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Update CUDA matrix_multiplication test

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augustin64 2022-10-21 14:36:26 +02:00
parent 757d641580
commit 35ac91585f
1 changed files with 63 additions and 53 deletions
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118
test/matrix_multiplication.cu
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@ -55,34 +55,76 @@ float** create_empty_matrix(int n, int p) {
return matrix; return matrix;
} }
float max_float(float a, float b) {
return a > b ? a : b;
}
bool check_matrices_equality(float** m1, float** m2, int n, int p, int acceptation) {
bool check_matrices_equality(float** m1, float** m2, int n, int p) {
float err_max = 0.;
float err_moy = 0.;
for (int i=0; i < n; i++) { for (int i=0; i < n; i++) {
for (int j=0; j < p; j++) { for (int j=0; j < p; j++) {
if (fabs(m1[i][j] - m2[i][j]) > 0.8) { if (fabs(m1[i][j] - m2[i][j]) > 0.01*acceptation) {
//printf("%d %d\n", i, j); return false;
//return false; }
}
err_max = max_float(err_max, fabs(m1[i][j] - m2[i][j]));
err_moy += fabs(m1[i][j] - m2[i][j]);
} }
} }
printf("err_max: %f\n", err_max);
printf("err_moy: %f\n", err_moy/(n*p));
return true; return true;
} }
void run_matrices_test(int n, int p, int q) {
clock_t start, end;
double cpu_time_used;
float** matrix1 = create_matrix(n, p);
float** matrix2 = create_matrix(p, q);
float** result_gpu = create_empty_matrix(n, q);
float** result_cpu = create_empty_matrix(n, q);
printf("(%d,%d)x(%d,%d) Computing on GPU.\n", n, p, p, q);
start = clock();
matrix_multiplication_device(matrix1, matrix2, result_gpu, n, p, q);
end = clock();
cpu_time_used = ((double) (end - start)) / CLOCKS_PER_SEC;
printf("(%d,%d)x(%d,%d) Time used for GPU: %lf seconds\n", n, p, p, q, cpu_time_used);
printf("OK\n");
printf("(%d,%d)x(%d,%d) Computing on CPU.\n", n, p, p, q);
start = clock();
matrix_multiplication_host(matrix1, matrix2, result_cpu, n, p, q);
end = clock();
cpu_time_used = ((double) (end - start)) / CLOCKS_PER_SEC;
printf("(%d,%d)x(%d,%d) Time used for CPU: %lf seconds\n", n, p, p, q, cpu_time_used);
printf("OK\n");
// Vérification de l'égalité des matrices
printf("(%d,%d)x(%d,%d) Checking equality.\n", n, p, p, q);
if (!check_matrices_equality(result_gpu, result_cpu, n, q, p)) {
exit(1);
}
printf("OK\n");
// On libère l'espace mémoire alloué
for (int i=0; i < n; i++) {
free(matrix1[i]);
}
free(matrix1);
for (int i=0; i < p; i++) {
free(matrix2[i]);
}
free(matrix2);
for (int i=0; i < n; i++) {
free(result_cpu[i]);
}
free(result_cpu);
for (int i=0; i < n; i++) {
free(result_gpu[i]);
}
free(result_gpu);
}
int main() { int main() {
clock_t start, end;
double cpu_time_used;
printf("Checking CUDA compatibility.\n"); printf("Checking CUDA compatibility.\n");
bool cuda_compatible = check_cuda_compatibility(); bool cuda_compatible = check_cuda_compatibility();
if (!cuda_compatible) { if (!cuda_compatible) {
@ -91,42 +133,10 @@ int main() {
} }
printf("OK\n"); printf("OK\n");
printf("Generating matrices.\n");
srand(time(NULL)); srand(time(NULL));
int n = 200; run_matrices_test(200, 1000, 200);
int p = 1000; run_matrices_test(200, 1000, 20);
int q = 200; run_matrices_test(20, 1000, 200);
float** matrix1 = create_matrix(n, p);
float** matrix2 = create_matrix(p, q);
float** result_gpu = create_empty_matrix(n, q);
float** result_cpu = create_empty_matrix(n, q);
printf("OK\n");
printf("Computing on GPU.\n");
start = clock();
matrix_multiplication_device(matrix1, matrix2, result_gpu, n, p, q);
end = clock();
cpu_time_used = ((double) (end - start)) / CLOCKS_PER_SEC;
printf("Time used for GPU: %lf seconds\n", cpu_time_used);
printf("OK\n");
printf("Computing on CPU.\n");
start = clock();
matrix_multiplication_host(matrix1, matrix2, result_cpu, n, p, q);
end = clock();
cpu_time_used = ((double) (end - start)) / CLOCKS_PER_SEC;
printf("Time used for CPU: %lf seconds\n", cpu_time_used);
printf("OK\n");
printf("Checking equality.\n");
if (!check_matrices_equality(result_gpu, result_cpu, n, q)) {
return 1;
}
printf("OK\n");
return 0; return 0;
} }
@ -135,4 +145,4 @@ int main() {
// Cette différence est linéaire en p. (err_moy = p*1.639e-6) // Cette différence est linéaire en p. (err_moy = p*1.639e-6)
// Elle ne varie pas en fonction de n et q. // Elle ne varie pas en fonction de n et q.
// Cette erreur est sûrement dûe à différences mineurs dans la précision du stockage des flottants // Cette erreur est sûrement dûe à différences mineurs dans la précision du stockage des flottants
// Dans la mémoire RAM et VRAM (du GPU) // dans la mémoire RAM et VRAM (du GPU)