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Implement copy_3d_array in CUDA

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augustin64 2023-03-28 12:38:06 +02:00
parent 57954a27c0
commit 2d6b4fe011
4 changed files with 88 additions and 13 deletions
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17
src/cnn/cnn.c
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@ -12,6 +12,7 @@
#include "include/make.h"
#include "../include/colors.h"
#include "../include/utils.h"
#include "include/cnn.h"
// Augmente les dimensions de l'image d'entrée
@ -188,7 +189,7 @@ void forward_propagation(Network* network) {
*/
if (k_i->cnn) { // Convolution
make_convolution(k_i->cnn, input, output, output_width);
copy_input_to_input_z(output, output_z, output_depth, output_width, output_width);
copy_3d_array(output, output_z, output_depth, output_width, output_width);
apply_function_to_matrix(activation, output, output_depth, output_width);
}
else if (k_i->nn) { // Full connection
@ -197,7 +198,7 @@ void forward_propagation(Network* network) {
} else { // Matrice -> Vecteur
make_dense_linearized(k_i->nn, input, output[0][0], input_depth, input_width, output_width);
}
copy_input_to_input_z(output, output_z, 1, 1, output_width);
copy_3d_array(output, output_z, 1, 1, output_width);
apply_function_to_vector(activation, output, output_width);
}
else { // Pooling
@ -214,7 +215,7 @@ void forward_propagation(Network* network) {
printf("identifiant: %d, position: %d\n", pooling, i);
}
}
copy_input_to_input_z(output, output_z, output_depth, output_width, output_width);
copy_3d_array(output, output_z, output_depth, output_width, output_width);
}
}
}
@ -281,16 +282,6 @@ void drop_neurones(float*** input, int depth, int dim1, int dim2, int dropout) {
}
}
void copy_input_to_input_z(float*** output, float*** output_z, int output_depth, int output_rows, int output_columns) {
for (int i=0; i<output_depth; i++) {
for (int j=0; j<output_rows; j++) {
for (int k=0; k<output_columns; k++) {
output_z[i][j][k] = output[i][j][k];
}
}
}
}
float compute_mean_squared_error(float* output, float* wanted_output, int len) {
/*
* $E = \frac{ \sum_{i=0}^n (output_i - desired output_i)^2 }{n}$

7
src/include/utils.h
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@ -38,4 +38,11 @@ extern "C"
*/
bool check_cuda_compatibility();
#ifdef __CUDACC__
extern "C"
#endif
/*
* Copier des valeurs d'un tableau de dimension 3 de mémoire partagée
*/
void copy_3d_array(float*** source, float*** dest, int dimension1, int dimension2, int dimension3);
#endif

38
src/utils.c
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@ -11,6 +11,10 @@
#include "include/utils.h"
#define BLOCKSIZE_x 16
#define BLOCKSIZE_y 8
#define BLOCKSIZE_z 8
int i_div_up(int a, int b) { // Partie entière supérieure de a/b
return ((a % b) != 0) ? (a / b + 1) : (a / b);
@ -55,3 +59,37 @@ bool check_cuda_compatibility() {
return false;
#endif
}
#ifdef __CUDACC__
__global__ void copy_3d_array_kernel(float*** source, float*** dest, int dimension1, int dimension2, int dimension3) {
int idx = threadIdx.x + blockDim.x*blockIdx.x; // < dimension1
int idy = threadIdx.y + blockDim.y*blockIdx.y; // < dimension2
int idz = threadIdx.z + blockDim.z*blockIdx.z; // < dimension3
if (idx >= dimension1 || idy >= dimension2 || idz >= dimension3) {
return;
}
dest[idx][idy][idz] = source[idx][idy][idz];
}
void copy_3d_array(float*** source, float*** dest, int dimension1, int dimension2, int dimension3) {
dim3 gridSize(i_div_up(dimension1, BLOCKSIZE_x), i_div_up(dimension2, BLOCKSIZE_y), i_div_up(dimension3, BLOCKSIZE_z));
dim3 blockSize(BLOCKSIZE_x, BLOCKSIZE_y, BLOCKSIZE_z);
copy_3d_array_kernel<<<gridSize, blockSize>>>(source, dest, dimension1, dimension2, dimension3);
gpuErrchk( cudaPeekAtLastError() );
gpuErrchk( cudaDeviceSynchronize() );
}
#else
void copy_3d_array(float*** source, float*** dest, int dimension1, int dimension2, int dimension3) {
for (int i=0; i < dimension1; i++) {
for (int j=0; j < dimension2; j++) {
for (int k=0; k < dimension3; k++) {
dest[i][j][k] = source[i][j][k];
}
}
}
}
#endif

39
src/utils.cu
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@ -11,6 +11,10 @@
#include "include/utils.h"
#define BLOCKSIZE_x 16
#define BLOCKSIZE_y 8
#define BLOCKSIZE_z 8
int i_div_up(int a, int b) { // Partie entière supérieure de a/b
return ((a % b) != 0) ? (a / b + 1) : (a / b);
@ -55,3 +59,38 @@ bool check_cuda_compatibility() {
return false;
#endif
}
#ifdef __CUDACC__
__global__ void copy_3d_array_kernel(float*** source, float*** dest, int dimension1, int dimension2, int dimension3) {
int idx = threadIdx.x + blockDim.x*blockIdx.x; // < dimension1
int idy = threadIdx.y + blockDim.y*blockIdx.y; // < dimension2
int idz = threadIdx.z + blockDim.z*blockIdx.z; // < dimension3
if (idx >= dimension1 || idy >= dimension2 || idz >= dimension3) {
return;
}
dest[idx][idy][idz] = source[idx][idy][idz];
}
extern "C"
void copy_3d_array(float*** source, float*** dest, int dimension1, int dimension2, int dimension3) {
dim3 gridSize(i_div_up(dimension1, BLOCKSIZE_x), i_div_up(dimension2, BLOCKSIZE_y), i_div_up(dimension3, BLOCKSIZE_z));
dim3 blockSize(BLOCKSIZE_x, BLOCKSIZE_y, BLOCKSIZE_z);
copy_3d_array_kernel<<<gridSize, blockSize>>>(source, dest, dimension1, dimension2, dimension3);
gpuErrchk( cudaPeekAtLastError() );
gpuErrchk( cudaDeviceSynchronize() );
}
#else
void copy_3d_array(float*** source, float*** dest, int dimension1, int dimension2, int dimension3) {
for (int i=0; i < dimension1; i++) {
for (int j=0; j < dimension2; j++) {
for (int k=0; k < dimension3; k++) {
dest[i][j][k] = source[i][j][k];
}
}
}
}
#endif