centOS 快速安装和配置 NVIDIA docker Container Toolkit
要在 CentOS 上正确安装和配置 NVIDIA Container Toolkit，您可以按照以下步骤进行操作，如果1和2都已经完成，可以直接进行第3步NVIDIA Container Toolkit安装配置。
1. 安装 NVIDIA GPU 驱动程序：
您可以从 NVIDIA 官方网站下载适用于您的 GPU 型号和 CentOS 版本的驱动程序，并按照安装指南进行安装。确保您的系统已正确安装并配置了 NVIDIA GPU 驱动程序。
也可参考之前写的
在线安装：
https://blog.csdn.net/holyvslin/article/details/132299184
下载安装：
https://blog.csdn.net/holyvslin/article/details/132143104
2. 安装 Docker CE：
2.1 删除旧版本的 Docker（如果存在）：
sudo yum remove -y docker docker-common docker-selinux docker-engine
2.2 安装必要的软件包：
sudo yum install -y yum-utils device-mapper-persistent-data lvm2
2.3 添加 Docker CE 存储库：
sudo yum-config-manager --add-repo https://download.docker.com/linux/centos/docker-ce.repo
2.4 安装 Docker CE：
sudo yum install -y docker-ce
2.5 启动 Docker 服务：
sudo systemctl start docker
2.6 设置 Docker 开机自启：
sudo systemctl enable docker
3. 安装 NVIDIA Container Toolkit：
3.1 添加 NVIDIA Container Toolkit 存储库密钥：
distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.repo | sudo tee /etc/yum.repos.d/nvidia-docker.repo
安装过程：
[xxx]# distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
[xxx]# curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.repo | sudo tee /etc/yum.repos.d/nvidia-docker.repo
[libnvidia-container]
name=libnvidia-container
baseurl=https://nvidia.github.io/libnvidia-container/stable/centos7/$basearch
repo_gpgcheck=1
gpgcheck=0
enabled=1
gpgkey=https://nvidia.github.io/libnvidia-container/gpgkey
sslverify=1
sslcacert=/etc/pki/tls/certs/ca-bundle.crt[libnvidia-container-experimental]
name=libnvidia-container-experimental
baseurl=https://nvidia.github.io/libnvidia-container/experimental/centos7/$basearch
repo_gpgcheck=1
gpgcheck=0
enabled=0
gpgkey=https://nvidia.github.io/libnvidia-container/gpgkey
sslverify=1
sslcacert=/etc/pki/tls/certs/ca-bundle.crt[nvidia-container-runtime]
name=nvidia-container-runtime
baseurl=https://nvidia.github.io/nvidia-container-runtime/stable/centos7/$basearch
repo_gpgcheck=1
gpgcheck=0
enabled=1
gpgkey=https://nvidia.github.io/nvidia-container-runtime/gpgkey
sslverify=1
sslcacert=/etc/pki/tls/certs/ca-bundle.crt[nvidia-container-runtime-experimental]
name=nvidia-container-runtime-experimental
baseurl=https://nvidia.github.io/nvidia-container-runtime/experimental/centos7/$basearch
repo_gpgcheck=1
gpgcheck=0
enabled=0
gpgkey=https://nvidia.github.io/nvidia-container-runtime/gpgkey
sslverify=1
sslcacert=/etc/pki/tls/certs/ca-bundle.crt[nvidia-docker]
name=nvidia-docker
baseurl=https://nvidia.github.io/nvidia-docker/centos7/$basearch
repo_gpgcheck=1
gpgcheck=0
enabled=1
gpgkey=https://nvidia.github.io/nvidia-docker/gpgkey
sslverify=1
sslcacert=/etc/pki/tls/certs/ca-bundle.crt3.2 安装 NVIDIA Container Toolkit：
sudo yum install -y nvidia-docker2
安装过程
[ xxx ]# yum install -y nvidia-docker2
Loaded plugins: fastestmirror, langpacks, nvidia
Loading mirror speeds from cached hostfile
epel/x86_64/metalink | 14 kB 00:00:00base | 3.6 kB 00:00:00
centos-sclo-rh | 3.0 kB 00:00:00
centos-sclo-sclo | 3.0 kB 00:00:00
cuda-rhel7-x86_64 | 3.0 kB 00:00:00
docker-ce-stable | 3.5 kB 00:00:00
epel | 4.7 kB 00:00:00
extras | 2.9 kB 00:00:00
libnvidia-container/x86_64/signature | 833 B 00:00:00
Retrieving key from https://nvidia.github.io/libnvidia-container/gpgkey
Importing GPG key 0xF796ECB0:Userid : "NVIDIA CORPORATION (Open Source Projects) <cudatools@nvidia.com>"Fingerprint: c95b 321b 61e8 8c18 09c4 f759 ddca e044 f796 ecb0From : https://nvidia.github.io/libnvidia-container/gpgkey
libnvidia-container/x86_64/signature | 2.1 kB 00:00:00 !!!
