服务器重装和配置：Ubuntu16.04 + Anaconda3 + GTX1080驱动 + CUDA8 + cuDNN + 常用工具安装

前一篇[基于Ubuntu16.04的GeForce GTX 1080驱动安装，遇到的问题及对应的解决方法]是在机器原有系统上安装GPU驱动，后来决定备份数据后重装系统，让服务器环境更干净清爽。

１．安装操作系统Ubuntu16.04

采用U盘启动安装的方式：

=> 插入系统U盘，开启电源

=> 按Delete键进入BIOS界面，在"Boot"中把"USB KEY"设到最高优先级（把Hard Disk设置到第二优先级，装好系统后拔掉U盘就会直接从硬盘启动），然后在"Save & Exit"中选择保存修改并重启

=> 按F11键进入选择系统菜单界面，这里选"Install Ubuntu"

=> 按照提示安装系统，选择语言，地区，划分分区等，这里是120G的sda，1T的sdb，32G内存，大致划分方法如下：

sda

　　/boot 1G

　　SWAP 32G

　　/ （120-1-32）G

sdb

　　/home 1T

２．更新源

安装好系统后，先更新源，方便后面能比较快地下载各种软件包。

备份/etc/apt/sources.list，然后将内容全部替代为：

# deb cdrom:[Ubuntu 16.04 LTS _Xenial Xerus_ - Release amd64 (20160420.1)]/ xenial main restricted

# See http://help.ubuntu.com/community/UpgradeNotes for how to upgrade to

# newer versions of the distribution.

deb http://mirrors.aliyun.com/ubuntu/ xenial main restricted universe multiverse

deb http://mirrors.aliyun.com/ubuntu/ xenial-security main restricted universe multiverse

deb http://mirrors.aliyun.com/ubuntu/ xenial-updates main restricted universe multiverse

deb http://mirrors.aliyun.com/ubuntu/ xenial-backports main restricted universe multiverse

##测试版源

deb http://mirrors.aliyun.com/ubuntu/ xenial-proposed main restricted universe multiverse

# 源码

deb-src http://mirrors.aliyun.com/ubuntu/ xenial main restricted universe multiverse

deb-src http://mirrors.aliyun.com/ubuntu/ xenial-security main restricted universe multiverse

deb-src http://mirrors.aliyun.com/ubuntu/ xenial-updates main restricted universe multiverse

deb-src http://mirrors.aliyun.com/ubuntu/ xenial-backports main restricted universe multiverse

##测试版源

deb-src http://mirrors.aliyun.com/ubuntu/ xenial-proposed main restricted universe multiverse

# Canonical 合作伙伴和附加

deb http://archive.canonical.com/ubuntu/ xenial partner

deb http://extras.ubuntu.com/ubuntu/ xenial main

然后进行更新：

$ sudo apt-get update

$ sudo apt-get upgrade

３．安装常用的工具

（１）terminator

$ sudo apt-get install terminator

=> 退出之前的终端，再重新ctrl+alt+t就可以进入新装的terminator

=> 在Preference设置终端背景，透明度，字体类型和大小等等

（２）vim

$ sudo apt-get install vim

（３）ssh

$ sudo apt-get install openssh-server

（本地机器ssh免密码登录服务器设置参考：http://www.cnblogs.com/bymo/p/7390619.html）

（４）Sogou Pinyin输入法

下载deb安装包然后 sudo dpkg -i sogoupinyin_2.1.0.0086_amd64.deb

（详细参考：http://blog.csdn.net/leijiezhang/article/details/53707181）

（５）google-chrome

# 将下载源加入到系统的源列表

$ sudo wget http://www.linuxidc.com/files/repo/google-chrome.list -P /etc/apt/sources.list.d/

#导入谷歌软件的公钥，用于下面步骤中对下载软件进行验证。如果顺利的话，命令将返回“OK”

$ wget -q -O - https://dl.google.com/linux/linux_signing_key.pub  | sudo apt-key add -

$ sudo apt-get update

$ sudo apt-get install google-chrome-stable

#启动

$ /usr/bin/google-chrome-stable

安装参考：https://www.cnblogs.com/don9/p/7289830.html

如果启动失败，解决方法参考：http://blog.csdn.net/qq_22551385/article/details/78172178

４．编程/深度学习环境配置

（１） Anaconda3

=> 从清华大学开源软件镜像站下载安装包 Anaconda3-5.0.1-Linux-x86_64.sh

=> 官方安装指南：https://docs.anaconda.com/anaconda/install/linux

$ sudo bash Anaconda3-5.0.-Linux-x86_64.sh

期间会请求授权信息，输入yes；提示安装路径，默认是/home/<user>/anaconda3，本文修改到/opt/anaconda3；提示是否要将Anaconda的安装路径添加到PATH环境变量中，输入yes

