filename stringlengths 19 182 | omp_pragma_line stringlengths 24 416 | context_chars int64 100 100 | text stringlengths 152 177k |
|---|---|---|---|
HPCL/benchmarks/miniapps/CloverLeaf_OpenMP/pack_kernel_c.c | #pragma omp parallel for private(j,k,index) | 100 | ATA) {
x_inc=1;
y_inc=0;
}
if(field_type==Y_FACE_DATA) {
x_inc=0;
y_inc=1;
}
<LOOP-START>for (k=y_min-depth;k<=y_max+y_inc+depth;k++) {
#pragma ivdep
for (j=1;j<=depth;j++) {
index=buffer_offset + j+(k+depth-1)*depth;
left_snd_buffer[FTNREF1D(index,1)]=field[FTNREF2D(x_min+x_inc-1... |
HPCL/benchmarks/miniapps/CloverLeaf_OpenMP/pack_kernel_c.c | #pragma omp parallel for private(j,k,index) | 100 | ATA) {
x_inc=1;
y_inc=0;
}
if(field_type==Y_FACE_DATA) {
x_inc=0;
y_inc=1;
}
<LOOP-START>for (k=y_min-depth;k<=y_max+y_inc+depth;k++) {
#pragma ivdep
for (j=1;j<=depth;j++) {
index=buffer_offset + j+(k+depth-1)*depth;
field[FTNREF2D(x_min-j,k,x_max+4+x_inc,x_min-2,y_min-2)]=left_r... |
HPCL/benchmarks/miniapps/CloverLeaf_OpenMP/pack_kernel_c.c | #pragma omp parallel for private(j,k,index) | 100 | ATA) {
x_inc=1;
y_inc=0;
}
if(field_type==Y_FACE_DATA) {
x_inc=0;
y_inc=1;
}
<LOOP-START>for (k=y_min-depth;k<=y_max+y_inc+depth;k++) {
#pragma ivdep
for (j=1;j<=depth;j++) {
index=buffer_offset + j+(k+depth-1)*depth;
right_snd_buffer[FTNREF1D(index,1)]=field[FTNREF2D(x_max+1-j,k,... |
HPCL/benchmarks/miniapps/CloverLeaf_OpenMP/pack_kernel_c.c | #pragma omp parallel for private(j,k,index) | 100 | ATA) {
x_inc=1;
y_inc=0;
}
if(field_type==Y_FACE_DATA) {
x_inc=0;
y_inc=1;
}
<LOOP-START>for (k=y_min-depth;k<=y_max+y_inc+depth;k++) {
#pragma ivdep
for (j=1;j<=depth;j++) {
index=buffer_offset + j+(k+depth-1)*depth;
field[FTNREF2D(x_max+x_inc+j,k,x_max+4+x_inc,x_min-2,y_min-2)]=... |
HPCL/benchmarks/miniapps/CloverLeaf_OpenMP/pack_kernel_c.c | #pragma omp parallel for private(j,index) | 100 | nc=0;
}
if(field_type==Y_FACE_DATA) {
x_inc=0;
y_inc=1;
}
for (k=1;k<=depth;k++) {
<LOOP-START>for (j=x_min-depth;j<=x_max+x_inc+depth;j++) {
index= buffer_offset + k+(j+depth-1)*depth;
top_snd_buffer[FTNREF1D(index,1)]=field[FTNREF2D(j,y_max+1-k,x_max+4+x_inc,x_min-2,y_min-2)];
}<LOOP-... |
HPCL/benchmarks/miniapps/CloverLeaf_OpenMP/pack_kernel_c.c | #pragma omp parallel for private(j,index) | 100 | nc=0;
}
if(field_type==Y_FACE_DATA) {
x_inc=0;
y_inc=1;
}
for (k=1;k<=depth;k++) {
<LOOP-START>for (j=x_min-depth;j<=x_max+x_inc+depth;j++) {
index= buffer_offset + k+(j+depth-1)*depth;
bottom_snd_buffer[FTNREF1D(index,1)]=field[FTNREF2D(j,y_min+y_inc-1+k,x_max+4+x_inc,x_min-2,y_min-2)];
... |
HPCL/benchmarks/miniapps/CloverLeaf_OpenMP/pack_kernel_c.c | #pragma omp parallel for private(j,index) | 100 | nc=0;
}
if(field_type==Y_FACE_DATA) {
x_inc=0;
y_inc=1;
}
for (k=1;k<=depth;k++) {
<LOOP-START>for (j=x_min-depth;j<=x_max+x_inc+depth;j++) {
index= buffer_offset + k+(j+depth-1)*depth;
field[FTNREF2D(j,y_min-k,x_max+4+x_inc,x_min-2,y_min-2)]=bottom_rcv_buffer[FTNREF1D(index,1)];
}<LOOP... |
HPCL/benchmarks/miniapps/CloverLeaf_OpenMP/pack_kernel_c.c | #pragma omp parallel for private(j,index) | 100 | nc=0;
}
if(field_type==Y_FACE_DATA) {
x_inc=0;
y_inc=1;
}
for (k=1;k<=depth;k++) {
<LOOP-START>for (j=x_min-depth;j<=x_max+x_inc+depth;j++) {
index= buffer_offset + k+(j+depth-1)*depth;
field[FTNREF2D(j,y_max+y_inc+k,x_max+4+x_inc,x_min-2,y_min-2)]=top_rcv_buffer[FTNREF1D(index,1)];
}<L... |
HPCL/benchmarks/miniapps/xsbench/openmp-threading/GridInit.c | #pragma omp parallel for | 100 | d * sizeof(int);
double du = 1.0 / in.hash_bins;
// For each energy level in the hash table
<LOOP-START>for( long e = 0; e < in.hash_bins; e++ )
{
double energy = e * du;
// We need to determine the bounding energy levels for all isotopes
for( long i = 0; i < in.n_isotopes; i++ )
{
SD.index_g... |
HPCL/benchmarks/miniapps/xsbench/openmp-threading/Simulation.c | #pragma omp parallel for schedule(dynamic, 100) | 100 | als and Energies
////////////////////////////////////////////////////////////////////////////////
<LOOP-START>for( int i = 0; i < in.lookups; i++ )
{
// Set the initial seed value
uint64_t seed = STARTING_SEED;
// Forward seed to lookup index (we need 2 samples per lookup)
seed = fast_forward_LCG(seed, 2*i... |
HPCL/benchmarks/miniapps/xsbench/openmp-threading/Simulation.c | #pragma omp parallel for schedule(dynamic, 100) | 100 | als and Energies
