433*t]] * R[C[i + 433*t]] : R[B[i + 433*t]] + R[C[i + 433*t]];
R[i + 1287*t] = Op[i + 434*t] ? R[B[i + 434*t]] * R[C[i + 434*t]] : R[B[i + 434*t]] + R[C[i + 434*t]];
R[i + 1288*t] = Op[i + 435*t] ? R[B[i + 435*t]] * R[C[i + 435*t]] : R[B[i + 435*t]] + R[C[i + 435*t]];
R[i + 1289*t] = Op[i + 436*t] ? R[B[i + 436*t]] * R[C[i + 436*t]] : R[B[i + 436*t]] + R[C[i + 436*t]];
R[i + 1290*t] = Op[i + 437*t] ? R[B[i + 437*t]] * R[C[i + 437*t]] : R[B[i + 437*t]] + R[C[i + 437*t]];
R[i + 1291*t] = Op[i + 438*t] ? R[B[i + 438*t]] * R[C[i + 438*t]] : R[B[i + 438*t]] + R[C[i + 438*t]];
R[i + 1292*t] = Op[i + 439*t] ? R[B[i + 439*t]] * R[C[i + 439*t]] : R[B[i + 439*t]] + R[C[i + 439*t]];
R[i + 1293*t] = Op[i + 440*t] ? R[B[i + 440*t]] * R[C[i + 440*t]] : R[B[i + 440*t]] + R[C[i + 440*t]];
R[i + 1294*t] = Op[i + 441*t] ? R[B[i + 441*t]] * R[C[i + 441*t]] : R[B[i + 441*t]] + R[C[i + 441*t]];
R[i + 1295*t] = Op[i + 442*t] ? R[B[i + 442*t]] * R[C[i + 442*t]] : R[B[i + 442*t]] + R[C[i + 442*t]];
R[i + 1296*t] = Op[i + 443*t] ? R[B[i + 443*t]] * R[C[i + 443*t]] : R[B[i + 443*t]] + R[C[i + 443*t]];
R[i + 1297*t] = Op[i + 444*t] ? R[B[i + 444*t]] * R[C[i + 444*t]] : R[B[i + 444*t]] + R[C[i + 444*t]];
R[i + 1298*t] = Op[i + 445*t] ? R[B[i + 445*t]] * R[C[i + 445*t]] : R[B[i + 445*t]] + R[C[i + 445*t]];
R[i + 1299*t] = Op[i + 446*t] ? R[B[i + 446*t]] * R[C[i + 446*t]] : R[B[i + 446*t]] + R[C[i + 446*t]];
R[i + 1300*t] = Op[i + 447*t] ? R[B[i + 447*t]] * R[C[i + 447*t]] : R[B[i + 447*t]] + R[C[i + 447*t]];
R[i + 1301*t] = Op[i + 448*t] ? R[B[i + 448*t]] * R[C[i + 448*t]] : R[B[i + 448*t]] + R[C[i + 448*t]];
R[i + 1302*t] = Op[i + 449*t] ? R[B[i + 449*t]] * R[C[i + 449*t]] : R[B[i + 449*t]] + R[C[i + 449*t]];
R[i + 1303*t] = Op[i + 450*t] ? R[B[i + 450*t]] * R[C[i + 450*t]] : R[B[i + 450*t]] + R[C[i + 450*t]];
R[i + 1304*t] = Op[i + 451*t] ? R[B[i + 451*t]] * R[C[i + 451*t]] : R[B[i + 451*t]] + R[C[i + 451*t]];
R[i + 1305*t] = Op[i + 452*t] ? R[B[i + 452*t]] * R[C[i + 452*t]] : R[B[i + 452*t]] + R[C[i + 452*t]];
R[i + 1306*t] = Op[i + 453*t] ? R[B[i + 453*t]] * R[C[i + 453*t]] : R[B[i + 453*t]] + R[C[i + 453*t]];
R[i + 1307*t] = Op[i + 454*t] ? R[B[i + 454*t]] * R[C[i + 454*t]] : R[B[i + 454*t]] + R[C[i + 454*t]];
R[i + 1308*t] = Op[i + 455*t] ? R[B[i + 455*t]] * R[C[i + 455*t]] : R[B[i + 455*t]] + R[C[i + 455*t]];
R[i + 1309*t] = Op[i + 456*t] ? R[B[i + 456*t]] * R[C[i + 456*t]] : R[B[i + 456*t]] + R[C[i + 456*t]];
R[i + 1310*t] = Op[i + 457*t] ? R[B[i + 457*t]] * R[C[i + 457*t]] : R[B[i + 457*t]] + R[C[i + 457*t]];
R[i + 1311*t] = Op[i + 458*t] ? R[B[i + 458*t]] * R[C[i + 458*t]] : R[B[i + 458*t]] + R[C[i + 458*t]];
R[i + 1312*t] = Op[i + 459*t] ? R[B[i + 459*t]] * R[C[i + 459*t]] : R[B[i + 459*t]] + R[C[i + 459*t]];
R[i + 1313*t] = Op[i + 460*t] ? R[B[i + 460*t]] * R[C[i + 460*t]] : R[B[i + 460*t]] + R[C[i + 460*t]];
R[i + 1314*t] = Op[i + 461*t] ? R[B[i + 461*t]] * R[C[i + 461*t]] : R[B[i + 461*t]] + R[C[i + 461*t]];
R[i + 1315*t] = Op[i + 462*t] ? R[B[i + 462*t]] * R[C[i + 462*t]] : R[B[i + 462*t]] + R[C[i + 462*t]];
R[i + 1316*t] = Op[i + 463*t] ? R[B[i + 463*t]] * R[C[i + 463*t]] : R[B[i + 463*t]] + R[C[i + 463*t]];
R[i + 1317*t] = Op[i + 464*t] ? R[B[i + 464*t]] * R[C[i + 464*t]] : R[B[i + 464*t]] + R[C[i + 464*t]];
R[i + 1318*t] = Op[i + 465*t] ? R[B[i + 465*t]] * R[C[i + 465*t]] : R[B[i + 465*t]] + R[C[i + 465*t]];
R[i + 1319*t] = Op[i + 466*t] ? R[B[i + 466*t]] * R[C[i + 466*t]] : R[B[i + 466*t]] + R[C[i + 466*t]];
R[i + 1320*t] = Op[i + 467*t] ? R[B[i + 467*t]] * R[C[i + 467*t]] : R[B[i + 467*t]] + R[C[i + 467*t]];
R[i + 1321*t] = Op[i + 468*t] ? R[B[i + 468*t]] * R[C[i + 468*t]] : R[B[i + 468*t]] + R[C[i + 468*t]];
R[i + 1322*t] = Op[i + 469*t] ? R[B[i + 469*t]] * R[C[i + 469*t]] : R[B[i + 469*t]] + R[C[i + 469*t]];
R[i + 1323*t] = Op[i + 470*t] ? R[B[i + 470*t]] * R[C[i + 470*t]] : R[B[i + 470*t]] + R[C[i + 470*t]];
R[i + 1324*t] = Op[i + 471*t] ? R[B[i + 471*t]] * R[C[i + 471*t]] : R[B[i + 471*t]] + R[C[i + 471*t]];
R[i + 1325*t] = Op[i + 472*t] ? R[B[i + 472*t]] * R[C[i + 472*t]] : R[B[i + 472*t]] + R[C[i + 472*t]];
R[i + 1326*t] = Op[i + 473*t] ? R[B[i + 473*t]] * R[C[i + 473*t]] : R[B[i + 473*t]] + R[C[i + 473*t]];
R[i + 1327*t] = Op[i + 474*t] ? R[B[i + 474*t]] * R[C[i + 474*t]] : R[B[i + 474*t]] + R[C[i + 474*t]];
R[i + 1328*t] = Op[i + 475*t] ? R[B[i + 475*t]] * R[C[i + 475*t]] : R[B[i + 475*t]] + R[C[i + 475*t]];
R[i + 1329*t] = Op[i + 476*t] ? R[B[i + 476*t]] * R[C[i + 476*t]] : R[B[i + 476*t]] + R[C[i + 476*t]];
R[i + 1330*t] = Op[i + 477*t] ? R[B[i + 477*t]] * R[C[i + 477*t]] : R[B[i + 477*t]] + R[C[i + 477*t]];
R[i + 1331*t] = Op[i + 478*t] ? R[B[i + 478*t]] * R[C[i + 478*t]] : R[B[i + 478*t]] + R[C[i + 478*t]];
R[i + 1332*t] = Op[i + 479*t] ? R[B[i + 479*t]] * R[C[i + 479*t]] : R[B[i + 479*t]] + R[C[i + 479*t]];
R[i + 1333*t] = Op[i + 480*t] ? R[B[i + 480*t]] * R[C[i + 480*t]] : R[B[i + 480*t]] + R[C[i + 480*t]];
R[i + 1334*t] = Op[i + 481*t] ? R[B[i + 481*t]] * R[C[i + 481*t]] : R[B[i + 481*t]] + R[C[i + 481*t]];
R[i + 1335*t] = Op[i + 482*t] ? R[B[i + 482*t]] * R[C[i + 482*t]] : R[B[i + 482*t]] + R[C[i + 482*t]];
R[i + 1336*t] = Op[i + 483*t] ? R[B[i + 483*t]] * R[C[i + 483*t]] : R[B[i + 483*t]] + R[C[i + 483*t]];
R[i + 1337*t] = Op[i + 484*t] ? R[B[i + 484*t]] * R[C[i + 484*t]] : R[B[i + 484*t]] + R[C[i + 484*t]];
R[i + 1338*t] = Op[i + 485*t] ? R[B[i + 485*t]] * R[C[i + 485*t]] : R[B[i + 485*t]] + R[C[i + 485*t]];
R[i + 1339*t] = Op[i + 486*t] ? R[B[i + 486*t]] * R[C[i + 486*t]] : R[B[i + 486*t]] + R[C[i + 486*t]];
R[i + 1340*t] = Op[i + 487*t] ? R[B[i + 487*t]] * R[C[i + 487*t]] : R[B[i + 487*t]] + R[C[i + 487*t]];
R[i + 1341*t] = Op[i + 488*t] ? R[B[i + 488*t]] * R[C[i + 488*t]] : R[B[i + 488*t]] + R[C[i + 488*t]];
R[i + 1342*t] = Op[i + 489*t] ? R[B[i + 489*t]] * R[C[i + 489*t]] : R[B[i + 489*t]] + R[C[i + 489*t]];
R[i + 1343*t] = Op[i + 490*t] ? R[B[i + 490*t]] * R[C[i + 490*t]] : R[B[i + 490*t]] + R[C[i + 490*t]];
R[i + 1344*t] = Op[i + 491*t] ? R[B[i + 491*t]] * R[C[i + 491*t]] : R[B[i + 491*t]] + R[C[i + 491*t]];
R[i + 1345*t] = Op[i + 492*t] ? R[B[i + 492*t]] * R[C[i + 492*t]] : R[B[i + 492*t]] + R[C[i + 492*t]];
R[i + 1346*t] = Op[i + 493*t] ? R[B[i + 493*t]] * R[C[i + 493*t]] : R[B[i + 493*t]] + R[C[i + 493*t]];
R[i + 1347*t] = Op[i + 494*t] ? R[B[i + 494*t]] * R[C[i + 494*t]] : R[B[i + 494*t]] + R[C[i + 494*t]];
R[i + 1348*t] = Op[i + 495*t] ? R[B[i + 495*t]] * R[C[i + 495*t]] : R[B[i + 495*t]] + R[C[i + 495*t]];
R[i + 1349*t] = Op[i + 496*t] ? R[B[i + 496*t]] * R[C[i + 496*t]] : R[B[i + 496*t]] + R[C[i + 496*t]];
R[i + 1350*t] = Op[i + 497*t] ? R[B[i + 497*t]] * R[C[i + 497*t]] : R[B[i + 497*t]] + R[C[i + 497*t]];
R[i + 1351*t] = Op[i + 498*t] ? R[B[i + 498*t]] * R[C[i + 498*t]] : R[B[i + 498*t]] + R[C[i + 498*t]];
R[i + 1352*t] = Op[i + 499*t] ? R[B[i + 499*t]] * R[C[i + 499*t]] : R[B[i + 499*t]] + R[C[i + 499*t]];
R[i + 1353*t] = Op[i + 500*t] ? R[B[i + 500*t]] * R[C[i + 500*t]] : R[B[i + 500*t]] + R[C[i + 500*t]];
R[i + 1354*t] = Op[i + 501*t] ? R[B[i + 501*t]] * R[C[i + 501*t]] : R[B[i + 501*t]] + R[C[i + 501*t]];
R[i + 1355*t] = Op[i + 502*t] ? R[B[i + 502*t]] * R[C[i + 502*t]] : R[B[i + 502*t]] + R[C[i + 502*t]];
R[i + 1356*t] = Op[i + 503*t] ? R[B[i + 503*t]] * R[C[i + 503*t]] : R[B[i + 503*t]] + R[C[i + 503*t]];
R[i + 1357*t] = Op[i + 504*t] ? R[B[i + 504*t]] * R[C[i + 504*t]] : R[B[i + 504*t]] + R[C[i + 504*t]];
R[i + 1358*t] = Op[i + 505*t] ? R[B[i + 505*t]] * R[C[i + 505*t]] : R[B[i + 505*t]] + R[C[i + 505*t]];
R[i + 1359*t] = Op[i + 506*t] ? R[B[i + 506*t]] * R[C[i + 506*t]] : R[B[i + 506*t]] + R[C[i + 506*t]];
R[i + 1360*t] = Op[i + 507*t] ? R[B[i + 507*t]] * R[C[i + 507*t]] : R[B[i + 507*t]] + R[C[i + 507*t]];
R[i + 1361*t] = Op[i + 508*t] ? R[B[i + 508*t]] * R[C[i + 508*t]] : R[B[i + 508*t]] + R[C[i + 508*t]];
R[i + 1362*t] = Op[i + 509*t] ? R[B[i + 509*t]] * R[C[i + 509*t]] : R[B[i + 509*t]] + R[C[i + 509*t]];
R[i + 1363*t] = Op[i + 510*t] ? R[B[i + 510*t]] * R[C[i + 510*t]] : R[B[i + 510*t]] + R[C[i + 510*t]];
R[i + 1364*t] = Op[i + 511*t] ? R[B[i + 511*t]] * R[C[i + 511*t]] : R[B[i + 511*t]] + R[C[i + 511*t]];
R[i + 1365*t] = Op[i + 512*t] ? R[B[i + 512*t]] * R[C[i + 512*t]] : R[B[i + 512*t]] + R[C[i + 512*t]];
R[i + 1366*t] = Op[i + 513*t] ? R[B[i + 513*t]] * R[C[i + 513*t]] : R[B[i + 513*t]] + R[C[i + 513*t]];
R[i + 1367*t] = Op[i + 514*t] ? R[B[i + 514*t]] * R[C[i + 514*t]] : R[B[i + 514*t]] + R[C[i + 514*t]];
R[i + 1368*t] = Op[i + 515*t] ? R[B[i + 515*t]] * R[C[i + 515*t]] : R[B[i + 515*t]] + R[C[i + 515*t]];
R[i + 1369*t] = Op[i + 516*t] ? R[B[i + 516*t]] * R[C[i + 516*t]] : R[B[i + 516*t]] + R[C[i + 516*t]];
R[i + 1370*t] = Op[i + 517*t] ? R[B[i + 517*t]] * R[C[i + 517*t]] : R[B[i + 517*t]] + R[C[i + 517*t]];
R[i + 1371*t] = Op[i + 518*t] ? R[B[i + 518*t]] * R[C[i + 518*t]] : R[B[i + 518*t]] + R[C[i + 518*t]];
R[i + 1372*t] = Op[i + 519*t] ? R[B[i + 519*t]] * R[C[i + 519*t]] : R[B[i + 519*t]] + R[C[i + 519*t]];
R[i + 1373*t] = Op[i + 520*t] ? R[B[i + 520*t]] * R[C[i + 520*t]] : R[B[i + 520*t]] + R[C[i + 520*t]];
R[i + 1374*t] = Op[i + 521*t] ? R[B[i + 521*t]] * R[C[i + 521*t]] : R[B[i + 521*t]] + R[C[i + 521*t]];
R[i + 1375*t] = Op[i + 522*t] ? R[B[i + 522*t]] * R[C[i + 522*t]] : R[B[i + 522*t]] + R[C[i + 522*t]];
R[i + 1376*t] = Op[i + 523*t] ? R[B[i + 523*t]] * R[C[i + 523*t]] : R[B[i + 523*t]] + R[C[i + 523*t]];
R[i + 1377*t] = Op[i + 524*t] ? R[B[i + 524*t]] * R[C[i + 524*t]] : R[B[i + 524*t]] + R[C[i + 524*t]];
R[i + 1378*t] = Op[i + 525*t] ? R[B[i + 525*t]] * R[C[i + 525*t]] : R[B[i + 525*t]] + R[C[i + 525*t]];
R[i + 1379*t] = Op[i + 526*t] ? R[B[i + 526*t]] * R[C[i + 526*t]] : R[B[i + 526*t]] + R[C[i + 526*t]];
R[i + 1380*t] = Op[i + 527*t] ? R[B[i + 527*t]] * R[C[i + 527*t]] : R[B[i + 527*t]] + R[C[i + 527*t]];
R[i + 1381*t] = Op[i + 528*t] ? R[B[i + 528*t]] * R[C[i + 528*t]] : R[B[i + 528*t]] + R[C[i + 528*t]];
R[i + 1382*t] = Op[i + 529*t] ? R[B[i + 529*t]] * R[C[i + 529*t]] : R[B[i + 529*t]] + R[C[i + 529*t]];
R[i + 1383*t] = Op[i + 530*t] ? R[B[i + 530*t]] * R[C[i + 530*t]] : R[B[i + 530*t]] + R[C[i + 530*t]];
__syncthreads();
R[i + 1384*t] = Op[i + 531*t] ? R[B[i + 531*t]] * R[C[i + 531*t]] : R[B[i + 531*t]] + R[C[i + 531*t]];
R[i + 1385*t] = Op[i + 532*t] ? R[B[i + 532*t]] * R[C[i + 532*t]] : R[B[i + 532*t]] + R[C[i + 532*t]];
R[i + 1386*t] = Op[i + 533*t] ? R[B[i + 533*t]] * R[C[i + 533*t]] : R[B[i + 533*t]] + R[C[i + 533*t]];
R[i + 1387*t] = Op[i + 534*t] ? R[B[i + 534*t]] * R[C[i + 534*t]] : R[B[i + 534*t]] + R[C[i + 534*t]];
R[i + 1388*t] = Op[i + 535*t] ? R[B[i + 535*t]] * R[C[i + 535*t]] : R[B[i + 535*t]] + R[C[i + 535*t]];
R[i + 1389*t] = Op[i + 536*t] ? R[B[i + 536*t]] * R[C[i + 536*t]] : R[B[i + 536*t]] + R[C[i + 536*t]];
R[i + 1390*t] = Op[i + 537*t] ? R[B[i + 537*t]] * R[C[i + 537*t]] : R[B[i + 537*t]] + R[C[i + 537*t]];
R[i + 1391*t] = Op[i + 538*t] ? R[B[i + 538*t]] * R[C[i + 538*t]] : R[B[i + 538*t]] + R[C[i + 538*t]];
R[i + 1392*t] = Op[i + 539*t] ? R[B[i + 539*t]] * R[C[i + 539*t]] : R[B[i + 539*t]] + R[C[i + 539*t]];
R[i + 1393*t] = Op[i + 540*t] ? R[B[i + 540*t]] * R[C[i + 540*t]] : R[B[i + 540*t]] + R[C[i + 540*t]];
R[i + 1394*t] = Op[i + 541*t] ? R[B[i + 541*t]] * R[C[i + 541*t]] : R[B[i + 541*t]] + R[C[i + 541*t]];
R[i + 1395*t] = Op[i + 542*t] ? R[B[i + 542*t]] * R[C[i + 542*t]] : R[B[i + 542*t]] + R[C[i + 542*t]];
R[i + 1396*t] = Op[i + 543*t] ? R[B[i + 543*t]] * R[C[i + 543*t]] : R[B[i + 543*t]] + R[C[i + 543*t]];
R[i + 1397*t] = Op[i + 544*t] ? R[B[i + 544*t]] * R[C[i + 544*t]] : R[B[i + 544*t]] + R[C[i + 544*t]];
R[i + 1398*t] = Op[i + 545*t] ? R[B[i + 545*t]] * R[C[i + 545*t]] : R[B[i + 545*t]] + R[C[i + 545*t]];
R[i + 1399*t] = Op[i + 546*t] ? R[B[i + 546*t]] * R[C[i + 546*t]] : R[B[i + 546*t]] + R[C[i + 546*t]];
R[i + 1400*t] = Op[i + 547*t] ? R[B[i + 547*t]] * R[C[i + 547*t]] : R[B[i + 547*t]] + R[C[i + 547*t]];
R[i + 1401*t] = Op[i + 548*t] ? R[B[i + 548*t]] * R[C[i + 548*t]] : R[B[i + 548*t]] + R[C[i + 548*t]];
