Ubuntu16.04下安装nvidia-docker2

若docker-ce、nvidia、CUDA等都安装完成之后，开启docker服务时，能够正常运行，并有预测结果，那表示服务开启没问题；若都安装成功之后，用docker命令开启服务时，一直报错，可能表示你没有安装nvidia-docker2：
报错信息：

tf-serving@tfserving-KVM:~/model/yolo$ docker: Error response from daemon: OCI runtime create failed: unable to retrieve OCI runtime error (open /run/containerd/io.containerd.runtime.v1.linux/moby/f40efd9bd62fc00e53e1d48ea0cbbf8e2c76efdac28238239c6a0c49f52aaebc/log.json: no such file or directory): fork/exec /usr/bin/nvidia-container-runtime: no such file or directory: : unknown.

$ systemctl status docker.service

结果：
docker.service - Docker Application Container Engine
   Loaded: loaded (/lib/systemd/system/docker.service; enabled; vendor preset: enabled)
  Drop-In: /etc/systemd/system/docker.service.d
           └─override.conf
   Active: failed (Result: start-limit-hit) since 四 2019-06-20 11:43:26 CST; 8s ago
     Docs: https://docs.docker.com
  Process: 8024 ExecStart=/usr/bin/dockerd --host=fd:// --add-runtime=nvidia=/usr/bin/nvidia-container-runtime (code=exited, status=1/FAILURE)
 Main PID: 8024 (code=exited, status=1/FAILURE)

6月 20 11:43:26 tfserving-KVM systemd[1]: Failed to start Docker Application Container Engine.
6月 20 11:43:26 tfserving-KVM systemd[1]: docker.service: Unit entered failed state.
6月 20 11:43:26 tfserving-KVM systemd[1]: docker.service: Failed with result 'exit-code'.
6月 20 11:43:26 tfserving-KVM systemd[1]: docker.service: Service hold-off time over, scheduling restart.
6月 20 11:43:26 tfserving-KVM systemd[1]: Stopped Docker Application Container Engine.
6月 20 11:43:26 tfserving-KVM systemd[1]: docker.service: Start request repeated too quickly.
6月 20 11:43:26 tfserving-KVM systemd[1]: Failed to start Docker Application Container Engine.
6月 20 11:43:26 tfserving-KVM systemd[1]: docker.service: Unit entered failed state.
6月 20 11:43:26 tfserving-KVM systemd[1]: docker.service: Failed with result 'start-limit-hit'.

出现类似这样的信息，错误，解决办法，可尝试：

（1）重新安装docker-ce及tensorflow_model_server;

（2）安装nvidia-docker2，步骤如下：

0 If you have nvidia-docker 1.0 installed: we need to remove it and all existing GPU containers

docker volume ls -q -f driver=nvidia-docker | xargs -r -I{} -n1 docker ps -q -a -f volume={} | xargs -r docker rm -f
sudo apt-get purge -y nvidia-docker

 

1. 创建用户组
sudo groupadd docker

 

2.添加用户进入docker组，以便该用户可以使用docker
sudo gpasswd -a ${USER} docker

 

3.重启服务
sudo service docker restart

 

4.修改docker仓库和存放目录
sudo vim /etc/docker/daemon.json

 

5.修改如下，其中https://cwoel6s9.mirror.aliyuncs.com 为从阿里服务器申请的镜像地址，/data/docker     为存放目录

{
    "registry-mirrors": [
        "https://cwoel6s9.mirror.aliyuncs.com"
    ],
    "graph":"/data/docker",
    "storage-driver": "overlay",
    "runtimes": {
        "nvidia": {
            "path": "nvidia-container-runtime",
            "runtimeArgs": []
        }
    }
}  

 

6.重启docker，并使用docker info查看修改信息
systemctl daemon-reload 
systemctl restart docker
docker info

 

7.nvidia-docker 安装,添加源
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

 

8.安装nvidia-docker2软件包并重新加载Docker守护程序配置
sudo apt-get install nvidia-docker2
sudo pkill -SIGHUP dockerd

 

安装完成后，当需要使用gpu时，使用nvidia-docker代替docker！

# 注意：执行这一步，如果没有安装nvidia驱动，会报错：
# docker：ERROR response from Daemon....
# 安装nvida驱动就可以了