目錄：

1、安裝Docker-ce
2、安裝顯卡驅(qū)動(dòng)
3、安裝nvidia-docker

一、安裝Docker-ce

方法一：
使用官方腳本自動(dòng)安裝

curl -fsSL https://get.docker.com | bash -s docker --mirror Aliyun

方法二：參考以前寫過(guò)的文章：
http://www.itdecent.cn/p/42d1c9fb538c

二、安裝顯卡驅(qū)動(dòng)：

①安裝前進(jìn)行環(huán)境準(zhǔn)備：

1. 禁用nouveau，創(chuàng)建文件，并添加如下內(nèi)容

sudo vim /etc/modprobe.d/blacklist-nouveau.conf

添加如下內(nèi)容：

blacklist nouveau
options nouveau modeset=0

執(zhí)行如下命令使禁用生效，并重啟

sudo update-initramfs -u
sudo reboot
lsmod | grep nouveau ##重啟后驗(yàn)證是否生效

②安裝顯卡

1、先查看顯卡型號(hào)：

ubuntu:~$ lspci | grep -i 3d
06:00.0 3D controller: NVIDIA Corporation GK210GL [Tesla K80] (rev a1)
07:00.0 3D controller: NVIDIA Corporation GK210GL [Tesla K80] (rev a1)
84:00.0 3D controller: NVIDIA Corporation GK210GL [Tesla K80] (rev a1)
85:00.0 3D controller: NVIDIA Corporation GK210GL [Tesla K80] (rev a1)

2、到英偉達(dá)官網(wǎng)https://www.nvidia.cn/Download/index.aspx?lang=cn
查找對(duì)應(yīng)的顯卡型號(hào)，并進(jìn)行下載：
3、獲取對(duì)應(yīng)的run，并添加執(zhí)行權(quán)限，運(yùn)行安裝：

ubuntu@ubuntu:/tmp$ chmod +x NVIDIA-Linux-x86_64-418.67.run && sudo sh NVIDIA-Linux-x86_64-418.67.run

ps：在安裝的過(guò)程中，如果遇到gcc、make等環(huán)境不存在，退出并進(jìn)行環(huán)境安裝：sudo apt install gcc && sudo apt install make等等

4、安裝后，即可查看是否安裝成功：

ubuntu@ubuntu:/home$ nvidia-smi 
Mon Aug  5 09:20:30 2019       
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 418.67       Driver Version: 418.67       CUDA Version: 10.1     |
|-------------------------------+----------------------+----------------------+
| 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 K80           Off  | 00000000:06:00.0 Off |                    0 |
| N/A   41C    P0    60W / 149W |      0MiB / 11441MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+
|   1  Tesla K80           Off  | 00000000:07:00.0 Off |                    0 |
| N/A   38C    P0    82W / 149W |      0MiB / 11441MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+
|   2  Tesla K80           Off  | 00000000:84:00.0 Off |                    0 |
| N/A   42C    P0    64W / 149W |      0MiB / 11441MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+
|   3  Tesla K80           Off  | 00000000:85:00.0 Off |                    0 |
| N/A   37C    P0    84W / 149W |      0MiB / 11441MiB |     97%      Default |
+-------------------------------+----------------------+----------------------+

三、安裝nvidia-docker2

1、 獲取gpg密鑰并添加密鑰

$ curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add -

2、 定義變量distribution，等于變量$(...)，值為 ubuntu18.04

$ distribution=$(. /etc/os-release;echo $ID$VERSION_ID)

3、獲取ubuntu18.04版本的nvidia-docker列表，結(jié)果返回給標(biāo)準(zhǔn)輸出，tee命令讀取標(biāo)準(zhǔn)輸入的數(shù)據(jù)（即上一條curl命令的輸出），并將內(nèi)容輸出成文件，并且在屏幕上顯示

$ curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | \
sudo tee /etc/apt/sources.list.d/nvidia-docker.list

4、更新源并安裝nvidia-docker2

$ sudo apt-get update &&  sudo apt-get install nvidia-docker2

5、重新加載docker守護(hù)進(jìn)程配置
$ sudo pkill -SIGHUP dockerd
6、驗(yàn)證是否成功安裝：

$ sudo docker run --runtime=nvidia --rm nvidia/cuda nvidia-smi
ubuntu@ubuntu:/home$ sudo docker run --runtime=nvidia --rm nvidia/cuda nvidia-smi
[sudo] password for ubuntu: 
Mon Aug  5 09:26:32 2019       
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 418.67       Driver Version: 418.67       CUDA Version: 10.1     |
|-------------------------------+----------------------+----------------------+
| 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 K80           Off  | 00000000:06:00.0 Off |                    0 |
| N/A   42C    P0    60W / 149W |      0MiB / 11441MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+
|   1  Tesla K80           Off  | 00000000:07:00.0 Off |                    0 |
| N/A   39C    P0    83W / 149W |      0MiB / 11441MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+
|   2  Tesla K80           Off  | 00000000:84:00.0 Off |                    0 |
| N/A   43C    P0    64W / 149W |      0MiB / 11441MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+
|   3  Tesla K80           Off  | 00000000:85:00.0 Off |                    0 |
| N/A   37C    P0    84W / 149W |      0MiB / 11441MiB |     99%      Default |
+-------------------------------+----------------------+----------------------+

參考如下鏈接：
https://blog.csdn.net/qxqxqzzz/article/details/89706628
https://blog.csdn.net/new_delete_/article/details/81544438