nvidia-container-runtime/x86_64/signature | 833 B 00:00:00
Retrieving key from https://nvidia.github.io/nvidia-container-runtime/gpgkey
Importing GPG key 0xF796ECB0:Userid : "NVIDIA CORPORATION (Open Source Projects) <cudatools@nvidia.com>"Fingerprint: c95b 321b 61e8 8c18 09c4 f759 ddca e044 f796 ecb0From : https://nvidia.github.io/nvidia-container-runtime/gpgkey
nvidia-container-runtime/x86_64/signature | 2.1 kB 00:00:00 !!!
nvidia-docker/x86_64/signature | 833 B 00:00:00
Retrieving key from https://nvidia.github.io/nvidia-docker/gpgkey
Importing GPG key 0xF796ECB0:Userid : "NVIDIA CORPORATION (Open Source Projects) <cudatools@nvidia.com>"Fingerprint: c95b 321b 61e8 8c18 09c4 f759 ddca e044 f796 ecb0From : https://nvidia.github.io/nvidia-docker/gpgkey
nvidia-docker/x86_64/signature | 2.1 kB 00:00:00 !!!
updates | 2.9 kB 00:00:00
(1/6): nvidia-docker/x86_64/primary | 8.0 kB 00:00:01
(2/6): epel/x86_64/updateinfo | 1.0 MB 00:00:01
(3/6): nvidia-container-runtime/x86_64/primary | 11 kB 00:00:01
(4/6): libnvidia-container/x86_64/primary | 35 kB 00:00:01
(5/6): epel/x86_64/primary_db | 7.0 MB 00:00:04
(6/6): updates/7/x86_64/primary_db | 22 MB 00:00:10
libnvidia-container 231/231
nvidia-container-runtime 71/71
nvidia-docker 54/54
Resolving Dependencies
--> Running transaction check
---> Package nvidia-docker2.noarch 0:2.13.0-1 will be installed
--> Processing Dependency: nvidia-container-toolkit >= 1.13.0-1 for package: nvidia-docker2-2.13.0-1.noarch
--> Running transaction check
---> Package nvidia-container-toolkit.x86_64 0:1.13.5-1 will be installed
--> Processing Dependency: nvidia-container-toolkit-base = 1.13.5-1 for package: nvidia-container-toolkit-1.13.5-1.x86_64
--> Processing Dependency: libnvidia-container-tools < 2.0.0 for package: nvidia-container-toolkit-1.13.5-1.x86_64
--> Processing Dependency: libnvidia-container-tools >= 1.13.5-1 for package: nvidia-container-toolkit-1.13.5-1.x86_64
--> Running transaction check
---> Package libnvidia-container-tools.x86_64 0:1.13.5-1 will be installed
--> Processing Dependency: libnvidia-container1(x86-64) >= 1.13.5-1 for package: libnvidia-container-tools-1.13.5-1.x86_64
--> Processing Dependency: libnvidia-container.so.1(NVC_1.0)(64bit) for package: libnvidia-container-tools-1.13.5-1.x86_64
--> Processing Dependency: libnvidia-container.so.1()(64bit) for package: libnvidia-container-tools-1.13.5-1.x86_64
---> Package nvidia-container-toolkit-base.x86_64 0:1.13.5-1 will be installed
--> Running transaction check
---> Package libnvidia-container1.x86_64 0:1.13.5-1 will be installed
--> Finished Dependency ResolutionDependencies Resolved====================================================================================================================================================================Package Arch Version Repository Size