R[i + 1402*t] = Op[i + 549*t] ? R[B[i + 549*t]] * R[C[i + 549*t]] : R[B[i + 549*t]] + R[C[i + 549*t]];
R[i + 1403*t] = Op[i + 550*t] ? R[B[i + 550*t]] * R[C[i + 550*t]] : R[B[i + 550*t]] + R[C[i + 550*t]];
R[i + 1404*t] = Op[i + 551*t] ? R[B[i + 551*t]] * R[C[i + 551*t]] : R[B[i + 551*t]] + R[C[i + 551*t]];
R[i + 1405*t] = Op[i + 552*t] ? R[B[i + 552*t]] * R[C[i + 552*t]] : R[B[i + 552*t]] + R[C[i + 552*t]];
R[i + 1406*t] = Op[i + 553*t] ? R[B[i + 553*t]] * R[C[i + 553*t]] : R[B[i + 553*t]] + R[C[i + 553*t]];
R[i + 1407*t] = Op[i + 554*t] ? R[B[i + 554*t]] * R[C[i + 554*t]] : R[B[i + 554*t]] + R[C[i + 554*t]];
R[i + 1408*t] = Op[i + 555*t] ? R[B[i + 555*t]] * R[C[i + 555*t]] : R[B[i + 555*t]] + R[C[i + 555*t]];
R[i + 1409*t] = Op[i + 556*t] ? R[B[i + 556*t]] * R[C[i + 556*t]] : R[B[i + 556*t]] + R[C[i + 556*t]];
R[i + 1410*t] = Op[i + 557*t] ? R[B[i + 557*t]] * R[C[i + 557*t]] : R[B[i + 557*t]] + R[C[i + 557*t]];
R[i + 1411*t] = Op[i + 558*t] ? R[B[i + 558*t]] * R[C[i + 558*t]] : R[B[i + 558*t]] + R[C[i + 558*t]];
R[i + 1412*t] = Op[i + 559*t] ? R[B[i + 559*t]] * R[C[i + 559*t]] : R[B[i + 559*t]] + R[C[i + 559*t]];
R[i + 1413*t] = Op[i + 560*t] ? R[B[i + 560*t]] * R[C[i + 560*t]] : R[B[i + 560*t]] + R[C[i + 560*t]];
R[i + 1414*t] = Op[i + 561*t] ? R[B[i + 561*t]] * R[C[i + 561*t]] : R[B[i + 561*t]] + R[C[i + 561*t]];
R[i + 1415*t] = Op[i + 562*t] ? R[B[i + 562*t]] * R[C[i + 562*t]] : R[B[i + 562*t]] + R[C[i + 562*t]];
R[i + 1416*t] = Op[i + 563*t] ? R[B[i + 563*t]] * R[C[i + 563*t]] : R[B[i + 563*t]] + R[C[i + 563*t]];
R[i + 1417*t] = Op[i + 564*t] ? R[B[i + 564*t]] * R[C[i + 564*t]] : R[B[i + 564*t]] + R[C[i + 564*t]];
R[i + 1418*t] = Op[i + 565*t] ? R[B[i + 565*t]] * R[C[i + 565*t]] : R[B[i + 565*t]] + R[C[i + 565*t]];
R[i + 1419*t] = Op[i + 566*t] ? R[B[i + 566*t]] * R[C[i + 566*t]] : R[B[i + 566*t]] + R[C[i + 566*t]];
R[i + 1420*t] = Op[i + 567*t] ? R[B[i + 567*t]] * R[C[i + 567*t]] : R[B[i + 567*t]] + R[C[i + 567*t]];
R[i + 1421*t] = Op[i + 568*t] ? R[B[i + 568*t]] * R[C[i + 568*t]] : R[B[i + 568*t]] + R[C[i + 568*t]];
R[i + 1422*t] = Op[i + 569*t] ? R[B[i + 569*t]] * R[C[i + 569*t]] : R[B[i + 569*t]] + R[C[i + 569*t]];
R[i + 1423*t] = Op[i + 570*t] ? R[B[i + 570*t]] * R[C[i + 570*t]] : R[B[i + 570*t]] + R[C[i + 570*t]];
R[i + 1424*t] = Op[i + 571*t] ? R[B[i + 571*t]] * R[C[i + 571*t]] : R[B[i + 571*t]] + R[C[i + 571*t]];
R[i + 1425*t] = Op[i + 572*t] ? R[B[i + 572*t]] * R[C[i + 572*t]] : R[B[i + 572*t]] + R[C[i + 572*t]];
R[i + 1426*t] = Op[i + 573*t] ? R[B[i + 573*t]] * R[C[i + 573*t]] : R[B[i + 573*t]] + R[C[i + 573*t]];
R[i + 1427*t] = Op[i + 574*t] ? R[B[i + 574*t]] * R[C[i + 574*t]] : R[B[i + 574*t]] + R[C[i + 574*t]];
R[i + 1428*t] = Op[i + 575*t] ? R[B[i + 575*t]] * R[C[i + 575*t]] : R[B[i + 575*t]] + R[C[i + 575*t]];
R[i + 1429*t] = Op[i + 576*t] ? R[B[i + 576*t]] * R[C[i + 576*t]] : R[B[i + 576*t]] + R[C[i + 576*t]];
R[i + 1430*t] = Op[i + 577*t] ? R[B[i + 577*t]] * R[C[i + 577*t]] : R[B[i + 577*t]] + R[C[i + 577*t]];
R[i + 1431*t] = Op[i + 578*t] ? R[B[i + 578*t]] * R[C[i + 578*t]] : R[B[i + 578*t]] + R[C[i + 578*t]];
R[i + 1432*t] = Op[i + 579*t] ? R[B[i + 579*t]] * R[C[i + 579*t]] : R[B[i + 579*t]] + R[C[i + 579*t]];
R[i + 1433*t] = Op[i + 580*t] ? R[B[i + 580*t]] * R[C[i + 580*t]] : R[B[i + 580*t]] + R[C[i + 580*t]];
R[i + 1434*t] = Op[i + 581*t] ? R[B[i + 581*t]] * R[C[i + 581*t]] : R[B[i + 581*t]] + R[C[i + 581*t]];
R[i + 1435*t] = Op[i + 582*t] ? R[B[i + 582*t]] * R[C[i + 582*t]] : R[B[i + 582*t]] + R[C[i + 582*t]];
R[i + 1436*t] = Op[i + 583*t] ? R[B[i + 583*t]] * R[C[i + 583*t]] : R[B[i + 583*t]] + R[C[i + 583*t]];
R[i + 1437*t] = Op[i + 584*t] ? R[B[i + 584*t]] * R[C[i + 584*t]] : R[B[i + 584*t]] + R[C[i + 584*t]];
R[i + 1438*t] = Op[i + 585*t] ? R[B[i + 585*t]] * R[C[i + 585*t]] : R[B[i + 585*t]] + R[C[i + 585*t]];
R[i + 1439*t] = Op[i + 586*t] ? R[B[i + 586*t]] * R[C[i + 586*t]] : R[B[i + 586*t]] + R[C[i + 586*t]];
R[i + 1440*t] = Op[i + 587*t] ? R[B[i + 587*t]] * R[C[i + 587*t]] : R[B[i + 587*t]] + R[C[i + 587*t]];
R[i + 1441*t] = Op[i + 588*t] ? R[B[i + 588*t]] * R[C[i + 588*t]] : R[B[i + 588*t]] + R[C[i + 588*t]];
R[i + 1442*t] = Op[i + 589*t] ? R[B[i + 589*t]] * R[C[i + 589*t]] : R[B[i + 589*t]] + R[C[i + 589*t]];
R[i + 1443*t] = Op[i + 590*t] ? R[B[i + 590*t]] * R[C[i + 590*t]] : R[B[i + 590*t]] + R[C[i + 590*t]];
R[i + 1444*t] = Op[i + 591*t] ? R[B[i + 591*t]] * R[C[i + 591*t]] : R[B[i + 591*t]] + R[C[i + 591*t]];
R[i + 1445*t] = Op[i + 592*t] ? R[B[i + 592*t]] * R[C[i + 592*t]] : R[B[i + 592*t]] + R[C[i + 592*t]];
R[i + 1446*t] = Op[i + 593*t] ? R[B[i + 593*t]] * R[C[i + 593*t]] : R[B[i + 593*t]] + R[C[i + 593*t]];
R[i + 1447*t] = Op[i + 594*t] ? R[B[i + 594*t]] * R[C[i + 594*t]] : R[B[i + 594*t]] + R[C[i + 594*t]];
R[i + 1448*t] = Op[i + 595*t] ? R[B[i + 595*t]] * R[C[i + 595*t]] : R[B[i + 595*t]] + R[C[i + 595*t]];
R[i + 1449*t] = Op[i + 596*t] ? R[B[i + 596*t]] * R[C[i + 596*t]] : R[B[i + 596*t]] + R[C[i + 596*t]];
R[i + 1450*t] = Op[i + 597*t] ? R[B[i + 597*t]] * R[C[i + 597*t]] : R[B[i + 597*t]] + R[C[i + 597*t]];
R[i + 1451*t] = Op[i + 598*t] ? R[B[i + 598*t]] * R[C[i + 598*t]] : R[B[i + 598*t]] + R[C[i + 598*t]];
R[i + 1452*t] = Op[i + 599*t] ? R[B[i + 599*t]] * R[C[i + 599*t]] : R[B[i + 599*t]] + R[C[i + 599*t]];
R[i + 1453*t] = Op[i + 600*t] ? R[B[i + 600*t]] * R[C[i + 600*t]] : R[B[i + 600*t]] + R[C[i + 600*t]];
R[i + 1454*t] = Op[i + 601*t] ? R[B[i + 601*t]] * R[C[i + 601*t]] : R[B[i + 601*t]] + R[C[i + 601*t]];
R[i + 1455*t] = Op[i + 602*t] ? R[B[i + 602*t]] * R[C[i + 602*t]] : R[B[i + 602*t]] + R[C[i + 602*t]];
R[i + 1456*t] = Op[i + 603*t] ? R[B[i + 603*t]] * R[C[i + 603*t]] : R[B[i + 603*t]] + R[C[i + 603*t]];
R[i + 1457*t] = Op[i + 604*t] ? R[B[i + 604*t]] * R[C[i + 604*t]] : R[B[i + 604*t]] + R[C[i + 604*t]];
R[i + 1458*t] = Op[i + 605*t] ? R[B[i + 605*t]] * R[C[i + 605*t]] : R[B[i + 605*t]] + R[C[i + 605*t]];
R[i + 1459*t] = Op[i + 606*t] ? R[B[i + 606*t]] * R[C[i + 606*t]] : R[B[i + 606*t]] + R[C[i + 606*t]];
R[i + 1460*t] = Op[i + 607*t] ? R[B[i + 607*t]] * R[C[i + 607*t]] : R[B[i + 607*t]] + R[C[i + 607*t]];
R[i + 1461*t] = Op[i + 608*t] ? R[B[i + 608*t]] * R[C[i + 608*t]] : R[B[i + 608*t]] + R[C[i + 608*t]];
R[i + 1462*t] = Op[i + 609*t] ? R[B[i + 609*t]] * R[C[i + 609*t]] : R[B[i + 609*t]] + R[C[i + 609*t]];
R[i + 1463*t] = Op[i + 610*t] ? R[B[i + 610*t]] * R[C[i + 610*t]] : R[B[i + 610*t]] + R[C[i + 610*t]];
R[i + 1464*t] = Op[i + 611*t] ? R[B[i + 611*t]] * R[C[i + 611*t]] : R[B[i + 611*t]] + R[C[i + 611*t]];
R[i + 1465*t] = Op[i + 612*t] ? R[B[i + 612*t]] * R[C[i + 612*t]] : R[B[i + 612*t]] + R[C[i + 612*t]];
R[i + 1466*t] = Op[i + 613*t] ? R[B[i + 613*t]] * R[C[i + 613*t]] : R[B[i + 613*t]] + R[C[i + 613*t]];
R[i + 1467*t] = Op[i + 614*t] ? R[B[i + 614*t]] * R[C[i + 614*t]] : R[B[i + 614*t]] + R[C[i + 614*t]];
R[i + 1468*t] = Op[i + 615*t] ? R[B[i + 615*t]] * R[C[i + 615*t]] : R[B[i + 615*t]] + R[C[i + 615*t]];
R[i + 1469*t] = Op[i + 616*t] ? R[B[i + 616*t]] * R[C[i + 616*t]] : R[B[i + 616*t]] + R[C[i + 616*t]];
R[i + 1470*t] = Op[i + 617*t] ? R[B[i + 617*t]] * R[C[i + 617*t]] : R[B[i + 617*t]] + R[C[i + 617*t]];
R[i + 1471*t] = Op[i + 618*t] ? R[B[i + 618*t]] * R[C[i + 618*t]] : R[B[i + 618*t]] + R[C[i + 618*t]];
R[i + 1472*t] = Op[i + 619*t] ? R[B[i + 619*t]] * R[C[i + 619*t]] : R[B[i + 619*t]] + R[C[i + 619*t]];
R[i + 1473*t] = Op[i + 620*t] ? R[B[i + 620*t]] * R[C[i + 620*t]] : R[B[i + 620*t]] + R[C[i + 620*t]];
R[i + 1474*t] = Op[i + 621*t] ? R[B[i + 621*t]] * R[C[i + 621*t]] : R[B[i + 621*t]] + R[C[i + 621*t]];
R[i + 1475*t] = Op[i + 622*t] ? R[B[i + 622*t]] * R[C[i + 622*t]] : R[B[i + 622*t]] + R[C[i + 622*t]];
R[i + 1476*t] = Op[i + 623*t] ? R[B[i + 623*t]] * R[C[i + 623*t]] : R[B[i + 623*t]] + R[C[i + 623*t]];
R[i + 1477*t] = Op[i + 624*t] ? R[B[i + 624*t]] * R[C[i + 624*t]] : R[B[i + 624*t]] + R[C[i + 624*t]];
R[i + 1478*t] = Op[i + 625*t] ? R[B[i + 625*t]] * R[C[i + 625*t]] : R[B[i + 625*t]] + R[C[i + 625*t]];
R[i + 1479*t] = Op[i + 626*t] ? R[B[i + 626*t]] * R[C[i + 626*t]] : R[B[i + 626*t]] + R[C[i + 626*t]];
R[i + 1480*t] = Op[i + 627*t] ? R[B[i + 627*t]] * R[C[i + 627*t]] : R[B[i + 627*t]] + R[C[i + 627*t]];
R[i + 1481*t] = Op[i + 628*t] ? R[B[i + 628*t]] * R[C[i + 628*t]] : R[B[i + 628*t]] + R[C[i + 628*t]];
R[i + 1482*t] = Op[i + 629*t] ? R[B[i + 629*t]] * R[C[i + 629*t]] : R[B[i + 629*t]] + R[C[i + 629*t]];
R[i + 1483*t] = Op[i + 630*t] ? R[B[i + 630*t]] * R[C[i + 630*t]] : R[B[i + 630*t]] + R[C[i + 630*t]];
R[i + 1484*t] = Op[i + 631*t] ? R[B[i + 631*t]] * R[C[i + 631*t]] : R[B[i + 631*t]] + R[C[i + 631*t]];
R[i + 1485*t] = Op[i + 632*t] ? R[B[i + 632*t]] * R[C[i + 632*t]] : R[B[i + 632*t]] + R[C[i + 632*t]];
R[i + 1486*t] = Op[i + 633*t] ? R[B[i + 633*t]] * R[C[i + 633*t]] : R[B[i + 633*t]] + R[C[i + 633*t]];
R[i + 1487*t] = Op[i + 634*t] ? R[B[i + 634*t]] * R[C[i + 634*t]] : R[B[i + 634*t]] + R[C[i + 634*t]];
R[i + 1488*t] = Op[i + 635*t] ? R[B[i + 635*t]] * R[C[i + 635*t]] : R[B[i + 635*t]] + R[C[i + 635*t]];
R[i + 1489*t] = Op[i + 636*t] ? R[B[i + 636*t]] * R[C[i + 636*t]] : R[B[i + 636*t]] + R[C[i + 636*t]];
R[i + 1490*t] = Op[i + 637*t] ? R[B[i + 637*t]] * R[C[i + 637*t]] : R[B[i + 637*t]] + R[C[i + 637*t]];
R[i + 1491*t] = Op[i + 638*t] ? R[B[i + 638*t]] * R[C[i + 638*t]] : R[B[i + 638*t]] + R[C[i + 638*t]];
R[i + 1492*t] = Op[i + 639*t] ? R[B[i + 639*t]] * R[C[i + 639*t]] : R[B[i + 639*t]] + R[C[i + 639*t]];
R[i + 1493*t] = Op[i + 640*t] ? R[B[i + 640*t]] * R[C[i + 640*t]] : R[B[i + 640*t]] + R[C[i + 640*t]];
R[i + 1494*t] = Op[i + 641*t] ? R[B[i + 641*t]] * R[C[i + 641*t]] : R[B[i + 641*t]] + R[C[i + 641*t]];
R[i + 1495*t] = Op[i + 642*t] ? R[B[i + 642*t]] * R[C[i + 642*t]] : R[B[i + 642*t]] + R[C[i + 642*t]];
R[i + 1496*t] = Op[i + 643*t] ? R[B[i + 643*t]] * R[C[i + 643*t]] : R[B[i + 643*t]] + R[C[i + 643*t]];
R[i + 1497*t] = Op[i + 644*t] ? R[B[i + 644*t]] * R[C[i + 644*t]] : R[B[i + 644*t]] + R[C[i + 644*t]];
R[i + 1498*t] = Op[i + 645*t] ? R[B[i + 645*t]] * R[C[i + 645*t]] : R[B[i + 645*t]] + R[C[i + 645*t]];
R[i + 1499*t] = Op[i + 646*t] ? R[B[i + 646*t]] * R[C[i + 646*t]] : R[B[i + 646*t]] + R[C[i + 646*t]];
R[i + 1500*t] = Op[i + 647*t] ? R[B[i + 647*t]] * R[C[i + 647*t]] : R[B[i + 647*t]] + R[C[i + 647*t]];
R[i + 1501*t] = Op[i + 648*t] ? R[B[i + 648*t]] * R[C[i + 648*t]] : R[B[i + 648*t]] + R[C[i + 648*t]];
R[i + 1502*t] = Op[i + 649*t] ? R[B[i + 649*t]] * R[C[i + 649*t]] : R[B[i + 649*t]] + R[C[i + 649*t]];
R[i + 1503*t] = Op[i + 650*t] ? R[B[i + 650*t]] * R[C[i + 650*t]] : R[B[i + 650*t]] + R[C[i + 650*t]];
R[i + 1504*t] = Op[i + 651*t] ? R[B[i + 651*t]] * R[C[i + 651*t]] : R[B[i + 651*t]] + R[C[i + 651*t]];
R[i + 1505*t] = Op[i + 652*t] ? R[B[i + 652*t]] * R[C[i + 652*t]] : R[B[i + 652*t]] + R[C[i + 652*t]];
R[i + 1506*t] = Op[i + 653*t] ? R[B[i + 653*t]] * R[C[i + 653*t]] : R[B[i + 653*t]] + R[C[i + 653*t]];
R[i + 1507*t] = Op[i + 654*t] ? R[B[i + 654*t]] * R[C[i + 654*t]] : R[B[i + 654*t]] + R[C[i + 654*t]];
R[i + 1508*t] = Op[i + 655*t] ? R[B[i + 655*t]] * R[C[i + 655*t]] : R[B[i + 655*t]] + R[C[i + 655*t]];
R[i + 1509*t] = Op[i + 656*t] ? R[B[i + 656*t]] * R[C[i + 656*t]] : R[B[i + 656*t]] + R[C[i + 656*t]];
R[i + 1510*t] = Op[i + 657*t] ? R[B[i + 657*t]] * R[C[i + 657*t]] : R[B[i + 657*t]] + R[C[i + 657*t]];
R[i + 1511*t] = Op[i + 658*t] ? R[B[i + 658*t]] * R[C[i + 658*t]] : R[B[i + 658*t]] + R[C[i + 658*t]];
R[i + 1512*t] = Op[i + 659*t] ? R[B[i + 659*t]] * R[C[i + 659*t]] : R[B[i + 659*t]] + R[C[i + 659*t]];
R[i + 1513*t] = Op[i + 660*t] ? R[B[i + 660*t]] * R[C[i + 660*t]] : R[B[i + 660*t]] + R[C[i + 660*t]];
R[i + 1514*t] = Op[i + 661*t] ? R[B[i + 661*t]] * R[C[i + 661*t]] : R[B[i + 661*t]] + R[C[i + 661*t]];
R[i + 1515*t] = Op[i + 662*t] ? R[B[i + 662*t]] * R[C[i + 662*t]] : R[B[i + 662*t]] + R[C[i + 662*t]];
R[i + 1516*t] = Op[i + 663*t] ? R[B[i + 663*t]] * R[C[i + 663*t]] : R[B[i + 663*t]] + R[C[i + 663*t]];