////////////////////////////////////////////////////////////////////////////////
<LOOP-START>for( int i = 0; i < in.lookups; i++ )
{
// Set the initial seed value
uint64_t seed = STARTING_SEED;
// Forward seed to lookup index (we need 2 samples per lookup)
seed = fast_forward_LCG(seed, 2*i... |
flame/blis/kernels/bgq/1/bli_axpyv_bgq_int.c | #pragma omp parallel for | 100 | r4double xv, yv, zv;
vector4double alphav = vec_lds( 0 * sizeof(double), (double*)alpha );
<LOOP-START>for ( dim_t i = 0; i < n_run; i++ )
{
xv = vec_lda( 0 * sizeof(double), &x[i*4] );
yv = vec_lda( 0 * sizeof(double), &y[i*4] );
zv = vec_madd( alphav, xv, yv );
vec_sta( zv, 0... |
nowke/hpc_lab/11_black_white_image/black_white_static.c | #pragma omp parallel for private(y, color, red, green, blue, tmp) schedule(static) | 100 | int width = gdImageSX(img);
int height = gdImageSY(img);
double t1 = omp_get_wtime();
<LOOP-START>for(x=0; x<width; x++) {
for(y=0; y<height; y++) {
color = x + 0;
color = gdImageGetPixel(img, x, y);
red = gdImageRed(img, color);
green = gdImageGre... |
nowke/hpc_lab/11_black_white_image/black_white.c | #pragma omp parallel for private(y, color, red, green, blue, tmp) | 100 | int width = gdImageSX(img);
int height = gdImageSY(img);
double t1 = omp_get_wtime();
<LOOP-START>for(x=0; x<width; x++) {
for(y=0; y<height; y++) {
color = x + 0;
color = gdImageGetPixel(img, x, y);
red = gdImageRed(img, color);
green = gdImageGre... |
nowke/hpc_lab/11_black_white_image/black_white_dynamic.c | #pragma omp parallel for private(y, color, red, green, blue, tmp) schedule(dynamic) | 100 | int width = gdImageSX(img);
int height = gdImageSY(img);
double t1 = omp_get_wtime();
<LOOP-START>for(x=0; x<width; x++) {
for(y=0; y<height; y++) {
color = x + 0;
color = gdImageGetPixel(img, x, y);
red = gdImageRed(img, color);
green = gdImageGre... |
nowke/hpc_lab/11_black_white_image/black_white_guided.c | #pragma omp parallel for private(y, color, red, green, blue, tmp) schedule(guided) | 100 | int width = gdImageSX(img);
int height = gdImageSY(img);
double t1 = omp_get_wtime();
<LOOP-START>for(x=0; x<width; x++) {
for(y=0; y<height; y++) {
color = x + 0;
color = gdImageGetPixel(img, x, y);
red = gdImageRed(img, color);
green = gdImageGre... |
nowke/hpc_lab/1_pi_calculation/pi_calculation.c | #pragma omp parallel for private(x) reduction(+:sum) | 100 | ulate_pi() {
double sum = 0.0;
double step = 1.0 / intervals;
double x;
int i;
<LOOP-START>for (i=1; i < intervals; i++) {
x = step * (i+0.5); // We take 0.5 as we are taking middle point of rectangular area
sum += 4.0 / (1.0 + x * x);
}<LOOP-END> <OMP-START>#pragma omp parallel... |
nowke/hpc_lab/5_negative_image/negative_critical.c | #pragma omp parallel for private(y, color, red, green, blue) num_threads(num_threads) | 100 | int width = gdImageSX(img);
int height = gdImageSY(img);
double t1 = omp_get_wtime();
<LOOP-START>for(x=0; x<width; x++) {
#pragma omp critical
{
for(y=0; y<height; y++) {
color = x + 0;
color = gdImageGetPixel(img, x, y);
red =... |
nowke/hpc_lab/5_negative_image/negative.c | #pragma omp parallel for private(y, color, red, green, blue) num_threads(num_threads) | 100 | int width = gdImageSX(img);
int height = gdImageSY(img);
double t1 = omp_get_wtime();
<LOOP-START>for(x=0; x<width; x++) {
for(y=0; y<height; y++) {
color = x + 0;
color = gdImageGetPixel(img, x, y);
red = 255 - gdImageRed(img, color);
green = 255 ... |
nowke/hpc_lab/7_points_clustering/points_clustering.cpp | #pragma omp parallel for num_threads(num_threads) | 100 | point
cluster_count[i] = 1;
points[i][1] = i;
}
}
void cluster_points() {
<LOOP-START>for (long i=0; i<num_points; i++) {
double min_dist = 1000, cur_dist = -1;
int cluster_index = -1;
for (int j=0; j<K; j++) {
cur_dist = fabs((double)points[i][0] - cluster_... |
nowke/hpc_lab/2_matrix/matrix.c | #pragma omp parallel for private(j, k) | 100 | B[i][j] = rand() % 10;
}
}
}
void multiply_matrix() {
int i, j, k;
<LOOP-START>for (i=0; i < matrix_size; i++) {
for (j=0; j < matrix_size; j++) {
C[i][j] = 0;
for (k=0; k < matrix_size; k++) {
C[i][j] += A[i][k] * B[k][j];
}
... |
nowke/hpc_lab/6_multitasking/multitask.cpp | #pragma omp parallel for private(a) num_threads(num_threads) | 100 | e answer!
