标签:style blog io ar color os sp for on
将数据加载到GPU后,如何在grid下的block进行并行计算(一个grid包含多个block)
/****How do we run code in parallel on the device****/
/****Use block****/
_global_ void add(int *a, int *b, int *c)
{
c[blockIdx.x] = a[blockIdx.x] + b[blockIdx.x];
}
#define N 512
int main()
{
int *a, *b, *c; //host copies of a, b, c
int *d_a, *d_b, *d_c; //device copies of a, b, c
int size = N * sizeof(int);
//Alloc space for device copies of a, b, c
cudaMalloc((void **)&d_a, size);
cudaMalloc((void **)&d_b, size);
cudaMalloc((void **)&d_c, size);
//Alloc space for host copies of a, b, c and setup input values
a = (int *)malloc(size); random_ints(a, N);
b = (int *)malloc(size); random_ints(b, N);
c = (int *)malloc(size);
//Copy the data into device
cudeMemcpy(d_a, a, size, cudaMemcpyHostToDevice);
cudaMemcpy(d_b, b, size, cudaMemcpyHostToDevice);
//Launch add() kernel on GPU with N blocks
add<<<N,1>>>(d_a, d_b, d_c);
//Copy result back to host
cudaMemcpy(c, d_c, size, cudaMemcpyDeviceToHost);
//Cleanup
free(a); free(b); free(c);
cudeFree(d_a); cudaFree(d_b); cudaFree(d_c);
return 0;
}
/**** What‘s the function of random_ints****/
void random_ints(int* a, int N)
{
int i;
for (i = 0; i < N; ++i)
a[i] = rand();
}
标签:style blog io ar color os sp for on
原文地址:http://www.cnblogs.com/lxy2017/p/4130440.html