R[i + 1517*t] = Op[i + 664*t] ? R[B[i + 664*t]] * R[C[i + 664*t]] : R[B[i + 664*t]] + R[C[i + 664*t]];
R[i + 1518*t] = Op[i + 665*t] ? R[B[i + 665*t]] * R[C[i + 665*t]] : R[B[i + 665*t]] + R[C[i + 665*t]];
R[i + 1519*t] = Op[i + 666*t] ? R[B[i + 666*t]] * R[C[i + 666*t]] : R[B[i + 666*t]] + R[C[i + 666*t]];
R[i + 1520*t] = Op[i + 667*t] ? R[B[i + 667*t]] * R[C[i + 667*t]] : R[B[i + 667*t]] + R[C[i + 667*t]];
R[i + 1521*t] = Op[i + 668*t] ? R[B[i + 668*t]] * R[C[i + 668*t]] : R[B[i + 668*t]] + R[C[i + 668*t]];
R[i + 1522*t] = Op[i + 669*t] ? R[B[i + 669*t]] * R[C[i + 669*t]] : R[B[i + 669*t]] + R[C[i + 669*t]];
__syncthreads();
R[i + 1523*t] = Op[i + 670*t] ? R[B[i + 670*t]] * R[C[i + 670*t]] : R[B[i + 670*t]] + R[C[i + 670*t]];
R[i + 1524*t] = Op[i + 671*t] ? R[B[i + 671*t]] * R[C[i + 671*t]] : R[B[i + 671*t]] + R[C[i + 671*t]];
R[i + 1525*t] = Op[i + 672*t] ? R[B[i + 672*t]] * R[C[i + 672*t]] : R[B[i + 672*t]] + R[C[i + 672*t]];
R[i + 1526*t] = Op[i + 673*t] ? R[B[i + 673*t]] * R[C[i + 673*t]] : R[B[i + 673*t]] + R[C[i + 673*t]];
R[i + 1527*t] = Op[i + 674*t] ? R[B[i + 674*t]] * R[C[i + 674*t]] : R[B[i + 674*t]] + R[C[i + 674*t]];
R[i + 1528*t] = Op[i + 675*t] ? R[B[i + 675*t]] * R[C[i + 675*t]] : R[B[i + 675*t]] + R[C[i + 675*t]];
R[i + 1529*t] = Op[i + 676*t] ? R[B[i + 676*t]] * R[C[i + 676*t]] : R[B[i + 676*t]] + R[C[i + 676*t]];
R[i + 1530*t] = Op[i + 677*t] ? R[B[i + 677*t]] * R[C[i + 677*t]] : R[B[i + 677*t]] + R[C[i + 677*t]];
R[i + 1531*t] = Op[i + 678*t] ? R[B[i + 678*t]] * R[C[i + 678*t]] : R[B[i + 678*t]] + R[C[i + 678*t]];
R[i + 1532*t] = Op[i + 679*t] ? R[B[i + 679*t]] * R[C[i + 679*t]] : R[B[i + 679*t]] + R[C[i + 679*t]];
R[i + 1533*t] = Op[i + 680*t] ? R[B[i + 680*t]] * R[C[i + 680*t]] : R[B[i + 680*t]] + R[C[i + 680*t]];
R[i + 1534*t] = Op[i + 681*t] ? R[B[i + 681*t]] * R[C[i + 681*t]] : R[B[i + 681*t]] + R[C[i + 681*t]];
R[i + 1535*t] = Op[i + 682*t] ? R[B[i + 682*t]] * R[C[i + 682*t]] : R[B[i + 682*t]] + R[C[i + 682*t]];
R[i + 1536*t] = Op[i + 683*t] ? R[B[i + 683*t]] * R[C[i + 683*t]] : R[B[i + 683*t]] + R[C[i + 683*t]];
R[i + 1537*t] = Op[i + 684*t] ? R[B[i + 684*t]] * R[C[i + 684*t]] : R[B[i + 684*t]] + R[C[i + 684*t]];
R[i + 1538*t] = Op[i + 685*t] ? R[B[i + 685*t]] * R[C[i + 685*t]] : R[B[i + 685*t]] + R[C[i + 685*t]];
R[i + 1539*t] = Op[i + 686*t] ? R[B[i + 686*t]] * R[C[i + 686*t]] : R[B[i + 686*t]] + R[C[i + 686*t]];
R[i + 1540*t] = Op[i + 687*t] ? R[B[i + 687*t]] * R[C[i + 687*t]] : R[B[i + 687*t]] + R[C[i + 687*t]];
R[i + 1541*t] = Op[i + 688*t] ? R[B[i + 688*t]] * R[C[i + 688*t]] : R[B[i + 688*t]] + R[C[i + 688*t]];
R[i + 1542*t] = Op[i + 689*t] ? R[B[i + 689*t]] * R[C[i + 689*t]] : R[B[i + 689*t]] + R[C[i + 689*t]];
R[i + 1543*t] = Op[i + 690*t] ? R[B[i + 690*t]] * R[C[i + 690*t]] : R[B[i + 690*t]] + R[C[i + 690*t]];
R[i + 1544*t] = Op[i + 691*t] ? R[B[i + 691*t]] * R[C[i + 691*t]] : R[B[i + 691*t]] + R[C[i + 691*t]];
R[i + 1545*t] = Op[i + 692*t] ? R[B[i + 692*t]] * R[C[i + 692*t]] : R[B[i + 692*t]] + R[C[i + 692*t]];
R[i + 1546*t] = Op[i + 693*t] ? R[B[i + 693*t]] * R[C[i + 693*t]] : R[B[i + 693*t]] + R[C[i + 693*t]];
R[i + 1547*t] = Op[i + 694*t] ? R[B[i + 694*t]] * R[C[i + 694*t]] : R[B[i + 694*t]] + R[C[i + 694*t]];
R[i + 1548*t] = Op[i + 695*t] ? R[B[i + 695*t]] * R[C[i + 695*t]] : R[B[i + 695*t]] + R[C[i + 695*t]];
R[i + 1549*t] = Op[i + 696*t] ? R[B[i + 696*t]] * R[C[i + 696*t]] : R[B[i + 696*t]] + R[C[i + 696*t]];
R[i + 1550*t] = Op[i + 697*t] ? R[B[i + 697*t]] * R[C[i + 697*t]] : R[B[i + 697*t]] + R[C[i + 697*t]];
R[i + 1551*t] = Op[i + 698*t] ? R[B[i + 698*t]] * R[C[i + 698*t]] : R[B[i + 698*t]] + R[C[i + 698*t]];
R[i + 1552*t] = Op[i + 699*t] ? R[B[i + 699*t]] * R[C[i + 699*t]] : R[B[i + 699*t]] + R[C[i + 699*t]];
R[i + 1553*t] = Op[i + 700*t] ? R[B[i + 700*t]] * R[C[i + 700*t]] : R[B[i + 700*t]] + R[C[i + 700*t]];
R[i + 1554*t] = Op[i + 701*t] ? R[B[i + 701*t]] * R[C[i + 701*t]] : R[B[i + 701*t]] + R[C[i + 701*t]];
R[i + 1555*t] = Op[i + 702*t] ? R[B[i + 702*t]] * R[C[i + 702*t]] : R[B[i + 702*t]] + R[C[i + 702*t]];
R[i + 1556*t] = Op[i + 703*t] ? R[B[i + 703*t]] * R[C[i + 703*t]] : R[B[i + 703*t]] + R[C[i + 703*t]];
R[i + 1557*t] = Op[i + 704*t] ? R[B[i + 704*t]] * R[C[i + 704*t]] : R[B[i + 704*t]] + R[C[i + 704*t]];
R[i + 1558*t] = Op[i + 705*t] ? R[B[i + 705*t]] * R[C[i + 705*t]] : R[B[i + 705*t]] + R[C[i + 705*t]];
R[i + 1559*t] = Op[i + 706*t] ? R[B[i + 706*t]] * R[C[i + 706*t]] : R[B[i + 706*t]] + R[C[i + 706*t]];
R[i + 1560*t] = Op[i + 707*t] ? R[B[i + 707*t]] * R[C[i + 707*t]] : R[B[i + 707*t]] + R[C[i + 707*t]];
R[i + 1561*t] = Op[i + 708*t] ? R[B[i + 708*t]] * R[C[i + 708*t]] : R[B[i + 708*t]] + R[C[i + 708*t]];
R[i + 1562*t] = Op[i + 709*t] ? R[B[i + 709*t]] * R[C[i + 709*t]] : R[B[i + 709*t]] + R[C[i + 709*t]];
R[i + 1563*t] = Op[i + 710*t] ? R[B[i + 710*t]] * R[C[i + 710*t]] : R[B[i + 710*t]] + R[C[i + 710*t]];
R[i + 1564*t] = Op[i + 711*t] ? R[B[i + 711*t]] * R[C[i + 711*t]] : R[B[i + 711*t]] + R[C[i + 711*t]];
R[i + 1565*t] = Op[i + 712*t] ? R[B[i + 712*t]] * R[C[i + 712*t]] : R[B[i + 712*t]] + R[C[i + 712*t]];
R[i + 1566*t] = Op[i + 713*t] ? R[B[i + 713*t]] * R[C[i + 713*t]] : R[B[i + 713*t]] + R[C[i + 713*t]];
R[i + 1567*t] = Op[i + 714*t] ? R[B[i + 714*t]] * R[C[i + 714*t]] : R[B[i + 714*t]] + R[C[i + 714*t]];
R[i + 1568*t] = Op[i + 715*t] ? R[B[i + 715*t]] * R[C[i + 715*t]] : R[B[i + 715*t]] + R[C[i + 715*t]];
R[i + 1569*t] = Op[i + 716*t] ? R[B[i + 716*t]] * R[C[i + 716*t]] : R[B[i + 716*t]] + R[C[i + 716*t]];
R[i + 1570*t] = Op[i + 717*t] ? R[B[i + 717*t]] * R[C[i + 717*t]] : R[B[i + 717*t]] + R[C[i + 717*t]];
R[i + 1571*t] = Op[i + 718*t] ? R[B[i + 718*t]] * R[C[i + 718*t]] : R[B[i + 718*t]] + R[C[i + 718*t]];
R[i + 1572*t] = Op[i + 719*t] ? R[B[i + 719*t]] * R[C[i + 719*t]] : R[B[i + 719*t]] + R[C[i + 719*t]];
R[i + 1573*t] = Op[i + 720*t] ? R[B[i + 720*t]] * R[C[i + 720*t]] : R[B[i + 720*t]] + R[C[i + 720*t]];
R[i + 1574*t] = Op[i + 721*t] ? R[B[i + 721*t]] * R[C[i + 721*t]] : R[B[i + 721*t]] + R[C[i + 721*t]];
R[i + 1575*t] = Op[i + 722*t] ? R[B[i + 722*t]] * R[C[i + 722*t]] : R[B[i + 722*t]] + R[C[i + 722*t]];
R[i + 1576*t] = Op[i + 723*t] ? R[B[i + 723*t]] * R[C[i + 723*t]] : R[B[i + 723*t]] + R[C[i + 723*t]];
R[i + 1577*t] = Op[i + 724*t] ? R[B[i + 724*t]] * R[C[i + 724*t]] : R[B[i + 724*t]] + R[C[i + 724*t]];
R[i + 1578*t] = Op[i + 725*t] ? R[B[i + 725*t]] * R[C[i + 725*t]] : R[B[i + 725*t]] + R[C[i + 725*t]];
R[i + 1579*t] = Op[i + 726*t] ? R[B[i + 726*t]] * R[C[i + 726*t]] : R[B[i + 726*t]] + R[C[i + 726*t]];
R[i + 1580*t] = Op[i + 727*t] ? R[B[i + 727*t]] * R[C[i + 727*t]] : R[B[i + 727*t]] + R[C[i + 727*t]];
R[i + 1581*t] = Op[i + 728*t] ? R[B[i + 728*t]] * R[C[i + 728*t]] : R[B[i + 728*t]] + R[C[i + 728*t]];
R[i + 1582*t] = Op[i + 729*t] ? R[B[i + 729*t]] * R[C[i + 729*t]] : R[B[i + 729*t]] + R[C[i + 729*t]];
R[i + 1583*t] = Op[i + 730*t] ? R[B[i + 730*t]] * R[C[i + 730*t]] : R[B[i + 730*t]] + R[C[i + 730*t]];
R[i + 1584*t] = Op[i + 731*t] ? R[B[i + 731*t]] * R[C[i + 731*t]] : R[B[i + 731*t]] + R[C[i + 731*t]];
R[i + 1585*t] = Op[i + 732*t] ? R[B[i + 732*t]] * R[C[i + 732*t]] : R[B[i + 732*t]] + R[C[i + 732*t]];
R[i + 1586*t] = Op[i + 733*t] ? R[B[i + 733*t]] * R[C[i + 733*t]] : R[B[i + 733*t]] + R[C[i + 733*t]];
R[i + 1587*t] = Op[i + 734*t] ? R[B[i + 734*t]] * R[C[i + 734*t]] : R[B[i + 734*t]] + R[C[i + 734*t]];
R[i + 1588*t] = Op[i + 735*t] ? R[B[i + 735*t]] * R[C[i + 735*t]] : R[B[i + 735*t]] + R[C[i + 735*t]];
R[i + 1589*t] = Op[i + 736*t] ? R[B[i + 736*t]] * R[C[i + 736*t]] : R[B[i + 736*t]] + R[C[i + 736*t]];
R[i + 1590*t] = Op[i + 737*t] ? R[B[i + 737*t]] * R[C[i + 737*t]] : R[B[i + 737*t]] + R[C[i + 737*t]];
R[i + 1591*t] = Op[i + 738*t] ? R[B[i + 738*t]] * R[C[i + 738*t]] : R[B[i + 738*t]] + R[C[i + 738*t]];
R[i + 1592*t] = Op[i + 739*t] ? R[B[i + 739*t]] * R[C[i + 739*t]] : R[B[i + 739*t]] + R[C[i + 739*t]];
R[i + 1593*t] = Op[i + 740*t] ? R[B[i + 740*t]] * R[C[i + 740*t]] : R[B[i + 740*t]] + R[C[i + 740*t]];
R[i + 1594*t] = Op[i + 741*t] ? R[B[i + 741*t]] * R[C[i + 741*t]] : R[B[i + 741*t]] + R[C[i + 741*t]];
R[i + 1595*t] = Op[i + 742*t] ? R[B[i + 742*t]] * R[C[i + 742*t]] : R[B[i + 742*t]] + R[C[i + 742*t]];
R[i + 1596*t] = Op[i + 743*t] ? R[B[i + 743*t]] * R[C[i + 743*t]] : R[B[i + 743*t]] + R[C[i + 743*t]];
R[i + 1597*t] = Op[i + 744*t] ? R[B[i + 744*t]] * R[C[i + 744*t]] : R[B[i + 744*t]] + R[C[i + 744*t]];
R[i + 1598*t] = Op[i + 745*t] ? R[B[i + 745*t]] * R[C[i + 745*t]] : R[B[i + 745*t]] + R[C[i + 745*t]];
R[i + 1599*t] = Op[i + 746*t] ? R[B[i + 746*t]] * R[C[i + 746*t]] : R[B[i + 746*t]] + R[C[i + 746*t]];
R[i + 1600*t] = Op[i + 747*t] ? R[B[i + 747*t]] * R[C[i + 747*t]] : R[B[i + 747*t]] + R[C[i + 747*t]];
R[i + 1601*t] = Op[i + 748*t] ? R[B[i + 748*t]] * R[C[i + 748*t]] : R[B[i + 748*t]] + R[C[i + 748*t]];
R[i + 1602*t] = Op[i + 749*t] ? R[B[i + 749*t]] * R[C[i + 749*t]] : R[B[i + 749*t]] + R[C[i + 749*t]];
__syncthreads();
R[i + 1603*t] = Op[i + 750*t] ? R[B[i + 750*t]] * R[C[i + 750*t]] : R[B[i + 750*t]] + R[C[i + 750*t]];
R[i + 1604*t] = Op[i + 751*t] ? R[B[i + 751*t]] * R[C[i + 751*t]] : R[B[i + 751*t]] + R[C[i + 751*t]];
R[i + 1605*t] = Op[i + 752*t] ? R[B[i + 752*t]] * R[C[i + 752*t]] : R[B[i + 752*t]] + R[C[i + 752*t]];
R[i + 1606*t] = Op[i + 753*t] ? R[B[i + 753*t]] * R[C[i + 753*t]] : R[B[i + 753*t]] + R[C[i + 753*t]];
R[i + 1607*t] = Op[i + 754*t] ? R[B[i + 754*t]] * R[C[i + 754*t]] : R[B[i + 754*t]] + R[C[i + 754*t]];
R[i + 1608*t] = Op[i + 755*t] ? R[B[i + 755*t]] * R[C[i + 755*t]] : R[B[i + 755*t]] + R[C[i + 755*t]];
R[i + 1609*t] = Op[i + 756*t] ? R[B[i + 756*t]] * R[C[i + 756*t]] : R[B[i + 756*t]] + R[C[i + 756*t]];
R[i + 1610*t] = Op[i + 757*t] ? R[B[i + 757*t]] * R[C[i + 757*t]] : R[B[i + 757*t]] + R[C[i + 757*t]];
R[i + 1611*t] = Op[i + 758*t] ? R[B[i + 758*t]] * R[C[i + 758*t]] : R[B[i + 758*t]] + R[C[i + 758*t]];
R[i + 1612*t] = Op[i + 759*t] ? R[B[i + 759*t]] * R[C[i + 759*t]] : R[B[i + 759*t]] + R[C[i + 759*t]];
R[i + 1613*t] = Op[i + 760*t] ? R[B[i + 760*t]] * R[C[i + 760*t]] : R[B[i + 760*t]] + R[C[i + 760*t]];
R[i + 1614*t] = Op[i + 761*t] ? R[B[i + 761*t]] * R[C[i + 761*t]] : R[B[i + 761*t]] + R[C[i + 761*t]];
R[i + 1615*t] = Op[i + 762*t] ? R[B[i + 762*t]] * R[C[i + 762*t]] : R[B[i + 762*t]] + R[C[i + 762*t]];
R[i + 1616*t] = Op[i + 763*t] ? R[B[i + 763*t]] * R[C[i + 763*t]] : R[B[i + 763*t]] + R[C[i + 763*t]];
R[i + 1617*t] = Op[i + 764*t] ? R[B[i + 764*t]] * R[C[i + 764*t]] : R[B[i + 764*t]] + R[C[i + 764*t]];
R[i + 1618*t] = Op[i + 765*t] ? R[B[i + 765*t]] * R[C[i + 765*t]] : R[B[i + 765*t]] + R[C[i + 765*t]];
R[i + 1619*t] = Op[i + 766*t] ? R[B[i + 766*t]] * R[C[i + 766*t]] : R[B[i + 766*t]] + R[C[i + 766*t]];
R[i + 1620*t] = Op[i + 767*t] ? R[B[i + 767*t]] * R[C[i + 767*t]] : R[B[i + 767*t]] + R[C[i + 767*t]];
R[i + 1621*t] = Op[i + 768*t] ? R[B[i + 768*t]] * R[C[i + 768*t]] : R[B[i + 768*t]] + R[C[i + 768*t]];
R[i + 1622*t] = Op[i + 769*t] ? R[B[i + 769*t]] * R[C[i + 769*t]] : R[B[i + 769*t]] + R[C[i + 769*t]];
R[i + 1623*t] = Op[i + 770*t] ? R[B[i + 770*t]] * R[C[i + 770*t]] : R[B[i + 770*t]] + R[C[i + 770*t]];
R[i + 1624*t] = Op[i + 771*t] ? R[B[i + 771*t]] * R[C[i + 771*t]] : R[B[i + 771*t]] + R[C[i + 771*t]];
R[i + 1625*t] = Op[i + 772*t] ? R[B[i + 772*t]] * R[C[i + 772*t]] : R[B[i + 772*t]] + R[C[i + 772*t]];
R[i + 1626*t] = Op[i + 773*t] ? R[B[i + 773*t]] * R[C[i + 773*t]] : R[B[i + 773*t]] + R[C[i + 773*t]];
R[i + 1627*t] = Op[i + 774*t] ? R[B[i + 774*t]] * R[C[i + 774*t]] : R[B[i + 774*t]] + R[C[i + 774*t]];
R[i + 1628*t] = Op[i + 775*t] ? R[B[i + 775*t]] * R[C[i + 775*t]] : R[B[i + 775*t]] + R[C[i + 775*t]];
R[i + 1629*t] = Op[i + 776*t] ? R[B[i + 776*t]] * R[C[i + 776*t]] : R[B[i + 776*t]] + R[C[i + 776*t]];
R[i + 1630*t] = Op[i + 777*t] ? R[B[i + 777*t]] * R[C[i + 777*t]] : R[B[i + 777*t]] + R[C[i + 777*t]];
R[i + 1631*t] = Op[i + 778*t] ? R[B[i + 778*t]] * R[C[i + 778*t]] : R[B[i + 778*t]] + R[C[i + 778*t]];
