Docker的好处之一,就是在Container里面可以随意瞎搞,不用担心弄崩Host的环境。
而nvidia-docker2
的好处是NVidia帮你配好了Host和Container之间的CUDA相关的链接,让你可以直接在Container里面使用GPU。
安装环境
- OS:Ubuntu 18.04 64 bit
- 显卡:NVidia GTX 1080
- CUDA:10.0
- cnDNN:7.4
任务:安装Docker CE
及nvidia-docker2
,以便后期开展深度学习
配置Docker源
# 更新源 $ sudo apt-get update # 启用HTTPS $ sudo apt-get install apt-transport-https ca-certificates curl gnupg-agent software-properties-common # 添加GPG key $ curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add - # 添加稳定版的源 $ sudo add-apt-repository "deb [arch=amd64] https://download.docker.com/linux/ubuntu $(lsb_release -cs) stable"
安装Docker CE
# 更新源 $ sudo apt-get update # 安装Docker CE $ sudo apt-get install docker-ce
如果这种方式安装失败,也有解决方案。
报错时屏幕上会显示下载失败的deb文件,想办法下载下来,然后挨个手动安装就好。
此时我需要下载的是下面三个文件:
- containerd.io_1.2.2-1_amd64.deb
- docker-ce-cli_18.09.1~3-0~ubuntu-bionic_amd64.deb
- docker-ce_18.09.1~3-0~ubuntu-bionic_amd64.deb
手动依次安装:
$ sudo dpkg -i containerd.io_1.2.2-1_amd64.deb $ sudo dpkg -i docker-ce-cli_18.09.1~3-0~ubuntu-bionic_amd64.deb $ sudo dpkg -i docker-ce_18.09.1~3-0~ubuntu-bionic_amd64.deb
验证Docker CE
如果出现下面的内容,说明安装成功。
$ sudo docker run hello-world Unable to find image 'hello-world:latest' locally latest: Pulling from library/hello-world 1b930d010525: Pull complete Digest: sha256:2557e3c07ed1e38f26e389462d03ed943586f744621577a99efb77324b0fe535 Status: Downloaded newer image for hello-world:latest 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/
配置nvidia-docker2
源
# 添加源 $ curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add - $ distribution=$(. /etc/os-release;echo $ID$VERSION_ID) $ curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list
安装nvidia-docker2
# 安装nvidia-docker2 $ sudo apt-get install -y nvidia-docker2 # 重启Docker daemon $ sudo pkill -SIGHUP dockerd
验证nvidia-docker2
$ sudo nvidia-docker run --rm nvidia/cuda nvidia-smi
能看到显卡信息就说明OK了,当前image是基于Ubuntu 18.04的。