int main(void){
matrix* A = create_matrix(3, 3);
value temp_a[9] = { 0, 0, 1,
0, 1, 0,
1, 0, 0};
insert_array(temp_a, A);
matrix* B = create_matrix(3, 1);
value temp_b[3] = { 0,
4,
3};
insert_array(temp_b, B);
matrix* X = create_matrix(3, 1);
gauss_jordan_solver(A, X, B);
/* X should be */
matrix* solution = create_matrix(3, 1);
value temp_solution[3] = {3,
4,
0};
insert_array(temp_solution, solution);
assert(compare_matrices(X, solution));
free_matrix(A);
free_matrix(B);
free_matrix(X);
free_matrix(solution);
return 0;
}
static char *test_compare_matrices()
{
// By default newly create marices have all elements
// equal to 0. So a and b should be equal.
Matrix *a = create_matrix(2, 2);
Matrix *b = create_matrix(2, 2);
mu_assert("a != b", compare_matrices(a, b) == 1);
// Let's modify their values a bit.
a->value[1][1] = 2;
b->value[0][0] = 1;
// They should be not equal now
mu_assert("a == b, should be different", compare_matrices(a, b) == 0);
destroy_matrix(a);
destroy_matrix(b);
return 0;
}
int main(){
clock_t begin, end;
double time_spent;
begin = clock();
matrix* Q = create_matrix(4, 4);
value Q_arr[16] = {1, 0, 1, 0,
0, 2, 0, 1,
1, 0, 2, 0,
0, 1, 0, 1};
insert_array(Q_arr, Q);
sparse_matrix* s_Q = create_sparse_matrix(Q, 8);
matrix* q = create_matrix(4, 1);
value q_arr[4] = {3,
20,
5,
15};
insert_array(q_arr, q);
matrix* expected = create_matrix(4, 1);
value e_arr[4] = {1,
5,
2,
10};
insert_array(e_arr, expected);
matrix* x = create_zero_matrix(4, 1);
conjugate_gradient(s_Q, x, q);
assert(compare_matrices(x, expected));
free_matrix(Q);
free_matrix(q);
free_matrix(x);
free_matrix(expected);
free_sparse_matrix(s_Q);
end = clock();
time_spent = (double)(end - begin) / CLOCKS_PER_SEC;
printf("time taken was: %f \n", time_spent);
}
static char *test_add_matrices()
{
// We should create 2 empty matrices. If we add them we should get
// an empty matrix.
Matrix *a = create_matrix(2, 2);
Matrix *b = create_matrix(2, 2);
// We will store the result of the adition in a third matrix c.
Matrix *c = create_matrix(2, 2);
add_matrices(a, b, &c);
// Since a and b are empty their result will an empty matrix too
// so it makes sense to compare c against b or a.
mu_assert("c != a or b", compare_matrices(a, c));
destroy_matrix(a);
destroy_matrix(b);
destroy_matrix(c);
return 0;
}
static char *test_compute_inverse()
{
Matrix *a = create_matrix(3, 3);
// The matrix b will contain the value of the a's inverse.
Matrix *b = create_matrix(3, 3);
b->value[0][0] = -1;
b->value[0][1] = 0.5;
b->value[0][2] = 0;
b->value[1][0] = 0.5;
b->value[1][1] = -1;
b->value[1][2] = 0.5;
b->value[2][0] = 0.3333333;
b->value[2][1] = 0.5;
b->value[2][2] = -0.333333;
for(int i = 0, k = 1; i < 3; i++) {
for(int j = 0; j < 3; j++, k++) {
if(k != 5) {
a->value[i][j] = k;
}
else {
// The matrix that has all the values from 1 to 9 in spiral
// has no inverse, so I replaced the 5 with an four.
