cudamemcpyasync，memcpy无法在内核中复制，而直接复制有效 [英] cudamemcpyasync, memcpy fails to copy inside kernel while direct copying works

问题描述

我正在尝试从cuda内核中的源float数组（包含1.0f）复制到目标float数组（包含2.0f）。我尝试使用三种不同的方式：

I am trying to copy from a source float array(containing 1.0f) to a destination float array(containing 2.0f) inside a cuda kernel. I try three different ways using:

• cudamemcpysync


• memcpy


• 直接复制（dst [i] = src [i]）

当我在执行内核后读取结果时我发现当直接复制方法有效时，cudamemcpyasync和memcpy都无法复制。

When i read the results after the kernel has been executed I found that both cudamemcpyasync and memcpy has failed to copy while the direct copy method has worked.

为什么cudamemcpyasync和memcpy方法失败了？

Why has the cudamemcpyasync and memcpy method failed?

我正在使用GTX TitanX（SM_52）。

I am using GTX TitanX(SM_52).

使用以下命令编译：nvcc -arch = compute_52 main.cu

compiled using: nvcc -arch=compute_52 main.cu

main.cu：

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


__global__
void cudamemcpy_inside_kernel(float *src, float *dst, int size)
{
  int idx = blockIdx.x*blockDim.x + threadIdx.x;

    if(idx < size){
//        memcpy(dst +idx*sizeof(float), src + idx*sizeof(float), 1); // FAILS TO COPY
//        cudaMemcpyAsync(dst +idx*sizeof(float), src + idx*sizeof(float), 1, cudaMemcpyDeviceToDevice); // FAILS TO COPY
//          dst[idx] = src[idx]; // COPIES SUCCESSFULLY
    }

}

int current = 0;
int UniqueNumber () { return ++current; }

int main(void)
{
  int N = 1000;

  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));


  for (int i = 0; i < N; i++) {
    x[i] = 1.0f;
    y[i] = 2.0f;
  }

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


//  cudamemcpy_inside_kernel<<<(N+255)/256, 256>>>(d_x, d_y, N);
  cudamemcpy_inside_kernel<<<2, 512>>>(d_x, d_y, N);
  cudaDeviceSynchronize();

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

  for (int i = 0; i < N; i++)
     printf(" %f\n", y[i]); // y[i] should have all 1.0f

}

推荐答案

在两个memcpy调用中，您的source，destination和size参数均错误。诸如此类：

You have the source, destination, and size arguments wrong in both memcpy calls. Something like this:

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

template<int action>
__global__
void cudamemcpy_inside_kernel(float *src, float *dst, int size)
{
  int idx = blockIdx.x*blockDim.x + threadIdx.x;
  if(idx < size)
    switch(action) {
      case 1:
        memcpy(dst+idx, src+idx, sizeof(float));
        break;
      case 2:
        cudaMemcpyAsync(dst+idx, src+idx, sizeof(float), cudaMemcpyDeviceToDevice);
        break;
      default:
        dst[idx] = src[idx];
    }
}

int main(void)
{
  int N = 10;

  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));


  for (int i = 0; i < N; i++) {
    x[i] = 1.0f;
    y[i] = 2.0f;
  }
  cudaMemcpy(d_x, x, N*sizeof(float), cudaMemcpyHostToDevice);

  printf("Assignment \n");
  cudaMemcpy(d_y, y, N*sizeof(float), cudaMemcpyHostToDevice);
  cudamemcpy_inside_kernel<0><<<(N+255)/256, 256>>>(d_x, d_y, N);
  cudaMemcpy(y, d_y, N*sizeof(float), cudaMemcpyDeviceToHost);
  for (int i = 0; i < N; i++)
     printf(" %f\n", y[i]);

  printf("\n Memcpy \n");
  cudaMemcpy(d_y, y, N*sizeof(float), cudaMemcpyHostToDevice);
  cudamemcpy_inside_kernel<1><<<(N+255)/256, 256>>>(d_x, d_y, N);
  cudaMemcpy(y, d_y, N*sizeof(float), cudaMemcpyDeviceToHost);
  for (int i = 0; i < N; i++)
     printf(" %f\n", y[i]);

  printf("\n cudaMemcpyAsync \n");
  cudaMemcpy(d_y, y, N*sizeof(float), cudaMemcpyHostToDevice);
  cudamemcpy_inside_kernel<2><<<(N+255)/256, 256>>>(d_x, d_y, N);
  cudaMemcpy(y, d_y, N*sizeof(float), cudaMemcpyDeviceToHost);
  for (int i = 0; i < N; i++)
     printf(" %f\n", y[i]);

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

将按预期工作：

$ nvcc -arch=sm_52 -dc -o memcpy_kernel.o memcpy_kernel.cu
$ nvcc -arch=sm_52 -o memcpy_kernel memcpy_kernel.o
$ ./memcpy_kernel 
Assignment 
 1.000000
 1.000000
 1.000000
 1.000000
 1.000000
 1.000000
 1.000000
 1.000000
 1.000000
 1.000000

 Memcpy 
 1.000000
 1.000000
 1.000000
 1.000000
 1.000000
 1.000000
 1.000000
 1.000000
 1.000000
 1.000000

 cudaMemcpyAsync 
 1.000000
 1.000000
 1.000000
 1.000000
 1.000000
 1.000000
 1.000000
 1.000000
 1.000000
 1.000000

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