目錄：
1、安裝Docker-ce
2寞冯、安裝顯卡驅動
3渴析、安裝nvidia-docker
一、安裝Docker-ce
方法一：
使用官方腳本自動安裝
curl -fsSL https://get.docker.com | bash -s docker --mirror Aliyun
方法二：參考以前寫過的文章：
http://www.reibang.com/p/42d1c9fb538c
二吮龄、安裝顯卡驅動：
①安裝前進行環(huán)境準備：
- 禁用nouveau俭茧，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漓帚，并重啟
sudo update-initramfs -u
sudo reboot
lsmod | grep nouveau ##重啟后驗證是否生效
②安裝顯卡
1母债、先查看顯卡型號：
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、到英偉達官網(wǎng)https://www.nvidia.cn/Download/index.aspx?lang=cn
查找對應的顯卡型號尝抖，并進行下載：
3毡们、獲取對應的run，并添加執(zhí)行權限昧辽，運行安裝：
ubuntu@ubuntu:/tmp$ chmod +x NVIDIA-Linux-x86_64-418.67.run && sudo sh NVIDIA-Linux-x86_64-418.67.run
ps：在安裝的過程中衙熔，如果遇到gcc、make等環(huán)境不存在奴迅，退出并進行環(huán)境安裝：sudo apt install gcc && sudo apt install make等等
4青责、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 |
+-------------------------------+----------------------+----------------------+
三取具、安裝nvidia-docker2
1脖隶、 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暇检，等于變量$(...)产阱，值為 ubuntu18.04
$ distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
3、獲取ubuntu18.04版本的nvidia-docker列表块仆，結果返回給標準輸出构蹬，tee命令讀取標準輸入的數(shù)據(jù)（即上一條curl命令的輸出），并將內(nèi)容輸出成文件悔据，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庄敛、更新源并安裝nvidia-docker2
$ sudo apt-get update && sudo apt-get install nvidia-docker2
5、重新加載docker守護進程配置
$ sudo pkill -SIGHUP dockerd
6科汗、驗證是否成功安裝：
$ 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