*/
double* sine_table(int num) {
double* sines = new double[num];
double a;
<LOOP-START>for (int i=0; i<num; i++) {
sines[i] = 0.0;
for (int j=0; j <= i; j++) {
a = j * PI / (num - 1);
sines[i] += sin(a);
}
}<LOOP-END> <OMP-START>#pragma omp pa... |
nowke/hpc_lab/9_points_classification/points_classification.cpp | #pragma omp parallel for num_threads(num_threads) | 100 | int dx = x2-x1, dy = y2-y1;
return (double)sqrt(dx*dx + dy*dy);
}
void classify_points() {
<LOOP-START>for (long i=0; i<num_points; i++) {
double min_dist = 1000, cur_dist = 1;
int cluster_index = -1;
for (int j=0; j<K; j++) {
cur_dist = get_distance(
... |
abhi4578/Parallelization-of-PSO/omp_parallel.c | #pragma omp parallel for private(a,b) reduction(min:gBestFitness) | 100 | int)nDimensions];
double gBestFitness = DBL_MAX;
int min;
//particle initialization
<LOOP-START>for (i=0; i<distributed_particles; i++) {
for (j=0; j<(int)nDimensions; j++)
{
a = x_min + (x_max - x_min) * gsl_rng_uniform(r);
b = x_min + (x_max - x_min) *... |
abhi4578/Parallelization-of-PSO/mpiomp.c | #pragma omp parallel for | 100 | ain(int argc, char *argv[]) {
int i,j;
double nParticles;
//Argument handling START
<LOOP-START>for(i=1; i < argc-1; i++) {
if (strcmp(argv[i], "-D") == 0)
nDimensions = strtol(argv[i+1],NULL,10);
else if (strcmp(argv[i], "-m") == 0)
nParticles = strtol(argv[i+1]... |
abhi4578/Parallelization-of-PSO/mpiomp.c | #pragma omp parallel for private(a,b) reduction(min:gBestFitness) | 100 | int)nDimensions];
double gBestFitness = DBL_MAX;
int min;
//particle initialization
<LOOP-START>for (i=0; i<distributed_particles; i++) {
// #pragma omp parallel for private(a,b)
for (j=0; j<(int)nDimensions; j++) {
a = x_min + (x_max - x_min) * gsl_rng_uniform(r);
... |
abhi4578/Parallelization-of-PSO/mpiomp.c | #pragma omp parallel for private(a,b) | 100 | private(a,b) reduction(min:gBestFitness)
for (i=0; i<distributed_particles; i++) {
// <LOOP-START>for (j=0; j<(int)nDimensions; j++) {
a = x_min + (x_max - x_min) * gsl_rng_uniform(r);
b = x_min + (x_max - x_min) * gsl_rng_uniform(r);
positions[i][j] = a;
... |
abhi4578/Parallelization-of-PSO/omp.c | #pragma omp parallel for private(a,b) reduction(min:gBestFitness) | 100 | int)nDimensions];
double gBestFitness = DBL_MAX;
int min;
//particle initialization
<LOOP-START>for (i=0; i<distributed_particles; i++) {
for (j=0; j<(int)nDimensions; j++)
{
a = x_min + (x_max - x_min) * gsl_rng_uniform(r);
b = x_min + (x_max - x_min) *... |
ecrc/stars-h/src/control/problem.c | #pragma omp parallel for private(dest, src, i, j) | 100 | esize *= A->shape[i];
if(A->order == 'C')
{
lda = A->shape[A->ndim-1];
//<LOOP-START>for(i = 0; i < nrows; i++)
for(j = 0; j < ncols; j++)
{
dest = j*(size_t)ld+i;
src = irow[i]*lda+icol[j];
memcpy(result+dest*esize, A->d... |
ecrc/stars-h/src/control/problem.c | #pragma omp parallel for private(dest, src, i, j) | 100 | A->data+src*esize, esize);
}
}
else
{
lda = A->shape[0];
//<LOOP-START>for(i = 0; i < nrows; i++)
for(j = 0; j < ncols; j++)
{
dest = j*(size_t)ld+i;
src = icol[j]*lda+irow[i];
memcpy(result+dest*esize, A->d... |
ecrc/stars-h/src/backends/openmp/blrm/dfe.c | #pragma omp parallel for schedule(dynamic, 1) | 100 | s_far;
char symm = F->symm;
int info = 0;
// Simple cycle over all far-field blocks
<LOOP-START>for(bi = 0; bi < nblocks_far; bi++)
{
if(info != 0)
continue;
// Get indexes and sizes of block row and column
STARSH_int i = F->block_far[2*bi];
STARSH_int j =... |
ecrc/stars-h/src/backends/openmp/blrm/dfe.c | #pragma omp parallel for schedule(dynamic, 1) | 100 | // not Error code)
if(M->onfly == 0)
// Simple cycle over all near-field blocks
<LOOP-START>for(bi = 0; bi < nblocks_near; bi++)
{
// Get indexes and sizes of corresponding block row and column
STARSH_int i = F->block_near[2*bi];
STARSH_int j = F->block_ne... |
ecrc/stars-h/src/backends/openmp/blrm/dfe.c | #pragma omp parallel for schedule(dynamic, 1) | 100 | ck_norm[bi] *= sqrt2;
}
else
// Simple cycle over all near-field blocks
<LOOP-START>for(bi = 0; bi < nblocks_near; bi++)
{
if(info != 0)
continue;
// Get indexes and sizes of corresponding block row and column
STARSH_int i = F->bloc... |
ecrc/stars-h/src/backends/openmp/blrm/dmml.c | #pragma omp parallel for schedule(static) | 100 | axrank = 100;
int maxnb = nrows/F->nbrows;
// Setting B = beta*B
if(beta == 0.)
