这个程序是怎么启动多卡的

加速计算 CUDA
1

问题是：下面的程序如何启动多卡的，我运行的结果是nuprintf(“CPU thread %d (of %d) uses CUDA device %d\n”, cpu_thread_id, num_cpu_threads, gpu_id);CPU thread 0(of 1)uses CUDA device 0 .
而我实际上我有两块卡啊

#include <omp.h>
#include <stdio.h> // stdio functions are used since C++ streams aren’t necessarily thread safe
#include <cutil_inline.h>

using namespace std;

// a simple kernel that simply increments each array element by b
global void kernelAddConstant(int *g_a, const int b)
{
int idx = blockIdx.x * blockDim.x + threadIdx.x;
g_a[idx] += b;
}

// a predicate that checks whether each array elemen is set to its index plus b
int correctResult(int *data, const int n, const int b)
{
for(int i = 0; i < n; i++)
if(data[i] != i + b)
return 0;
return 1;
}

int main(int argc, char *argv)
{
int num_gpus = 0; // number of CUDA GPUs

/////////////////////////////////////////////////////////////////
// determine the number of CUDA capable GPUs
//

cudaGetDeviceCount(&num_gpus);
if(num_gpus < 1)
{
printf(“no CUDA capable devices were detected\n”);
return 1;
}

/////////////////////////////////////////////////////////////////
// display CPU and GPU configuration
//

printf(“number of host CPUs:\t%d\n”, omp_get_num_procs());
printf(“number of CUDA devices:\t%d\n”, num_gpus);
for(int i = 0; i < num_gpus; i++)
{
cudaDeviceProp dprop;
cudaGetDeviceProperties(&dprop, i);
printf(" %d: %s\n", i, dprop.name);
}
printf(“---------------------------\n”);

/////////////////////////////////////////////////////////////////
// initialize data
//
unsigned int n = num_gpus * 8192;
unsigned int nbytes = n * sizeof(int);
int a = 0; // pointer to data on the CPU
int b = 3; // value by which the array is incremented
a = (int)malloc(nbytes);
if(0 == a)
{
printf(“couldn’t allocate CPU memory\n”);
return 1;
}
for(unsigned int i = 0; i < n; i++)
a[i] = i;

////////////////////////////////////////////////////////////////
// run as many CPU threads as there are CUDA devices
// each CPU thread controls a different device, processing its
// portion of the data. It’s possible to use more CPU threads
// than there are CUDA devices, in which case several CPU
// threads will be allocating resources and launching kernels
// on the same device. For example, try omp_set_num_threads(2num_gpus);
// Recall that all variables declared inside an “omp parallel” scope are
// local to each CPU thread
//
omp_set_num_threads(num_gpus); // create as many CPU threads as there are CUDA devices
//omp_set_num_threads(2num_gpus);// create twice as many CPU threads as there are CUDA devices
#pragma omp parallel
{
unsigned int cpu_thread_id = omp_get_thread_num();
unsigned int num_cpu_threads = omp_get_num_threads();

	// set and check the CUDA device for this CPU thread
	int gpu_id = -1;
	CUDA_SAFE_CALL(cudaSetDevice(cpu_thread_id % num_gpus));	// "% num_gpus" allows more CPU threads than GPU devices
	CUDA_SAFE_CALL(cudaGetDevice(&gpu_id));
	printf("CPU thread %d (of %d) uses CUDA device %d\n", cpu_thread_id, num_cpu_threads, gpu_id);

	int *d_a = 0;	// pointer to memory on the device associated with this CPU thread
	int *sub_a = a + cpu_thread_id * n / num_cpu_threads;	// pointer to this CPU thread's portion of data
	unsigned int nbytes_per_kernel = nbytes / num_cpu_threads;
	dim3 gpu_threads(128);	// 128 threads per block
	dim3 gpu_blocks(n / (gpu_threads.x * num_cpu_threads));

CUDA_SAFE_CALL(cudaMalloc((void**)&d_a, nbytes_per_kernel));
CUDA_SAFE_CALL(cudaMemset(d_a, 0, nbytes_per_kernel));
CUDA_SAFE_CALL(cudaMemcpy(d_a, sub_a, nbytes_per_kernel, cudaMemcpyHostToDevice));
kernelAddConstant<<<gpu_blocks, gpu_threads>>>(d_a, b);

CUDA_SAFE_CALL(cudaMemcpy(sub_a, d_a, nbytes_per_kernel, cudaMemcpyDeviceToHost));
CUDA_SAFE_CALL(cudaFree(d_a));

}
printf(“---------------------------\n”);

if(cudaSuccess != cudaGetLastError())
	printf("%s\n", cudaGetErrorString(cudaGetLastError()));


////////////////////////////////////////////////////////////////
// check the result
//

if(correctResult(a, n, b))
printf(“PASSED\n”);
else
printf(“FAILED\n”);

free(a); // free CPU memory

cudaThreadExit();

cutilExit(argc, argv);

return 0;
}

[ 本帖最后由 keyule 于 2010-4-15 09:43 编辑 ]