R[i + 1632*t] = Op[i + 779*t] ? R[B[i + 779*t]] * R[C[i + 779*t]] : R[B[i + 779*t]] + R[C[i + 779*t]];
R[i + 1633*t] = Op[i + 780*t] ? R[B[i + 780*t]] * R[C[i + 780*t]] : R[B[i + 780*t]] + R[C[i + 780*t]];
R[i + 1634*t] = Op[i + 781*t] ? R[B[i + 781*t]] * R[C[i + 781*t]] : R[B[i + 781*t]] + R[C[i + 781*t]];
R[i + 1635*t] = Op[i + 782*t] ? R[B[i + 782*t]] * R[C[i + 782*t]] : R[B[i + 782*t]] + R[C[i + 782*t]];
R[i + 1636*t] = Op[i + 783*t] ? R[B[i + 783*t]] * R[C[i + 783*t]] : R[B[i + 783*t]] + R[C[i + 783*t]];
R[i + 1637*t] = Op[i + 784*t] ? R[B[i + 784*t]] * R[C[i + 784*t]] : R[B[i + 784*t]] + R[C[i + 784*t]];
R[i + 1638*t] = Op[i + 785*t] ? R[B[i + 785*t]] * R[C[i + 785*t]] : R[B[i + 785*t]] + R[C[i + 785*t]];
R[i + 1639*t] = Op[i + 786*t] ? R[B[i + 786*t]] * R[C[i + 786*t]] : R[B[i + 786*t]] + R[C[i + 786*t]];
R[i + 1640*t] = Op[i + 787*t] ? R[B[i + 787*t]] * R[C[i + 787*t]] : R[B[i + 787*t]] + R[C[i + 787*t]];
R[i + 1641*t] = Op[i + 788*t] ? R[B[i + 788*t]] * R[C[i + 788*t]] : R[B[i + 788*t]] + R[C[i + 788*t]];
R[i + 1642*t] = Op[i + 789*t] ? R[B[i + 789*t]] * R[C[i + 789*t]] : R[B[i + 789*t]] + R[C[i + 789*t]];
R[i + 1643*t] = Op[i + 790*t] ? R[B[i + 790*t]] * R[C[i + 790*t]] : R[B[i + 790*t]] + R[C[i + 790*t]];
R[i + 1644*t] = Op[i + 791*t] ? R[B[i + 791*t]] * R[C[i + 791*t]] : R[B[i + 791*t]] + R[C[i + 791*t]];
R[i + 1645*t] = Op[i + 792*t] ? R[B[i + 792*t]] * R[C[i + 792*t]] : R[B[i + 792*t]] + R[C[i + 792*t]];
R[i + 1646*t] = Op[i + 793*t] ? R[B[i + 793*t]] * R[C[i + 793*t]] : R[B[i + 793*t]] + R[C[i + 793*t]];
R[i + 1647*t] = Op[i + 794*t] ? R[B[i + 794*t]] * R[C[i + 794*t]] : R[B[i + 794*t]] + R[C[i + 794*t]];
R[i + 1648*t] = Op[i + 795*t] ? R[B[i + 795*t]] * R[C[i + 795*t]] : R[B[i + 795*t]] + R[C[i + 795*t]];
R[i + 1649*t] = Op[i + 796*t] ? R[B[i + 796*t]] * R[C[i + 796*t]] : R[B[i + 796*t]] + R[C[i + 796*t]];
R[i + 1650*t] = Op[i + 797*t] ? R[B[i + 797*t]] * R[C[i + 797*t]] : R[B[i + 797*t]] + R[C[i + 797*t]];
R[i + 1651*t] = Op[i + 798*t] ? R[B[i + 798*t]] * R[C[i + 798*t]] : R[B[i + 798*t]] + R[C[i + 798*t]];
R[i + 1652*t] = Op[i + 799*t] ? R[B[i + 799*t]] * R[C[i + 799*t]] : R[B[i + 799*t]] + R[C[i + 799*t]];
R[i + 1653*t] = Op[i + 800*t] ? R[B[i + 800*t]] * R[C[i + 800*t]] : R[B[i + 800*t]] + R[C[i + 800*t]];
R[i + 1654*t] = Op[i + 801*t] ? R[B[i + 801*t]] * R[C[i + 801*t]] : R[B[i + 801*t]] + R[C[i + 801*t]];
R[i + 1655*t] = Op[i + 802*t] ? R[B[i + 802*t]] * R[C[i + 802*t]] : R[B[i + 802*t]] + R[C[i + 802*t]];
R[i + 1656*t] = Op[i + 803*t] ? R[B[i + 803*t]] * R[C[i + 803*t]] : R[B[i + 803*t]] + R[C[i + 803*t]];
R[i + 1657*t] = Op[i + 804*t] ? R[B[i + 804*t]] * R[C[i + 804*t]] : R[B[i + 804*t]] + R[C[i + 804*t]];
R[i + 1658*t] = Op[i + 805*t] ? R[B[i + 805*t]] * R[C[i + 805*t]] : R[B[i + 805*t]] + R[C[i + 805*t]];
R[i + 1659*t] = Op[i + 806*t] ? R[B[i + 806*t]] * R[C[i + 806*t]] : R[B[i + 806*t]] + R[C[i + 806*t]];
R[i + 1660*t] = Op[i + 807*t] ? R[B[i + 807*t]] * R[C[i + 807*t]] : R[B[i + 807*t]] + R[C[i + 807*t]];
R[i + 1661*t] = Op[i + 808*t] ? R[B[i + 808*t]] * R[C[i + 808*t]] : R[B[i + 808*t]] + R[C[i + 808*t]];
R[i + 1662*t] = Op[i + 809*t] ? R[B[i + 809*t]] * R[C[i + 809*t]] : R[B[i + 809*t]] + R[C[i + 809*t]];
R[i + 1663*t] = Op[i + 810*t] ? R[B[i + 810*t]] * R[C[i + 810*t]] : R[B[i + 810*t]] + R[C[i + 810*t]];
R[i + 1664*t] = Op[i + 811*t] ? R[B[i + 811*t]] * R[C[i + 811*t]] : R[B[i + 811*t]] + R[C[i + 811*t]];
R[i + 1665*t] = Op[i + 812*t] ? R[B[i + 812*t]] * R[C[i + 812*t]] : R[B[i + 812*t]] + R[C[i + 812*t]];
R[i + 1666*t] = Op[i + 813*t] ? R[B[i + 813*t]] * R[C[i + 813*t]] : R[B[i + 813*t]] + R[C[i + 813*t]];
R[i + 1667*t] = Op[i + 814*t] ? R[B[i + 814*t]] * R[C[i + 814*t]] : R[B[i + 814*t]] + R[C[i + 814*t]];
R[i + 1668*t] = Op[i + 815*t] ? R[B[i + 815*t]] * R[C[i + 815*t]] : R[B[i + 815*t]] + R[C[i + 815*t]];
R[i + 1669*t] = Op[i + 816*t] ? R[B[i + 816*t]] * R[C[i + 816*t]] : R[B[i + 816*t]] + R[C[i + 816*t]];
R[i + 1670*t] = Op[i + 817*t] ? R[B[i + 817*t]] * R[C[i + 817*t]] : R[B[i + 817*t]] + R[C[i + 817*t]];
R[i + 1671*t] = Op[i + 818*t] ? R[B[i + 818*t]] * R[C[i + 818*t]] : R[B[i + 818*t]] + R[C[i + 818*t]];
R[i + 1672*t] = Op[i + 819*t] ? R[B[i + 819*t]] * R[C[i + 819*t]] : R[B[i + 819*t]] + R[C[i + 819*t]];
R[i + 1673*t] = Op[i + 820*t] ? R[B[i + 820*t]] * R[C[i + 820*t]] : R[B[i + 820*t]] + R[C[i + 820*t]];
R[i + 1674*t] = Op[i + 821*t] ? R[B[i + 821*t]] * R[C[i + 821*t]] : R[B[i + 821*t]] + R[C[i + 821*t]];
R[i + 1675*t] = Op[i + 822*t] ? R[B[i + 822*t]] * R[C[i + 822*t]] : R[B[i + 822*t]] + R[C[i + 822*t]];
R[i + 1676*t] = Op[i + 823*t] ? R[B[i + 823*t]] * R[C[i + 823*t]] : R[B[i + 823*t]] + R[C[i + 823*t]];
R[i + 1677*t] = Op[i + 824*t] ? R[B[i + 824*t]] * R[C[i + 824*t]] : R[B[i + 824*t]] + R[C[i + 824*t]];
R[i + 1678*t] = Op[i + 825*t] ? R[B[i + 825*t]] * R[C[i + 825*t]] : R[B[i + 825*t]] + R[C[i + 825*t]];
R[i + 1679*t] = Op[i + 826*t] ? R[B[i + 826*t]] * R[C[i + 826*t]] : R[B[i + 826*t]] + R[C[i + 826*t]];
R[i + 1680*t] = Op[i + 827*t] ? R[B[i + 827*t]] * R[C[i + 827*t]] : R[B[i + 827*t]] + R[C[i + 827*t]];
R[i + 1681*t] = Op[i + 828*t] ? R[B[i + 828*t]] * R[C[i + 828*t]] : R[B[i + 828*t]] + R[C[i + 828*t]];
R[i + 1682*t] = Op[i + 829*t] ? R[B[i + 829*t]] * R[C[i + 829*t]] : R[B[i + 829*t]] + R[C[i + 829*t]];
R[i + 1683*t] = Op[i + 830*t] ? R[B[i + 830*t]] * R[C[i + 830*t]] : R[B[i + 830*t]] + R[C[i + 830*t]];
R[i + 1684*t] = Op[i + 831*t] ? R[B[i + 831*t]] * R[C[i + 831*t]] : R[B[i + 831*t]] + R[C[i + 831*t]];
R[i + 1685*t] = Op[i + 832*t] ? R[B[i + 832*t]] * R[C[i + 832*t]] : R[B[i + 832*t]] + R[C[i + 832*t]];
R[i + 1686*t] = Op[i + 833*t] ? R[B[i + 833*t]] * R[C[i + 833*t]] : R[B[i + 833*t]] + R[C[i + 833*t]];
R[i + 1687*t] = Op[i + 834*t] ? R[B[i + 834*t]] * R[C[i + 834*t]] : R[B[i + 834*t]] + R[C[i + 834*t]];
R[i + 1688*t] = Op[i + 835*t] ? R[B[i + 835*t]] * R[C[i + 835*t]] : R[B[i + 835*t]] + R[C[i + 835*t]];
R[i + 1689*t] = Op[i + 836*t] ? R[B[i + 836*t]] * R[C[i + 836*t]] : R[B[i + 836*t]] + R[C[i + 836*t]];
R[i + 1690*t] = Op[i + 837*t] ? R[B[i + 837*t]] * R[C[i + 837*t]] : R[B[i + 837*t]] + R[C[i + 837*t]];
R[i + 1691*t] = Op[i + 838*t] ? R[B[i + 838*t]] * R[C[i + 838*t]] : R[B[i + 838*t]] + R[C[i + 838*t]];
R[i + 1692*t] = Op[i + 839*t] ? R[B[i + 839*t]] * R[C[i + 839*t]] : R[B[i + 839*t]] + R[C[i + 839*t]];
R[i + 1693*t] = Op[i + 840*t] ? R[B[i + 840*t]] * R[C[i + 840*t]] : R[B[i + 840*t]] + R[C[i + 840*t]];
R[i + 1694*t] = Op[i + 841*t] ? R[B[i + 841*t]] * R[C[i + 841*t]] : R[B[i + 841*t]] + R[C[i + 841*t]];
R[i + 1695*t] = Op[i + 842*t] ? R[B[i + 842*t]] * R[C[i + 842*t]] : R[B[i + 842*t]] + R[C[i + 842*t]];
R[i + 1696*t] = Op[i + 843*t] ? R[B[i + 843*t]] * R[C[i + 843*t]] : R[B[i + 843*t]] + R[C[i + 843*t]];
R[i + 1697*t] = Op[i + 844*t] ? R[B[i + 844*t]] * R[C[i + 844*t]] : R[B[i + 844*t]] + R[C[i + 844*t]];
R[i + 1698*t] = Op[i + 845*t] ? R[B[i + 845*t]] * R[C[i + 845*t]] : R[B[i + 845*t]] + R[C[i + 845*t]];
R[i + 1699*t] = Op[i + 846*t] ? R[B[i + 846*t]] * R[C[i + 846*t]] : R[B[i + 846*t]] + R[C[i + 846*t]];
R[i + 1700*t] = Op[i + 847*t] ? R[B[i + 847*t]] * R[C[i + 847*t]] : R[B[i + 847*t]] + R[C[i + 847*t]];
R[i + 1701*t] = Op[i + 848*t] ? R[B[i + 848*t]] * R[C[i + 848*t]] : R[B[i + 848*t]] + R[C[i + 848*t]];
R[i + 1702*t] = Op[i + 849*t] ? R[B[i + 849*t]] * R[C[i + 849*t]] : R[B[i + 849*t]] + R[C[i + 849*t]];
R[i + 1703*t] = Op[i + 850*t] ? R[B[i + 850*t]] * R[C[i + 850*t]] : R[B[i + 850*t]] + R[C[i + 850*t]];
R[i + 1704*t] = Op[i + 851*t] ? R[B[i + 851*t]] * R[C[i + 851*t]] : R[B[i + 851*t]] + R[C[i + 851*t]];
R[i + 1705*t] = Op[i + 852*t] ? R[B[i + 852*t]] * R[C[i + 852*t]] : R[B[i + 852*t]] + R[C[i + 852*t]];
R[i + 1706*t] = Op[i + 853*t] ? R[B[i + 853*t]] * R[C[i + 853*t]] : R[B[i + 853*t]] + R[C[i + 853*t]];
R[i + 1707*t] = Op[i + 854*t] ? R[B[i + 854*t]] * R[C[i + 854*t]] : R[B[i + 854*t]] + R[C[i + 854*t]];
R[i + 1708*t] = Op[i + 855*t] ? R[B[i + 855*t]] * R[C[i + 855*t]] : R[B[i + 855*t]] + R[C[i + 855*t]];
R[i + 1709*t] = Op[i + 856*t] ? R[B[i + 856*t]] * R[C[i + 856*t]] : R[B[i + 856*t]] + R[C[i + 856*t]];
__syncthreads();
R[i + 1710*t] = Op[i + 857*t] ? R[B[i + 857*t]] * R[C[i + 857*t]] : R[B[i + 857*t]] + R[C[i + 857*t]];
R[i + 1711*t] = Op[i + 858*t] ? R[B[i + 858*t]] * R[C[i + 858*t]] : R[B[i + 858*t]] + R[C[i + 858*t]];
R[i + 1712*t] = Op[i + 859*t] ? R[B[i + 859*t]] * R[C[i + 859*t]] : R[B[i + 859*t]] + R[C[i + 859*t]];
R[i + 1713*t] = Op[i + 860*t] ? R[B[i + 860*t]] * R[C[i + 860*t]] : R[B[i + 860*t]] + R[C[i + 860*t]];
R[i + 1714*t] = Op[i + 861*t] ? R[B[i + 861*t]] * R[C[i + 861*t]] : R[B[i + 861*t]] + R[C[i + 861*t]];
R[i + 1715*t] = Op[i + 862*t] ? R[B[i + 862*t]] * R[C[i + 862*t]] : R[B[i + 862*t]] + R[C[i + 862*t]];
R[i + 1716*t] = Op[i + 863*t] ? R[B[i + 863*t]] * R[C[i + 863*t]] : R[B[i + 863*t]] + R[C[i + 863*t]];
R[i + 1717*t] = Op[i + 864*t] ? R[B[i + 864*t]] * R[C[i + 864*t]] : R[B[i + 864*t]] + R[C[i + 864*t]];
R[i + 1718*t] = Op[i + 865*t] ? R[B[i + 865*t]] * R[C[i + 865*t]] : R[B[i + 865*t]] + R[C[i + 865*t]];
R[i + 1719*t] = Op[i + 866*t] ? R[B[i + 866*t]] * R[C[i + 866*t]] : R[B[i + 866*t]] + R[C[i + 866*t]];
R[i + 1720*t] = Op[i + 867*t] ? R[B[i + 867*t]] * R[C[i + 867*t]] : R[B[i + 867*t]] + R[C[i + 867*t]];
R[i + 1721*t] = Op[i + 868*t] ? R[B[i + 868*t]] * R[C[i + 868*t]] : R[B[i + 868*t]] + R[C[i + 868*t]];
R[i + 1722*t] = Op[i + 869*t] ? R[B[i + 869*t]] * R[C[i + 869*t]] : R[B[i + 869*t]] + R[C[i + 869*t]];
R[i + 1723*t] = Op[i + 870*t] ? R[B[i + 870*t]] * R[C[i + 870*t]] : R[B[i + 870*t]] + R[C[i + 870*t]];
R[i + 1724*t] = Op[i + 871*t] ? R[B[i + 871*t]] * R[C[i + 871*t]] : R[B[i + 871*t]] + R[C[i + 871*t]];
R[i + 1725*t] = Op[i + 872*t] ? R[B[i + 872*t]] * R[C[i + 872*t]] : R[B[i + 872*t]] + R[C[i + 872*t]];
R[i + 1726*t] = Op[i + 873*t] ? R[B[i + 873*t]] * R[C[i + 873*t]] : R[B[i + 873*t]] + R[C[i + 873*t]];
R[i + 1727*t] = Op[i + 874*t] ? R[B[i + 874*t]] * R[C[i + 874*t]] : R[B[i + 874*t]] + R[C[i + 874*t]];
R[i + 1728*t] = Op[i + 875*t] ? R[B[i + 875*t]] * R[C[i + 875*t]] : R[B[i + 875*t]] + R[C[i + 875*t]];
R[i + 1729*t] = Op[i + 876*t] ? R[B[i + 876*t]] * R[C[i + 876*t]] : R[B[i + 876*t]] + R[C[i + 876*t]];
R[i + 1730*t] = Op[i + 877*t] ? R[B[i + 877*t]] * R[C[i + 877*t]] : R[B[i + 877*t]] + R[C[i + 877*t]];
R[i + 1731*t] = Op[i + 878*t] ? R[B[i + 878*t]] * R[C[i + 878*t]] : R[B[i + 878*t]] + R[C[i + 878*t]];
R[i + 1732*t] = Op[i + 879*t] ? R[B[i + 879*t]] * R[C[i + 879*t]] : R[B[i + 879*t]] + R[C[i + 879*t]];
R[i + 1733*t] = Op[i + 880*t] ? R[B[i + 880*t]] * R[C[i + 880*t]] : R[B[i + 880*t]] + R[C[i + 880*t]];
R[i + 1734*t] = Op[i + 881*t] ? R[B[i + 881*t]] * R[C[i + 881*t]] : R[B[i + 881*t]] + R[C[i + 881*t]];
R[i + 1735*t] = Op[i + 882*t] ? R[B[i + 882*t]] * R[C[i + 882*t]] : R[B[i + 882*t]] + R[C[i + 882*t]];
R[i + 1736*t] = Op[i + 883*t] ? R[B[i + 883*t]] * R[C[i + 883*t]] : R[B[i + 883*t]] + R[C[i + 883*t]];
R[i + 1737*t] = Op[i + 884*t] ? R[B[i + 884*t]] * R[C[i + 884*t]] : R[B[i + 884*t]] + R[C[i + 884*t]];
R[i + 1738*t] = Op[i + 885*t] ? R[B[i + 885*t]] * R[C[i + 885*t]] : R[B[i + 885*t]] + R[C[i + 885*t]];
R[i + 1739*t] = Op[i + 886*t] ? R[B[i + 886*t]] * R[C[i + 886*t]] : R[B[i + 886*t]] + R[C[i + 886*t]];
R[i + 1740*t] = Op[i + 887*t] ? R[B[i + 887*t]] * R[C[i + 887*t]] : R[B[i + 887*t]] + R[C[i + 887*t]];
R[i + 1741*t] = Op[i + 888*t] ? R[B[i + 888*t]] * R[C[i + 888*t]] : R[B[i + 888*t]] + R[C[i + 888*t]];
R[i + 1742*t] = Op[i + 889*t] ? R[B[i + 889*t]] * R[C[i + 889*t]] : R[B[i + 889*t]] + R[C[i + 889*t]];
R[i + 1743*t] = Op[i + 890*t] ? R[B[i + 890*t]] * R[C[i + 890*t]] : R[B[i + 890*t]] + R[C[i + 890*t]];
R[i + 1744*t] = Op[i + 891*t] ? R[B[i + 891*t]] * R[C[i + 891*t]] : R[B[i + 891*t]] + R[C[i + 891*t]];
R[i + 1745*t] = Op[i + 892*t] ? R[B[i + 892*t]] * R[C[i + 892*t]] : R[B[i + 892*t]] + R[C[i + 892*t]];
R[i + 1746*t] = Op[i + 893*t] ? R[B[i + 893*t]] * R[C[i + 893*t]] : R[B[i + 893*t]] + R[C[i + 893*t]];
