Go through the installation process first
1. Set up docker-ce repository:
sudo yum-config-manager --add-repo=https://download.docker.com/linux/centos/docker-ce.repo
2. Install containerd.io package:
sudo yum install -y https://download.docker.com/linux/centos/7/x86_64/stable/Packages/containerd.io-1.4.3-3.1.el7.x86_64.rpm
3. Install the docker-ce software package:
sudo yum install docker-ce -y
Make sure the Docker service is running using the following command:
sudo systemctl --now enable docker
Finally, test your Docker installation by running the hello-world container:
sudo docker run --rm hello-world
It is normal to display as follows
Hello from Docker!
This message shows that your installation appears to be working correctly.
To generate this message, Docker took the following steps:
1. The Docker client contacted the Docker daemon.
2. The Docker daemon pulled the "hello-world" image from the Docker Hub.
(amd64)
3. The Docker daemon created a new container from that image which runs the
executable that produces the output you are currently reading.
4. The Docker daemon streamed that output to the Docker client, which sent it
to your terminal.
To try something more ambitious, you can run an Ubuntu container with:
$ docker run -it ubuntu bash
Share images, automate workflows, and more with a free Docker ID:
https://hub.docker.com/
For more examples and ideas, visit:
https://docs.docker.com/get-started/
4. Set up the nvidia-container-toolkit repository and GPG key:
distribution=$(. /etc/os-release;echo $ID$VERSION_ID) && curl -s -L https://nvidia.github.io/libnvidia-container/$distribution/libnvidia-container.repo | sudo tee /etc/yum.repos.d/nvidia-container-toolkit.repo
Add the experimental branch to the repository list:
yum-config-manager --enable libnvidia-container-experimental
5. Install the nvidia-container-toolkit package after updating the package list:
sudo yum clean expire-cache
sudo yum install -y nvidia-container-toolkit
Configure the Docker daemon to recognize the NVIDIA container runtime:
sudo nvidia-ctk runtime configure --runtime=docker
After setting the default runtime, restart the Docker daemon to complete the installation:
sudo systemctl restart docker
At this point, you can test your working setup by running a basic CUDA container:
sudo docker run --rm --runtime=nvidia --gpus all nvidia/cuda:12.1.1-base-centos7 nvidia-smi
This should produce console output similar to the following:
+---------------------------------------------------------------------------------------+
| NVIDIA-SMI 530.30.02 Driver Version: 530.30.02 CUDA Version: 12.1 |
|-----------------------------------------+----------------------+----------------------+
| 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 GTX 1080 Ti Off| 00000000:01:00.0 Off | N/A |
| 20% 38C P0 57W / 250W| 0MiB / 11264MiB | 0% Default |
| | | N/A |
+-----------------------------------------+----------------------+----------------------+
+---------------------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=======================================================================================|
| No running processes found |
+---------------------------------------------------------------------------------------+
Reason for error
Cannot be installed in a virtual environment
在第4步的储存库地址设置时使用了curl命令
而虚拟环境中的curl和本地源环境所使用的不是一个
所以储存库地址会设置错误
导致找不到nvidia-container-toolkit的软件包