GPU ANT1裸金属服务器的Docker模式环境搭建指导

0. 前置条件

ANT1裸金属服务器的系统是ubuntu18.04或ubuntu20.04.

1. NVIDIA驱动安装

wget https://us.download.nvidia.com/tesla/515.105.01/NVIDIA-Linux-x86_64-515.105.01.run
chmod +x NVIDIA-Linux-x86_64-515.105.01.run
./NVIDIA-Linux-x86_64-515.105.01.run

2. CUDA安装(可选，若在宿主机上不开发，可以忽略)

wget https://developer.download.nvidia.com/compute/cuda/11.7.1/local_installers/cuda_11.7.1_515.65.01_linux.run
chmod +x cuda_11.7.1_515.65.01_linux.run
./cuda_11.7.1_515.65.01_linux.run --toolkit --samples --silent

3. 安装NVIDIA Docker

(1) 安装docker

curl https://get.docker.com | sh && sudo systemctl --now enable docker

(2) 安装nvidia容器插件

distribution=$(. /etc/os-release;echo $ID$VERSION_ID) 
&& curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg
&& curl -s -L https://nvidia.github.io/libnvidia-container/$distribution/libnvidia-container.list |
 sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' | sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list
apt-get update
apt-get install -y nvidia-container-toolkit
nvidia-ctk runtime configure --runtime=docker
systemctl restart docker

4. 方案验证

基于pytorch2.0镜像验证（本例子镜像较大，拉取可能要花点时间）

docker run -ti --runtime=nvidia --gpus all pytorch/pytorch:2.0.0-cuda11.7-cudnn8-devel bash