<LOOP-START>for(int i = 0; i < nrows; i++)
for(int j = 0; j < nrhs; j++)
B[j*ldb+i] = 0.;
else
#pragma omp parallel for schedule(static)
for(int i = 0; i < nrows; i++)
... |
ecrc/stars-h/src/backends/openmp/blrm/dmml.c | #pragma omp parallel for schedule(static) | 100 | s; i++)
for(int j = 0; j < nrhs; j++)
B[j*ldb+i] = 0.;
else
<LOOP-START>for(int i = 0; i < nrows; i++)
for(int j = 0; j < nrhs; j++)
B[j*ldb+i] *= beta;
double *temp_D, *temp_B;
int num_threads;
#pragma omp parallel
#pragma omp master
... |
ecrc/stars-h/src/backends/openmp/blrm/dmml.c | #pragma omp parallel for schedule(dynamic, 1) | 100 | [j] = 0.;
}
int ldout = nrows;
// Simple cycle over all far-field admissible blocks
<LOOP-START>for(bi = 0; bi < nblocks_far; bi++)
{
// Get indexes of corresponding block row and block column
STARSH_int i = F->block_far[2*bi];
STARSH_int j = F->block_far[2*bi+1];
// ... |
ecrc/stars-h/src/backends/openmp/blrm/dmml.c | #pragma omp parallel for schedule(dynamic, 1) | 100 | );
}
}
if(M->onfly == 1)
// Simple cycle over all near-field blocks
<LOOP-START>for(bi = 0; bi < nblocks_near; bi++)
{
// Get indexes and sizes of corresponding block row and column
STARSH_int i = F->block_near[2*bi];
STARSH_int j = F->block_ne... |
ecrc/stars-h/src/backends/openmp/blrm/dmml.c | #pragma omp parallel for schedule(dynamic, 1) | 100 | ldout);
}
}
else
// Simple cycle over all near-field blocks
<LOOP-START>for(bi = 0; bi < nblocks_near; bi++)
{
// Get indexes and sizes of corresponding block row and column
STARSH_int i = F->block_near[2*bi];
STARSH_int j = F->block_ne... |
ecrc/stars-h/src/backends/openmp/blrm/dsdd.c | #pragma omp parallel for schedule(dynamic,1) | 100 | }
// Work variables
int info;
// Simple cycle over all far-field admissible blocks
<LOOP-START>for(bi = 0; bi < nblocks_far; bi++)
{
int info;
// Get indexes of corresponding block row and block column
STARSH_int i = block_far[2*bi];
STARSH_int j = block_far[2*bi+1];... |
ecrc/stars-h/src/backends/openmp/blrm/dsdd.c | #pragma omp parallel for schedule(static) | 100 | ar, 2*new_nblocks_near);
// At first get all near-field blocks, assumed to be dense
<LOOP-START>for(bi = 0; bi < 2*nblocks_near; bi++)
block_near[bi] = F->block_near[bi];
// Add false far-field blocks
#pragma omp parallel for schedule(static)
for(bi = 0; bi < nblocks_... |
ecrc/stars-h/src/backends/openmp/blrm/dsdd.c | #pragma omp parallel for schedule(static) | 100 | bi++)
block_near[bi] = F->block_near[bi];
// Add false far-field blocks
<LOOP-START>for(bi = 0; bi < nblocks_false_far; bi++)
{
STARSH_int bj = false_far[bi];
block_near[2*(bi+nblocks_near)] = F->block_far[2*bj];
block_near[2*(bi+nblocks_near)+1] =... |
ecrc/stars-h/src/backends/openmp/blrm/dsdd.c | #pragma omp parallel for schedule(dynamic,1) | 100 | STARSH_MALLOC(alloc_D, size_D);
// For each near-field block compute its elements
<LOOP-START>for(bi = 0; bi < new_nblocks_near; bi++)
{
// Get indexes of corresponding block row and block column
STARSH_int i = block_near[2*bi];
STARSH_int j = block_near[2*b... |
ecrc/stars-h/src/backends/openmp/blrm/drsdd.c | #pragma omp parallel for schedule(dynamic,1) | 100 | }
// Work variables
int info;
// Simple cycle over all far-field admissible blocks
<LOOP-START>for(bi = 0; bi < nblocks_far; bi++)
{
// Get indexes of corresponding block row and block column
STARSH_int i = block_far[2*bi];
STARSH_int j = block_far[2*bi+1];
// Get co... |
ecrc/stars-h/src/backends/openmp/blrm/drsdd.c | #pragma omp parallel for schedule(static) | 100 | ar, 2*new_nblocks_near);
// At first get all near-field blocks, assumed to be dense
<LOOP-START>for(bi = 0; bi < 2*nblocks_near; bi++)
block_near[bi] = F->block_near[bi];
// Add false far-field blocks
#pragma omp parallel for schedule(static)
for(bi = 0; bi < nblocks_... |
ecrc/stars-h/src/backends/openmp/blrm/drsdd.c | #pragma omp parallel for schedule(static) | 100 | bi++)
block_near[bi] = F->block_near[bi];
// Add false far-field blocks
<LOOP-START>for(bi = 0; bi < nblocks_false_far; bi++)
{
STARSH_int bj = false_far[bi];
block_near[2*(bi+nblocks_near)] = F->block_far[2*bj];
block_near[2*(bi+nblocks_near)+1] =... |
ecrc/stars-h/src/backends/openmp/blrm/drsdd.c | #pragma omp parallel for schedule(dynamic,1) | 100 | STARSH_MALLOC(alloc_D, size_D);
// For each near-field block compute its elements
//<LOOP-START>for(bi = 0; bi < new_nblocks_near; bi++)
{
// Get indexes of corresponding block row and block column
STARSH_int i = block_near[2*bi];
STARSH_int j = block_near[2*b... |
ecrc/stars-h/src/backends/openmp/blrm/dqp3.c | #pragma omp parallel for schedule(dynamic,1) | 100 | }
// Work variables
int info;
// Simple cycle over all far-field admissible blocks
<LOOP-START>for(bi = 0; bi < nblocks_far; bi++)
{
// Get indexes of corresponding block row and block column
STARSH_int i = block_far[2*bi];
STARSH_int j = block_far[2*bi+1];
// Get co... |