====================================================================================================================================================================
Installing:nvidia-docker2 noarch 2.13.0-1 libnvidia-container 8.7 k
Installing for dependencies:libnvidia-container-tools x86_64 1.13.5-1 libnvidia-container 52 klibnvidia-container1 x86_64 1.13.5-1 libnvidia-container 1.0 Mnvidia-container-toolkit x86_64 1.13.5-1 libnvidia-container 909 knvidia-container-toolkit-base x86_64 1.13.5-1 libnvidia-container 3.1 MTransaction Summary
====================================================================================================================================================================
Install 1 Package (+4 Dependent packages)Total download size: 5.1 M
Installed size: 15 M
Downloading packages:
(1/5): libnvidia-container-tools-1.13.5-1.x86_64.rpm | 52 kB 00:00:01
(2/5): libnvidia-container1-1.13.5-1.x86_64.rpm | 1.0 MB 00:00:01
(3/5): nvidia-container-toolkit-1.13.5-1.x86_64.rpm | 909 kB 00:00:01
(4/5): nvidia-docker2-2.13.0-1.noarch.rpm | 8.7 kB 00:00:00
(5/5): nvidia-container-toolkit-base-1.13.5-1.x86_64.rpm | 3.1 MB 00:00:02
--------------------------------------------------------------------------------------------------------------------------------------------------------------------
Total 1.1 MB/s | 5.1 MB 00:00:04
Running transaction check
Running transaction test
Transaction test succeeded
Running transactionInstalling : libnvidia-container1-1.13.5-1.x86_64 1/5Installing : libnvidia-container-tools-1.13.5-1.x86_64 2/5Installing : nvidia-container-toolkit-base-1.13.5-1.x86_64 3/5Installing : nvidia-container-toolkit-1.13.5-1.x86_64 4/5Installing : nvidia-docker2-2.13.0-1.noarch 5/5
warning: /etc/docker/daemon.json saved as /etc/docker/daemon.json.rpmorigVerifying : nvidia-container-toolkit-base-1.13.5-1.x86_64 1/5Verifying : libnvidia-container-tools-1.13.5-1.x86_64 2/5Verifying : nvidia-docker2-2.13.0-1.noarch 3/5Verifying : libnvidia-container1-1.13.5-1.x86_64 4/5Verifying : nvidia-container-toolkit-1.13.5-1.x86_64 5/5Installed:nvidia-docker2.noarch 0:2.13.0-1Dependency Installed:libnvidia-container-tools.x86_64 0:1.13.5-1 libnvidia-container1.x86_64 0:1.13.5-1 nvidia-container-toolkit.x86_64 0:1.13.5-1nvidia-container-toolkit-base.x86_64 0:1.13.5-1Complete!4. 配置 Docker：
4.1 创建或编辑 Docker 配置文件 /etc/docker/daemon.json
sudo nano /etc/docker/daemon.json
4.2 添加以下内容到文件中：
{"default-runtime": "nvidia","runtimes": {"nvidia": {"path": "nvidia-container-runtime","runtimeArgs": []}}
}
4.3 保存并关闭文件。
5. 重启 Docker 服务：
sudo systemctl restart docker
完成上述步骤后，您的 CentOS 系统将具备 NVIDIA Container Toolkit 的安装和配置。您可以使用带有 GPU 功能的 Docker 容器，并确保容器正确地使用 GPU 资源。
请注意，上述步骤适用于 CentOS 7 及更高版本。如果您使用的是其他版本的 CentOS，请参考 NVIDIA Container Toolkit 官方文档中针对您的 CentOS 版本的安装和配置指南。
6. NVIDIA Container Toolkit 的官方文档链接：
https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/index.html