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Nvidia Docker 安装

安装 Nvidia Driver​

推荐使用 graphics drivers PPA 安装 Nvidia 驱动。

sudo add-apt-repository ppa:graphics-drivers/ppa
sudo apt update

检测推荐的 Nvidia 显卡驱动：

ubuntu-drivers devices

安装 Nvidia 驱动（以下是 RTX2060 上的情况）：

# Ubuntu 16.04 only search 430 for CUDA < 10.2
apt-cache search nvidia
sudo apt install nvidia-430

# Ubuntu 18.04 could search 440 for CUDA <= 10.2
apt-cache search nvidia | grep ^nvidia-driver
sudo apt install nvidia-driver-440

驱动对应的 CUDA 版本，请见 CUDA Compatibility 。

最后， sudo reboot 重启。之后，运行 nvidia-smi 输出 Nvidia 驱动信息:

$ nvidia-smi
Fri Apr 17 07:31:55 2020
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 440.82       Driver Version: 440.82       CUDA Version: 10.2     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|===============================+======================+======================|
|   0  GeForce RTX 2060    Off  | 00000000:01:00.0 Off |                  N/A |
| N/A   40C    P8     5W /  N/A |    263MiB /  5934MiB |      3%      Default |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes:                                                       GPU Memory |
|  GPU       PID   Type   Process name                             Usage      |
|=============================================================================|
|    0      1560      G   /usr/lib/xorg/Xorg                           144MiB |
|    0      1726      G   /usr/bin/gnome-shell                          76MiB |
|    0      2063      G   ...uest-channel-token=10544833948196615517    39MiB |
+-----------------------------------------------------------------------------+

如果安装 CUDA Toolkit ，请先了解 CUDA Compatibility 。安装 CUDA Toolkit 时，注意其携带的驱动版本，最好将其与驱动分别进行安装。而驱动从官方上直接找合适的版本。

或者， NVIDIA Driver Downloads 下载驱动后安装：

# Ctrl + Alt + F2/F3
systemctl isolate multi-user.target

sudo sh NVIDIA-Linux-x86_64-460.67.run
sudo reboot

安装 Docker​

# update the apt package index
sudo apt-get update
# install packages to allow apt to use a repository over HTTPS
sudo apt-get install apt-transport-https ca-certificates curl gnupg lsb-release

# add Docker’s official GPG key
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo gpg --dearmor -o /usr/share/keyrings/docker-archive-keyring.gpg

# set up the stable repository
echo \
  "deb [arch=amd64 signed-by=/usr/share/keyrings/docker-archive-keyring.gpg] https://download.docker.com/linux/ubuntu \
  $(lsb_release -cs) stable" | sudo tee /etc/apt/sources.list.d/docker.list > /dev/null

# update the apt package index
sudo apt-get update
# install the latest version of Docker Engine and containerd
sudo apt-get install docker-ce docker-ce-cli containerd.io

之后，将 Docker 设为 non-root 用户可用：

sudo groupadd docker
sudo usermod -aG docker $USER
newgrp docker

参考​

安装 Nvidia Docker​

# setting up Docker
curl https://get.docker.com | sh \
  && sudo systemctl --now enable docker

# add the package repositories
distribution=$(. /etc/os-release;echo $ID$VERSION_ID) \
   && curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add - \
   && curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list

sudo apt-get update
sudo apt-get install -y nvidia-docker2
sudo systemctl restart docker

使用​

docker run --rm --gpus all nvidia/cuda:11.0-base nvidia-smi
$ docker run --rm --gpus all nvidia/cuda:11.2.2-base-ubuntu18.04 nvidia-smi
Thu Mar 25 06:49:21 2021
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 460.67       Driver Version: 460.67       CUDA Version: 11.2     |
|-------------------------------+----------------------+----------------------+
| 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  GeForce RTX 2060    Off  | 00000000:01:00.0 Off |                  N/A |
| N/A   52C    P0    26W /  N/A |    301MiB /  5934MiB |     30%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
+-----------------------------------------------------------------------------+

配置​

可配置 nvidia 为默认运行时，使用 docker-compose 时需要：

$ sudo mkdir -p /etc/docker
$ sudo tee /etc/docker/daemon.json <<-EOF
{
  "default-runtime": "nvidia",
  "runtimes": {
    "nvidia": {
      "path": "nvidia-container-runtime",
      "runtimeArgs": []
    }
  }
}
EOF

$ sudo systemctl daemon-reload
$ sudo systemctl restart docker

参考​