R[i + 1747*t] = Op[i + 894*t] ? R[B[i + 894*t]] * R[C[i + 894*t]] : R[B[i + 894*t]] + R[C[i + 894*t]];
R[i + 1748*t] = Op[i + 895*t] ? R[B[i + 895*t]] * R[C[i + 895*t]] : R[B[i + 895*t]] + R[C[i + 895*t]];
R[i + 1749*t] = Op[i + 896*t] ? R[B[i + 896*t]] * R[C[i + 896*t]] : R[B[i + 896*t]] + R[C[i + 896*t]];
R[i + 1750*t] = Op[i + 897*t] ? R[B[i + 897*t]] * R[C[i + 897*t]] : R[B[i + 897*t]] + R[C[i + 897*t]];
R[i + 1751*t] = Op[i + 898*t] ? R[B[i + 898*t]] * R[C[i + 898*t]] : R[B[i + 898*t]] + R[C[i + 898*t]];
R[i + 1752*t] = Op[i + 899*t] ? R[B[i + 899*t]] * R[C[i + 899*t]] : R[B[i + 899*t]] + R[C[i + 899*t]];
R[i + 1753*t] = Op[i + 900*t] ? R[B[i + 900*t]] * R[C[i + 900*t]] : R[B[i + 900*t]] + R[C[i + 900*t]];
R[i + 1754*t] = Op[i + 901*t] ? R[B[i + 901*t]] * R[C[i + 901*t]] : R[B[i + 901*t]] + R[C[i + 901*t]];
R[i + 1755*t] = Op[i + 902*t] ? R[B[i + 902*t]] * R[C[i + 902*t]] : R[B[i + 902*t]] + R[C[i + 902*t]];
R[i + 1756*t] = Op[i + 903*t] ? R[B[i + 903*t]] * R[C[i + 903*t]] : R[B[i + 903*t]] + R[C[i + 903*t]];
R[i + 1757*t] = Op[i + 904*t] ? R[B[i + 904*t]] * R[C[i + 904*t]] : R[B[i + 904*t]] + R[C[i + 904*t]];
R[i + 1758*t] = Op[i + 905*t] ? R[B[i + 905*t]] * R[C[i + 905*t]] : R[B[i + 905*t]] + R[C[i + 905*t]];
R[i + 1759*t] = Op[i + 906*t] ? R[B[i + 906*t]] * R[C[i + 906*t]] : R[B[i + 906*t]] + R[C[i + 906*t]];
R[i + 1760*t] = Op[i + 907*t] ? R[B[i + 907*t]] * R[C[i + 907*t]] : R[B[i + 907*t]] + R[C[i + 907*t]];
R[i + 1761*t] = Op[i + 908*t] ? R[B[i + 908*t]] * R[C[i + 908*t]] : R[B[i + 908*t]] + R[C[i + 908*t]];
R[i + 1762*t] = Op[i + 909*t] ? R[B[i + 909*t]] * R[C[i + 909*t]] : R[B[i + 909*t]] + R[C[i + 909*t]];
R[i + 1763*t] = Op[i + 910*t] ? R[B[i + 910*t]] * R[C[i + 910*t]] : R[B[i + 910*t]] + R[C[i + 910*t]];
R[i + 1764*t] = Op[i + 911*t] ? R[B[i + 911*t]] * R[C[i + 911*t]] : R[B[i + 911*t]] + R[C[i + 911*t]];
R[i + 1765*t] = Op[i + 912*t] ? R[B[i + 912*t]] * R[C[i + 912*t]] : R[B[i + 912*t]] + R[C[i + 912*t]];
R[i + 1766*t] = Op[i + 913*t] ? R[B[i + 913*t]] * R[C[i + 913*t]] : R[B[i + 913*t]] + R[C[i + 913*t]];
R[i + 1767*t] = Op[i + 914*t] ? R[B[i + 914*t]] * R[C[i + 914*t]] : R[B[i + 914*t]] + R[C[i + 914*t]];
R[i + 1768*t] = Op[i + 915*t] ? R[B[i + 915*t]] * R[C[i + 915*t]] : R[B[i + 915*t]] + R[C[i + 915*t]];
R[i + 1769*t] = Op[i + 916*t] ? R[B[i + 916*t]] * R[C[i + 916*t]] : R[B[i + 916*t]] + R[C[i + 916*t]];
R[i + 1770*t] = Op[i + 917*t] ? R[B[i + 917*t]] * R[C[i + 917*t]] : R[B[i + 917*t]] + R[C[i + 917*t]];
R[i + 1771*t] = Op[i + 918*t] ? R[B[i + 918*t]] * R[C[i + 918*t]] : R[B[i + 918*t]] + R[C[i + 918*t]];
R[i + 1772*t] = Op[i + 919*t] ? R[B[i + 919*t]] * R[C[i + 919*t]] : R[B[i + 919*t]] + R[C[i + 919*t]];
R[i + 1773*t] = Op[i + 920*t] ? R[B[i + 920*t]] * R[C[i + 920*t]] : R[B[i + 920*t]] + R[C[i + 920*t]];
R[i + 1774*t] = Op[i + 921*t] ? R[B[i + 921*t]] * R[C[i + 921*t]] : R[B[i + 921*t]] + R[C[i + 921*t]];
R[i + 1775*t] = Op[i + 922*t] ? R[B[i + 922*t]] * R[C[i + 922*t]] : R[B[i + 922*t]] + R[C[i + 922*t]];
R[i + 1776*t] = Op[i + 923*t] ? R[B[i + 923*t]] * R[C[i + 923*t]] : R[B[i + 923*t]] + R[C[i + 923*t]];
R[i + 1777*t] = Op[i + 924*t] ? R[B[i + 924*t]] * R[C[i + 924*t]] : R[B[i + 924*t]] + R[C[i + 924*t]];
R[i + 1778*t] = Op[i + 925*t] ? R[B[i + 925*t]] * R[C[i + 925*t]] : R[B[i + 925*t]] + R[C[i + 925*t]];
R[i + 1779*t] = Op[i + 926*t] ? R[B[i + 926*t]] * R[C[i + 926*t]] : R[B[i + 926*t]] + R[C[i + 926*t]];
R[i + 1780*t] = Op[i + 927*t] ? R[B[i + 927*t]] * R[C[i + 927*t]] : R[B[i + 927*t]] + R[C[i + 927*t]];
R[i + 1781*t] = Op[i + 928*t] ? R[B[i + 928*t]] * R[C[i + 928*t]] : R[B[i + 928*t]] + R[C[i + 928*t]];
R[i + 1782*t] = Op[i + 929*t] ? R[B[i + 929*t]] * R[C[i + 929*t]] : R[B[i + 929*t]] + R[C[i + 929*t]];
R[i + 1783*t] = Op[i + 930*t] ? R[B[i + 930*t]] * R[C[i + 930*t]] : R[B[i + 930*t]] + R[C[i + 930*t]];
R[i + 1784*t] = Op[i + 931*t] ? R[B[i + 931*t]] * R[C[i + 931*t]] : R[B[i + 931*t]] + R[C[i + 931*t]];
R[i + 1785*t] = Op[i + 932*t] ? R[B[i + 932*t]] * R[C[i + 932*t]] : R[B[i + 932*t]] + R[C[i + 932*t]];
R[i + 1786*t] = Op[i + 933*t] ? R[B[i + 933*t]] * R[C[i + 933*t]] : R[B[i + 933*t]] + R[C[i + 933*t]];
R[i + 1787*t] = Op[i + 934*t] ? R[B[i + 934*t]] * R[C[i + 934*t]] : R[B[i + 934*t]] + R[C[i + 934*t]];
R[i + 1788*t] = Op[i + 935*t] ? R[B[i + 935*t]] * R[C[i + 935*t]] : R[B[i + 935*t]] + R[C[i + 935*t]];
R[i + 1789*t] = Op[i + 936*t] ? R[B[i + 936*t]] * R[C[i + 936*t]] : R[B[i + 936*t]] + R[C[i + 936*t]];
R[i + 1790*t] = Op[i + 937*t] ? R[B[i + 937*t]] * R[C[i + 937*t]] : R[B[i + 937*t]] + R[C[i + 937*t]];
R[i + 1791*t] = Op[i + 938*t] ? R[B[i + 938*t]] * R[C[i + 938*t]] : R[B[i + 938*t]] + R[C[i + 938*t]];
R[i + 1792*t] = Op[i + 939*t] ? R[B[i + 939*t]] * R[C[i + 939*t]] : R[B[i + 939*t]] + R[C[i + 939*t]];
R[i + 1793*t] = Op[i + 940*t] ? R[B[i + 940*t]] * R[C[i + 940*t]] : R[B[i + 940*t]] + R[C[i + 940*t]];
R[i + 1794*t] = Op[i + 941*t] ? R[B[i + 941*t]] * R[C[i + 941*t]] : R[B[i + 941*t]] + R[C[i + 941*t]];
R[i + 1795*t] = Op[i + 942*t] ? R[B[i + 942*t]] * R[C[i + 942*t]] : R[B[i + 942*t]] + R[C[i + 942*t]];
R[i + 1796*t] = Op[i + 943*t] ? R[B[i + 943*t]] * R[C[i + 943*t]] : R[B[i + 943*t]] + R[C[i + 943*t]];
__syncthreads();
R[i + 1797*t] = Op[i + 944*t] ? R[B[i + 944*t]] * R[C[i + 944*t]] : R[B[i + 944*t]] + R[C[i + 944*t]];
R[i + 1798*t] = Op[i + 945*t] ? R[B[i + 945*t]] * R[C[i + 945*t]] : R[B[i + 945*t]] + R[C[i + 945*t]];
R[i + 1799*t] = Op[i + 946*t] ? R[B[i + 946*t]] * R[C[i + 946*t]] : R[B[i + 946*t]] + R[C[i + 946*t]];
R[i + 1800*t] = Op[i + 947*t] ? R[B[i + 947*t]] * R[C[i + 947*t]] : R[B[i + 947*t]] + R[C[i + 947*t]];
R[i + 1801*t] = Op[i + 948*t] ? R[B[i + 948*t]] * R[C[i + 948*t]] : R[B[i + 948*t]] + R[C[i + 948*t]];
R[i + 1802*t] = Op[i + 949*t] ? R[B[i + 949*t]] * R[C[i + 949*t]] : R[B[i + 949*t]] + R[C[i + 949*t]];
R[i + 1803*t] = Op[i + 950*t] ? R[B[i + 950*t]] * R[C[i + 950*t]] : R[B[i + 950*t]] + R[C[i + 950*t]];
R[i + 1804*t] = Op[i + 951*t] ? R[B[i + 951*t]] * R[C[i + 951*t]] : R[B[i + 951*t]] + R[C[i + 951*t]];
R[i + 1805*t] = Op[i + 952*t] ? R[B[i + 952*t]] * R[C[i + 952*t]] : R[B[i + 952*t]] + R[C[i + 952*t]];
R[i + 1806*t] = Op[i + 953*t] ? R[B[i + 953*t]] * R[C[i + 953*t]] : R[B[i + 953*t]] + R[C[i + 953*t]];
R[i + 1807*t] = Op[i + 954*t] ? R[B[i + 954*t]] * R[C[i + 954*t]] : R[B[i + 954*t]] + R[C[i + 954*t]];
R[i + 1808*t] = Op[i + 955*t] ? R[B[i + 955*t]] * R[C[i + 955*t]] : R[B[i + 955*t]] + R[C[i + 955*t]];
R[i + 1809*t] = Op[i + 956*t] ? R[B[i + 956*t]] * R[C[i + 956*t]] : R[B[i + 956*t]] + R[C[i + 956*t]];
R[i + 1810*t] = Op[i + 957*t] ? R[B[i + 957*t]] * R[C[i + 957*t]] : R[B[i + 957*t]] + R[C[i + 957*t]];
R[i + 1811*t] = Op[i + 958*t] ? R[B[i + 958*t]] * R[C[i + 958*t]] : R[B[i + 958*t]] + R[C[i + 958*t]];
R[i + 1812*t] = Op[i + 959*t] ? R[B[i + 959*t]] * R[C[i + 959*t]] : R[B[i + 959*t]] + R[C[i + 959*t]];
R[i + 1813*t] = Op[i + 960*t] ? R[B[i + 960*t]] * R[C[i + 960*t]] : R[B[i + 960*t]] + R[C[i + 960*t]];
R[i + 1814*t] = Op[i + 961*t] ? R[B[i + 961*t]] * R[C[i + 961*t]] : R[B[i + 961*t]] + R[C[i + 961*t]];
R[i + 1815*t] = Op[i + 962*t] ? R[B[i + 962*t]] * R[C[i + 962*t]] : R[B[i + 962*t]] + R[C[i + 962*t]];
R[i + 1816*t] = Op[i + 963*t] ? R[B[i + 963*t]] * R[C[i + 963*t]] : R[B[i + 963*t]] + R[C[i + 963*t]];
R[i + 1817*t] = Op[i + 964*t] ? R[B[i + 964*t]] * R[C[i + 964*t]] : R[B[i + 964*t]] + R[C[i + 964*t]];
R[i + 1818*t] = Op[i + 965*t] ? R[B[i + 965*t]] * R[C[i + 965*t]] : R[B[i + 965*t]] + R[C[i + 965*t]];
R[i + 1819*t] = Op[i + 966*t] ? R[B[i + 966*t]] * R[C[i + 966*t]] : R[B[i + 966*t]] + R[C[i + 966*t]];
R[i + 1820*t] = Op[i + 967*t] ? R[B[i + 967*t]] * R[C[i + 967*t]] : R[B[i + 967*t]] + R[C[i + 967*t]];
R[i + 1821*t] = Op[i + 968*t] ? R[B[i + 968*t]] * R[C[i + 968*t]] : R[B[i + 968*t]] + R[C[i + 968*t]];
R[i + 1822*t] = Op[i + 969*t] ? R[B[i + 969*t]] * R[C[i + 969*t]] : R[B[i + 969*t]] + R[C[i + 969*t]];
R[i + 1823*t] = Op[i + 970*t] ? R[B[i + 970*t]] * R[C[i + 970*t]] : R[B[i + 970*t]] + R[C[i + 970*t]];
R[i + 1824*t] = Op[i + 971*t] ? R[B[i + 971*t]] * R[C[i + 971*t]] : R[B[i + 971*t]] + R[C[i + 971*t]];
R[i + 1825*t] = Op[i + 972*t] ? R[B[i + 972*t]] * R[C[i + 972*t]] : R[B[i + 972*t]] + R[C[i + 972*t]];
R[i + 1826*t] = Op[i + 973*t] ? R[B[i + 973*t]] * R[C[i + 973*t]] : R[B[i + 973*t]] + R[C[i + 973*t]];
R[i + 1827*t] = Op[i + 974*t] ? R[B[i + 974*t]] * R[C[i + 974*t]] : R[B[i + 974*t]] + R[C[i + 974*t]];
R[i + 1828*t] = Op[i + 975*t] ? R[B[i + 975*t]] * R[C[i + 975*t]] : R[B[i + 975*t]] + R[C[i + 975*t]];
R[i + 1829*t] = Op[i + 976*t] ? R[B[i + 976*t]] * R[C[i + 976*t]] : R[B[i + 976*t]] + R[C[i + 976*t]];
R[i + 1830*t] = Op[i + 977*t] ? R[B[i + 977*t]] * R[C[i + 977*t]] : R[B[i + 977*t]] + R[C[i + 977*t]];
R[i + 1831*t] = Op[i + 978*t] ? R[B[i + 978*t]] * R[C[i + 978*t]] : R[B[i + 978*t]] + R[C[i + 978*t]];
R[i + 1832*t] = Op[i + 979*t] ? R[B[i + 979*t]] * R[C[i + 979*t]] : R[B[i + 979*t]] + R[C[i + 979*t]];
R[i + 1833*t] = Op[i + 980*t] ? R[B[i + 980*t]] * R[C[i + 980*t]] : R[B[i + 980*t]] + R[C[i + 980*t]];
R[i + 1834*t] = Op[i + 981*t] ? R[B[i + 981*t]] * R[C[i + 981*t]] : R[B[i + 981*t]] + R[C[i + 981*t]];
R[i + 1835*t] = Op[i + 982*t] ? R[B[i + 982*t]] * R[C[i + 982*t]] : R[B[i + 982*t]] + R[C[i + 982*t]];
R[i + 1836*t] = Op[i + 983*t] ? R[B[i + 983*t]] * R[C[i + 983*t]] : R[B[i + 983*t]] + R[C[i + 983*t]];
R[i + 1837*t] = Op[i + 984*t] ? R[B[i + 984*t]] * R[C[i + 984*t]] : R[B[i + 984*t]] + R[C[i + 984*t]];
R[i + 1838*t] = Op[i + 985*t] ? R[B[i + 985*t]] * R[C[i + 985*t]] : R[B[i + 985*t]] + R[C[i + 985*t]];
R[i + 1839*t] = Op[i + 986*t] ? R[B[i + 986*t]] * R[C[i + 986*t]] : R[B[i + 986*t]] + R[C[i + 986*t]];
R[i + 1840*t] = Op[i + 987*t] ? R[B[i + 987*t]] * R[C[i + 987*t]] : R[B[i + 987*t]] + R[C[i + 987*t]];
R[i + 1841*t] = Op[i + 988*t] ? R[B[i + 988*t]] * R[C[i + 988*t]] : R[B[i + 988*t]] + R[C[i + 988*t]];
R[i + 1842*t] = Op[i + 989*t] ? R[B[i + 989*t]] * R[C[i + 989*t]] : R[B[i + 989*t]] + R[C[i + 989*t]];
R[i + 1843*t] = Op[i + 990*t] ? R[B[i + 990*t]] * R[C[i + 990*t]] : R[B[i + 990*t]] + R[C[i + 990*t]];
R[i + 1844*t] = Op[i + 991*t] ? R[B[i + 991*t]] * R[C[i + 991*t]] : R[B[i + 991*t]] + R[C[i + 991*t]];
R[i + 1845*t] = Op[i + 992*t] ? R[B[i + 992*t]] * R[C[i + 992*t]] : R[B[i + 992*t]] + R[C[i + 992*t]];
R[i + 1846*t] = Op[i + 993*t] ? R[B[i + 993*t]] * R[C[i + 993*t]] : R[B[i + 993*t]] + R[C[i + 993*t]];
R[i + 1847*t] = Op[i + 994*t] ? R[B[i + 994*t]] * R[C[i + 994*t]] : R[B[i + 994*t]] + R[C[i + 994*t]];
R[i + 1848*t] = Op[i + 995*t] ? R[B[i + 995*t]] * R[C[i + 995*t]] : R[B[i + 995*t]] + R[C[i + 995*t]];
R[i + 1849*t] = Op[i + 996*t] ? R[B[i + 996*t]] * R[C[i + 996*t]] : R[B[i + 996*t]] + R[C[i + 996*t]];
__syncthreads();
R[i + 1850*t] = Op[i + 997*t] ? R[B[i + 997*t]] * R[C[i + 997*t]] : R[B[i + 997*t]] + R[C[i + 997*t]];
R[i + 1851*t] = Op[i + 998*t] ? R[B[i + 998*t]] * R[C[i + 998*t]] : R[B[i + 998*t]] + R[C[i + 998*t]];
R[i + 1852*t] = Op[i + 999*t] ? R[B[i + 999*t]] * R[C[i + 999*t]] : R[B[i + 999*t]] + R[C[i + 999*t]];
R[i + 1853*t] = Op[i + 1000*t] ? R[B[i + 1000*t]] * R[C[i + 1000*t]] : R[B[i + 1000*t]] + R[C[i + 1000*t]];
R[i + 1854*t] = Op[i + 1001*t] ? R[B[i + 1001*t]] * R[C[i + 1001*t]] : R[B[i + 1001*t]] + R[C[i + 1001*t]];
R[i + 1855*t] = Op[i + 1002*t] ? R[B[i + 1002*t]] * R[C[i + 1002*t]] : R[B[i + 1002*t]] + R[C[i + 1002*t]];
R[i + 1856*t] = Op[i + 1003*t] ? R[B[i + 1003*t]] * R[C[i + 1003*t]] : R[B[i + 1003*t]] + R[C[i + 1003*t]];
R[i + 1857*t] = Op[i + 1004*t] ? R[B[i + 1004*t]] * R[C[i + 1004*t]] : R[B[i + 1004*t]] + R[C[i + 1004*t]];
R[i + 1858*t] = Op[i + 1005*t] ? R[B[i + 1005*t]] * R[C[i + 1005*t]] : R[B[i + 1005*t]] + R[C[i + 1005*t]];
R[i + 1859*t] = Op[i + 1006*t] ? R[B[i + 1006*t]] * R[C[i + 1006*t]] : R[B[i + 1006*t]] + R[C[i + 1006*t]];
R[i + 1860*t] = Op[i + 1007*t] ? R[B[i + 1007*t]] * R[C[i + 1007*t]] : R[B[i + 1007*t]] + R[C[i + 1007*t]];
R[i + 1861*t] = Op[i + 1008*t] ? R[B[i + 1008*t]] * R[C[i + 1008*t]] : R[B[i + 1008*t]] + R[C[i + 1008*t]];
