Ubuntu22.04安装docker、nvidia-docker、NVIDIA Container Toolkit亲自安装必有效
Ubuntu22.04安装docker、nvidia-docker、NVIDIA Container Toolkit亲自安装必有效
- 安装docker
- 1.2更新ubuntu
- 1.3 添加docker库
- 1.3.1 安装docker的必要依赖
- 1.3.2 添加docker GPG密钥
- 1.3.2 添加docker仓库
- 1.3.3 更新apt
- 1.3.3 安装docker
- 1.3.5 验证docker
- 安装Nvidia-Docker、NVIDIA Container Toolkit
- 2.1 查看docker信息
- 2.2 安装NVIDIA Container Toolkit
- 2.3 验证安装
- 3. docker相关配置
安装docker
系统环境：Ubuntu 22.04
1.2更新ubuntu
$ sudo apt update
$ sudo apt upgrade
$ sudo apt full-upgrade
1.3 添加docker库
1.3.1 安装docker的必要依赖
sudo apt install apt-transport-https ca-certificates curl software-properties-common gnupg lsb-release
1.3.2 添加docker GPG密钥
curl -fsSL http://mirrors.aliyun.com/docker-ce/linux/ubuntu/gpg | sudo apt-key add -
1.3.2 添加docker仓库
sudo add-apt-repository "deb [arch=amd64] http://mirrors.aliyun.com/docker-ce/linux/ubuntu $(lsb_release -cs) stable"
1.3.3 更新apt
sudo apt update
1.3.3 安装docker
sudo apt install docker-ce docker-ce-cli containerd.io docker-compose-plugin
1.3.5 验证docker
#查看docker版本
sudo docker version
安装Nvidia-Docker、NVIDIA Container Toolkit
2.1 查看docker信息
docker info
2.2 安装NVIDIA Container Toolkit
distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
curl -s -L https://nvidia.github.io/libnvidia-container/gpgkey | sudo apt-key add -
curl -s -L https://nvidia.github.io/libnvidia-container/$distribution/libnvidia-container.list | sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list
sudo apt-get update && sudo apt-get install -y nvidia-container-toolkit
2.3 验证安装
systemctl restart docker
docker run --rm -it --gpus all ubuntu:22.04 /bin/bash
nvidia-smi
Tue Aug 1 00:57:29 2023
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 520.61.05 Driver Version: 520.61.05 CUDA Version: 11.8 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 NVIDIA GeForce ... Off | 00000000:01:00.0 On | N/A |
| 0% 51C P8 21W / 160W | 528MiB / 6144MiB | 29% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
+-----------------------------------------------------------------------------+
root@cad0abb4936b:/#
3. docker相关配置
vim /etc/docker/daemon.json
{ "registry-mirrors":[
"https://9cpn8tt6.mirror.aliyuncs.com",
"https://registry.docker-cn.com",
"https://mirror.ccs.tencentyun.com",
"https://docker.1panel.live",
"https://2a6bf1988cb6428c877f723ec7530dbc.mirror.swr.myhuaweicloud.com",
"https://docker.m.daocloud.io",
"https://hub-mirror.c.163.com",
"https://mirror.baidubce.com",
"https://your_preferred_mirror",
"https://dockerhub.icu",
"https://docker.registry.cyou",
"https://docker-cf.registry.cyou",
"https://dockercf.jsdelivr.fyi",
"https://docker.jsdelivr.fyi",
"https://dockertest.jsdelivr.fyi",
"https://mirror.aliyuncs.com",
"https://dockerproxy.com",
"https://mirror.baidubce.com",
"https://docker.m.daocloud.io",
"https://docker.nju.edu.cn",
"https://docker.mirrors.sjtug.sjtu.edu.cn",
"https://docker.mirrors.ustc.edu.cn",
"https://mirror.iscas.ac.cn",
"https://docker.rainbond.cc"
],
"data-root": "/data_1/docker",
"default-runtime": "nvidia",
"runtimes": {
"nvidia": {
"path": "nvidia-container-runtime",
"runtimeArgs": []
}
}
}
其中"data-root": “/data_1/docker”：为docker的镜像存储地址
