参考：

CUDA on WSL User GuideNVIDIA CUDA Installation Guide for LinuxWSL2 CUDA 工具包 11.1 下载

1.操作系统

我采用的版本是windows10 教育版 2004(20262)。Ensure that you install Build version 20145 or higher.

系统必须安装有nvidia的卡，同时安装对应wsl2的驱动。

2.安装WSL2

参考：将WSL2作为生产力工具

3.安装Docker

在wsl2中： curl https://get.docker.com | sh 关于Docker Desktop： 截止到2020.11.27，不支持Docker Desktop 参考：https://docs.nvidia.com/cuda/wsl-user-guide/index.html#known-limitations

4.安装cuda

从https://developer.nvidia.com/cuda-downloads下载相应的安装程序

在WSL2中： 注意：我使用的是Ubuntu18.04的镜像，如果是其他版本，请修改命令中的版本号 cd apt-get install -y gcc g++ make ./cuda_11.1.0_455.23.05_linux.run

cd ./NVIDIA_CUDA-11.1_Samples/1_Utilities/deviceQuery make ./deviceQuery

5.nvidia-docker toolkit

distribution=$(. /etc/os-release;echo $ID$VERSION_ID) curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add - curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list # To get access to experimental features such as CUDA on WSL or the new MIG capability on A100, you may want to add the experimental branch to the repository listing curl -s -L https://nvidia.github.io/libnvidia-container/experimental/$distribution/libnvidia-container-experimental.list | sudo tee /etc/apt/sources.list.d/libnvidia-container-experimental.list apt-get update apt-get install -y nvidia-docker2 service docker stop service docker start

6.验证

docker run --rm --gpus all nvcr.io/nvidia/k8s/cuda-sample:nbody nbody -gpu -benchmark

报错：

docker: Error response from daemon: cgroups: cannot find cgroup mount destination: unknown.

参考：https://blog.csdn.net/ren7wei/article/details/80855779

mkdir /sys/fs/cgroup/systemd mount -t cgroup -o none,name=systemd cgroup /sys/fs/cgroup/systemd

再次运行验证命令，通过

安装脚本可以参考：https://blog.csdn.net/fleaxin/article/details/110310874