a->value[i][j] = 4;
}
}
}
a->determinant = get_determinant(a);
compute_inverse(a);
mu_assert("The invers is not equal to the matrix b", compare_matrices(
a->inverse, b));
destroy_matrix(a);
destroy_matrix(b);
return 0;
}
int main(){
clock_t begin, end;
double time_spent;
begin = clock();
matrix* Q = create_matrix(2,2);
value Q_arr[4] = { 2, 0,
0, 2};
insert_array(Q_arr, Q);
matrix* q = create_matrix(2, 1);
value q_arr[2] = { -2,
-5};
insert_array(q_arr, q);
matrix* F = create_matrix(5, 2);
value F_arr[10] = { 1, -2,
-1, -2,
-1, 2,
1, 0,
0, 1};
insert_array(F_arr, F);
matrix* g = create_matrix(5, 1);
value g_arr[5] = { -2,
-6,
-2,
0,
0};
insert_array(g_arr, g);
/* starting point */
matrix* z = create_matrix(2,1);
value z_arr[2] = {1,
1};
insert_array(z_arr, z);
problem* problem = create_problem(Q, q, NULL, NULL, F, g, z, 0, 0);
quadopt_solver(problem);
matrix* expected = create_matrix(2, 1);
value e_arr[2] = {1.4,
1.7};
insert_array(e_arr, expected);
assert(compare_matrices(problem->solution, expected));
free_matrix(expected);
free_problem(problem);
end = clock();
time_spent = (double)(end - begin) / CLOCKS_PER_SEC;
printf("time taken was: %f \n", time_spent);
return 0;
}
int main(int argc, char **argv)
{
int i, j, k, kk;
// Randomly init A and B.
srand(2008);
randomInitArr((float*)A, HA*WA);
randomInitArr((float*)B, WA*WB);
#pragma hicuda global alloc A[*][*] copyin
#pragma hicuda global alloc B[*][*] copyin
#pragma hicuda global alloc C[*][*]
// Record the start time.
struct timeval start_time;
gettimeofday(&start_time, NULL);
// C = A * B
#pragma hicuda kernel matrixMul tblock(64,64) thread(16,16)
#pragma hicuda loop_partition over_tblock over_thread
for (i = 0; i < HA; ++i)
{
#pragma hicuda loop_partition over_tblock over_thread
for (j = 0; j < WB; ++j)
{
float sum = 0;
for (kk = 0; kk < WA; kk += TILE_SZ) {
#pragma hicuda shared alloc A[i][kk:kk+15] copyin
#pragma hicuda shared alloc B[kk:kk+15][j] copyin
#pragma hicuda barrier
for (k = 0; k < TILE_SZ; ++k) {
sum += A[i][kk+k] * B[kk+k][j];
}
#pragma hicuda barrier
#pragma hicuda shared remove A B
}
C[i][j] = sum;
}
}
#pragma hicuda kernel_end
#pragma hicuda global copyout C[*][*]
#pragma hicuda global free A B C
// Record the end time.
struct timeval end_time;
gettimeofday(&end_time, NULL);
printf("Time elapsed: %6f ms\n", get_time_diff(&start_time, &end_time));
// Compute reference solution.
computeGold((float*)reference, (float*)A, (float*)B, HA, WA, WB);
// Check result.
compare_matrices((float*)C, (float*)reference, HA*WB);
// printMatrix((float*)C, HA, WB);
return 0;
}
int main(void) {
clock_t begin, end;
double time_spent;
begin = clock();
matrix* a = create_matrix(4, 4);
value temp_a[16] = { 18, 60, 57, 96,
41, 24, 99, 58,
14, 30, 97, 66,
51, 13, 19, 85 };
insert_array(temp_a, a);
matrix* b = create_matrix(4, 4);
assert(insert_array(temp_a, b));
//tests check_boundaries
assert(check_boundaries(1,1,a));
assert(check_boundaries(4,4,a));
assert(!check_boundaries(4,5,a));
assert(!check_boundaries(5,4,a));
assert(!check_boundaries(0,1,a));
assert(!check_boundaries(1,0,a));
assert(!check_boundaries(-1,1,a));
assert(!check_boundaries(1,-1,a));
//tests compare_matrices,insert_value and get_value
assert(compare_matrices(a,b));
assert(insert_value(10,1,1,b));
assert(!compare_matrices(a,b));
assert(get_value(1,1,b)==10);
assert(insert_value(18,1,1,b));
assert(compare_matrices(a,b));
