CUDA错误处理

#include "cuda_runtime.h"
#include "device_launch_parameters.h"
#include <stdio.h>

__global__ void gpuAdd(int *d_a, int *d_b, int *d_c) 
{
	*d_c = *d_a + *d_b;
}

int main()
{
	//Defining host variables
	int h_a, h_b, h_c;
	//Defining Device Pointers
	int *d_a, *d_b, *d_c;
	//Initializing host variables
	h_a = 1;
	h_b = 4;

    cudaError_t cudaStatus;
	  
    // Allocate GPU buffers for three vectors (two input, one output).
    cudaStatus = cudaMalloc((void**)&d_c, sizeof(int));
    if (cudaStatus != cudaSuccess)
	{
        fprintf(stderr, "cudaMalloc failed!");
        goto Error;
    }

	cudaStatus = cudaMalloc((void**)&d_a, sizeof(int));
    if (cudaStatus != cudaSuccess) 
	{
        fprintf(stderr, "cudaMalloc failed!");
        goto Error;
    }

    cudaStatus = cudaMalloc((void**)&d_b, sizeof(int));
    if (cudaStatus != cudaSuccess) 
	{
        fprintf(stderr, "cudaMalloc failed!");
        goto Error;
    }

    // Copy input vectors from host memory to GPU buffers.
    cudaStatus = cudaMemcpy(d_a,&h_a, sizeof(int), cudaMemcpyHostToDevice);
    if (cudaStatus != cudaSuccess) 
	{
        fprintf(stderr, "cudaMemcpy failed!");
        goto Error;
    }

    cudaStatus = cudaMemcpy(d_b, &h_b, sizeof(int), cudaMemcpyHostToDevice);
    if (cudaStatus != cudaSuccess)
	{
        fprintf(stderr, "cudaMemcpy failed!");
        goto Error;
    }

    // Launch a kernel on the GPU with one thread for each element.
    gpuAdd<<<1, 1>>>(d_a, d_b, d_c);

    // Check for any errors launching the kernel
    cudaStatus = cudaGetLastError();
    if (cudaStatus != cudaSuccess)
	{
        fprintf(stderr, "addKernel launch failed: %s\n", cudaGetErrorString(cudaStatus));
        goto Error;
    }
    
    // Copy output vector from GPU buffer to host memory.
    cudaStatus = cudaMemcpy(&h_c, d_c, sizeof(int), cudaMemcpyDeviceToHost);
    if (cudaStatus != cudaSuccess)
	{
        fprintf(stderr, "cudaMemcpy failed!");
        goto Error;
    }
	printf("Passing Parameter by Reference Output: %d + %d = %d\n", h_a, h_b, h_c);

Error:
    cudaFree(d_c);
    cudaFree(d_a);
    cudaFree(d_b);  
    return 0;
}

无论在(上述检测位置的)何处侦测到错误发生，我们都会跳转到(Error标号)这里。在这里，我们释放设备上的显存分配，并退出main函数。这是一种非常高效的编写CUDA代码的方式，我们建议你用这种方式来编写你的CUDA代码。虽然在我们之前的代码例子中说过要避免不必要的复杂性，而在CUDA程序中加上错误处理代码会让程序变得（很)长，但这样做能够指出代码里是什么操作造成了问题。