#include "cuda_runtime.h"  
#include "device_launch_parameters.h"  
#include <stdio.h>  
cudaError_t addWithCuda(int *c, const int *a, const int *b, size_t size);  
__global__ void addKernel(int *c, const int *a, const int *b)  
{  
    int i = blockIdx.x;  
    c[i] = a[i] + b[i];  
}  
int main()  
{  
    const int arraySize = 5;  
    const int a[arraySize] = { 1, 2, 3, 4, 5 };  
    const int b[arraySize] = { 10, 20, 30, 40, 50 };  
    int c[arraySize] = { 0 };  
    // Add vectors in parallel.  
    cudaError_t cudaStatus;  
    int num = 0;  
    cudaDeviceProp prop;  
    cudaStatus = cudaGetDeviceCount(&num);  
    for(int i = 0;i<num;i++)  
    {  
        cudaGetDeviceProperties(&prop,i);  
    }  
    cudaStatus = addWithCuda(c, a, b, arraySize);  
    if (cudaStatus != cudaSuccess)   
    {  
        fprintf(stderr, "addWithCuda failed!");  
        return 1;  
    }  
    printf("{1,2,3,4,5} + {10,20,30,40,50} = {%d,%d,%d,%d,%d}\n",c[0],c[1],c[2],c[3],c[4]);  
    // cudaThreadExit must be called before exiting in order for profiling and  
    // tracing tools such as Nsight and Visual Profiler to show complete traces.  
    cudaStatus = cudaThreadExit();  
    if (cudaStatus != cudaSuccess)   
    {  
        fprintf(stderr, "cudaThreadExit failed!");  
        return 1;  
    }  
    return 0;  
}  
// Helper function for using CUDA to add vectors in parallel.  
cudaError_t addWithCuda(int *c, const int *a, const int *b, size_t size)  
{  
    int *dev_a = 0;  
    int *dev_b = 0;  
    int *dev_c = 0;  
    cudaError_t cudaStatus;  
  
    // Choose which GPU to run on, change this on a multi-GPU system.  
    cudaStatus = cudaSetDevice(0);  
    if (cudaStatus != cudaSuccess)   
    {  
        fprintf(stderr, "cudaSetDevice failed!  Do you have a CUDA-capable GPU installed?");  
        goto Error;  
    }  
    // Allocate GPU buffers for three vectors (two input, one output)    .  
    cudaStatus = cudaMalloc((void**)&dev_c, size * sizeof(int));  
    if (cudaStatus != cudaSuccess)   
    {  
        fprintf(stderr, "cudaMalloc failed!");  
        goto Error;  
    }  
    cudaStatus = cudaMalloc((void**)&dev_a, size * sizeof(int));  
    if (cudaStatus != cudaSuccess)   
    {  
        fprintf(stderr, "cudaMalloc failed!");  
        goto Error;  
    }  
    cudaStatus = cudaMalloc((void**)&dev_b, size * sizeof(int));  
    if (cudaStatus != cudaSuccess)   
    {  
        fprintf(stderr, "cudaMalloc failed!");  
        goto Error;  
    }  
    // Copy input vectors from host memory to GPU buffers.  
    cudaStatus = cudaMemcpy(dev_a, a, size * sizeof(int), cudaMemcpyHostToDevice);  
    if (cudaStatus != cudaSuccess)   
    {  
        fprintf(stderr, "cudaMemcpy failed!");  
        goto Error;  
    }  
    cudaStatus = cudaMemcpy(dev_b, b, size * sizeof(int), cudaMemcpyHostToDevice);  
    if (cudaStatus != cudaSuccess)   
    {  
        fprintf(stderr, "cudaMemcpy failed!");  
        goto Error;  
    }  
    cudaStream_t stream[5];  
    for(int i = 0;i<5;i++)  
    {  
        cudaStreamCreate(&stream[i]);   //创建流  
    }  
    // Launch a kernel on the GPU with one thread for each element.  
    for(int i = 0;i<5;i++)  
    {  
        addKernel<<<1,1,0,stream[i]>>>(dev_c+i, dev_a+i, dev_b+i);    //执行流  
    }  
    cudaDeviceSynchronize();  
    // cudaThreadSynchronize waits for the kernel to finish, and returns  
    // any errors encountered during the launch.  
    cudaStatus = cudaThreadSynchronize();  
    if (cudaStatus != cudaSuccess)   
    {  
        fprintf(stderr, "cudaThreadSynchronize returned error code %d after launching addKernel!\n", cudaStatus);  
        goto Error;  
    }  
    // Copy output vector from GPU buffer to host memory.  
    cudaStatus = cudaMemcpy(c, dev_c, size * sizeof(int), cudaMemcpyDeviceToHost);  
    if (cudaStatus != cudaSuccess)   
    {  
        fprintf(stderr, "cudaMemcpy failed!");  
        goto Error;  
    }  
Error:  
    for(int i = 0;i<5;i++)  
    {  
        cudaStreamDestroy(stream[i]);   //销毁流  
    }  
    cudaFree(dev_c);  
    cudaFree(dev_a);  
    cudaFree(dev_b);      
    return cudaStatus;  
}