//tests is_matrix
matrix* c=a;
assert(compare_matrices(a,c));
assert(!is_matrix(a,b));
assert(is_matrix(a,c));
//tests insert_value by trying to go outside the matrix
assert(insert_value(1,1,1,c));
assert(insert_value(2,2,2,c));
assert(insert_value(3,3,3,c));
assert(insert_value(4,4,4,c));
assert(!insert_value(5,5,5,c));
assert(!insert_value(-1,-1,-1,c));
assert(!insert_value(-1,-1,1,c));
assert(!insert_value(-1,1,-1,c));
//test get_value
assert(get_value(1,1,c)==1);
assert(get_value(2,2,c)==2);
assert(get_value(3,3,c)==3);
assert(get_value(4,4,c)==4);
assert(get_value(0,0,c)==0);
assert(get_value(1,-1,c)==0);
assert(get_value(-1,1,c)==0);
assert(get_value(5,5,c)==0);
//tests insert and get without boundary checks
insert_value_without_check(4,1,1,c);
insert_value_without_check(3,2,2,c);
insert_value_without_check(2,3,3,c);
insert_value_without_check(1,4,4,c);
assert(get_value_without_check(1,1,c)==4);
assert(get_value_without_check(2,2,c)==3);
assert(get_value_without_check(3,3,c)==2);
assert(get_value_without_check(4,4,c)==1);
//tests add_matrices
value temp_b[16]={
36,120,114,192,
82,48,198,116,
28, 60, 194,132,
102,26,38,170};
assert(insert_array(temp_b,a));
matrix* d = create_matrix(4, 4);
assert(add_matrices(b,b,d));
assert(compare_matrices(d,a));
//tests subtract_matrices
value temp_c[16]={
0,0,0,0,
0,0,0,0,
0, 0, 0,0,
0,0,0,0};
assert(insert_array(temp_c,a));
assert(subtract_matrices(b,b,d));
assert(compare_matrices(d,a));
//tests sum_of_row
assert(insert_array(temp_a,a));
assert(sum_of_row(1,a)==231);
assert(sum_of_row(4,a)==168);
assert(sum_of_row(0,a)==0);
assert(sum_of_row(5,a)==0);
//tests sum_of_column
assert(sum_of_column(1,a)==124);
assert(sum_of_column(4,a)==305);
assert(sum_of_column(0,a)==0);
assert(sum_of_column(5,a)==0);
//tests get_row_vector
matrix* e = create_matrix(1, 4);
value temp_d[4] = { 18, 60, 57, 96};
assert(insert_array(temp_d,e));
matrix* f = create_matrix(1, 4);
assert(!get_row_vector(0,a,f));
assert(!get_row_vector(5,a,f));
assert(get_row_vector(1,a,f));
assert(compare_matrices(e,f));
//tests get_column_vector
matrix* g = create_matrix(4, 1);
assert(insert_array(temp_d,e));
matrix* h = create_matrix(1, 4);
assert(!get_row_vector(0,a,h));
assert(!get_row_vector(5,a,h));
assert(get_row_vector(1,a,h));
assert(compare_matrices(e,h));
//tests mulitply_matrices
assert(multiply_matrices(a,a,b));
value temp_f[16]={8478,5478,14319,17130,
6066,6760,15418,16792,
6206,5328,14431,15096,
6052,5047,7652,14129.00};
assert(insert_array(temp_f,d));
assert(compare_matrices(b,d));
assert(!multiply_matrices(a,h,b));
assert(!multiply_matrices(a,a,h));
//tests transpose_matrix
value temp_g[16]={18,41,14,51,
60,24,30,13,
57,99,97,19,
96,58,66,85};
assert(insert_array(temp_g,d));
assert(transpose_matrix(a,b));
assert(compare_matrices(b,d));
assert(!transpose_matrix(e,b));
assert(!transpose_matrix(a,e));
//tests multiply_matrix_with_scalar
value temp_h[16] = { 36, 120, 114, 192,
82, 48, 198, 116,
28, 60, 194, 132,
102, 26, 38, 170 };
assert(insert_array(temp_h,b));
multiply_matrix_with_scalar(2,a);
assert(compare_matrices(a,b));
//test get_sub_matrix
matrix* i=create_matrix(2,2);
assert(insert_array(temp_a,a));
assert(get_sub_matrix(1,2,1,2,a,i));
matrix* j=create_matrix(2,2);
value temp_i[4] = { 18, 60, 41, 24};
assert(insert_array(temp_i,j));
assert(compare_matrices(j,i));
value temp_j[4] = { 97, 66, 19, 85};
assert(insert_array(temp_j,j));
