hongbo-miao/hongbomiao.com

#include <stdio.h>

#include "cuda_runtime.h"
#include "device_launch_parameters.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;
}