VS查看PTX代码

_梦魇花葬 2014-06-13 09:45:15

加精

首先，声明本人用的是Windows 7操作系统，使用Windows 8操作系统的小伙伴们会启动不了Nsight monitor，原因在于Windows 8操作系统的Framework版本过新，解决办法可以是：安装一个版本旧一点的Matlab，安装起初会提示下载安装旧版本的Framework，安装完成Framework就可以停止安装Matlab了，Nsight monitor也可以启动了。
下面回到正题，如何在VS中查看PTX代码呢？在此举个例子，按照这个步骤便可以查看到了。

本人使用的代码是CUDA自带的一个Sample：



#include "cuda_runtime.h"

#include "device_launch_parameters.h"



#include <stdio.h>



cudaError_t addWithCuda(int *c, const int *a, const int *b, unsigned int size);



__global__ void addKernel(int *c, const int *a, const int *b)

{

    int i = threadIdx.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 = 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]);



    // cudaDeviceReset must be called before exiting in order for profiling and

    // tracing tools such as Nsight and Visual Profiler to show complete traces.

    cudaStatus = cudaDeviceReset();

    if (cudaStatus != cudaSuccess) {

        fprintf(stderr, "cudaDeviceReset 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, unsigned int 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;

    }



    // Launch a kernel on the GPU with one thread for each element.

    addKernel<<<1, size>>>(dev_c, dev_a, dev_b);



    // Check for any errors launching the kernel

    cudaStatus = cudaGetLastError();

    if (cudaStatus != cudaSuccess) {

        fprintf(stderr, "addKernel launch failed: %s\n", cudaGetErrorString(cudaStatus));

        goto Error;

    }

    

    // cudaDeviceSynchronize waits for the kernel to finish, and returns

    // any errors encountered during the launch.

    cudaStatus = cudaDeviceSynchronize();

    if (cudaStatus != cudaSuccess) {

        fprintf(stderr, "cudaDeviceSynchronize 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:

    cudaFree(dev_c);

    cudaFree(dev_a);

    cudaFree(dev_b);

    

    return cudaStatus;

}