R[i + 1862*t] = Op[i + 1009*t] ? R[B[i + 1009*t]] * R[C[i + 1009*t]] : R[B[i + 1009*t]] + R[C[i + 1009*t]];
R[i + 1863*t] = Op[i + 1010*t] ? R[B[i + 1010*t]] * R[C[i + 1010*t]] : R[B[i + 1010*t]] + R[C[i + 1010*t]];
R[i + 1864*t] = Op[i + 1011*t] ? R[B[i + 1011*t]] * R[C[i + 1011*t]] : R[B[i + 1011*t]] + R[C[i + 1011*t]];
R[i + 1865*t] = Op[i + 1012*t] ? R[B[i + 1012*t]] * R[C[i + 1012*t]] : R[B[i + 1012*t]] + R[C[i + 1012*t]];
R[i + 1866*t] = Op[i + 1013*t] ? R[B[i + 1013*t]] * R[C[i + 1013*t]] : R[B[i + 1013*t]] + R[C[i + 1013*t]];
R[i + 1867*t] = Op[i + 1014*t] ? R[B[i + 1014*t]] * R[C[i + 1014*t]] : R[B[i + 1014*t]] + R[C[i + 1014*t]];
R[i + 1868*t] = Op[i + 1015*t] ? R[B[i + 1015*t]] * R[C[i + 1015*t]] : R[B[i + 1015*t]] + R[C[i + 1015*t]];
R[i + 1869*t] = Op[i + 1016*t] ? R[B[i + 1016*t]] * R[C[i + 1016*t]] : R[B[i + 1016*t]] + R[C[i + 1016*t]];
R[i + 1870*t] = Op[i + 1017*t] ? R[B[i + 1017*t]] * R[C[i + 1017*t]] : R[B[i + 1017*t]] + R[C[i + 1017*t]];
R[i + 1871*t] = Op[i + 1018*t] ? R[B[i + 1018*t]] * R[C[i + 1018*t]] : R[B[i + 1018*t]] + R[C[i + 1018*t]];
R[i + 1872*t] = Op[i + 1019*t] ? R[B[i + 1019*t]] * R[C[i + 1019*t]] : R[B[i + 1019*t]] + R[C[i + 1019*t]];
R[i + 1873*t] = Op[i + 1020*t] ? R[B[i + 1020*t]] * R[C[i + 1020*t]] : R[B[i + 1020*t]] + R[C[i + 1020*t]];
R[i + 1874*t] = Op[i + 1021*t] ? R[B[i + 1021*t]] * R[C[i + 1021*t]] : R[B[i + 1021*t]] + R[C[i + 1021*t]];
R[i + 1875*t] = Op[i + 1022*t] ? R[B[i + 1022*t]] * R[C[i + 1022*t]] : R[B[i + 1022*t]] + R[C[i + 1022*t]];
R[i + 1876*t] = Op[i + 1023*t] ? R[B[i + 1023*t]] * R[C[i + 1023*t]] : R[B[i + 1023*t]] + R[C[i + 1023*t]];
R[i + 1877*t] = Op[i + 1024*t] ? R[B[i + 1024*t]] * R[C[i + 1024*t]] : R[B[i + 1024*t]] + R[C[i + 1024*t]];
R[i + 1878*t] = Op[i + 1025*t] ? R[B[i + 1025*t]] * R[C[i + 1025*t]] : R[B[i + 1025*t]] + R[C[i + 1025*t]];
R[i + 1879*t] = Op[i + 1026*t] ? R[B[i + 1026*t]] * R[C[i + 1026*t]] : R[B[i + 1026*t]] + R[C[i + 1026*t]];
R[i + 1880*t] = Op[i + 1027*t] ? R[B[i + 1027*t]] * R[C[i + 1027*t]] : R[B[i + 1027*t]] + R[C[i + 1027*t]];
R[i + 1881*t] = Op[i + 1028*t] ? R[B[i + 1028*t]] * R[C[i + 1028*t]] : R[B[i + 1028*t]] + R[C[i + 1028*t]];
R[i + 1882*t] = Op[i + 1029*t] ? R[B[i + 1029*t]] * R[C[i + 1029*t]] : R[B[i + 1029*t]] + R[C[i + 1029*t]];
R[i + 1883*t] = Op[i + 1030*t] ? R[B[i + 1030*t]] * R[C[i + 1030*t]] : R[B[i + 1030*t]] + R[C[i + 1030*t]];
R[i + 1884*t] = Op[i + 1031*t] ? R[B[i + 1031*t]] * R[C[i + 1031*t]] : R[B[i + 1031*t]] + R[C[i + 1031*t]];
R[i + 1885*t] = Op[i + 1032*t] ? R[B[i + 1032*t]] * R[C[i + 1032*t]] : R[B[i + 1032*t]] + R[C[i + 1032*t]];
R[i + 1886*t] = Op[i + 1033*t] ? R[B[i + 1033*t]] * R[C[i + 1033*t]] : R[B[i + 1033*t]] + R[C[i + 1033*t]];
R[i + 1887*t] = Op[i + 1034*t] ? R[B[i + 1034*t]] * R[C[i + 1034*t]] : R[B[i + 1034*t]] + R[C[i + 1034*t]];
R[i + 1888*t] = Op[i + 1035*t] ? R[B[i + 1035*t]] * R[C[i + 1035*t]] : R[B[i + 1035*t]] + R[C[i + 1035*t]];
R[i + 1889*t] = Op[i + 1036*t] ? R[B[i + 1036*t]] * R[C[i + 1036*t]] : R[B[i + 1036*t]] + R[C[i + 1036*t]];
R[i + 1890*t] = Op[i + 1037*t] ? R[B[i + 1037*t]] * R[C[i + 1037*t]] : R[B[i + 1037*t]] + R[C[i + 1037*t]];
R[i + 1891*t] = Op[i + 1038*t] ? R[B[i + 1038*t]] * R[C[i + 1038*t]] : R[B[i + 1038*t]] + R[C[i + 1038*t]];
R[i + 1892*t] = Op[i + 1039*t] ? R[B[i + 1039*t]] * R[C[i + 1039*t]] : R[B[i + 1039*t]] + R[C[i + 1039*t]];
R[i + 1893*t] = Op[i + 1040*t] ? R[B[i + 1040*t]] * R[C[i + 1040*t]] : R[B[i + 1040*t]] + R[C[i + 1040*t]];
R[i + 1894*t] = Op[i + 1041*t] ? R[B[i + 1041*t]] * R[C[i + 1041*t]] : R[B[i + 1041*t]] + R[C[i + 1041*t]];
R[i + 1895*t] = Op[i + 1042*t] ? R[B[i + 1042*t]] * R[C[i + 1042*t]] : R[B[i + 1042*t]] + R[C[i + 1042*t]];
R[i + 1896*t] = Op[i + 1043*t] ? R[B[i + 1043*t]] * R[C[i + 1043*t]] : R[B[i + 1043*t]] + R[C[i + 1043*t]];
R[i + 1897*t] = Op[i + 1044*t] ? R[B[i + 1044*t]] * R[C[i + 1044*t]] : R[B[i + 1044*t]] + R[C[i + 1044*t]];
R[i + 1898*t] = Op[i + 1045*t] ? R[B[i + 1045*t]] * R[C[i + 1045*t]] : R[B[i + 1045*t]] + R[C[i + 1045*t]];
R[i + 1899*t] = Op[i + 1046*t] ? R[B[i + 1046*t]] * R[C[i + 1046*t]] : R[B[i + 1046*t]] + R[C[i + 1046*t]];
R[i + 1900*t] = Op[i + 1047*t] ? R[B[i + 1047*t]] * R[C[i + 1047*t]] : R[B[i + 1047*t]] + R[C[i + 1047*t]];
R[i + 1901*t] = Op[i + 1048*t] ? R[B[i + 1048*t]] * R[C[i + 1048*t]] : R[B[i + 1048*t]] + R[C[i + 1048*t]];
R[i + 1902*t] = Op[i + 1049*t] ? R[B[i + 1049*t]] * R[C[i + 1049*t]] : R[B[i + 1049*t]] + R[C[i + 1049*t]];
R[i + 1903*t] = Op[i + 1050*t] ? R[B[i + 1050*t]] * R[C[i + 1050*t]] : R[B[i + 1050*t]] + R[C[i + 1050*t]];
R[i + 1904*t] = Op[i + 1051*t] ? R[B[i + 1051*t]] * R[C[i + 1051*t]] : R[B[i + 1051*t]] + R[C[i + 1051*t]];
R[i + 1905*t] = Op[i + 1052*t] ? R[B[i + 1052*t]] * R[C[i + 1052*t]] : R[B[i + 1052*t]] + R[C[i + 1052*t]];
__syncthreads();
R[i + 1906*t] = Op[i + 1053*t] ? R[B[i + 1053*t]] * R[C[i + 1053*t]] : R[B[i + 1053*t]] + R[C[i + 1053*t]];
R[i + 1907*t] = Op[i + 1054*t] ? R[B[i + 1054*t]] * R[C[i + 1054*t]] : R[B[i + 1054*t]] + R[C[i + 1054*t]];
R[i + 1908*t] = Op[i + 1055*t] ? R[B[i + 1055*t]] * R[C[i + 1055*t]] : R[B[i + 1055*t]] + R[C[i + 1055*t]];
R[i + 1909*t] = Op[i + 1056*t] ? R[B[i + 1056*t]] * R[C[i + 1056*t]] : R[B[i + 1056*t]] + R[C[i + 1056*t]];
R[i + 1910*t] = Op[i + 1057*t] ? R[B[i + 1057*t]] * R[C[i + 1057*t]] : R[B[i + 1057*t]] + R[C[i + 1057*t]];
R[i + 1911*t] = Op[i + 1058*t] ? R[B[i + 1058*t]] * R[C[i + 1058*t]] : R[B[i + 1058*t]] + R[C[i + 1058*t]];
R[i + 1912*t] = Op[i + 1059*t] ? R[B[i + 1059*t]] * R[C[i + 1059*t]] : R[B[i + 1059*t]] + R[C[i + 1059*t]];
R[i + 1913*t] = Op[i + 1060*t] ? R[B[i + 1060*t]] * R[C[i + 1060*t]] : R[B[i + 1060*t]] + R[C[i + 1060*t]];
R[i + 1914*t] = Op[i + 1061*t] ? R[B[i + 1061*t]] * R[C[i + 1061*t]] : R[B[i + 1061*t]] + R[C[i + 1061*t]];
R[i + 1915*t] = Op[i + 1062*t] ? R[B[i + 1062*t]] * R[C[i + 1062*t]] : R[B[i + 1062*t]] + R[C[i + 1062*t]];
R[i + 1916*t] = Op[i + 1063*t] ? R[B[i + 1063*t]] * R[C[i + 1063*t]] : R[B[i + 1063*t]] + R[C[i + 1063*t]];
R[i + 1917*t] = Op[i + 1064*t] ? R[B[i + 1064*t]] * R[C[i + 1064*t]] : R[B[i + 1064*t]] + R[C[i + 1064*t]];
R[i + 1918*t] = Op[i + 1065*t] ? R[B[i + 1065*t]] * R[C[i + 1065*t]] : R[B[i + 1065*t]] + R[C[i + 1065*t]];
R[i + 1919*t] = Op[i + 1066*t] ? R[B[i + 1066*t]] * R[C[i + 1066*t]] : R[B[i + 1066*t]] + R[C[i + 1066*t]];
R[i + 1920*t] = Op[i + 1067*t] ? R[B[i + 1067*t]] * R[C[i + 1067*t]] : R[B[i + 1067*t]] + R[C[i + 1067*t]];
R[i + 1921*t] = Op[i + 1068*t] ? R[B[i + 1068*t]] * R[C[i + 1068*t]] : R[B[i + 1068*t]] + R[C[i + 1068*t]];
R[i + 1922*t] = Op[i + 1069*t] ? R[B[i + 1069*t]] * R[C[i + 1069*t]] : R[B[i + 1069*t]] + R[C[i + 1069*t]];
R[i + 1923*t] = Op[i + 1070*t] ? R[B[i + 1070*t]] * R[C[i + 1070*t]] : R[B[i + 1070*t]] + R[C[i + 1070*t]];
R[i + 1924*t] = Op[i + 1071*t] ? R[B[i + 1071*t]] * R[C[i + 1071*t]] : R[B[i + 1071*t]] + R[C[i + 1071*t]];
R[i + 1925*t] = Op[i + 1072*t] ? R[B[i + 1072*t]] * R[C[i + 1072*t]] : R[B[i + 1072*t]] + R[C[i + 1072*t]];
R[i + 1926*t] = Op[i + 1073*t] ? R[B[i + 1073*t]] * R[C[i + 1073*t]] : R[B[i + 1073*t]] + R[C[i + 1073*t]];
R[i + 1927*t] = Op[i + 1074*t] ? R[B[i + 1074*t]] * R[C[i + 1074*t]] : R[B[i + 1074*t]] + R[C[i + 1074*t]];
R[i + 1928*t] = Op[i + 1075*t] ? R[B[i + 1075*t]] * R[C[i + 1075*t]] : R[B[i + 1075*t]] + R[C[i + 1075*t]];
R[i + 1929*t] = Op[i + 1076*t] ? R[B[i + 1076*t]] * R[C[i + 1076*t]] : R[B[i + 1076*t]] + R[C[i + 1076*t]];
R[i + 1930*t] = Op[i + 1077*t] ? R[B[i + 1077*t]] * R[C[i + 1077*t]] : R[B[i + 1077*t]] + R[C[i + 1077*t]];
R[i + 1931*t] = Op[i + 1078*t] ? R[B[i + 1078*t]] * R[C[i + 1078*t]] : R[B[i + 1078*t]] + R[C[i + 1078*t]];
R[i + 1932*t] = Op[i + 1079*t] ? R[B[i + 1079*t]] * R[C[i + 1079*t]] : R[B[i + 1079*t]] + R[C[i + 1079*t]];
R[i + 1933*t] = Op[i + 1080*t] ? R[B[i + 1080*t]] * R[C[i + 1080*t]] : R[B[i + 1080*t]] + R[C[i + 1080*t]];
R[i + 1934*t] = Op[i + 1081*t] ? R[B[i + 1081*t]] * R[C[i + 1081*t]] : R[B[i + 1081*t]] + R[C[i + 1081*t]];
R[i + 1935*t] = Op[i + 1082*t] ? R[B[i + 1082*t]] * R[C[i + 1082*t]] : R[B[i + 1082*t]] + R[C[i + 1082*t]];
R[i + 1936*t] = Op[i + 1083*t] ? R[B[i + 1083*t]] * R[C[i + 1083*t]] : R[B[i + 1083*t]] + R[C[i + 1083*t]];
R[i + 1937*t] = Op[i + 1084*t] ? R[B[i + 1084*t]] * R[C[i + 1084*t]] : R[B[i + 1084*t]] + R[C[i + 1084*t]];
R[i + 1938*t] = Op[i + 1085*t] ? R[B[i + 1085*t]] * R[C[i + 1085*t]] : R[B[i + 1085*t]] + R[C[i + 1085*t]];
R[i + 1939*t] = Op[i + 1086*t] ? R[B[i + 1086*t]] * R[C[i + 1086*t]] : R[B[i + 1086*t]] + R[C[i + 1086*t]];
R[i + 1940*t] = Op[i + 1087*t] ? R[B[i + 1087*t]] * R[C[i + 1087*t]] : R[B[i + 1087*t]] + R[C[i + 1087*t]];
R[i + 1941*t] = Op[i + 1088*t] ? R[B[i + 1088*t]] * R[C[i + 1088*t]] : R[B[i + 1088*t]] + R[C[i + 1088*t]];
R[i + 1942*t] = Op[i + 1089*t] ? R[B[i + 1089*t]] * R[C[i + 1089*t]] : R[B[i + 1089*t]] + R[C[i + 1089*t]];
R[i + 1943*t] = Op[i + 1090*t] ? R[B[i + 1090*t]] * R[C[i + 1090*t]] : R[B[i + 1090*t]] + R[C[i + 1090*t]];
R[i + 1944*t] = Op[i + 1091*t] ? R[B[i + 1091*t]] * R[C[i + 1091*t]] : R[B[i + 1091*t]] + R[C[i + 1091*t]];
__syncthreads();
R[i + 1945*t] = Op[i + 1092*t] ? R[B[i + 1092*t]] * R[C[i + 1092*t]] : R[B[i + 1092*t]] + R[C[i + 1092*t]];
R[i + 1946*t] = Op[i + 1093*t] ? R[B[i + 1093*t]] * R[C[i + 1093*t]] : R[B[i + 1093*t]] + R[C[i + 1093*t]];
R[i + 1947*t] = Op[i + 1094*t] ? R[B[i + 1094*t]] * R[C[i + 1094*t]] : R[B[i + 1094*t]] + R[C[i + 1094*t]];
R[i + 1948*t] = Op[i + 1095*t] ? R[B[i + 1095*t]] * R[C[i + 1095*t]] : R[B[i + 1095*t]] + R[C[i + 1095*t]];
R[i + 1949*t] = Op[i + 1096*t] ? R[B[i + 1096*t]] * R[C[i + 1096*t]] : R[B[i + 1096*t]] + R[C[i + 1096*t]];
R[i + 1950*t] = Op[i + 1097*t] ? R[B[i + 1097*t]] * R[C[i + 1097*t]] : R[B[i + 1097*t]] + R[C[i + 1097*t]];
R[i + 1951*t] = Op[i + 1098*t] ? R[B[i + 1098*t]] * R[C[i + 1098*t]] : R[B[i + 1098*t]] + R[C[i + 1098*t]];
R[i + 1952*t] = Op[i + 1099*t] ? R[B[i + 1099*t]] * R[C[i + 1099*t]] : R[B[i + 1099*t]] + R[C[i + 1099*t]];
R[i + 1953*t] = Op[i + 1100*t] ? R[B[i + 1100*t]] * R[C[i + 1100*t]] : R[B[i + 1100*t]] + R[C[i + 1100*t]];
R[i + 1954*t] = Op[i + 1101*t] ? R[B[i + 1101*t]] * R[C[i + 1101*t]] : R[B[i + 1101*t]] + R[C[i + 1101*t]];
R[i + 1955*t] = Op[i + 1102*t] ? R[B[i + 1102*t]] * R[C[i + 1102*t]] : R[B[i + 1102*t]] + R[C[i + 1102*t]];
R[i + 1956*t] = Op[i + 1103*t] ? R[B[i + 1103*t]] * R[C[i + 1103*t]] : R[B[i + 1103*t]] + R[C[i + 1103*t]];
R[i + 1957*t] = Op[i + 1104*t] ? R[B[i + 1104*t]] * R[C[i + 1104*t]] : R[B[i + 1104*t]] + R[C[i + 1104*t]];
R[i + 1958*t] = Op[i + 1105*t] ? R[B[i + 1105*t]] * R[C[i + 1105*t]] : R[B[i + 1105*t]] + R[C[i + 1105*t]];
R[i + 1959*t] = Op[i + 1106*t] ? R[B[i + 1106*t]] * R[C[i + 1106*t]] : R[B[i + 1106*t]] + R[C[i + 1106*t]];
R[i + 1960*t] = Op[i + 1107*t] ? R[B[i + 1107*t]] * R[C[i + 1107*t]] : R[B[i + 1107*t]] + R[C[i + 1107*t]];
R[i + 1961*t] = Op[i + 1108*t] ? R[B[i + 1108*t]] * R[C[i + 1108*t]] : R[B[i + 1108*t]] + R[C[i + 1108*t]];
R[i + 1962*t] = Op[i + 1109*t] ? R[B[i + 1109*t]] * R[C[i + 1109*t]] : R[B[i + 1109*t]] + R[C[i + 1109*t]];
R[i + 1963*t] = Op[i + 1110*t] ? R[B[i + 1110*t]] * R[C[i + 1110*t]] : R[B[i + 1110*t]] + R[C[i + 1110*t]];
R[i + 1964*t] = Op[i + 1111*t] ? R[B[i + 1111*t]] * R[C[i + 1111*t]] : R[B[i + 1111*t]] + R[C[i + 1111*t]];
R[i + 1965*t] = Op[i + 1112*t] ? R[B[i + 1112*t]] * R[C[i + 1112*t]] : R[B[i + 1112*t]] + R[C[i + 1112*t]];
R[i + 1966*t] = Op[i + 1113*t] ? R[B[i + 1113*t]] * R[C[i + 1113*t]] : R[B[i + 1113*t]] + R[C[i + 1113*t]];
R[i + 1967*t] = Op[i + 1114*t] ? R[B[i + 1114*t]] * R[C[i + 1114*t]] : R[B[i + 1114*t]] + R[C[i + 1114*t]];
R[i + 1968*t] = Op[i + 1115*t] ? R[B[i + 1115*t]] * R[C[i + 1115*t]] : R[B[i + 1115*t]] + R[C[i + 1115*t]];
R[i + 1969*t] = Op[i + 1116*t] ? R[B[i + 1116*t]] * R[C[i + 1116*t]] : R[B[i + 1116*t]] + R[C[i + 1116*t]];
R[i + 1970*t] = Op[i + 1117*t] ? R[B[i + 1117*t]] * R[C[i + 1117*t]] : R[B[i + 1117*t]] + R[C[i + 1117*t]];
R[i + 1971*t] = Op[i + 1118*t] ? R[B[i + 1118*t]] * R[C[i + 1118*t]] : R[B[i + 1118*t]] + R[C[i + 1118*t]];