assert(get_sub_matrix(3,4,3,4,a,i));
assert(compare_matrices(j,i));
assert(!get_sub_matrix(2,4,3,4,a,i));
assert(!get_sub_matrix(3,4,2,4,a,i));
assert(!get_sub_matrix(4,5,4,5,a,i));
assert(!get_sub_matrix(0,1,0,1,a,i));
//test insert_row_vector
assert(insert_array(temp_a,a));
value temp_k[16] = { 18, 60, 57, 96,
18, 60, 57, 96,
14, 30, 97, 66,
51, 13, 19, 85 };
assert(insert_array(temp_k,b));
assert(insert_array(temp_d,e));
assert(insert_row_vector(2,e,a));
assert(compare_matrices(a,b));
end = clock();
time_spent = (double)(end - begin) / CLOCKS_PER_SEC;
printf("time taken was: %f \n",time_spent);
free_matrix(a);
free_matrix(b);
free_matrix(d);
free_matrix(e);
free_matrix(f);
free_matrix(g);
free_matrix(h);
free_matrix(i);
free_matrix(j);
return 0;
}
void measure_difference(ghog::lib::HogDescriptor* hog1,
ghog::lib::HogDescriptor* hog2,
std::string hog_name1,
std::string hog_name2,
std::vector< std::string > image_list,
cv::Size img_size,
cv::Size window_size,
int num_experiments,
boost::random::mt19937 random_gen)
{
std::cout << "Running difference experiment on descriptors " << hog_name1
<< " and " << hog_name2 << ", with " << image_list.size()
<< " images, using " << num_experiments << " windows of size "
<< window_size << std::endl;
cv::Size descriptor_size(hog1->get_descriptor_size(), 1);
cv::Mat input_img1;
cv::Mat normalized_img1;
cv::Mat grad_mag1;
cv::Mat grad_phase1;
cv::Mat descriptor1;
hog1->alloc_buffer(img_size, CV_32FC3, input_img1);
hog1->alloc_buffer(window_size, CV_32FC3, normalized_img1);
hog1->alloc_buffer(window_size, CV_32FC1, grad_mag1);
hog1->alloc_buffer(window_size, CV_32FC1, grad_phase1);
hog1->alloc_buffer(descriptor_size, CV_32FC1, descriptor1);
cv::Mat input_img2;
cv::Mat normalized_img2;
cv::Mat grad_mag2;
cv::Mat grad_phase2;
cv::Mat descriptor2;
hog2->alloc_buffer(img_size, CV_32FC3, input_img2);
hog2->alloc_buffer(window_size, CV_32FC3, normalized_img2);
hog2->alloc_buffer(window_size, CV_32FC1, grad_mag2);
hog2->alloc_buffer(window_size, CV_32FC1, grad_phase2);
hog2->alloc_buffer(descriptor_size, CV_32FC1, descriptor2);
boost::random::uniform_smallint< int > dist_w(1,
input_img1.cols - window_size.width - 2);
boost::random::uniform_smallint< int > dist_h(1,
input_img1.rows - window_size.height - 2);
std::vector< double > errors_normalization;
std::vector< double > magnitude_similarity;
std::vector< double > phase_similarity;
std::vector< double > descriptor_similarity;
std::vector< double > total_similarity;
std::cout << "Calculating partial difference" << std::endl;
for(int i = 0; i < image_list.size(); ++i)
{
cv::imread(image_list[i], CV_LOAD_IMAGE_COLOR).convertTo(input_img1,
CV_32FC3);
cv::imread(image_list[i], CV_LOAD_IMAGE_COLOR).convertTo(input_img2,
CV_32FC3);
input_img1 /= 256.0;
input_img2 /= 256.0;
for(int j = 0; j < num_experiments; ++j)
{
int pos_x = dist_w(random_gen);
int pos_y = dist_h(random_gen);
input_img1.rowRange(pos_y, pos_y + window_size.height).colRange(
pos_x, pos_x + window_size.width).copyTo(normalized_img1);
input_img2.rowRange(pos_y, pos_y + window_size.height).colRange(
pos_x, pos_x + window_size.width).copyTo(normalized_img2);
hog1->image_normalization_sync(normalized_img1);
hog2->image_normalization_sync(normalized_img2);
errors_normalization.push_back(
compare_matrices(normalized_img1, normalized_img2));
normalized_img1.copyTo(normalized_img2);
