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 Anaconda3-5.0.1-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-367 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-8.0_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-v6.0.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~
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补充：
sudo pip install ipython sudo pip install jupyter