（安装和其它测试参考：http://blog.csdn.net/huangjuegeek/article/details/73556763；http://blog.csdn.net/xiaerwoailuo/article/details/70054429）

（２）安装GTX1080驱动（nvidia367.27）

sudo add-apt-repository ppa:graphics-drivers/ppa  #第一次运行如果出现警告，按回车继续

sudo apt-get update

sudo apt-get install nvidia-

sudo apt-get install mesa-common-dev

sudo apt-get install freeglut3-dev

之后重启系统让GTX1080显卡驱动生效，然后用nvidia-smi命令可以查看到显卡设备

（之前这篇[基于Ubuntu16.04的GeForce GTX 1080驱动安装，遇到的问题及对应的解决方法]遇到那么多问题主要是因为之前的系统装过GTX1060的驱动，而本次在全新系统中的安装是比较顺畅的）

（３）下载和安装CUDA

=> GTX1080对应下载CUDA8（注意要登录账号才能下载），选择Ubuntu16.04系统runfile安装方案，1.4G

=> 执行 sudo sh cuda_8.0.27_linux.run 进行安装，安装过程中会有下面几个安装提示，后面的warning可以忽略

-------------------------------------------------------------

Do you accept the previously read EULA?

accept/decline/quit: accept  

Install NVIDIA Accelerated Graphics Driver for Linux-x86_64 367.48?

(y)es/(n)o/(q)uit: n

Install the CUDA 8.0 Toolkit?

(y)es/(n)o/(q)uit: y

Enter Toolkit Location

 [ default is /usr/local/cuda-8.0 ]: 

Do you want to install a symbolic link at /usr/local/cuda?

(y)es/(n)o/(q)uit: y

Install the CUDA 8.0 Samples?

(y)es/(n)o/(q)uit: y

Enter CUDA Samples Location

 [ default is /home/algsuper ]: 

Installing the CUDA Toolkit in /usr/local/cuda-8.0 ...

Missing recommended library: libXi.so

Missing recommended library: libXmu.so

Installing the CUDA Samples in /home/algsuper ...

Copying samples to /home/algsuper/NVIDIA_CUDA-.0_Samples now...

Finished copying samples.

===========

= Summary =

===========

Driver:   Not Selected

Toolkit:  Installed in /usr/local/cuda-8.0

Samples:  Installed in /home/algsuper, but missing recommended libraries

Please make sure that

 -   PATH includes /usr/local/cuda-8.0/bin

 -   LD_LIBRARY_PATH includes /usr/local/cuda-8.0/lib64, or, add /usr/local/cuda-8.0/lib64 to /etc/ld.so.conf and run ldconfig as root

To uninstall the CUDA Toolkit, run the uninstall script in /usr/local/cuda-8.0/bin

Please see CUDA_Installation_Guide_Linux.pdf in /usr/local/cuda-8.0/doc/pdf for detailed information on setting up CUDA.

***WARNING: Incomplete installation! This installation did not install the CUDA Driver. A driver of version at least 361.00 is required for CUDA 8.0 functionality to work.

To install the driver using this installer, run the following command, replacing <CudaInstaller> with the name of this run file:

    sudo <CudaInstaller>.run -silent -driver

Logfile is /tmp/cuda_install_2761.log

安装完毕后，再声明一下环境变量，并将其写入到 ~/.bashrc 的尾部:

export PATH=$PATH:/usr/local/cuda-8.0/bin

export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda-8.0/lib64

保存后，在终端输入 source ~/.bashrc 命令使修改生效．

后面的样例测试参考http://www.cnblogs.com/bymo/p/7987415.html

（４）安装cuDNN

=> 下载页面：https://developer.nvidia.com/rdp/cudnn-download

　　同样需要登录账号才能下载，勾选同意License之后会出现各种版本的下载链接，前面装的是cuda_8.0.27所以这里对应下载cuDNN v6.0 (April 27, 2017), for CUDA 8.0，选择cuDNN v6.0 Library for Linux下载tgz文件）
=> 安装指导页面：http://docs.nvidia.com/deeplearning/sdk/cudnn-install/index.html　

　　解压安装包，将相关链接库复制到cudn安装路径下的对应目录中：

# Unzip the cuDNN package.

$ tar -xzvf cudnn-8.0-linux-x64-v6..tgz

$ cd cuda

# Copy the following files into the CUDA Toolkit directory.

$ sudo cp cuda/include/cudnn.h /usr/local/cuda/include

$ sudo cp cuda/lib64/libcudnn* /usr/local/cuda/lib64

$ sudo chmod a+r /usr/local/cuda/include/cudnn.h /usr/local/cuda/lib64/libcudnn*

（５）virtualenv

sudo apt-get install python-virtualenv

虚拟环境virtualenv的配置和使用参考：http://www.cnblogs.com/bymo/p/7341338.html

后面有空的时候再配置一下Vim，先这样啦，晚安~

==========================================================

补充：

sudo pip install ipython

sudo pip install jupyter