hog1->calc_gradient_sync(normalized_img1, grad_mag1, grad_phase1);
hog2->calc_gradient_sync(normalized_img2, grad_mag2, grad_phase2);
magnitude_similarity.push_back(
compare_matrices(grad_mag1, grad_mag2));
phase_similarity.push_back(
compare_matrices(grad_phase1, grad_phase2));
grad_mag1.copyTo(grad_mag2);
grad_phase1.copyTo(grad_phase2);
hog1->create_descriptor_sync(grad_mag1, grad_phase1, descriptor1);
hog2->create_descriptor_sync(grad_mag2, grad_phase2, descriptor2);
descriptor_similarity.push_back(
compare_matrices(descriptor1, descriptor2));
}
}
std::cout << "Error on image normalization:" << std::endl;
report_statistics(errors_normalization, 1, "normalized euclidian distance");
std::cout << "Error on magnitude calculation:" << std::endl;
report_statistics(magnitude_similarity, 1, "normalized euclidian distance");
std::cout << "Error on phase calculation:" << std::endl;
report_statistics(phase_similarity, 1, "normalized euclidian distance");
std::cout << "Error on descriptor calculation:" << std::endl;
report_statistics(descriptor_similarity, 1,
"normalized euclidian distance");
std::cout << "Calculating complete difference" << std::endl;
for(int i = 0; i < image_list.size(); ++i)
{
cv::imread(image_list[i], CV_LOAD_IMAGE_COLOR).convertTo(input_img1,
CV_32FC3);
cv::imread(image_list[i], CV_LOAD_IMAGE_COLOR).convertTo(input_img2,
CV_32FC3);
input_img1 /= 256.0;
input_img2 /= 256.0;
for(int j = 0; j < num_experiments; ++j)
{
int pos_x = dist_w(random_gen);
int pos_y = dist_h(random_gen);
input_img1.rowRange(pos_y, pos_y + window_size.height).colRange(
pos_x, pos_x + window_size.width).copyTo(normalized_img1);
input_img2.rowRange(pos_y, pos_y + window_size.height).colRange(
pos_x, pos_x + window_size.width).copyTo(normalized_img2);
hog1->image_normalization_sync(input_img1);
hog1->calc_gradient_sync(normalized_img1, grad_mag1, grad_phase1);
hog1->create_descriptor_sync(grad_mag1, grad_phase1, descriptor1);
hog2->image_normalization_sync(input_img2);
hog2->calc_gradient_sync(normalized_img2, grad_mag2, grad_phase2);
hog2->create_descriptor_sync(grad_mag2, grad_phase2, descriptor2);
total_similarity.push_back(
compare_matrices(descriptor1, descriptor2));
}
}
std::cout << "Total similarity :" << std::endl;
report_statistics(total_similarity, 1, "normalized euclidian distance");
std::cout << std::endl;
}
int main(int argc, char **argv )
{
int
me, /* holds the index of "this" process */
nprocs, /* holds the number of processes involved */
nprows, npcols, /* mesh sizes */
myrow, mycol, /* this node's mesh coordinates */
n, /* global matrix size */
local_m, /* local row size of A, B, C */
local_n; /* local column size of A, B, C */
double
*global_A, /* array in which to hold matrix A */
*global_B, /* array in which to hold matrix B */
*global_C, /* array in which to hold matrix C */
*local_A, /* array in which to hold local part of matrix A */
*local_B, /* array in which to hold local part of matrix B */
*local_C, /* array in which to hold local part of matrix C */
*local_C_ref, /* array in which to hold local part of matrix C */
local_diff, /* hold difference between sequential and */
diff, /* parallel result */
d_one = 1.0; /* double precision one, to pass by address */
MPI_Comm
comm_row, comm_col; /* communicators for the row and col in which this
node exists */
/* Initialize MPI, passing in the command-line parameters. MPI_Init
