DeepLearning nvidia-docker2 の変更点

追加された行はこの色です。
削除された行はこの色です。
DeepLearning nvidia-docker2 へ行く。
DeepLearning nvidia-docker2 の差分を削除
 #contents
 *docker-ce のインストール [#h4f1205c]
 docker-ce の配布サイトを apt-get に登録する。docker-ce のインストールは、次項の nvidia-docker2 のインストール時に、その依存アプリとしてインストールする。
  $ sudo apt-get -y update
  $ sudo apt-get -y install curl apt-transport-https ca-certificates curl software-properties-common
  $ curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -
  $ sudo add-apt-repository "deb [arch=amd64] https://download.docker.com/linux/ubuntu $(lsb_release -cs) stable test edge"
 -すでにインストール済みの場合には一旦削除する ($ sudo apt-get remove docker-ce)
 -Ubuntu の apt サイトからインストールしてしまった場合も削除する ($ sudo apt-get remove docker-io)
 *nvidia-docker2 のインストール [#cb14049f]
 https://github.com/NVIDIA/nvidia-docker
  $ 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
  $ sudo apt-get update
  
  $ sudo apt-get install -y nvidia-docker2
  $ sudo pkill -SIGHUP dockerd
 *docker-compose のインストール [#r522b0d6]
 https://github.com/docker/compose/releases
  $ sudo -s
  # curl -L https://github.com/docker/compose/releases/download/1.23.2/docker-compose-`uname -s`-`uname -m` \
    -o /usr/local/bin/docker-compose
  # chmod +x /usr/local/bin/docker-compose
  # exit
  
  $ docker-compose -version
  docker-compose version 1.23.2, build 1110ad01
 *インストールの確認 [#z3d81e69]
  $ sudo docker run --runtime=nvidia --rm nvidia/cuda nvidia-smi
  Sat Jan  5 09:59:00 2019
  +-----------------------------------------------------------------------------+
  | NVIDIA-SMI 410.93       Driver Version: 410.93       CUDA Version: 10.0     |
  |-------------------------------+----------------------+----------------------+
  | 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 2070    Off  | 00000000:01:00.0 Off |                  N/A |
  | 19%   23C    P8    21W / 175W |      8MiB /  7952MiB |      0%      Default |
  +-------------------------------+----------------------+----------------------+
  
  +-----------------------------------------------------------------------------+
  | Processes:                                                       GPU Memory |
  |  GPU       PID   Type   Process name                             Usage      |
  |=============================================================================|
  +-----------------------------------------------------------------------------+
 #br
  $ sudo docker run --runtime=nvidia --rm nvidia/cuda nvcc --version
  nvcc: NVIDIA (R) Cuda compiler driver
  Copyright (c) 2005-2018 NVIDIA Corporation
  Built on Sat_Aug_25_21:08:01_CDT_2018
  Cuda compilation tools, release 10.0, V10.0.130
 ----
 Docker Compose 版
 -docker-compose.yaml
 #code(plain){{{
 version: '2.3'
 services:
   nvidia:
     image: nvidia/cuda
     runtime: nvidia
     command: nvidia-smi
 }}}
 -実行結果
  ~/Docker/sample$ sudo docker-compose up
  Creating network "sample_default" with the default driver
  Creating sample_nvidia_1 ... done
  Attaching to sample_nvidia_1
  nvidia_1  | Sat Jan  5 13:07:58 2019
  nvidia_1  | +-----------------------------------------------------------------------------+
  nvidia_1  | | NVIDIA-SMI 410.93       Driver Version: 410.93       CUDA Version: 10.0     |
  nvidia_1  | |-------------------------------+----------------------+----------------------+
  nvidia_1  | | GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
  nvidia_1  | | Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
  nvidia_1  | |===============================+======================+======================|
  nvidia_1  | |   0  GeForce RTX 2070    Off  | 00000000:01:00.0 Off |                  N/A |
  nvidia_1  | | 19%   22C    P8    19W / 175W |      8MiB /  7952MiB |      0%      Default |
  nvidia_1  | +-------------------------------+----------------------+----------------------+
  nvidia_1  |
  nvidia_1  | +-----------------------------------------------------------------------------+
  nvidia_1  | | Processes:                                                       GPU Memory |
  nvidia_1  | |  GPU       PID   Type   Process name                             Usage      |
  nvidia_1  | |=============================================================================|
  nvidia_1  | +-----------------------------------------------------------------------------+
  sample_nvidia_1 exited with code 0
 *sudo コマンドなしに docker コマンドを実行する [#o63081c5]
  $ sudo groupadd docker
  $ sudo gpasswd -a $USER docker
  $ sudo systemctl restart docker
 設定を反映するには X-Window 上でのログオフ・ログインが必要
 *docker-ce を apt-get upgrade から除外する [#bb7245e8]
 -nvidia-docker2 が、最新版の docker-ce に追随するまでタイムラグが有るため、docker-ce を upgrade しようとして nvidia-docker2 の依存関係から処理エラーになる場合がある
 -docker-ce の更新を抑止する
  $ echo docker-ce hold | sudo dpkg --set-selections
  $ echo docker-ce-cli hold | sudo dpkg --set-selections
  $ sudo dpkg --get-selections | grep docker
  docker-ce					hold
  docker-ce-cli					hold
  nvidia-docker2					install
 これで、nivida-docker2 の更新だけが有効になった
 -(更新抑止の解除方法)
  $ echo [package] install | sudo dpkg --set-selections
 *デフォルト runtime を nvidia-docker にする [#m9a76d45]
 -/etc/docker/daemon.json
 -/etc/docker/daemon.json を変更する
 #code(plain){{{
 {
     "default-runtime": "nvidia",
     "runtimes": {
         "nvidia": {
             "path": "/usr/bin/nvidia-container-runtime",
             "runtimeArgs": []
         }
     }
 }
 }}}
 -docker を再起動する
  $ sudo systemctl restart docker
 -実行確認
  $ docker run --rm nvidia/cuda nvidia-smi
  Wed Feb 20 17:07:03 2019
  +-----------------------------------------------------------------------------+
  | NVIDIA-SMI 410.93       Driver Version: 410.93       CUDA Version: 10.0     |
  |-------------------------------+----------------------+----------------------+
  | 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 2070    Off  | 00000000:01:00.0 Off |                  N/A |
  | 18%   28C    P8    19W / 175W |      8MiB /  7952MiB |      0%      Default |
  +-------------------------------+----------------------+----------------------+
  
  +-----------------------------------------------------------------------------+
  | Processes:                                                       GPU Memory |
  |  GPU       PID   Type   Process name                             Usage      |
  |=============================================================================|
  +-----------------------------------------------------------------------------+
 ----
 [[Deep Learning]]