私はCUBLASライブラリを調べようとしているので、そのAPIを使用して行列乗算のコードを作成しました。しかし、私は奇妙な出力を得ています。以下のコードと出力を貼り付けています。私を助けてください。
#include<cublas.h>
// Thread block size
#define BLOCK_SIZE 3
#define WA 3 // Matrix A width
#define HA 3 // Matrix A height
#define WB 3 // Matrix B width
#define HB WA // Matrix B height
#define WC WB // Matrix C width
#define HC HA // Matrix C height
// Allocates a matrix with random float entries.
void randomInit(float* data, int size)
{
for (int i = 0; i < size; ++i)
data[i] = i;
}
/////////////////////////////////////////////////////////
// Program main
/////////////////////////////////////////////////////////
int main(int argc, char** argv)
{
// 1. allocate host memory for matrices A and B
unsigned int size_A = WA * HA;
unsigned int mem_size_A = sizeof(float) * size_A;
float* h_A = (float*) malloc(mem_size_A);
unsigned int size_B = WB * HB;
unsigned int mem_size_B = sizeof(float) * size_B;
float* h_B = (float*) malloc(mem_size_B);
cublasStatus_t status;
// 2. initialize host memory
randomInit(h_A, size_A);
randomInit(h_B, size_B);
// 3. print out A and B
printf("\n\nMatrix A\n");
for(int i = 0; i < size_A; i++)
{
printf("%f ", h_A[i]);
if(((i + 1) % WA) == 0)
printf("\n");
}
printf("\n\nMatrix B\n");
for(int i = 0; i < size_B; i++)
{
printf("%f ", h_B[i]);
if(((i + 1) % WB) == 0)
printf("\n");
}
// 8. allocate device memory
float* d_A;
float* d_B;
cudaMalloc((void**) &d_A, mem_size_A);
cudaMalloc((void**) &d_B, mem_size_B);
// 9. copy host memory to device
status = cublasSetMatrix(BLOCK_SIZE,BLOCK_SIZE,sizeof(float), h_A, BLOCK_SIZE,d_A, BLOCK_SIZE);
if (status != CUBLAS_STATUS_SUCCESS) {
fprintf (stderr, "!!!! CUBLAS initialization error\n");
return EXIT_FAILURE;
}
status = cublasSetMatrix(BLOCK_SIZE,BLOCK_SIZE,sizeof(float), h_B, BLOCK_SIZE,d_B, BLOCK_SIZE);
if (status != CUBLAS_STATUS_SUCCESS) {
fprintf (stderr, "!!!! CUBLAS initialization error\n");
return EXIT_FAILURE;
}
// 4. allocate host memory for the result C
unsigned int size_C = WC * HC;
unsigned int mem_size_C = sizeof(float) * size_C;
float* h_C = (float*) malloc(mem_size_C);
// 10. allocate device memory for the result
float* d_C;
cudaMalloc((void**) &d_C, mem_size_C);
// 5. perform the calculation
cublasSgemm('N','N',BLOCK_SIZE,BLOCK_SIZE,BLOCK_SIZE,1.0f,d_A,BLOCK_SIZE,d_B,BLOCK_SIZE,1.0f,d_C,BLOCK_SIZE);
status = cublasGetError();
if (status) {
fprintf (stderr, "!!!! kernel execution error.\n");
return EXIT_FAILURE;
}
// 11. copy result from device to host
status = cublasGetMatrix(BLOCK_SIZE,BLOCK_SIZE,sizeof(float),d_C, BLOCK_SIZE,h_C,BLOCK_SIZE);
if (status != CUBLAS_STATUS_SUCCESS) {
fprintf (stderr, "!!!! device access error (read C)\n");
return EXIT_FAILURE;
}
// 6. print out the results
printf("\n\nMatrix C (Results)\n");
for(int i = 0; i < size_C; i++)
{
printf("%f ", h_C[i]);
if(((i + 1) % WC) == 0)
printf("\n");
}
printf("\n");
// 7. clean up memory
free(h_A);
free(h_B);
free(h_C);
cudaFree(d_A);
cudaFree(d_B);
cudaFree(d_C);
}
- - - - -出力 - - - - - - -
マトリックスA
0.000000 1.000000 2.000000
3.000000 4.000000 5.000000
6.000000 7.000000 8.000000
マトリックスB
0.000000 1.000000 2.000000
3.000000 4.000000 5.000000
6.000000 7.000000 8.000000
マトリックスC(結果)
-1998397155538108416.000000 -1998397155538108416.000000 -1998397155538108416.000000
-1998397155538108416.000000 -1998397155538108416.000000 -1998397155538108416.000000
-1998397155538108416.000000 -1998397155538108416.000000 -1998397155538108416.000000