目录：
1、安装Docker-ce
2、安装显卡驱动
3、安装nvidia-docker
一、安装Docker-ce
方法一：
使用官方脚本自动安装
curl -fsSL https://get.docker.com | bash -s docker --mirror Aliyun
方法二：参考以前写过的文章：
https://www.jianshu.com/p/42d1c9fb538c
二、安装显卡驱动：
①安装前进行环境准备：
- 禁用nouveau，创建文件，并添加如下内容
sudo vim /etc/modprobe.d/blacklist-nouveau.conf
添加如下内容：
blacklist nouveau
options nouveau modeset=0
执行如下命令使禁用生效，并重启
sudo update-initramfs -u
sudo reboot
lsmod | grep nouveau ##重启后验证是否生效
②安装显卡
1、先查看显卡型号：
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、到英伟达官网https://www.nvidia.cn/Download/index.aspx?lang=cn
查找对应的显卡型号，并进行下载：
3、获取对应的run，并添加执行权限，运行安装：
ubuntu@ubuntu:/tmp$ chmod +x NVIDIA-Linux-x86_64-418.67.run && sudo sh NVIDIA-Linux-x86_64-418.67.run
ps：在安装的过程中，如果遇到gcc、make等环境不存在，退出并进行环境安装：sudo apt install gcc && sudo apt install make等等
4、安装后，即可查看是否安装成功：
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、安装nvidia-docker2
1、 获取gpg密钥并添加密钥
$ curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add -
2、 定义变量distribution，等于变量$(...)，值为 ubuntu18.04
$ distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
3、获取ubuntu18.04版本的nvidia-docker列表，结果返回给标准输出，tee命令读取标准输入的数据（即上一条curl命令的输出），并将内容输出成文件，并且在屏幕上显示
$ curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | \
sudo tee /etc/apt/sources.list.d/nvidia-docker.list
4、更新源并安装nvidia-docker2
$ sudo apt-get update && sudo apt-get install nvidia-docker2
5、重新加载docker守护进程配置
$ sudo pkill -SIGHUP dockerd
6、验证是否成功安装：
$ 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 |
+-------------------------------+----------------------+----------------------+
参考如下链接：
https://blog.csdn.net/qxqxqzzz/article/details/89706628
https://blog.csdn.net/new_delete_/article/details/81544438
