cuda编程入门示例19---矩阵相乘

#include <stdio.h>
#include <stdlib.h>
#include <time.h>
#include <cuda.h>
#include <cuda_runtime.h>

#define BLOCK_SIZE 16
static void HandleError(cudaError_t err, const char *file, int line)
{
if (err != cudaSuccess)
{
printf("%s in %s at line %d\n", cudaGetErrorString(err), file, line);
exit(EXIT_FAILURE);
}
}
#define HANDLE_ERROR( err ) (HandleError( err, __FILE__, __LINE__ ))

#define HANDLE_NULL( a ) {if ((a) == NULL) { \
printf("Host memory failed in %s at line %d\n", \
__FILE__, __LINE__); \
exit(EXIT_FAILURE); }}

static bool InitCUDA()
{
int count;

cudaGetDeviceCount(&count);
if (count == 0)
{
fprintf(stderr, "There is no device.\n");
return false;
}

int i;
cudaDeviceProp prop = {0};

for (i = 0; i < count; i++)
{
if (cudaGetDeviceProperties(&prop, i) == cudaSuccess)
{
if (prop.major >= 1)
{
printf("%s\n", prop.name);
break;
}
}
}

if (i >= count)
{
fprintf(stderr, "There is no device supporting CUDA 1.x.\n");
return false;
}

cudaSetDevice(i);

return true;
}

static void matgen(float* a, int lda, int n)
{
int i, j;

for (i = 0; i < n; i++)
{
for (j = 0; j < n; j++)
{
a[i * lda + j] = (float)rand() / RAND_MAX + (float)rand() / (RAND_MAX * RAND_MAX);
}
}
}

static  void matmult(const float* a, int lda, const float* b, int ldb, float* c, int ldc, int n)
{
int i, j, k;

for (i = 0; i < n; i++)
{
for (j = 0; j < n; j++)
{
double t = 0;
for (k = 0; k < n; k++)
{
t += a[i * lda + k] * b[j + k * ldb];
}

c[i * ldc + j] = t;
}
}
}

static void compare_mat(const float* a, int lda, const float* b, int ldb, int n)
{
float max_err = 0;
float average_err = 0;
float max_absolute_err = 0;
int i, j;

for (i = 0; i < n; i++)
{
for (j = 0; j < n; j++)
{
if (b[i * ldb + j] != 0)
{
float tmp = fabs(a[i * lda + j] - b[i * ldb + j]);
if (max_absolute_err < tmp)
{
max_absolute_err = tmp;
}

float err = fabs(tmp / b[i * ldb + j]);
if (max_err < err)
{
max_err = err;
}

average_err += err;
}
}
}

printf("Max absolute error: %g\nMax error: %g\nAverage error: %g\n", \
max_absolute_err, max_err, average_err / (n * n));
}

__global__ static void matMultCUDA(const float* dev_a, size_t lda, const float* dev_b, size_t ldb, float* dev_c, size_t ldc, int n)
{
const int tid = threadIdx.x;
const int bid = blockIdx.x;
const int id = bid * blockDim.x + tid;
const int row = id / n;
const int col = id % n;

if (row < n && col < n)
{
float t = 0;
for (int i = 0; i < n; i++)
{
t += dev_a[row * lda + i] * dev_b[i * ldb + col];
}

dev_c[row * ldc + col] = t;
}
}

static clock_t matmultCUDA(const float* a, int lda, const float* b, int ldb, float* c, int ldc, int n)
{
const int thread_num = 256;
float *dev_a, *dev_b, *dev_c;
clock_t time;

time = clock();
HANDLE_ERROR(cudaMalloc((void**)&dev_a, sizeof(float)* n * n));
HANDLE_ERROR(cudaMalloc((void**)&dev_b, sizeof(float)* n * n));
HANDLE_ERROR(cudaMalloc((void**)&dev_c, sizeof(float)* n * n));

HANDLE_ERROR(cudaMemcpy2D(dev_a, sizeof(float)* n, a, sizeof(float)* lda, sizeof(float)* n, n, cudaMemcpyHostToDevice));
HANDLE_ERROR(cudaMemcpy2D(dev_b, sizeof(float)* n, b, sizeof(float)* ldb, sizeof(float)* n, n, cudaMemcpyHostToDevice));

int blocks = (n * n + thread_num - 1) / thread_num;

matMultCUDA << <blocks, thread_num >> >(dev_a, n, dev_b, n, dev_c, n, n);

HANDLE_ERROR(cudaMemcpy2D(c, sizeof(float)* ldc, dev_c, sizeof(float)* n, sizeof(float)* n, n, cudaMemcpyDeviceToHost));

cudaFree(dev_a);
cudaFree(dev_b);
cudaFree(dev_c);

return clock() - time;
}

int main(int argc, char *argv[])
{
const int n = 64 * 4 * 2;
float *a, *b, *c, *d;

HANDLE_NULL(a = (float*)malloc(sizeof(float)* n * n));
HANDLE_NULL(b = (float*)malloc(sizeof(float)* n * n));
HANDLE_NULL(c = (float*)malloc(sizeof(float)* n * n));
HANDLE_NULL(d = (float*)malloc(sizeof(float)* n * n));

srand(0);
matgen(a, n, n);
matgen(b, n, n);

clock_t time = matmultCUDA(a, n, b, n, c, n, n);
matmult(a, n, b, n, d, n, n);
compare_mat(c, n, d, n, n);

double sec = (double)time / CLOCKS_PER_SEC;
printf("Time used: %.6fs (%.6lf GFLOPS)\n", sec, 2.0 * n * n * n / (sec * 1E9));

free(a);
free(b);
free(c);
free(d);

//remember to release the device
cudaDeviceReset();

return 0;
}