R[i + 1972*t] = Op[i + 1119*t] ? R[B[i + 1119*t]] * R[C[i + 1119*t]] : R[B[i + 1119*t]] + R[C[i + 1119*t]];
R[i + 1973*t] = Op[i + 1120*t] ? R[B[i + 1120*t]] * R[C[i + 1120*t]] : R[B[i + 1120*t]] + R[C[i + 1120*t]];
R[i + 1974*t] = Op[i + 1121*t] ? R[B[i + 1121*t]] * R[C[i + 1121*t]] : R[B[i + 1121*t]] + R[C[i + 1121*t]];
R[i + 1975*t] = Op[i + 1122*t] ? R[B[i + 1122*t]] * R[C[i + 1122*t]] : R[B[i + 1122*t]] + R[C[i + 1122*t]];
R[i + 1976*t] = Op[i + 1123*t] ? R[B[i + 1123*t]] * R[C[i + 1123*t]] : R[B[i + 1123*t]] + R[C[i + 1123*t]];
R[i + 1977*t] = Op[i + 1124*t] ? R[B[i + 1124*t]] * R[C[i + 1124*t]] : R[B[i + 1124*t]] + R[C[i + 1124*t]];
R[i + 1978*t] = Op[i + 1125*t] ? R[B[i + 1125*t]] * R[C[i + 1125*t]] : R[B[i + 1125*t]] + R[C[i + 1125*t]];
R[i + 1979*t] = Op[i + 1126*t] ? R[B[i + 1126*t]] * R[C[i + 1126*t]] : R[B[i + 1126*t]] + R[C[i + 1126*t]];
R[i + 1980*t] = Op[i + 1127*t] ? R[B[i + 1127*t]] * R[C[i + 1127*t]] : R[B[i + 1127*t]] + R[C[i + 1127*t]];
R[i + 1981*t] = Op[i + 1128*t] ? R[B[i + 1128*t]] * R[C[i + 1128*t]] : R[B[i + 1128*t]] + R[C[i + 1128*t]];
__syncthreads();
R[i + 1982*t] = Op[i + 1129*t] ? R[B[i + 1129*t]] * R[C[i + 1129*t]] : R[B[i + 1129*t]] + R[C[i + 1129*t]];
R[i + 1983*t] = Op[i + 1130*t] ? R[B[i + 1130*t]] * R[C[i + 1130*t]] : R[B[i + 1130*t]] + R[C[i + 1130*t]];
R[i + 1984*t] = Op[i + 1131*t] ? R[B[i + 1131*t]] * R[C[i + 1131*t]] : R[B[i + 1131*t]] + R[C[i + 1131*t]];
R[i + 1985*t] = Op[i + 1132*t] ? R[B[i + 1132*t]] * R[C[i + 1132*t]] : R[B[i + 1132*t]] + R[C[i + 1132*t]];
R[i + 1986*t] = Op[i + 1133*t] ? R[B[i + 1133*t]] * R[C[i + 1133*t]] : R[B[i + 1133*t]] + R[C[i + 1133*t]];
R[i + 1987*t] = Op[i + 1134*t] ? R[B[i + 1134*t]] * R[C[i + 1134*t]] : R[B[i + 1134*t]] + R[C[i + 1134*t]];
R[i + 1988*t] = Op[i + 1135*t] ? R[B[i + 1135*t]] * R[C[i + 1135*t]] : R[B[i + 1135*t]] + R[C[i + 1135*t]];
R[i + 1989*t] = Op[i + 1136*t] ? R[B[i + 1136*t]] * R[C[i + 1136*t]] : R[B[i + 1136*t]] + R[C[i + 1136*t]];
R[i + 1990*t] = Op[i + 1137*t] ? R[B[i + 1137*t]] * R[C[i + 1137*t]] : R[B[i + 1137*t]] + R[C[i + 1137*t]];
R[i + 1991*t] = Op[i + 1138*t] ? R[B[i + 1138*t]] * R[C[i + 1138*t]] : R[B[i + 1138*t]] + R[C[i + 1138*t]];
R[i + 1992*t] = Op[i + 1139*t] ? R[B[i + 1139*t]] * R[C[i + 1139*t]] : R[B[i + 1139*t]] + R[C[i + 1139*t]];
R[i + 1993*t] = Op[i + 1140*t] ? R[B[i + 1140*t]] * R[C[i + 1140*t]] : R[B[i + 1140*t]] + R[C[i + 1140*t]];
R[i + 1994*t] = Op[i + 1141*t] ? R[B[i + 1141*t]] * R[C[i + 1141*t]] : R[B[i + 1141*t]] + R[C[i + 1141*t]];
R[i + 1995*t] = Op[i + 1142*t] ? R[B[i + 1142*t]] * R[C[i + 1142*t]] : R[B[i + 1142*t]] + R[C[i + 1142*t]];
R[i + 1996*t] = Op[i + 1143*t] ? R[B[i + 1143*t]] * R[C[i + 1143*t]] : R[B[i + 1143*t]] + R[C[i + 1143*t]];
R[i + 1997*t] = Op[i + 1144*t] ? R[B[i + 1144*t]] * R[C[i + 1144*t]] : R[B[i + 1144*t]] + R[C[i + 1144*t]];
R[i + 1998*t] = Op[i + 1145*t] ? R[B[i + 1145*t]] * R[C[i + 1145*t]] : R[B[i + 1145*t]] + R[C[i + 1145*t]];
R[i + 1999*t] = Op[i + 1146*t] ? R[B[i + 1146*t]] * R[C[i + 1146*t]] : R[B[i + 1146*t]] + R[C[i + 1146*t]];
R[i + 2000*t] = Op[i + 1147*t] ? R[B[i + 1147*t]] * R[C[i + 1147*t]] : R[B[i + 1147*t]] + R[C[i + 1147*t]];
R[i + 2001*t] = Op[i + 1148*t] ? R[B[i + 1148*t]] * R[C[i + 1148*t]] : R[B[i + 1148*t]] + R[C[i + 1148*t]];
R[i + 2002*t] = Op[i + 1149*t] ? R[B[i + 1149*t]] * R[C[i + 1149*t]] : R[B[i + 1149*t]] + R[C[i + 1149*t]];
R[i + 2003*t] = Op[i + 1150*t] ? R[B[i + 1150*t]] * R[C[i + 1150*t]] : R[B[i + 1150*t]] + R[C[i + 1150*t]];
R[i + 2004*t] = Op[i + 1151*t] ? R[B[i + 1151*t]] * R[C[i + 1151*t]] : R[B[i + 1151*t]] + R[C[i + 1151*t]];
R[i + 2005*t] = Op[i + 1152*t] ? R[B[i + 1152*t]] * R[C[i + 1152*t]] : R[B[i + 1152*t]] + R[C[i + 1152*t]];
R[i + 2006*t] = Op[i + 1153*t] ? R[B[i + 1153*t]] * R[C[i + 1153*t]] : R[B[i + 1153*t]] + R[C[i + 1153*t]];
R[i + 2007*t] = Op[i + 1154*t] ? R[B[i + 1154*t]] * R[C[i + 1154*t]] : R[B[i + 1154*t]] + R[C[i + 1154*t]];
R[i + 2008*t] = Op[i + 1155*t] ? R[B[i + 1155*t]] * R[C[i + 1155*t]] : R[B[i + 1155*t]] + R[C[i + 1155*t]];
R[i + 2009*t] = Op[i + 1156*t] ? R[B[i + 1156*t]] * R[C[i + 1156*t]] : R[B[i + 1156*t]] + R[C[i + 1156*t]];
R[i + 2010*t] = Op[i + 1157*t] ? R[B[i + 1157*t]] * R[C[i + 1157*t]] : R[B[i + 1157*t]] + R[C[i + 1157*t]];
R[i + 2011*t] = Op[i + 1158*t] ? R[B[i + 1158*t]] * R[C[i + 1158*t]] : R[B[i + 1158*t]] + R[C[i + 1158*t]];
R[i + 2012*t] = Op[i + 1159*t] ? R[B[i + 1159*t]] * R[C[i + 1159*t]] : R[B[i + 1159*t]] + R[C[i + 1159*t]];
R[i + 2013*t] = Op[i + 1160*t] ? R[B[i + 1160*t]] * R[C[i + 1160*t]] : R[B[i + 1160*t]] + R[C[i + 1160*t]];
__syncthreads();
R[i + 2014*t] = Op[i + 1161*t] ? R[B[i + 1161*t]] * R[C[i + 1161*t]] : R[B[i + 1161*t]] + R[C[i + 1161*t]];
R[i + 2015*t] = Op[i + 1162*t] ? R[B[i + 1162*t]] * R[C[i + 1162*t]] : R[B[i + 1162*t]] + R[C[i + 1162*t]];
R[i + 2016*t] = Op[i + 1163*t] ? R[B[i + 1163*t]] * R[C[i + 1163*t]] : R[B[i + 1163*t]] + R[C[i + 1163*t]];
R[i + 2017*t] = Op[i + 1164*t] ? R[B[i + 1164*t]] * R[C[i + 1164*t]] : R[B[i + 1164*t]] + R[C[i + 1164*t]];
R[i + 2018*t] = Op[i + 1165*t] ? R[B[i + 1165*t]] * R[C[i + 1165*t]] : R[B[i + 1165*t]] + R[C[i + 1165*t]];
R[i + 2019*t] = Op[i + 1166*t] ? R[B[i + 1166*t]] * R[C[i + 1166*t]] : R[B[i + 1166*t]] + R[C[i + 1166*t]];
R[i + 2020*t] = Op[i + 1167*t] ? R[B[i + 1167*t]] * R[C[i + 1167*t]] : R[B[i + 1167*t]] + R[C[i + 1167*t]];
R[i + 2021*t] = Op[i + 1168*t] ? R[B[i + 1168*t]] * R[C[i + 1168*t]] : R[B[i + 1168*t]] + R[C[i + 1168*t]];
R[i + 2022*t] = Op[i + 1169*t] ? R[B[i + 1169*t]] * R[C[i + 1169*t]] : R[B[i + 1169*t]] + R[C[i + 1169*t]];
R[i + 2023*t] = Op[i + 1170*t] ? R[B[i + 1170*t]] * R[C[i + 1170*t]] : R[B[i + 1170*t]] + R[C[i + 1170*t]];
R[i + 2024*t] = Op[i + 1171*t] ? R[B[i + 1171*t]] * R[C[i + 1171*t]] : R[B[i + 1171*t]] + R[C[i + 1171*t]];
R[i + 2025*t] = Op[i + 1172*t] ? R[B[i + 1172*t]] * R[C[i + 1172*t]] : R[B[i + 1172*t]] + R[C[i + 1172*t]];
R[i + 2026*t] = Op[i + 1173*t] ? R[B[i + 1173*t]] * R[C[i + 1173*t]] : R[B[i + 1173*t]] + R[C[i + 1173*t]];
R[i + 2027*t] = Op[i + 1174*t] ? R[B[i + 1174*t]] * R[C[i + 1174*t]] : R[B[i + 1174*t]] + R[C[i + 1174*t]];
R[i + 2028*t] = Op[i + 1175*t] ? R[B[i + 1175*t]] * R[C[i + 1175*t]] : R[B[i + 1175*t]] + R[C[i + 1175*t]];
R[i + 2029*t] = Op[i + 1176*t] ? R[B[i + 1176*t]] * R[C[i + 1176*t]] : R[B[i + 1176*t]] + R[C[i + 1176*t]];
R[i + 2030*t] = Op[i + 1177*t] ? R[B[i + 1177*t]] * R[C[i + 1177*t]] : R[B[i + 1177*t]] + R[C[i + 1177*t]];
R[i + 2031*t] = Op[i + 1178*t] ? R[B[i + 1178*t]] * R[C[i + 1178*t]] : R[B[i + 1178*t]] + R[C[i + 1178*t]];
R[i + 2032*t] = Op[i + 1179*t] ? R[B[i + 1179*t]] * R[C[i + 1179*t]] : R[B[i + 1179*t]] + R[C[i + 1179*t]];
__syncthreads();
R[i + 2033*t] = Op[i + 1180*t] ? R[B[i + 1180*t]] * R[C[i + 1180*t]] : R[B[i + 1180*t]] + R[C[i + 1180*t]];
R[i + 2034*t] = Op[i + 1181*t] ? R[B[i + 1181*t]] * R[C[i + 1181*t]] : R[B[i + 1181*t]] + R[C[i + 1181*t]];
R[i + 2035*t] = Op[i + 1182*t] ? R[B[i + 1182*t]] * R[C[i + 1182*t]] : R[B[i + 1182*t]] + R[C[i + 1182*t]];
R[i + 2036*t] = Op[i + 1183*t] ? R[B[i + 1183*t]] * R[C[i + 1183*t]] : R[B[i + 1183*t]] + R[C[i + 1183*t]];
R[i + 2037*t] = Op[i + 1184*t] ? R[B[i + 1184*t]] * R[C[i + 1184*t]] : R[B[i + 1184*t]] + R[C[i + 1184*t]];
R[i + 2038*t] = Op[i + 1185*t] ? R[B[i + 1185*t]] * R[C[i + 1185*t]] : R[B[i + 1185*t]] + R[C[i + 1185*t]];
R[i + 2039*t] = Op[i + 1186*t] ? R[B[i + 1186*t]] * R[C[i + 1186*t]] : R[B[i + 1186*t]] + R[C[i + 1186*t]];
R[i + 2040*t] = Op[i + 1187*t] ? R[B[i + 1187*t]] * R[C[i + 1187*t]] : R[B[i + 1187*t]] + R[C[i + 1187*t]];
R[i + 2041*t] = Op[i + 1188*t] ? R[B[i + 1188*t]] * R[C[i + 1188*t]] : R[B[i + 1188*t]] + R[C[i + 1188*t]];
R[i + 2042*t] = Op[i + 1189*t] ? R[B[i + 1189*t]] * R[C[i + 1189*t]] : R[B[i + 1189*t]] + R[C[i + 1189*t]];
R[i + 2043*t] = Op[i + 1190*t] ? R[B[i + 1190*t]] * R[C[i + 1190*t]] : R[B[i + 1190*t]] + R[C[i + 1190*t]];
R[i + 2044*t] = Op[i + 1191*t] ? R[B[i + 1191*t]] * R[C[i + 1191*t]] : R[B[i + 1191*t]] + R[C[i + 1191*t]];
R[i + 2045*t] = Op[i + 1192*t] ? R[B[i + 1192*t]] * R[C[i + 1192*t]] : R[B[i + 1192*t]] + R[C[i + 1192*t]];
R[i + 2046*t] = Op[i + 1193*t] ? R[B[i + 1193*t]] * R[C[i + 1193*t]] : R[B[i + 1193*t]] + R[C[i + 1193*t]];
R[i + 2047*t] = Op[i + 1194*t] ? R[B[i + 1194*t]] * R[C[i + 1194*t]] : R[B[i + 1194*t]] + R[C[i + 1194*t]];
R[i + 2048*t] = Op[i + 1195*t] ? R[B[i + 1195*t]] * R[C[i + 1195*t]] : R[B[i + 1195*t]] + R[C[i + 1195*t]];
__syncthreads();
R[i + 2049*t] = Op[i + 1196*t] ? R[B[i + 1196*t]] * R[C[i + 1196*t]] : R[B[i + 1196*t]] + R[C[i + 1196*t]];
R[i + 2050*t] = Op[i + 1197*t] ? R[B[i + 1197*t]] * R[C[i + 1197*t]] : R[B[i + 1197*t]] + R[C[i + 1197*t]];
R[i + 2051*t] = Op[i + 1198*t] ? R[B[i + 1198*t]] * R[C[i + 1198*t]] : R[B[i + 1198*t]] + R[C[i + 1198*t]];
R[i + 2052*t] = Op[i + 1199*t] ? R[B[i + 1199*t]] * R[C[i + 1199*t]] : R[B[i + 1199*t]] + R[C[i + 1199*t]];
R[i + 2053*t] = Op[i + 1200*t] ? R[B[i + 1200*t]] * R[C[i + 1200*t]] : R[B[i + 1200*t]] + R[C[i + 1200*t]];
R[i + 2054*t] = Op[i + 1201*t] ? R[B[i + 1201*t]] * R[C[i + 1201*t]] : R[B[i + 1201*t]] + R[C[i + 1201*t]];
R[i + 2055*t] = Op[i + 1202*t] ? R[B[i + 1202*t]] * R[C[i + 1202*t]] : R[B[i + 1202*t]] + R[C[i + 1202*t]];
R[i + 2056*t] = Op[i + 1203*t] ? R[B[i + 1203*t]] * R[C[i + 1203*t]] : R[B[i + 1203*t]] + R[C[i + 1203*t]];
R[i + 2057*t] = Op[i + 1204*t] ? R[B[i + 1204*t]] * R[C[i + 1204*t]] : R[B[i + 1204*t]] + R[C[i + 1204*t]];
R[i + 2058*t] = Op[i + 1205*t] ? R[B[i + 1205*t]] * R[C[i + 1205*t]] : R[B[i + 1205*t]] + R[C[i + 1205*t]];
R[i + 2059*t] = Op[i + 1206*t] ? R[B[i + 1206*t]] * R[C[i + 1206*t]] : R[B[i + 1206*t]] + R[C[i + 1206*t]];
R[i + 2060*t] = Op[i + 1207*t] ? R[B[i + 1207*t]] * R[C[i + 1207*t]] : R[B[i + 1207*t]] + R[C[i + 1207*t]];
R[i + 2061*t] = Op[i + 1208*t] ? R[B[i + 1208*t]] * R[C[i + 1208*t]] : R[B[i + 1208*t]] + R[C[i + 1208*t]];
R[i + 2062*t] = Op[i + 1209*t] ? R[B[i + 1209*t]] * R[C[i + 1209*t]] : R[B[i + 1209*t]] + R[C[i + 1209*t]];
R[i + 2063*t] = Op[i + 1210*t] ? R[B[i + 1210*t]] * R[C[i + 1210*t]] : R[B[i + 1210*t]] + R[C[i + 1210*t]];
R[i + 2064*t] = Op[i + 1211*t] ? R[B[i + 1211*t]] * R[C[i + 1211*t]] : R[B[i + 1211*t]] + R[C[i + 1211*t]];
__syncthreads();
R[i + 2065*t] = Op[i + 1212*t] ? R[B[i + 1212*t]] * R[C[i + 1212*t]] : R[B[i + 1212*t]] + R[C[i + 1212*t]];
R[i + 2066*t] = Op[i + 1213*t] ? R[B[i + 1213*t]] * R[C[i + 1213*t]] : R[B[i + 1213*t]] + R[C[i + 1213*t]];
R[i + 2067*t] = Op[i + 1214*t] ? R[B[i + 1214*t]] * R[C[i + 1214*t]] : R[B[i + 1214*t]] + R[C[i + 1214*t]];
R[i + 2068*t] = Op[i + 1215*t] ? R[B[i + 1215*t]] * R[C[i + 1215*t]] : R[B[i + 1215*t]] + R[C[i + 1215*t]];
R[i + 2069*t] = Op[i + 1216*t] ? R[B[i + 1216*t]] * R[C[i + 1216*t]] : R[B[i + 1216*t]] + R[C[i + 1216*t]];
R[i + 2070*t] = Op[i + 1217*t] ? R[B[i + 1217*t]] * R[C[i + 1217*t]] : R[B[i + 1217*t]] + R[C[i + 1217*t]];
R[i + 2071*t] = Op[i + 1218*t] ? R[B[i + 1218*t]] * R[C[i + 1218*t]] : R[B[i + 1218*t]] + R[C[i + 1218*t]];
R[i + 2072*t] = Op[i + 1219*t] ? R[B[i + 1219*t]] * R[C[i + 1219*t]] : R[B[i + 1219*t]] + R[C[i + 1219*t]];
R[i + 2073*t] = Op[i + 1220*t] ? R[B[i + 1220*t]] * R[C[i + 1220*t]] : R[B[i + 1220*t]] + R[C[i + 1220*t]];
R[i + 2074*t] = Op[i + 1221*t] ? R[B[i + 1221*t]] * R[C[i + 1221*t]] : R[B[i + 1221*t]] + R[C[i + 1221*t]];
R[i + 2075*t] = Op[i + 1222*t] ? R[B[i + 1222*t]] * R[C[i + 1222*t]] : R[B[i + 1222*t]] + R[C[i + 1222*t]];
__syncthreads();
R[i + 2076*t] = Op[i + 1223*t] ? R[B[i + 1223*t]] * R[C[i + 1223*t]] : R[B[i + 1223*t]] + R[C[i + 1223*t]];
R[i + 2077*t] = Op[i + 1224*t] ? R[B[i + 1224*t]] * R[C[i + 1224*t]] : R[B[i + 1224*t]] + R[C[i + 1224*t]];
R[i + 2078*t] = Op[i + 1225*t] ? R[B[i + 1225*t]] * R[C[i + 1225*t]] : R[B[i + 1225*t]] + R[C[i + 1225*t]];
R[i + 2079*t] = Op[i + 1226*t] ? R[B[i + 1226*t]] * R[C[i + 1226*t]] : R[B[i + 1226*t]] + R[C[i + 1226*t]];
R[i + 2080*t] = Op[i + 1227*t] ? R[B[i + 1227*t]] * R[C[i + 1227*t]] : R[B[i + 1227*t]] + R[C[i + 1227*t]];
