用于普通教程示例的CUDA分段错误

我正在尝试运行这个示例 add.cu (见下文) this official nvidia tutorial 使用 nvcc add.cu -o add_cuda; ./add_cuda 然后得到 Segmentation fault (core dumped) .

我在Ubuntu 18上安装了Nvidia Cuda工具包,使用 sudo apt install nvidia-cuda-toolkit . 我有一个Nvidia GF100GL Quadro 5000,正在使用 NVIDIA driver metapackage from nvidia-driver-390 (proprietary, tested)

我有很少的C++经验,但是纯C++代码从教程开始编译并正确运行。

在评论之后,我添加了一张支票 cudaMallocManaged 然后得到 operation not supported .

#include <iostream>
#include <math.h>
// Kernel function to add the elements of two arrays
__global__
void add(int n, float *x, float *y)
{
  for (int i = 0; i < n; i++)
    y[i] = x[i] + y[i];
}

int main(void)
{
  int N = 1<<20;
  float *x, *y;

  // Allocate Unified Memory – accessible from CPU or GPU
  cudaMallocManaged(&x, N*sizeof(float));
  cudaMallocManaged(&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;
  }

  // Run kernel on 1M elements on the GPU
  add<<<1, 1>>>(N, x, y);

  // Wait for GPU to finish before accessing on host
  cudaDeviceSynchronize();

  // Check for errors (all values should be 3.0f)
  float maxError = 0.0f;
  for (int i = 0; i < N; i++)
    maxError = fmax(maxError, fabs(y[i]-3.0f));
  std::cout << "Max error: " << maxError << std::endl;

  // Free memory
  cudaFree(x);
  cudaFree(y);

  return 0;
}