strips out the command-line parameters for MPI (e.g., the -np 5
in our example) and then returns argc and argv with without those
parameters. */
MPI_Init( &argc, &argv );
/* Inquire how many processes were started up by mpiexec */
MPI_Comm_size( MPI_COMM_WORLD, &nprocs );
/* Inquire the index (rank) of "this" process within the proceses
started up by mpiexec */
MPI_Comm_rank( MPI_COMM_WORLD, &me );
/* Process 0 accepts input */
if ( me == 0 ){
printf("enter matrix size n:");
scanf( "%d", &n );
printf("enter nprows, npcols:");
scanf( "%d%d", &nprows, &npcols );
}
/* share parameters with all nodes */
MPI_Bcast( &n, 1, MPI_INT, 0, MPI_COMM_WORLD );
MPI_Bcast( &nprows, 1, MPI_INT, 0, MPI_COMM_WORLD );
MPI_Bcast( &npcols, 1, MPI_INT, 0, MPI_COMM_WORLD );
if ( nprows * npcols != nprocs ){
printf( "mesh not of right size\n" );
exit( 0 );
}
/* Figure out what my index is */
mycol = me / nprows;
myrow = me % nprows;
/* create a communicator for the row of which I am part */
MPI_Comm_split( MPI_COMM_WORLD, myrow, mycol, &comm_row );
/* create a communicator for the column of which I am part */
MPI_Comm_split( MPI_COMM_WORLD, mycol, myrow, &comm_col );
/* create buffers into which to hold the global A, B, C (everyone will have a copy) */
global_A = ( double * ) malloc ( sizeof( double ) * n * n );
global_B = ( double * ) malloc ( sizeof( double ) * n * n );
global_C = ( double * ) malloc ( sizeof( double ) * n * n );
/* create random matrices on node zero and share with all nodes */
if ( me == 0 ){
random_matrix( n, n, global_A, n );
random_matrix( n, n, global_B, n );
random_matrix( n, n, global_C, n );
}
MPI_Bcast( global_A, n*n, MPI_DOUBLE, 0, MPI_COMM_WORLD );
MPI_Bcast( global_B, n*n, MPI_DOUBLE, 0, MPI_COMM_WORLD );
MPI_Bcast( global_C, n*n, MPI_DOUBLE, 0, MPI_COMM_WORLD );
/* compute local matrix sizes */
local_m = n / nprows + ( myrow < n % nprows ? 1 : 0 );
local_n = n / npcols + ( mycol < n % npcols ? 1 : 0 );
/* create buffer into which to hold the ocal A, B, C */
local_A = ( double * ) malloc ( sizeof( double ) * local_m * local_n );
local_B = ( double * ) malloc ( sizeof( double ) * local_m * local_n );
local_C = ( double * ) malloc ( sizeof( double ) * local_m * local_n );
/* copy the local parts */
CopyMatrixGlobalToLocal( n, n,
global_A, n,
local_A, local_m,
comm_row, comm_col );
CopyMatrixGlobalToLocal( n, n,
global_B, n,
local_B, local_m,
comm_row, comm_col );
CopyMatrixGlobalToLocal( n, n,
global_C, n,
local_C, local_m,
comm_row, comm_col );
/* Compute parallel matrix-matrix multiply */
ParallelMMult( n, n, n,
local_A, local_m,
local_B, local_m,
local_C, local_m,
comm_row, comm_col );
/* Compute sequential matrix-matrix multiply on all nodes */
dgemm_( "N", "N", &n, &n, &n,
&d_one, global_A, &n, global_B, &n,
&d_one, global_C, &n );
local_C_ref = ( double * ) malloc ( sizeof( double ) * local_m * local_n );
CopyMatrixGlobalToLocal( n, n,
global_C, n,
local_C_ref, local_m,
comm_row, comm_col );
local_diff = compare_matrices( local_m, local_n,
local_C, local_m,
local_C_ref, local_m );
MPI_Allreduce( &local_diff, &diff, 1, MPI_DOUBLE, MPI_SUM, MPI_COMM_WORLD );
if ( me == 0 )
printf("\ndiff = %le\n", diff );
free( global_A );
free( global_B );
free( global_C );
free( local_A );
free( local_B );
free( local_C );
free( local_C_ref);
MPI_Comm_free( &comm_row );
MPI_Comm_free( &comm_col );
/* Cleanup up the MPI environment */
MPI_Finalize();
exit( 0 );
}