ecrc/stars-h/src/backends/openmp/blrm/dqp3.c | #pragma omp parallel for schedule(static) | 100 | ar, 2*new_nblocks_near);
// At first get all near-field blocks, assumed to be dense
<LOOP-START>for(bi = 0; bi < 2*nblocks_near; bi++)
block_near[bi] = F->block_near[bi];
// Add false far-field blocks
#pragma omp parallel for schedule(static)
for(bi = 0; bi < nblocks_... |
ecrc/stars-h/src/backends/openmp/blrm/dqp3.c | #pragma omp parallel for schedule(static) | 100 | bi++)
block_near[bi] = F->block_near[bi];
// Add false far-field blocks
<LOOP-START>for(bi = 0; bi < nblocks_false_far; bi++)
{
STARSH_int bj = false_far[bi];
block_near[2*(bi+nblocks_near)] = F->block_far[2*bj];
block_near[2*(bi+nblocks_near)+1] =... |
ecrc/stars-h/src/backends/openmp/blrm/dqp3.c | #pragma omp parallel for schedule(dynamic,1) | 100 | STARSH_MALLOC(alloc_D, size_D);
// For each near-field block compute its elements
<LOOP-START>for(bi = 0; bi < new_nblocks_near; bi++)
{
// Get indexes of corresponding block row and block column
STARSH_int i = block_near[2*bi];
STARSH_int j = block_near[2*b... |
ecrc/stars-h/src/backends/mpi/blrm/dfe.c | #pragma omp parallel for schedule(dynamic, 1) | 100 | far_local;
char symm = F->symm;
int info;
// Simple cycle over all far-field blocks
<LOOP-START>for(lbi = 0; lbi < nblocks_far_local; lbi++)
{
STARSH_int bi = F->block_far_local[lbi];
// Get indexes and sizes of block row and column
STARSH_int i = F->block_far[2*bi];
... |
ecrc/stars-h/src/backends/mpi/blrm/dfe.c | #pragma omp parallel for schedule(dynamic, 1) | 100 | 2;
}
}
if(M->onfly == 0)
// Simple cycle over all near-field blocks
<LOOP-START>for(lbi = 0; lbi < nblocks_near_local; lbi++)
{
STARSH_int bi = F->block_near_local[lbi];
// Get indexes and sizes of corresponding block row and column
STARSH_int ... |
ecrc/stars-h/src/backends/mpi/blrm/dfe.c | #pragma omp parallel for schedule(dynamic, 1) | 100 | k_norm[lbi] *= sqrt2;
}
else
// Simple cycle over all near-field blocks
<LOOP-START>for(lbi = 0; lbi < nblocks_near_local; lbi++)
{
STARSH_int bi = F->block_near_local[lbi];
// Get indexes and sizes of corresponding block row and column
STARSH_int ... |
ecrc/stars-h/src/backends/mpi/blrm/dmml.c | #pragma omp parallel for schedule(static) | 100 | nrhs*(size_t)nrows; j++)
out[j] = 0.;
}
if(beta != 0. && mpi_rank == 0)
<LOOP-START>for(STARSH_int i = 0; i < nrows; i++)
for(STARSH_int j = 0; j < nrhs; j++)
temp_B[j*ldb+i] = beta*B[j*ldb+i];
int ldout = nrows;
// Simple cycle over all far-field admissib... |
ecrc/stars-h/src/backends/mpi/blrm/dmml.c | #pragma omp parallel for schedule(dynamic, 1) | 100 | eta*B[j*ldb+i];
int ldout = nrows;
// Simple cycle over all far-field admissible blocks
<LOOP-START>for(lbi = 0; lbi < nblocks_far_local; lbi++)
{
STARSH_int bi = F->block_far_local[lbi];
// Get indexes of corresponding block row and block column
STARSH_int i = F->block_far[2*bi]... |
ecrc/stars-h/src/backends/mpi/blrm/dmml.c | #pragma omp parallel for schedule(dynamic, 1) | 100 | );
}
}
if(M->onfly == 1)
// Simple cycle over all near-field blocks
<LOOP-START>for(lbi = 0; lbi < nblocks_near_local; lbi++)
{
STARSH_int bi = F->block_near_local[lbi];
// Get indexes and sizes of corresponding block row and column
STARSH_int ... |
ecrc/stars-h/src/backends/mpi/blrm/dmml.c | #pragma omp parallel for schedule(dynamic, 1) | 100 | ldout);
}
}
else
// Simple cycle over all near-field blocks
<LOOP-START>for(lbi = 0; lbi < nblocks_near_local; lbi++)
{
STARSH_int bi = F->block_near_local[lbi];
// Get indexes and sizes of corresponding block row and column
STARSH_int ... |
ecrc/stars-h/src/backends/mpi/blrm/dmml.c | #pragma omp parallel for schedule(static) | 100 | ;
}
}
// Reduce result to temp_B, corresponding to master openmp thread
<LOOP-START>for(int i = 0; i < ldout; i++)
for(int j = 0; j < nrhs; j++)
for(int k = 1; k < num_threads; k++)
temp_B[j*(size_t)ldout+i] +=
temp_B[(k*(size_t)nrh... |
ecrc/stars-h/src/backends/mpi/blrm/dmml.c | #pragma omp parallel for schedule(static) | 100 | ecv+j*(size_t)ldout, maxnb, MPI_DOUBLE, 0,
mpi_leadingy);
}
<LOOP-START>for(int i = 0; i < ldout; i++)
for(int j = 0; j < nrhs; j++)
temp_B[j*(size_t)ldb+i] *= beta;
}
//if(mpi_rank == 0)
// STARSH_WARNING("MORE DATA DISTRIBUTED");
/... |
ecrc/stars-h/src/backends/mpi/blrm/dmml.c | #pragma omp parallel for schedule(dynamic, 1) | 100 | ARSH_WARNING("MORE DATA DISTRIBUTED");
// Simple cycle over all far-field admissible blocks
<LOOP-START>for(lbi = 0; lbi < nblocks_far_local; lbi++)
{
STARSH_int bi = F->block_far_local[lbi];
// Get indexes of corresponding block row and block column
STARSH_int i = F->block_far[2*bi]... |
ecrc/stars-h/src/backends/mpi/blrm/dmml.c | #pragma omp parallel for schedule(dynamic, 1) | 100 | H FAR", mpi_rank);
if(M->onfly == 1)
// Simple cycle over all near-field blocks
<LOOP-START>for(lbi = 0; lbi < nblocks_near_local; lbi++)
{
STARSH_int bi = F->block_near_local[lbi];
// Get indexes and sizes of corresponding block row and column
STARSH_int ... |
