[Ubuntu]nvidia-docker安装¶
安装Nvidia容器工具包，允许在容器中实现GPU加速
环境¶
当前主机系统为Ubuntu 18.04，Docker版本为19.03.5，并且主机已安装了Nvidia驱动，参考[Ubuntu 18.04]PPA方式安装Nvidia驱动
安装¶
在主机系统上安装Nvidia容器工具包
# 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-container-toolkit
$ sudo systemctl restart docker
测试¶
Nvidia提供了几个已配置好cuda的镜像，参考nvidia
安装完成后，测试容器中是否可以使用cuda
$ docker run --gpus all nvidia/cuda:10.2-base-ubuntu18.04 nvidia-smi
Unable to find image 'nvidia/cuda:10.2-base-ubuntu18.04' locally
10.2-base-ubuntu18.04: Pulling from nvidia/cuda
Digest: sha256:15fc2f88d247eaa8781f6d3d01613250771ac9394e4543257f2bba5610b96974
Status: Downloaded newer image for nvidia/cuda:10.2-base-ubuntu18.04
Tue Dec 24 12:01:41 2019
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 440.26 Driver Version: 440.26 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 940MX Off | 00000000:02:00.0 Off | N/A |
| N/A 42C P0 N/A / N/A | 643MiB / 2004MiB | 21% Default |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
+-----------------------------------------------------------------------------+