R[i + 2081*t] = Op[i + 1228*t] ? R[B[i + 1228*t]] * R[C[i + 1228*t]] : R[B[i + 1228*t]] + R[C[i + 1228*t]];
R[i + 2082*t] = Op[i + 1229*t] ? R[B[i + 1229*t]] * R[C[i + 1229*t]] : R[B[i + 1229*t]] + R[C[i + 1229*t]];
R[i + 2083*t] = Op[i + 1230*t] ? R[B[i + 1230*t]] * R[C[i + 1230*t]] : R[B[i + 1230*t]] + R[C[i + 1230*t]];
R[i + 2084*t] = Op[i + 1231*t] ? R[B[i + 1231*t]] * R[C[i + 1231*t]] : R[B[i + 1231*t]] + R[C[i + 1231*t]];
__syncthreads();
R[i + 2085*t] = Op[i + 1232*t] ? R[B[i + 1232*t]] * R[C[i + 1232*t]] : R[B[i + 1232*t]] + R[C[i + 1232*t]];
R[i + 2086*t] = Op[i + 1233*t] ? R[B[i + 1233*t]] * R[C[i + 1233*t]] : R[B[i + 1233*t]] + R[C[i + 1233*t]];
R[i + 2087*t] = Op[i + 1234*t] ? R[B[i + 1234*t]] * R[C[i + 1234*t]] : R[B[i + 1234*t]] + R[C[i + 1234*t]];
R[i + 2088*t] = Op[i + 1235*t] ? R[B[i + 1235*t]] * R[C[i + 1235*t]] : R[B[i + 1235*t]] + R[C[i + 1235*t]];
R[i + 2089*t] = Op[i + 1236*t] ? R[B[i + 1236*t]] * R[C[i + 1236*t]] : R[B[i + 1236*t]] + R[C[i + 1236*t]];
R[i + 2090*t] = Op[i + 1237*t] ? R[B[i + 1237*t]] * R[C[i + 1237*t]] : R[B[i + 1237*t]] + R[C[i + 1237*t]];
R[i + 2091*t] = Op[i + 1238*t] ? R[B[i + 1238*t]] * R[C[i + 1238*t]] : R[B[i + 1238*t]] + R[C[i + 1238*t]];
R[i + 2092*t] = Op[i + 1239*t] ? R[B[i + 1239*t]] * R[C[i + 1239*t]] : R[B[i + 1239*t]] + R[C[i + 1239*t]];
__syncthreads();
R[i + 2093*t] = Op[i + 1240*t] ? R[B[i + 1240*t]] * R[C[i + 1240*t]] : R[B[i + 1240*t]] + R[C[i + 1240*t]];
R[i + 2094*t] = Op[i + 1241*t] ? R[B[i + 1241*t]] * R[C[i + 1241*t]] : R[B[i + 1241*t]] + R[C[i + 1241*t]];
R[i + 2095*t] = Op[i + 1242*t] ? R[B[i + 1242*t]] * R[C[i + 1242*t]] : R[B[i + 1242*t]] + R[C[i + 1242*t]];
R[i + 2096*t] = Op[i + 1243*t] ? R[B[i + 1243*t]] * R[C[i + 1243*t]] : R[B[i + 1243*t]] + R[C[i + 1243*t]];
R[i + 2097*t] = Op[i + 1244*t] ? R[B[i + 1244*t]] * R[C[i + 1244*t]] : R[B[i + 1244*t]] + R[C[i + 1244*t]];
R[i + 2098*t] = Op[i + 1245*t] ? R[B[i + 1245*t]] * R[C[i + 1245*t]] : R[B[i + 1245*t]] + R[C[i + 1245*t]];
R[i + 2099*t] = Op[i + 1246*t] ? R[B[i + 1246*t]] * R[C[i + 1246*t]] : R[B[i + 1246*t]] + R[C[i + 1246*t]];
__syncthreads();
R[i + 2100*t] = Op[i + 1247*t] ? R[B[i + 1247*t]] * R[C[i + 1247*t]] : R[B[i + 1247*t]] + R[C[i + 1247*t]];
R[i + 2101*t] = Op[i + 1248*t] ? R[B[i + 1248*t]] * R[C[i + 1248*t]] : R[B[i + 1248*t]] + R[C[i + 1248*t]];
R[i + 2102*t] = Op[i + 1249*t] ? R[B[i + 1249*t]] * R[C[i + 1249*t]] : R[B[i + 1249*t]] + R[C[i + 1249*t]];
R[i + 2103*t] = Op[i + 1250*t] ? R[B[i + 1250*t]] * R[C[i + 1250*t]] : R[B[i + 1250*t]] + R[C[i + 1250*t]];
R[i + 2104*t] = Op[i + 1251*t] ? R[B[i + 1251*t]] * R[C[i + 1251*t]] : R[B[i + 1251*t]] + R[C[i + 1251*t]];
__syncthreads();
R[i + 2105*t] = Op[i + 1252*t] ? R[B[i + 1252*t]] * R[C[i + 1252*t]] : R[B[i + 1252*t]] + R[C[i + 1252*t]];
R[i + 2106*t] = Op[i + 1253*t] ? R[B[i + 1253*t]] * R[C[i + 1253*t]] : R[B[i + 1253*t]] + R[C[i + 1253*t]];
R[i + 2107*t] = Op[i + 1254*t] ? R[B[i + 1254*t]] * R[C[i + 1254*t]] : R[B[i + 1254*t]] + R[C[i + 1254*t]];
R[i + 2108*t] = Op[i + 1255*t] ? R[B[i + 1255*t]] * R[C[i + 1255*t]] : R[B[i + 1255*t]] + R[C[i + 1255*t]];
__syncthreads();
R[i + 2109*t] = Op[i + 1256*t] ? R[B[i + 1256*t]] * R[C[i + 1256*t]] : R[B[i + 1256*t]] + R[C[i + 1256*t]];
R[i + 2110*t] = Op[i + 1257*t] ? R[B[i + 1257*t]] * R[C[i + 1257*t]] : R[B[i + 1257*t]] + R[C[i + 1257*t]];
R[i + 2111*t] = Op[i + 1258*t] ? R[B[i + 1258*t]] * R[C[i + 1258*t]] : R[B[i + 1258*t]] + R[C[i + 1258*t]];
__syncthreads();
R[i + 2112*t] = Op[i + 1259*t] ? R[B[i + 1259*t]] * R[C[i + 1259*t]] : R[B[i + 1259*t]] + R[C[i + 1259*t]];
R[i + 2113*t] = Op[i + 1260*t] ? R[B[i + 1260*t]] * R[C[i + 1260*t]] : R[B[i + 1260*t]] + R[C[i + 1260*t]];
__syncthreads();
R[i + 2114*t] = Op[i + 1261*t] ? R[B[i + 1261*t]] * R[C[i + 1261*t]] : R[B[i + 1261*t]] + R[C[i + 1261*t]];
R[i + 2115*t] = Op[i + 1262*t] ? R[B[i + 1262*t]] * R[C[i + 1262*t]] : R[B[i + 1262*t]] + R[C[i + 1262*t]];
__syncthreads();
R[i + 2116*t] = Op[i + 1263*t] ? R[B[i + 1263*t]] * R[C[i + 1263*t]] : R[B[i + 1263*t]] + R[C[i + 1263*t]];
__syncthreads();
R[i + 2117*t] = Op[i + 1264*t] ? R[B[i + 1264*t]] * R[C[i + 1264*t]] : R[B[i + 1264*t]] + R[C[i + 1264*t]];
__syncthreads();
R[i + 2118*t] = Op[i + 1265*t] ? R[B[i + 1265*t]] * R[C[i + 1265*t]] : R[B[i + 1265*t]] + R[C[i + 1265*t]];
__syncthreads();
R[i + 2119*t] = Op[i + 1266*t] ? R[B[i + 1266*t]] * R[C[i + 1266*t]] : R[B[i + 1266*t]] + R[C[i + 1266*t]];
__syncthreads();
R[i + 2120*t] = Op[i + 1267*t] ? R[B[i + 1267*t]] * R[C[i + 1267*t]] : R[B[i + 1267*t]] + R[C[i + 1267*t]];
__syncthreads();
R[i + 2121*t] = Op[i + 1268*t] ? R[B[i + 1268*t]] * R[C[i + 1268*t]] : R[B[i + 1268*t]] + R[C[i + 1268*t]];
__syncthreads();
R[i + 2122*t] = Op[i + 1269*t] ? R[B[i + 1269*t]] * R[C[i + 1269*t]] : R[B[i + 1269*t]] + R[C[i + 1269*t]];
__syncthreads();
R[i + 2123*t] = Op[i + 1270*t] ? R[B[i + 1270*t]] * R[C[i + 1270*t]] : R[B[i + 1270*t]] + R[C[i + 1270*t]];
if (i==0) { final += R[2123*t]; }
__syncthreads();
}
if (i==0) { A[0]= final;}
}
|
8,999 | __global__ void add(double *a, double *b, const float c, const int size){
int i = threadIdx.x + blockIdx.x * blockDim.x;
if (i < size){
a[i] += b[i] * c;
}
} |
9,000 | // Vector2D.cpp: implementation of the Vector2D class.
//
//////////////////////////////////////////////////////////////////////
#include "Geometry.cuh"
//////////////////////////////////////////////////////////////////////
// Construction/Destruction
//////////////////////////////////////////////////////////////////////
__host__ __device__ Vector2D& Vector2D::operator=(const Vector2D& v)
{
x = v.x; y = v.y;
return (*this);
}
__host__ __device__ Vector2D& Vector2D::operator+=(const Vector2D& v)
{
x += v.x; y += v.y;
return (*this);
}
__host__ __device__ Vector2D& Vector2D::operator-=(const Vector2D& v)
{
x -= v.x; y -= v.y;
return (*this);
}
__host__ __device__ Vector2D& Vector2D::operator*=(double u)
{
x *= u; y *= u;
return (*this);
}
__host__ __device__ Vector2D& Vector2D::operator/=(double u)
{
if (!EQUALZERO(u))
{
x /= u; y /= u;
}
return(*this);
}
__host__ __device__ Vector2D operator+(const Vector2D& lv, const Vector2D& rv)
{
Vector2D rel = lv;
rel += rv;
return rel;
}
__host__ __device__ Vector2D operator-(const Vector2D& lv, const Vector2D& rv)
{
Vector2D rel = lv;
rel -= rv;
return rel;
}
__host__ __device__ Vector2D operator*(const double u, const Vector2D& rv)
{
Vector2D rel = rv;
rel *= u;
return rel;
}
__host__ __device__ Vector2D operator*(const Vector2D& lv, const double u)
{
Vector2D rel = lv;
rel *= u;
return rel;
}
__host__ __device__ Vector2D operator/(const Vector2D& lv, const double u)
{
Vector2D rel = lv;
rel /= u;
return rel;
}
__host__ __device__ double operator*(const Vector2D& lv, const Vector2D& rv)
{
return lv.x*rv.x + lv.y*rv.y;
}
__host__ __device__ double operator^(const Vector2D& lv, const Vector2D& rv)
{
return lv.x*rv.y - lv.y*rv.x;
}
__host__ __device__ std::ostream& operator<< (std::ostream &output, Vector2D& v)
{
output << v.x << " " << v.y;
return output;
}
__host__ __device__ short Vector2D::AtWhere(Vector2D v0, Vector2D v1)
{
Vector2D vTemp1(v1.y - v0.y, v0.x - v1.x);
Vector2D vTemp2(x - v0.x, y - v0.y);
double d = vTemp1*vTemp2;
if (EQUALZERO(d))
return 0;
if (d > 0)//right
return 1;
return -1;
}
__host__ __device__ bool Vector2D::AtRight(Vector2D v0, Vector2D v1)
{
if (AtWhere(v0, v1) == 1)
return true;
return false;
}
__host__ __device__ bool Vector2D::AtLeft(Vector2D v0, Vector2D v1)
{
if (AtWhere(v0, v1) == -1)
return true;
return false;
}
__host__ __device__ bool Vector2D::OnLine(Vector2D v0, Vector2D v1)
{
if (AtWhere(v0, v1) == 0)
return true;
return false;
}
__host__ __device__ bool Vector2D::Intersect(Vector2D v1, Vector2D v2)//intersect with uint circle
{
Vector2D vOrigin;
short s = vOrigin.AtWhere(v1, v2);
Vector2D vTemp1 = v2 - v1;
vTemp1.normalize();
Vector2D vTemp2;
// if(s==0)//pass point (0,0)
if (s == 1)//right
{
vTemp2.x = -vTemp1.y;
vTemp2.y = vTemp1.x;
double d = vTemp2*v1;
vTemp2 *= d;
d = sqrt(1.0 - d*d);
vTemp1 *= d;
}
else if (s == -1)//left
{
vTemp2.x = vTemp1.y;
vTemp2.y = -vTemp1.x;
double d = vTemp2*v1;
vTemp2 *= d;
d = sqrt(1.0 - d*d);
vTemp1 *= d;
}
x = vTemp1.x + vTemp2.x;
y = vTemp1.y + vTemp2.y;
return true;
}
__host__ __device__ bool Vector2D::Intersect(Vector2D v1, Vector2D v2, Vector2D v3, Vector2D v4)//tow line intersect
{
double d = (v4.y - v3.y)*(v1.x - v2.x) - (v2.y - v1.y)*(v3.x - v4.x);
if (EQUALZERO(d))
return false;
double d1 = v1.x*v2.y - v2.x*v1.y;
double d2 = v3.x*v4.y - v4.x*v3.y;
x = ((v4.x - v3.x)*d1 - (v2.x - v1.x)*d2) / d;
y = ((v4.y - v3.y)*d1 - (v2.y - v1.y)*d2) / d;
return true;
}
__host__ __device__ double Vector2D::GetArea(Vector2D v)
{
return x*v.y - v.x*y;
}
/////////////////////////////////////////////////////////////
// Vector3D : 3D vector
/////////////////////////////////////////////////////////////
__host__ __device__ Vector3D& Vector3D::operator=(const Vector3D& v)
{
x = v.x; y = v.y; z = v.z;
return (*this);
}
__host__ __device__ Vector3D& Vector3D::operator+=(const Vector3D& v)
{
x += v.x; y += v.y; z += v.z;
return (*this);
}
__host__ __device__ Vector3D& Vector3D::operator-=(const Vector3D& v)
{
x -= v.x; y -= v.y; z -= v.z;
return (*this);
}
__host__ __device__ Vector3D& Vector3D::operator*=(double u)
{
x *= u; y *= u; z *= u;
return (*this);
}
__host__ __device__ Vector3D& Vector3D::operator/=(double u)
{
if (!EQUALZERO(u))
{
x /= u; y /= u; z /= u;
}
return(*this);
}
__host__ __device__ Vector3D& Vector3D::operator^=(const Vector3D& v)
{
double xx = y*v.z - z*v.y;
double yy = z*v.x - x*v.z;
double zz = x*v.y - y*v.x;
x = xx; y = yy; z = zz;
return (*this);
}
__host__ __device__ Vector3D operator+(const Vector3D& lv, const Vector3D& rv)
{
Vector3D rel = lv;
rel += rv;
return rel;
}
__host__ __device__ Vector3D operator-(const Vector3D& lv, const Vector3D& rv)
{
Vector3D rel = lv;
rel -= rv;
return rel;
}
__host__ __device__ Vector3D operator*(const double u, const Vector3D& rv)
{
Vector3D rel = rv;
rel *= u;
return rel;
}
__host__ __device__ Vector3D operator*(const Vector3D& lv, const double u)
{
Vector3D rel = lv;
rel *= u;
return rel;
}
__host__ __device__ Vector3D operator/(const Vector3D& lv, const double u)
{
Vector3D rel = lv;
rel /= u;
return rel;
}
__host__ __device__ double operator*(const Vector3D& lv, const Vector3D& rv)
{
return lv.x*rv.x + lv.y*rv.y + lv.z*rv.z;
}
__host__ __device__ Vector3D operator^(const Vector3D& lv, const Vector3D& rv)
{
Vector3D rel = lv;
rel ^= rv;
return rel;
}
__host__ __device__ std::ostream& operator<< (std::ostream &output, const Vector3D& v)
{
output << v.x << " " << v.y << " " << v.z;
return output;
}
__host__ __device__ double Area2(Vector2D &a, Vector2D &b, Vector2D &c){
return a.x*b.y + b.x*c.y + c.x*a.y -
b.x*a.y - c.x*b.y - a.x*c.y;
}
__host__ __device__ double SpcDivision(const double &a, const double &b){
if (!EQUALZERO(b)) return a / b;
if (EQUALZERO(a)) return 0;
if (a < 0) return -1e30;
else return 1e30;
return 0;
}
__host__ __device__ Vector3D Rotate(Vector3D point, double angle, Vector3D rAxis)
{
rAxis.normalize();
double c = cos(angle), s = sin(angle);
double m[3][3];
m[0][0] = c + (1 - c)*rAxis.x*rAxis.x;
m[0][1] = (1 - c)*rAxis.x*rAxis.y - s*rAxis.z;
m[0][2] = (1 - c)*rAxis.x*rAxis.z + s*rAxis.y;
m[1][0] = (1 - c)*rAxis.y*rAxis.x + s*rAxis.z;
m[1][1] = c + (1 - c)*rAxis.y*rAxis.y;
m[1][2] = (1 - c)*rAxis.y*rAxis.z - s*rAxis.x;
m[2][0] = (1 - c)*rAxis.z*rAxis.x - s*rAxis.y;
m[2][1] = (1 - c)*rAxis.z*rAxis.y + s*rAxis.x;
m[2][2] = c + (1 - c)*rAxis.z*rAxis.z;
Vector3D ret;
for (int i = 0; i < 3; ++i)
{
ret[i] = 0.0;
for (int j = 0; j < 3; ++j)
ret[i] += m[i][j] * point[j];
}
return ret;
}
__host__ __device__ bool toLeft(const Vector2D &p, const Vector2D &p0, const Vector2D &p1)
{
Vector2D vec0 = p1 - p0, vec1 = p - p0;
vec0.normalize(); vec1.normalize();
return ((vec0 ^ vec1) > 0.0);
} |
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