docker19.03讀取NVIDIA顯示卡
作者： 張首富
時間： 2019-09-06
w x： y18163201
前言
2019年7月的docker 19.03已經正式釋出了，這次釋出對我來說有兩大亮點。
1，就是docker不需要root許可權來啟動喝執行了
2，就是支援GPU的增強功能，我們在docker裡面想讀取nvidia顯示卡再也不需要額外的安裝nvidia-docker了
安裝nvidia驅動
確認已檢測到NVIDIA卡:
$ lspci -vv | grep -i nvidia
00:04.0 3D controller: NVIDIA Corporation GP100GL [Tesla P100 PCIe 16GB] (rev a1)
Subsystem: NVIDIA Corporation GP100GL [Tesla P100 PCIe 16GB]
Kernel modules: nvidiafb
這裡不再詳細介紹：如果不知道請移步ubuntu離線安裝TTS服務
安裝NVIDIA Container Runtime
$ cat nvidia-container-runtime-script.sh
curl -s -L https://nvidia.github.io/nvidia-container-runtime/gpgkey | \
sudo apt-key add -
distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
curl -s -L https://nvidia.github.io/nvidia-container-runtime/$distribution/nvidia-container-runtime.list | \
sudo tee /etc/apt/sources.list.d/nvidia-container-runtime.list
sudo apt-get update
執行指令碼
sh nvidia-container-runtime-script.sh
OK
deb https://nvidia.github.io/libnvidia-container/ubuntu18.04/$(ARCH) /
deb https://nvidia.github.io/nvidia-container-runtime/ubuntu18.04/$(ARCH) /
Hit:1 http://archive.canonical.com/ubuntu bionic InRelease
Get:2 https://nvidia.github.io/libnvidia-container/ubuntu18.04/amd64 InRelease [1139 B]
Get:3 https://nvidia.github.io/nvidia-container-runtime/ubuntu18.04/amd64 InRelease [1136 B]
Hit:4 http://security.ubuntu.com/ubuntu bionic-security InRelease
Get:5 https://nvidia.github.io/libnvidia-container/ubuntu18.04/amd64 Packages [4076 B]
Get:6 https://nvidia.github.io/nvidia-container-runtime/ubuntu18.04/amd64 Packages [3084 B]
Hit:7 http://us-east4-c.gce.clouds.archive.ubuntu.com/ubuntu bionic InRelease
Hit:8 http://us-east4-c.gce.clouds.archive.ubuntu.com/ubuntu bionic-updates InRelease
Hit:9 http://us-east4-c.gce.clouds.archive.ubuntu.com/ubuntu bionic-backports InRelease
Fetched 9435 B in 1s (17.8 kB/s)
Reading package lists... Done
$ apt-get install nvidia-container-runtime
Reading package lists... Done
Building dependency tree
Reading state information... Done
The following packages were automatically installed and are no longer required:
grub-pc-bin libnuma1
Use 'sudo apt autoremove' to remove them.
The following additional packages will be installed:
Get:1 https://nvidia.github.io/libnvidia-container/ubuntu18.04/amd64 libnvidia-container1 1.0.2-1 [59.1 kB]
Get:2 https://nvidia.github.io/libnvidia-container/ubuntu18.04/amd64 libnvidia-container-tools 1.0.2-1 [15.4 kB]
Get:3 https://nvidia.github.io/nvidia-container-runtime/ubuntu18.04/amd64 nvidia-container-runtime-hook 1.4.0-1 [575 kB]
...
Unpacking nvidia-container-runtime (2.0.0+docker18.09.6-3) ...
Setting up libnvidia-container1:amd64 (1.0.2-1) ...
Setting up libnvidia-container-tools (1.0.2-1) ...
Processing triggers for libc-bin (2.27-3ubuntu1) ...
Setting up nvidia-container-runtime-hook (1.4.0-1) ...
Setting up nvidia-container-runtime (2.0.0+docker18.09.6-3) ...
which nvidia-container-runtime-hook
/usr/bin/nvidia-container-runtime-hook
安裝docker-19.03
# step 1: 安裝必要的一些系統工具
yum install -y yum-utils device-mapper-persistent-data lvm2
# Step 2: 新增軟體源資訊
yum-config-manager --add-repo http://mirrors.aliyun.com/docker-ce/linux/centos/docker-ce.repo
# Step 3: 更新並安裝 Docker-CE
yum makecache fast
yum -y install docker-ce-19.03.2
# Step 4: 開啟Docker服務
systemctl start docker && systemctl enable docker
驗證docker版本是否安裝正常
$ docker version
Client: Docker Engine - Community
Version: 19.03.2
API version: 1.40
Go version: go1.12.8
Git commit: 6a30dfc
Built: Thu Aug 29 05:28:55 2019
OS/Arch: linux/amd64
Experimental: false
Server: Docker Engine - Community
Engine:
Version: 19.03.2
API version: 1.40 (minimum version 1.12)
Go version: go1.12.8
Git commit: 6a30dfc
Built: Thu Aug 29 05:27:34 2019
OS/Arch: linux/amd64
Experimental: false
containerd:
Version: 1.2.6
GitCommit: 894b81a4b802e4eb2a91d1ce216b8817763c29fb
runc:
Version: 1.0.0-rc8
GitCommit: 425e105d5a03fabd737a126ad93d62a9eeede87f
docker-init:
Version: 0.18.0
GitCommit: fec3683
驗證下-gpus選項
$ docker run --help | grep -i gpus
--gpus gpu-request GPU devices to add to the container ('all' to pass all GPUs)
執行利用GPU的Ubuntu容器
$ docker run -it --rm --gpus all ubuntu nvidia-smi
Unable to find image 'ubuntu:latest' locally
latest: Pulling from library/ubuntu
f476d66f5408: Pull complete
8882c27f669e: Pull complete
d9af21273955: Pull complete
f5029279ec12: Pull complete
Digest: sha256:d26d529daa4d8567167181d9d569f2a85da3c5ecaf539cace2c6223355d69981
Status: Downloaded newer image for ubuntu:latest
Tue May 7 15:52:15 2019
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 390.116 Driver Version: 390.116 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|===============================+======================+======================|
| 0 Tesla P4 Off | 00000000:00:04.0 Off | 0 |
| N/A 39C P0 22W / 75W | 0MiB / 7611MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
| No running processes found |
+-----------------------------------------------------------------------------+
:~$
故障排除
您是否遇到以下錯誤訊息：
$ docker run -it --rm --gpus all debian
docker: Error response from daemon: linux runtime spec devices: could not select device driver "" with capabilities: [[gpu]].
上述錯誤意味著Nvidia無法正確註冊Docker。它實際上意味著驅動程式未正確安裝在主機上。這也可能意味著安裝了nvidia容器工具而無需重新啟動docker守護程式：您需要重新啟動docker守護程式。
我建議你回去驗證是否安裝了nvidia-container-runtime或者重新啟動Docker守護程式。
列出GPU裝置
$ docker run -it --rm --gpus all ubuntu nvidia-smi -L
GPU 0: Tesla P4 (UUID: GPU-fa974b1d-3c17-ed92-28d0-805c6d089601)
$ docker run -it --rm --gpus all ubuntu nvidia-smi --query-gpu=index,name,uui
d,serial --format=csv
index, name, uuid, serial
0, Tesla P4, GPU-fa974b1d-3c17-ed92-28d0-805c6d089601, 0325017070224