ecrc/stars-h/src/backends/mpi/blrm/dmml.c | #pragma omp parallel for schedule(dynamic, 1) | 100 | size_t)maxnb, ldout);
}
else
// Simple cycle over all near-field blocks
<LOOP-START>for(lbi = 0; lbi < nblocks_near_local; lbi++)
{
STARSH_int bi = F->block_near_local[lbi];
// Get indexes and sizes of corresponding block row and column
STARSH_int ... |
ecrc/stars-h/src/backends/mpi/blrm/dmml.c | #pragma omp parallel for schedule(static) | 100 | )maxnb, ldout);
}
// Reduce result to temp_B, corresponding to master openmp thread
<LOOP-START>for(int i = 0; i < ldout; i++)
for(int j = 0; j < nrhs; j++)
for(int k = 1; k < num_threads; k++)
temp_B[j*(size_t)ldout+i] +=
temp_B[(k*(size_t)nrh... |
ecrc/stars-h/src/backends/mpi/blrm/dmml.c | #pragma omp parallel for schedule(static) | 100 | if(mpi_leadingy != MPI_COMM_NULL)
{
STARSH_MALLOC(final_B, nrhs*(size_t)ldout);
<LOOP-START>for(size_t i = 0; i < nrhs*(size_t)ldout; i++)
final_B[i] = 0.0;
}
MPI_Reduce(temp_B, final_B, nrhs*(size_t)ldout, MPI_DOUBLE, MPI_SUM, 0,
mpi_splity);
//STARSH_WARNING("RE... |
ecrc/stars-h/src/backends/mpi/blrm/dna.c | #pragma omp parallel for schedule(static) | 100 | r-field admissible blocks
// Since this is fake low-rank approximation, every tile is dense
<LOOP-START>for(lbi = 0; lbi < nblocks_far_local; lbi++)
far_rank[lbi] = -1;
/*
#pragma omp parallel for schedule(dynamic, 1)
for(lbi = 0; lbi < nblocks_far_local; lbi++)
{
size_t bi = blo... |
ecrc/stars-h/src/backends/mpi/blrm/dna.c | #pragma omp parallel for schedule(dynamic, 1) | 100 | ule(static)
for(lbi = 0; lbi < nblocks_far_local; lbi++)
far_rank[lbi] = -1;
/*
<LOOP-START>for(lbi = 0; lbi < nblocks_far_local; lbi++)
{
size_t bi = block_far_local[lbi];
// Get indexes of corresponding block row and block column
int i = block_far[2*bi];
int j =... |
ecrc/stars-h/src/backends/mpi/blrm/dna.c | #pragma omp parallel for schedule(static) | 100 | new_nblocks_near_local);
// At first get all near-field blocks, assumed to be dense
<LOOP-START>for(bi = 0; bi < 2*nblocks_near; bi++)
block_near[bi] = F->block_near[bi];
#pragma omp parallel for schedule(static)
for(lbi = 0; lbi < nblocks_near_local; lbi++)
block... |
ecrc/stars-h/src/backends/mpi/blrm/dna.c | #pragma omp parallel for schedule(static) | 100 | for(bi = 0; bi < 2*nblocks_near; bi++)
block_near[bi] = F->block_near[bi];
<LOOP-START>for(lbi = 0; lbi < nblocks_near_local; lbi++)
block_near_local[lbi] = F->block_near_local[lbi];
// Add false far-field blocks
#pragma omp parallel for schedule(static)
for(... |
ecrc/stars-h/src/backends/mpi/blrm/dna.c | #pragma omp parallel for schedule(static) | 100 | block_near_local[lbi] = F->block_near_local[lbi];
// Add false far-field blocks
<LOOP-START>for(bi = 0; bi < nblocks_false_far; bi++)
{
STARSH_int bj = false_far[bi];
block_near[2*(bi+nblocks_near)] = F->block_far[2*bj];
block_near[2*(bi+nblocks_near)+1] =... |
ecrc/stars-h/src/backends/mpi/blrm/dna.c | #pragma omp parallel for schedule(dynamic, 1) | 100 | STARSH_MALLOC(alloc_D, size_D);
// For each near-field block compute its elements
<LOOP-START>for(lbi = 0; lbi < new_nblocks_near_local; lbi++)
{
STARSH_int bi = block_near_local[lbi];
// Get indexes of corresponding block row and block column
STARSH_int i =... |
ecrc/stars-h/src/backends/mpi/blrm/dsdd.c | #pragma omp parallel for schedule(dynamic, 1) | 100 | }
// Work variables
int info;
// Simple cycle over all far-field admissible blocks
<LOOP-START>for(lbi = 0; lbi < nblocks_far_local; lbi++)
{
STARSH_int bi = block_far_local[lbi];
// Get indexes of corresponding block row and block column
STARSH_int i = block_far[2*bi];
... |
ecrc/stars-h/src/backends/mpi/blrm/dsdd.c | #pragma omp parallel for schedule(static) | 100 | new_nblocks_near_local);
// At first get all near-field blocks, assumed to be dense
<LOOP-START>for(bi = 0; bi < 2*nblocks_near; bi++)
block_near[bi] = F->block_near[bi];
#pragma omp parallel for schedule(static)
for(lbi = 0; lbi < nblocks_near_local; lbi++)
block... |
ecrc/stars-h/src/backends/mpi/blrm/dsdd.c | #pragma omp parallel for schedule(static) | 100 | for(bi = 0; bi < 2*nblocks_near; bi++)
block_near[bi] = F->block_near[bi];
<LOOP-START>for(lbi = 0; lbi < nblocks_near_local; lbi++)
block_near_local[lbi] = F->block_near_local[lbi];
// Add false far-field blocks
#pragma omp parallel for schedule(static)
for(... |
ecrc/stars-h/src/backends/mpi/blrm/dsdd.c | #pragma omp parallel for schedule(static) | 100 | block_near_local[lbi] = F->block_near_local[lbi];
// Add false far-field blocks
<LOOP-START>for(bi = 0; bi < nblocks_false_far; bi++)
{
STARSH_int bj = false_far[bi];
block_near[2*(bi+nblocks_near)] = F->block_far[2*bj];
block_near[2*(bi+nblocks_near)+1] =... |
ecrc/stars-h/src/backends/mpi/blrm/dsdd.c | #pragma omp parallel for schedule(dynamic, 1) | 100 | STARSH_MALLOC(alloc_D, size_D);
// For each near-field block compute its elements
<LOOP-START>for(lbi = 0; lbi < new_nblocks_near_local; lbi++)
