cuda编程---cuda硬件信息与错误处置

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一、硬件信息查询：

#include <stdio.h>

int main() {
    int nDevices;

    cudaGetDeviceCount(&nDevices);
    for (int i=0; i < nDevices; i++) {
        cudaDeviceProp prop;
        cudaGetDeviceProperties(&prop, i);
        printf("Device Number: %d\n", i);
        printf("  Device name: %s\n", prop.name);
        printf("  Memory Clock Rate (KHz): %d\n",
                prop.memoryClockRate);
        printf("  Memory Bus Width (bits): %d\n",prop.memoryBusWidth);
        printf("  Peak Memory Bandwidth (GB/s): %f\n\n",
                2.0*prop.memoryClockRate*(prop.memoryBusWidth/8)/1.0e6);
    }
    return 0;
}

二、错误处置：

1、代码段一：

#include <stdio.h>

int main() {
    int nDevices;

    cudaError_t err = cudaGetDeviceCount(&nDevices);
    if (err != cudaSuccess) printf("%s\n", cudaGetErrorString(err));

    for (int i=0; i < nDevices; i++) {
        cudaDeviceProp prop;
        cudaGetDeviceProperties(&prop, i);
        printf("Device Number: %d\n", i);
        printf("  Device name: %s\n", prop.name);
        printf("  Memory Clock Rate (KHz): %d\n",
                prop.memoryClockRate);
        printf("  Memory Bus Width (bits): %d\n",prop.memoryBusWidth);
        printf("  Peak Memory Bandwidth (GB/s): %f\n\n",
                2.0*prop.memoryClockRate*(prop.memoryBusWidth/8)/1.0e6);
    }
    return 0;
}

这段代码在下面处有改变：
cudaError_t err = cudaGetDeviceCount(&nDevices);
if (err != cudaSuccess)
printf("%s\n", cudaGetErrorString(err));

2、代码段二：

#include <iostream>
#include <math.h>
#include <stdio.h>

__global__
void saxpy(int n,float a,float *x,float *y)
{
    int i = blockIdx.x*blockDim.x +threadIdx.x;
    if (i < n) y[i] = a*x[i] + y[i];
}

int main(void){
    int N = 1 << 20; //1M element.

    //float *x=new float[N];
    //float *y=new float[N];

    //Allocate Unified Memory -- accessible from CPU or GPU
    float *x, *y, *d_x, *d_y;

    x = (float*)malloc(N*sizeof(float));
    y = (float*)malloc(N*sizeof(float));

    cudaMalloc(&d_x, N*sizeof(float));
    cudaMalloc(&d_y, N*sizeof(float));

    //initialize x and y arrays on the host.
    for (int i=0;i<N;i++){
        x[i]=1.0f;
        y[i]=2.0f;
    }
    cudaEvent_t start, stop;
    cudaEventCreate(&start);
    cudaEventCreate(&stop);

    cudaMemcpy(d_x, x, N*sizeof(float), cudaMemcpyHostToDevice);
    cudaMemcpy(d_y, y, N*sizeof(float), cudaMemcpyHostToDevice);

    cudaEventRecord(start);
    saxpy<<< (N+255)/256, 256>>>(N, 2.0, d_x, d_y);
    cudaError_t errSync = cudaGetLastError();
    cudaError_t errAsync = cudaDeviceSynchronize();
    if (errSync != cudaSuccess)
        printf("Sync kernel error: %s\n", cudaGetErrorString(errSync));
    if (errAsync != cudaSuccess)
        printf("Async kernel error: %s\n",cudaGetErrorString(errAsync));
    cudaEventRecord(stop);

    cudaMemcpy(y, d_y, N*sizeof(float), cudaMemcpyDeviceToHost);

    cudaEventSynchronize(stop);
    float milliseconds = 0;
    cudaEventElapsedTime(&milliseconds, start, stop);

    // Check for errors (all values should be 3.0f)
    float maxError=0.0f;

    for (int i=0;i<N;i++)
        maxError=max(maxError,fabs(y[i]-4.0f));

    printf("Max error: %f . \n", maxError);
    printf("Effective Bandwidth (GB/s): %f .\n", N*4*3/milliseconds/1e6);

    cudaFree(x);
    cudaFree(y);
    cudaFree(d_x);
    cudaFree(d_y);

    cudaEventDestroy(start);
    cudaEventDestroy(stop);

    return 0;
}