visual studio 配置cuda环境

一、新建项目

打开VS2017→ 新建项目→Win32控制台应用程序 → “空项目”打钩

二、调整配置管理器平台类型

右键项目→ 属性→ 配置管理器→ 全改为“x64”

 

 

 

三、配置生成属性

右键项目 → 生成依赖项→ 生成自定义→ 勾选“CUDA 11.1XXX”

 

 

四、配置基本库目录

注意：后续步骤中出现的目录地址需取决于你当前的CUDA版本及安装路径

右键项目→属性→ 配置属性→ VC++目录→ 包含目录，添加以下目录：

C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.1\include

C:\ProgramData\NVIDIA Corporation\CUDA Samples\v11.1\common\inc

 

 

 

右键项目→属性→ 配置属性→ VC++目录→ 库目录，添加以下目录：

C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.1\lib\x64

C:\ProgramData\NVIDIA Corporation\CUDA Samples\v11.1\common\lib\x64

 

 

五、配置CUDA静态链接库路径

右键项目→ 属性→ 配置属性→ 链接器→ 常规→ 附加库目录，添加以下目录：

$(CUDA_PATH_V11_1)\lib\$(Platform)

 

 

六、选用CUDA静态链接库

右键项目→ 属性→ 配置属性→ 链接器→ 输入→ 附加依赖项，添加以下库：

cublas.lib;cublas_device.lib;cuda.lib;cudadevrt.lib;cudart.lib;cudart_static.lib;cufft.lib;cufftw.lib;curand.lib;cusolver.lib;cusparse.lib;nppc.lib;nppial.lib;nppicc.lib;nppicom.lib;nppidei.lib;nppif.lib;nppig.lib;nppim.lib;nppist.lib;nppisu.lib;nppitc.lib;npps.lib;nvblas.lib;nvcuvid.lib;nvgraph.lib;nvml.lib;nvrtc.lib;OpenCL.lib;

添加的库目录 “C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.1\lib\x64” 中的库，可参选

 

注意：

kernel32.lib;user32.lib;gdi32.lib;winspool.lib;comdlg32.lib;advapi32.lib;shell32.lib;ole32.lib;oleaut32.lib;uuid.lib;odbc32.lib;odbccp32.lib;%(AdditionalDependencies)
这些库为原有！

cuda11的lib文件有：

cublas.lib
cublasLt.lib
cuda.lib
cudadevrt.lib
cudart.lib
cudart_static.lib
cudnn.lib
cudnn64_8.lib
cudnn_adv_infer.lib
cudnn_adv_infer64_8.lib
cudnn_adv_train.lib
cudnn_adv_train64_8.lib
cudnn_cnn_infer.lib
cudnn_cnn_infer64_8.lib
cudnn_cnn_train.lib
cudnn_cnn_train64_8.lib
cudnn_ops_infer.lib
cudnn_ops_infer64_8.lib
cudnn_ops_train.lib
cudnn_ops_train64_8.lib
cufft.lib
cufftw.lib
curand.lib
cusolver.lib
cusolverMg.lib
cusparse.lib
nppc.lib
nppial.lib
nppicc.lib
nppidei.lib
nppif.lib
nppig.lib
nppim.lib
nppist.lib
nppisu.lib
nppitc.lib
npps.lib
nvblas.lib
nvinfer.lib
nvinfer_plugin.lib
nvjpeg.lib
nvml.lib
nvonnxparser.lib
nvparsers.lib
nvptxcompiler_static.lib
nvrtc.lib
OpenCL.lib

 

 

七、配置源码文件风格

右键源文件→ 添加→ 新建项→ 选择 “CUDA C/C++ File”

右键 “xxx.cu" 源文件→ 属性→ 配置属性→ 常规→ 项类型→ 设置为“CUDA C/C++”

 

 

八、测试程序

#include "cuda_runtime.h"
#include "device_launch_parameters.h"
#include <stdio.h>
 
int main() {
  int deviceCount;
  cudaGetDeviceCount(&deviceCount);
 
  int dev;
  for (dev = 0; dev < deviceCount; dev++)
  {
    int driver_version(0), runtime_version(0);
    cudaDeviceProp deviceProp;
    cudaGetDeviceProperties(&deviceProp, dev);
    if (dev == 0)
      if (deviceProp.minor = 9999 && deviceProp.major == 9999)
        printf("\n");
    printf("\nDevice%d:\"%s\"\n", dev, deviceProp.name);
    cudaDriverGetVersion(&driver_version);
    printf("CUDA驱动版本:                  %d.%d\n", driver_version / 1000, (driver_version % 1000) / 10);
    cudaRuntimeGetVersion(&runtime_version);
    printf("CUDA运行时版本:                 %d.%d\n", runtime_version / 1000, (runtime_version % 1000) / 10);
    printf("设备计算能力:                  %d.%d\n", deviceProp.major, deviceProp.minor);
    printf("Total amount of Global Memory:         %u bytes\n", deviceProp.totalGlobalMem);
    printf("Number of SMs:                 %d\n", deviceProp.multiProcessorCount);
    printf("Total amount of Constant Memory:        %u bytes\n", deviceProp.totalConstMem);
    printf("Total amount of Shared Memory per block:    %u bytes\n", deviceProp.sharedMemPerBlock);
    printf("Total number of registers available per block: %d\n", deviceProp.regsPerBlock);
    printf("Warp size:                   %d\n", deviceProp.warpSize);
    printf("Maximum number of threads per SM:        %d\n", deviceProp.maxThreadsPerMultiProcessor);
    printf("Maximum number of threads per block:      %d\n", deviceProp.maxThreadsPerBlock);
    printf("Maximum size of each dimension of a block:   %d x %d x %d\n", deviceProp.maxThreadsDim[0],
      deviceProp.maxThreadsDim[1],
      deviceProp.maxThreadsDim[2]);
    printf("Maximum size of each dimension of a grid:    %d x %d x %d\n", deviceProp.maxGridSize[0], deviceProp.maxGridSize[1], deviceProp.maxGridSize[2]);
    printf("Maximum memory pitch:              %u bytes\n", deviceProp.memPitch);
    printf("Texture alignmemt:               %u bytes\n", deviceProp.texturePitchAlignment);
    printf("Clock rate:                   %.2f GHz\n", deviceProp.clockRate * 1e-6f);
    printf("Memory Clock rate:               %.0f MHz\n", deviceProp.memoryClockRate * 1e-3f);
    printf("Memory Bus Width:                %d-bit\n", deviceProp.memoryBusWidth);
  }
 
  return 0;
}

 

 

 

输出结果：