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很多时候我们需要不同的环境，例如torch环境与tensorflow环境，但是他们所依赖的cuda和cudnn版本不一致，这就需要同时安装多个版本，使得他们共存，并工作。
tensorflow 1.11 + cuda9.0
====================安装cuda9.0==============
由于CUDA 9.0仅支持GCC 6.0及以下版本，而Ubuntu 18.04预装GCC版本为7.3，故手动安装gcc-5与g++-5：
sudo apt-get install gcc-5
sudo apt-get install g++-5
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cd /usr/bin
sudo rm gcc
sudo ln -s gcc-5 gcc
sudo rm g++
sudo ln -s g++-5 g++
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gcc -v #查看版本
--------------------------------------------------
Using built-in specs.
COLLECT_GCC=gcc
COLLECT_LTO_WRAPPER=/usr/lib/gcc/x86_64-linux-gnu/5/lto-wrapper
Target: x86_64-linux-gnu
Configured with: ../src/configure -v --with-pkgversion='Ubuntu 5.5.0-12ubuntu1' --with-bugurl=file:///usr/share/doc/gcc-5/README.Bugs --enable-languages=c,ada,c++,go,d,fortran,objc,obj-c++ --prefix=/usr --program-suffix=-5 --enable-shared --enable-linker-build-id --libexecdir=/usr/lib --without-included-gettext --enable-threads=posix --libdir=/usr/lib --enable-nls --with-sysroot=/ --enable-clocale=gnu --enable-libstdcxx-debug --enable-libstdcxx-time=yes --with-default-libstdcxx-abi=new --enable-gnu-unique-object --disable-vtable-verify --enable-libmpx --enable-plugin --enable-default-pie --with-system-zlib --enable-objc-gc --enable-multiarch --disable-werror --with-arch-32=i686 --with-abi=m64 --with-multilib-list=m32,m64,mx32 --enable-multilib --with-tune=generic --enable-checking=release --build=x86_64-linux-gnu --host=x86_64-linux-gnu --target=x86_64-linux-gnu
Thread model: posix
gcc version 5.5.0 20171010 (Ubuntu 5.5.0-12ubuntu1)
===================下载cuda9.0=====================
由于不支持ubuntu18.04则下载ubuntu16.04版本，下载cuda和四个补丁文件。（此处可以下载安装其他版本的cuda实现cuda共存）
下载完成后进行安装，cd到下载文件路径下先安装cuda主文件，再安装4个补丁文件。
sudo sh cuda_9.0.176_384.81_linux.run??? # 开始安装
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Logging to /tmp/cuda_install_20700.log
Using more to view the EULA.
End User License Agreement
--------------------------
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Preface
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1. NVIDIA Software License Agreement
------------------------------------
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Release Date: October 20, 2016
------------------------------
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IMPORTANT NOTICE -- READ BEFORE DOWNLOADING, INSTALLING,
COPYING OR USING THE LICENSED SOFTWARE:
--------------------------------------------------------
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# 按 "q"键退出协议说明
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----------------------------------------------------------------------------------
Do you accept the previously read EULA?
accept/decline/quit: accept??? # 接受协议
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You are attempting to install on an unsupported configuration. Do you wish to continue?
(y)es/(n)o [ default is no ]: y
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Install NVIDIA Accelerated Graphics Driver for Linux-x86_64 384.81?
(y)es/(n)o/(q)uit: n??? # 由于已经安装显卡驱动，选择n，切记切记！
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Install the CUDA 9.0 Toolkit?
(y)es/(n)o/(q)uit: y
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Enter Toolkit Location
?[ default is /usr/local/cuda-9.0 ]:??? # 工具包安装地址，默认回车即可
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Do you want to install a symbolic link at /usr/local/cuda?
(y)es/(n)o/(q)uit: n??? #*因为本机已经安装了cuda10.1因此不要创建软链接，选择n，切记切记！
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Install the CUDA 9.0 Samples?
(y)es/(n)o/(q)uit: y??? # 安装样例
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Enter CUDA Samples Location
?[ default is /home/zzw ]: /data0/zzw/CUDA-9.0??? # 样例安装地址
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Installing the CUDA Toolkit in /usr/local/cuda-9.0 ...
Installing the CUDA Samples in /data0/zzw/CUDA-9.0 ...
Copying samples to /data0/zzw/CUDA-9.0/NVIDIA_CUDA-9.0_Samples now...
Finished copying samples.
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===========
= Summary =
===========
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Driver:?? Not Selected
Toolkit:? Installed in /usr/local/cuda-9.0
Samples:? Installed in /data0/zzw/CUDA-9.0
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Please make sure that
?-?? PATH includes /usr/local/cuda-9.0/bin
?-?? LD_LIBRARY_PATH includes /usr/local/cuda-9.0/lib64, or, add /usr/local/cuda-9.0/lib64 to /etc/ld.so.conf and run ldconfig as root
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To uninstall the CUDA Toolkit, run the uninstall script in /usr/local/cuda-9.0/bin
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Please see CUDA_Installation_Guide_Linux.pdf in /usr/local/cuda-9.0/doc/pdf for detailed information on setting up CUDA.
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***WARNING: Incomplete installation! This installation did not install the CUDA Driver. A driver of version at least 384.00 is required for CUDA 9.0 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
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Logfile is /tmp/cuda_install_20700.log
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# ***安装完成***
配置CUDA-9.0的环境变量(此处将原始cuda10.1版本的PATH注释，添加cuda9.0PATH)：
sudo gedit ~/.bashrc
#在bashrc末尾添加
export PATH="$PATH:/usr/local/cuda-9.0/bin"
export LD_LIBRARY_PATH="$LD_LIBRARY_PATH:/usr/local/cuda-9.0/lib64/"
export LIBRARY_PATH="$LIBRARY_PATH:/usr/local/cuda-9.0/lib64"
#source一下
source ~/.bashrc
安装四个补丁文件
sudo sh cuda_9.0.176.1_linux.run
sudo sh cuda_9.0.176.2_linux.run
sudo sh cuda_9.0.176.3_linux.run
sudo sh cuda_9.0.176.4_linux.run
================下载cudnn7.6.0=======================
tar -zxvf cudnn-9.0-linux-x64-v7.6.0.64.tgz
$ 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
$ sudo chmod a+r /usr/local/cuda/lib64/libcudnn*
多版本cuda和cudnn切换
多版本管理在完成cuda和cudnn安装基础上，只要进行环境变量更改和软链接创建即可。
========================================多版本cuda动态切换（举例）==============================================================
1、更改环境变量，将cuda-10.1变为cuda-9.0
sudo gedit ~/.bashrc
注释掉原来的cuda10.1版本的环境变量，替换为cuda9.0的环境变量
export PATH="$PATH:/usr/local/cuda-9.0/bin"
export LD_LIBRARY_PATH="$LD_LIBRARY_PATH:/usr/local/cuda-9.0/lib64/"
export LIBRARY_PATH="$LIBRARY_PATH:/usr/local/cuda-9.0/lib64"
2、删除之前的软连接，并生成新的软连接
sudo rm -rf /usr/local/cuda #删除之前创建的软链接
sudo ln -s /usr/local/cuda-9.0 /usr/local/cuda #创建新 cuda 的软链接
重启Terminal后可以使用使用如下命令检查：
cat? /usr/local/cuda/version.txt #查看cuda版本
cat /usr/local/cuda/include/cudnn.h | grep CUDNN_MAJOR -A 2? #查看cudnn版本
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