前提条件

• windows insider 版本
  Ensure that you install Build version 20145 or higher.
  You can check your build version number by running winver via the Windows Run command.

设置->更新与安全->windows预览体验计划->绑定微软账号，切换至dev或beta(更稳定(据说))->检查更新升级版本(升级之后桌面右下角会有显示版本号)

• wsl2 && Ubuntu
  A Linux distribution with the kernel 4.19.121+ is installed
  You can check the version number by running the following command in PowerShell:wsl cat /proc/version

WSL2设置
WSL2更新wsl --update

Ubuntu安装docker（目前[2021-1-6]貌似不支持docker for desktop）
curl https://get.docker.com | sh

安装驱动和cuda

• nvidia-win10驱动
  离线安装
• CUDA-子系统Toolit
  官方教程推测有网络原因(位置广东)apt update会404，于是同样离线下载或者

wget https://developer.download.nvidia.com/compute/cuda/11.2.0/local_installers/cuda_11.2.0_460.27.04_linux.runsudo
sh cuda_11.2.0_460.27.04_linux.run

接下来无脑accept和回车就OK

安装nvidia-docker

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/$distribution/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list
curl -s -L https://nvidia.github.io/libnvidia-container/experimental/$distribution/libnvidia-container-experimental.list | sudo tee /etc/apt/sources.list.d/libnvidia-container-experimental.list
sudo apt update
sudo apt install -y nvidia-docker2
sudo service docker start
sudo service docker start

测试效果

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

./deviceQuery Starting...

 CUDA Device Query (Runtime API) version (CUDART static linking)

Detected 1 CUDA Capable device(s)

Device 0: "GeForce RTX 3070"
  CUDA Driver Version / Runtime Version          11.3 / 11.1
  ............
deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 11.3, CUDA Runtime Version = 11.1, NumDevs = 1
Result = PASS

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

> Windowed mode
> Simulation data stored in video memory
> Single precision floating point simulation
> 1 Devices used for simulation
MapSMtoCores for SM 8.6 is undefined.  Default to use 64 Cores/SM
GPU Device 0: "GeForce RTX 3070" with compute capability 8.6

> Compute 8.6 CUDA device: [GeForce RTX 3070]
47104 bodies, total time for 10 iterations: 38.259 ms
= 579.943 billion interactions per second
= 11598.865 single-precision GFLOP/s at 20 flops per interaction

另

win terminal 分屏快捷键alt-shift-d
切换焦点alt+arrow
关闭当前分屏ctrl-shift-w

WSL2+CUDA-GTX3070

原文：https://www.cnblogs.com/TAiiiHu/p/14241470.html