{
STARSH_int bi = block_near_local[lbi];
// Get indexes of corresponding block row and block column
STARSH_int i =... |
ecrc/stars-h/src/backends/mpi/blrm/drsdd.c | #pragma omp parallel for schedule(dynamic, 1) | 100 | }
// Work variables
int info;
// Simple cycle over all far-field admissible blocks
<LOOP-START>for(lbi = 0; lbi < nblocks_far_local; lbi++)
{
STARSH_int bi = block_far_local[lbi];
// Get indexes of corresponding block row and block column
STARSH_int i = block_far[2*bi];
... |
ecrc/stars-h/src/backends/mpi/blrm/drsdd.c | #pragma omp parallel for schedule(static) | 100 | new_nblocks_near_local);
// At first get all near-field blocks, assumed to be dense
<LOOP-START>for(bi = 0; bi < 2*nblocks_near; bi++)
block_near[bi] = F->block_near[bi];
#pragma omp parallel for schedule(static)
for(lbi = 0; lbi < nblocks_near_local; lbi++)
block... |
ecrc/stars-h/src/backends/mpi/blrm/drsdd.c | #pragma omp parallel for schedule(static) | 100 | for(bi = 0; bi < 2*nblocks_near; bi++)
block_near[bi] = F->block_near[bi];
<LOOP-START>for(lbi = 0; lbi < nblocks_near_local; lbi++)
block_near_local[lbi] = F->block_near_local[lbi];
// Add false far-field blocks
#pragma omp parallel for schedule(static)
for(... |
ecrc/stars-h/src/backends/mpi/blrm/drsdd.c | #pragma omp parallel for schedule(static) | 100 | block_near_local[lbi] = F->block_near_local[lbi];
// Add false far-field blocks
<LOOP-START>for(bi = 0; bi < nblocks_false_far; bi++)
{
STARSH_int bj = false_far[bi];
block_near[2*(bi+nblocks_near)] = F->block_far[2*bj];
block_near[2*(bi+nblocks_near)+1] =... |
ecrc/stars-h/src/backends/mpi/blrm/drsdd.c | #pragma omp parallel for schedule(dynamic, 1) | 100 | STARSH_MALLOC(alloc_D, size_D);
// For each near-field block compute its elements
<LOOP-START>for(lbi = 0; lbi < new_nblocks_near_local; lbi++)
{
STARSH_int bi = block_near_local[lbi];
// Get indexes of corresponding block row and block column
STARSH_int i =... |
ecrc/stars-h/src/backends/mpi/blrm/dqp3.c | #pragma omp parallel for schedule(dynamic, 1) | 100 | }
// Work variables
int info;
// Simple cycle over all far-field admissible blocks
<LOOP-START>for(lbi = 0; lbi < nblocks_far_local; lbi++)
{
STARSH_int bi = block_far_local[lbi];
// Get indexes of corresponding block row and block column
STARSH_int i = block_far[2*bi];
... |
ecrc/stars-h/src/backends/mpi/blrm/dqp3.c | #pragma omp parallel for schedule(static) | 100 | new_nblocks_near_local);
// At first get all near-field blocks, assumed to be dense
<LOOP-START>for(bi = 0; bi < 2*nblocks_near; bi++)
block_near[bi] = F->block_near[bi];
#pragma omp parallel for schedule(static)
for(lbi = 0; lbi < nblocks_near_local; lbi++)
block... |
ecrc/stars-h/src/backends/mpi/blrm/dqp3.c | #pragma omp parallel for schedule(static) | 100 | for(bi = 0; bi < 2*nblocks_near; bi++)
block_near[bi] = F->block_near[bi];
<LOOP-START>for(lbi = 0; lbi < nblocks_near_local; lbi++)
block_near_local[lbi] = F->block_near_local[lbi];
// Add false far-field blocks
#pragma omp parallel for schedule(static)
for(... |
ecrc/stars-h/src/backends/mpi/blrm/dqp3.c | #pragma omp parallel for schedule(static) | 100 | block_near_local[lbi] = F->block_near_local[lbi];
// Add false far-field blocks
<LOOP-START>for(bi = 0; bi < nblocks_false_far; bi++)
{
STARSH_int bj = false_far[bi];
block_near[2*(bi+nblocks_near)] = F->block_far[2*bj];
block_near[2*(bi+nblocks_near)+1] =... |
ecrc/stars-h/src/backends/mpi/blrm/dqp3.c | #pragma omp parallel for schedule(dynamic, 1) | 100 | STARSH_MALLOC(alloc_D, size_D);
// For each near-field block compute its elements
<LOOP-START>for(lbi = 0; lbi < new_nblocks_near_local; lbi++)
{
STARSH_int bi = block_near_local[lbi];
// Get indexes of corresponding block row and block column
STARSH_int i =... |
PanosAntoniadis/pps-ntua/Lab1/ex2/parallel/OpenMP/fws_parfor.c | #pragma omp parallel for private(i, j) shared(A, k, N) | 100 | alloc(N*sizeof(int));
graph_init_random(A,-1,N,128*N);
gettimeofday(&t1,0);
for(k=0;k<N;k++)
<LOOP-START>for(i=0; i<N; i++)
for(j=0; j<N; j++)
A[i][j]=min(A[i][j], A[i][k] + A[k][j]);
gettimeofday(&t2,0);
time=(double)((t2.tv_sec-t1.tv_sec)*1000000+t2.tv_usec-t1.tv_usec)/1000000;
printf("FW,%d,%.4f\n... |
PanosAntoniadis/pps-ntua/Lab1/ex1/parallel/GoL_p.c | #pragma omp parallel for shared(N, previous, current) private(i, j, nbrs) | 100 | r ( t = 0 ; t < T ; t++ ) {
/* Use OpenMP parallel for in order to parallelize i and j loops */
<LOOP-START>for ( i = 1 ; i < N-1 ; i++ )
for ( j = 1 ; j < N-1 ; j++ ) {
nbrs = previous[i+1][j+1] + previous[i+1][j] + previous[i+1][j-1] \
+ previous[i][j-1] + previous[i][j+1] \
+ previous[i-1][j-1] ... |
SebKrantz/collapse/misc/legacy/sorted out 1.8.9 - 1.9.0/fnth_fmedian.cpp | #pragma omp parallel for num_threads(nthreads) | 100 | gcount(ngp);
if(Rf_isNull(gs)) {
for(int i = 0; i != l; ++i) ++gcount[g[i]];
<LOOP-START>for(int i = 1; i < ngp; ++i) {
