多GPU设备处理点积示例

 多GPU设备处理点积示例，项目打包下载

/*
* Copyright 1993-2010 NVIDIA Corporation.  All rights reserved.
*
* NVIDIA Corporation and its licensors retain all intellectual property and
* proprietary rights in and to this software and related documentation.
* Any use, reproduction, disclosure, or distribution of this software
* and related documentation without an express license agreement from
* NVIDIA Corporation is strictly prohibited.
*
* Please refer to the applicable NVIDIA end user license agreement (EULA)
* associated with this source code for terms and conditions that govern
* your use of this NVIDIA software.
*
*/


#include "../common/book.h"
#include "cuda.h"
#include "device_launch_parameters.h"
#include "device_functions.h"
#include "cuda_runtime.h"

#define imin(a,b) (a<b?a:b)

#define     N    (33*1024*1024)
const int threadsPerBlock = 256;
const int blocksPerGrid =
imin(32, (N / 2 + threadsPerBlock - 1) / threadsPerBlock);


__global__ void dot(int size, float *a, float *b, float *c) {
    __shared__ float cache[threadsPerBlock];
    int tid = threadIdx.x + blockIdx.x * blockDim.x;
    int cacheIndex = threadIdx.x;

    float   temp = 0;
    while (tid < size) {
        temp += a[tid] * b[tid];
        tid += blockDim.x * gridDim.x;
    }

    // set the cache values
    cache[cacheIndex] = temp;

    // synchronize threads in this block
    __syncthreads();

    //块内归约
    int i = blockDim.x / 2;
    while (i != 0) {
        if (cacheIndex < i)
            cache[cacheIndex] += cache[cacheIndex + i];
        __syncthreads();
        i /= 2;
    }

    if (cacheIndex == 0)
        c[blockIdx.x] = cache[0];
}


struct DataStruct {
    int     deviceID;
    int     size;
    float   *a;
    float   *b;
    float   returnValue;
};

unsigned WINAPI routine(void *pvoidData)
//void* routine(void *pvoidData) 
{
    DataStruct  *data = (DataStruct*)pvoidData;
    HANDLE_ERROR(cudaSetDevice(data->deviceID));

    int     size = data->size;
    float   *a, *b, c, *partial_c;
    float   *dev_a, *dev_b, *dev_partial_c;

    // allocate memory on the CPU side
    a = data->a;
    b = data->b;
    partial_c = (float*)malloc(blocksPerGrid*sizeof(float));

    // allocate the memory on the GPU
    HANDLE_ERROR(cudaMalloc((void**)&dev_a,
        size*sizeof(float)));
    HANDLE_ERROR(cudaMalloc((void**)&dev_b,
        size*sizeof(float)));
    HANDLE_ERROR(cudaMalloc((void**)&dev_partial_c,
        blocksPerGrid*sizeof(float)));

    // copy the arrays 'a' and 'b' to the GPU
    HANDLE_ERROR(cudaMemcpy(dev_a, a, size*sizeof(float),
        cudaMemcpyHostToDevice));
    HANDLE_ERROR(cudaMemcpy(dev_b, b, size*sizeof(float),
        cudaMemcpyHostToDevice));

    dot <<<blocksPerGrid, threadsPerBlock >>>(size, dev_a, dev_b,
        dev_partial_c);
    // copy the array 'c' back from the GPU to the CPU
    HANDLE_ERROR(cudaMemcpy(partial_c, dev_partial_c,
        blocksPerGrid*sizeof(float),
        cudaMemcpyDeviceToHost));

    // finish up on the CPU side
    c = 0;
    for (int i = 0; i<blocksPerGrid; i++) {
        c += partial_c[i];
    }

    HANDLE_ERROR(cudaFree(dev_a));
    HANDLE_ERROR(cudaFree(dev_b));
    HANDLE_ERROR(cudaFree(dev_partial_c));

    // free memory on the CPU side
    free(partial_c);

    data->returnValue = c;
    return 0;
}


int main(void) {
    int deviceCount;
    HANDLE_ERROR(cudaGetDeviceCount(&deviceCount));
    //要求两个设备
    if (deviceCount < 2) {
        printf("We need at least two compute 1.0 or greater "
            "devices, but only found %d
", deviceCount);
        return 0;
    }

    float   *a = (float*)malloc(sizeof(float)* N);
    HANDLE_NULL(a);
    float   *b = (float*)malloc(sizeof(float)* N);
    HANDLE_NULL(b);

    // fill in the host memory with data
    for (int i = 0; i<N; i++) {
        a[i] = i;
        b[i] = i * 2;
    }

    /*
    为多线程做准备
    每个DateStruct都为数据集大小的一半
    */
    DataStruct  data[2];
    data[0].deviceID = 0;
    data[0].size = N / 2;
    data[0].a = a;
    data[0].b = b;

    data[1].deviceID = 1;
    data[1].size = N / 2;
    data[1].a = a + N / 2;
    data[1].b = b + N / 2;

    CUTThread   thread = start_thread(routine, &(data[0]));
    routine(&(data[1]));
    end_thread(thread);


    // free memory on the CPU side
    free(a);
    free(b);

    printf("Value calculated:  %f
",
        data[0].returnValue + data[1].returnValue);

    return 0;
}