// if(gcount[i] == 0) stop("Group size of 0 encountered. This is probably because of unused factor levels. Use fdroplevels(f) to drop them.");
if(gcount[i] >... |
SebKrantz/collapse/misc/legacy/sorted out 1.8.9 - 1.9.0/fnth_fmedian.cpp | #pragma omp parallel for num_threads(nthreads) | 100 | IntegerVector gsv = gs;
if(ng != gsv.size()) stop("ng must match length(gs)");
<LOOP-START>for(int i = 0; i < ng; ++i) {
// if(gsv[i] == 0) stop("Group size of 0 encountered. This is probably because of unused factor levels. Use fdroplevels(f) to drop them.");
if(gsv[i] > 0) gma... |
SebKrantz/collapse/misc/legacy/sorted out 1.8.9 - 1.9.0/fnth_fmedian.cpp | #pragma omp parallel for num_threads(nthreads) | 100 | L);
for(int i = 0; i != l; ++i) if(nisnan(x[i])) gmap[g[i]][gcount[g[i]]++] = x[i];
<LOOP-START>for(int i = 1; i < ngp; ++i) {
if(gcount[i] != 0) {
int n = gcount[i], nth = lower ? (n-1)*Q : n*Q;
auto begin = gmap[i].begin(), mid = begin + nth, end = begin + n;
... |
SebKrantz/collapse/misc/legacy/sorted out 1.8.9 - 1.9.0/fnth_fmedian.cpp | #pragma omp parallel for num_threads(nthreads) | 100 | }
} else {
gmap[g[i]][gcount[g[i]]++] = x[i];
}
}
<LOOP-START>for(int i = 0; i < ng; ++i) {
if(isnan2(out[i]) || gcount[i+1] == 0) continue;
int n = gcount[i+1], nth = lower ? (n-1)*Q : n*Q;
auto begin = gmap[i+1].begin(), mid = begin + nth... |
SebKrantz/collapse/misc/legacy/sorted out 1.8.9 - 1.9.0/fnth_fmedian.cpp | #pragma omp parallel for num_threads(nthreads) | 100 | eads > col) nthreads = col;
NumericVector out = no_init_vector(col);
if(narm) {
<LOOP-START>for(int j = 0; j < col; ++j) {
NumericMatrix::ConstColumn colj = x( _ , j);
NumericVector column = no_init_vector(l); // without multithreading this could be taken out of the loop, see pre... |
SebKrantz/collapse/misc/legacy/sorted out 1.8.9 - 1.9.0/fnth_fmedian.cpp | #pragma omp parallel for num_threads(nthreads) | 100 | } else {
int nth = lower ? (l-1)*Q : l*Q;
bool tm = tiesmean && l%2 == 0;
<LOOP-START>for(int j = 0; j < col; ++j) {
{
NumericMatrix::ConstColumn colj = x( _ , j);
for(int i = 0; i != l; ++i) {
if(isnan2(colj[i])) {
out[j] = colj[... |
SebKrantz/collapse/misc/legacy/sorted out 1.8.9 - 1.9.0/fnth_fmedian.cpp | #pragma omp parallel for num_threads(nthreads) | 100 | gcount(ngp);
if(Rf_isNull(gs)) {
for(int i = 0; i != l; ++i) ++gcount[g[i]];
<LOOP-START>for(int i = 1; i < ngp; ++i) {
// if(gcount[i] == 0) stop("Group size of 0 encountered. This is probably because of unused factor levels. Use fdroplevels(f) to drop them.");
if(gcount[i] >... |
SebKrantz/collapse/misc/legacy/sorted out 1.8.9 - 1.9.0/fnth_fmedian.cpp | #pragma omp parallel for num_threads(nthreads) | 100 | IntegerVector gsv = gs;
if(ng != gsv.size()) stop("ng must match length(gs)");
<LOOP-START>for(int i = 0; i < ng; ++i) {
// if(gsv[i] == 0) stop("Group size of 0 encountered. This is probably because of unused factor levels. Use fdroplevels(f) to drop them.");
if(gsv[i] > 0) gma... |
SebKrantz/collapse/misc/legacy/sorted out 1.8.9 - 1.9.0/fnth_fmedian.cpp | #pragma omp parallel for num_threads(nthreads) | 100 | for(int i = 0; i != l; ++i) if(nisnan(column[i])) gmap[g[i]][gcount[g[i]]++] = column[i];
<LOOP-START>for(int i = 1; i < ngp; ++i) {
if(gcount[i] != 0) {
int n = gcount[i], nth = lower ? (n-1)*Q : n*Q;
auto begin = gmap[i].begin(), mid = begin + nth, end = begin + n;
... |
SebKrantz/collapse/misc/legacy/sorted out 1.8.9 - 1.9.0/fnth_fmedian.cpp | #pragma omp parallel for num_threads(nthreads) | 100 | } else {
gmap[g[i]][gcount[g[i]]++] = column[i];
}
}
<LOOP-START>for(int i = 0; i < ng; ++i) {
if(isnan2(nthj[i]) || gcount[i+1] == 0) continue;
int n = gcount[i+1], nth = lower ? (n-1)*Q : n*Q;
auto begin = gmap[i+1].begin(), mid = begi... |
SebKrantz/collapse/misc/legacy/sorted out 1.8.9 - 1.9.0/fnth_fmedian.cpp | #pragma omp parallel for num_threads(nthreads) | 100 | lement(begin+nth+1, pend)))*0.5 : column[nth];
}
}
} else {
<LOOP-START>for(int j = 0; j < l; ++j) out[j] = median_narm(x[j], lower, tiesmean, Q);
}
} else {
#pragma omp parallel for num_threads(nthreads)
for(int j = 0; j < l; ++j) out[j] = median_ke... |
SebKrantz/collapse/misc/legacy/sorted out 1.8.9 - 1.9.0/fnth_fmedian.cpp | #pragma omp parallel for num_threads(nthreads) | 100 | j = 0; j < l; ++j) out[j] = median_narm(x[j], lower, tiesmean, Q);
}
} else {
<LOOP-START>for(int j = 0; j < l; ++j) out[j] = median_keepna(x[j], lower, tiesmean, Q);
}
if(drop) {
Rf_setAttrib(out, R_NamesSymbol, Rf_getAttrib(x, R_NamesSymbol));
return out;
}<LOOP... |
SebKrantz/collapse/misc/legacy/sorted out 1.8.9 - 1.9.0/fnth_fmedian.cpp | #pragma omp parallel for num_threads(nthreads) | 100 | count(ngp);
if(Rf_isNull(gs)) {
for(int i = 0; i != lx1; ++i) ++gcount[g[i]];
<LOOP-START>for(int i = 1; i < ngp; ++i) {
// if(gcount[i] == 0) stop("Group size of 0 encountered. This is probably because of unused factor levels. Use fdroplevels(f) to drop them.");
if(gcount[i] >... |
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