Ubunto16.04+1070ti 安装Cuda8.0 和 tensorflow文档

  最近老板突然要说做项目，双手一挥就申请了张显卡，因此记录下这篇文档；

系统 / Ubunto16.04
显卡 / Nvidia GTX 1070ti

• NVIDIA显卡驱动

  • 安装准备

    • 屏蔽nouveau开源驱动

    touch /etc/modprobe.d/blacklist-nouveau.conf 
    echo "blacklist nouveau" >>blacklist-nouveau.conf 
    echo "options nouveau modeset = 0" >>blacklist-nouveau.conf
    

    • 更新前可以去blacklist-nouveau.conf查看命令是否添加成功，之后执行更新：

    sudo update-initramfs -u
    

    • 去Nvidia官网下载和显卡对应的驱动，我的是GTX1070ti，对应的最新的驱动是NVIDIA-Linux-x86_64-390.48.run
      

  • 安装NVIDIA显卡驱动：

    • 进入字符界面Ctrl+alt+F1之后，输入同户名和密码，登陆成功后执行：

    sudo service lightdm stop
    

    • 安装:其中–no-opengl-files很重要，不然安装后重启会出现循环登录的问题。

     sudo chmod 777 NVIDIA-Linux-x86_64-390.48.run   //执行权限
     sudo sh NVIDIA-Linux-x86_64-390.48.run –no-opengl-files   //执行
     sudo service lightdm start
     sudo reboot
    

    • 重启如果能够顺利登录，恭喜，之后测试是否安装成功：

    nvidia-smi
    

    打印出gpu相关信息表示安装成功。
    

  • 安装CUDA-8.0

    • 安装依赖：
      • 设置源：

      # deb cdrom:[Ubuntu 16.04 LTS _Xenial Xerus_ - Release amd64 (20160420.1)]/ xenial main restricted
      deb-src http://archive.ubuntu.com/ubuntu xenial main restricted #Added by software-properties
      deb http://mirrors.aliyun.com/ubuntu/ xenial main restricted
      deb-src http://mirrors.aliyun.com/ubuntu/ xenial main restricted multiverse universe #Added by software-properties
      deb http://mirrors.aliyun.com/ubuntu/ xenial-updates main restricted
      deb-src http://mirrors.aliyun.com/ubuntu/ xenial-updates main restricted multiverse universe #Added by software-properties
      deb http://mirrors.aliyun.com/ubuntu/ xenial universe
      deb http://mirrors.aliyun.com/ubuntu/ xenial-updates universe
      deb http://mirrors.aliyun.com/ubuntu/ xenial multiverse
      deb http://mirrors.aliyun.com/ubuntu/ xenial-updates multiverse
      deb http://mirrors.aliyun.com/ubuntu/ xenial-backports main restricted universe multiverse
      deb-src http://mirrors.aliyun.com/ubuntu/ xenial-backports main restricted universe multiverse #Added by software-properties
      deb http://archive.canonical.com/ubuntu xenial partner
      deb-src http://archive.canonical.com/ubuntu xenial partner
      deb http://mirrors.aliyun.com/ubuntu/ xenial-security main restricted
      deb-src http://mirrors.aliyun.com/ubuntu/ xenial-security main restricted multiverse universe #Added by software-properties
      deb http://mirrors.aliyun.com/ubuntu/ xenial-security universe
      deb http://mirrors.aliyun.com/ubuntu/ xenial-security multiverse
      

      将aliyun的源添加到/etc/apt/source.list中;
    • 安装相关依赖库：

      sudo apt-get install freeglut3-dev build-essential libx11-dev
      sudo apt-get install libxmu-dev libxi-dev libgl1-mesa-glx libglu1-mesa
      sudo apt-get install libglu1-mesa-dev
      ```
    

  • 安装：ubunto16系统默认的gcc-5.4.0就支持cuda-8.0，我的cuda-runfile文件是cuda_8.0.61_375.26_linux-run

     sudo sh cuda_8.0.44_linux.run --no-opengl-libs
    

    这里没有安装opengl，不会出现循环登录的bug；

    • 添加环境变量

    vim ~/.bashrc
    export PATH=/usr/local/cuda-8.0/bin:$PATH
    export LD_LIBRARY_PATH=/usr/local/cuda-8.0/lib64:$LD_LIBRARY_PATH
    sudo vim /etc/profile
    export CUDA_HOME=/usr/local/cuda-8.0
    

    • 设置动态链接库

    sudo vim /etc/profile
    

    写入

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

    创建cuda.conf文件

    sudo gedit /etc/ld.so.conf.d/cuda.conf
    

    添加以下路径

    /usr/local/cuda/lib64
    

    执行链接生效

    sudo ldconfig
    sudo reboot
    

    • 测试cuda是否安装成功

    cd /usr/local/cuda-8.0/samples/1_Utilities/deviceQuery 
    sudo make 
    ./deviceQuery
    

    得到以下结果表示安装成功。
    

  • 安装cuDNN-5.1

    • Cuda8.0对应的cnDNN版本是5.1，去官网注册下载；
    • 下载之后解压，将cuDNN里的文件copy到CUDA目录；

    sudo cp cudnn.h /usr/local/cuda/include/ 
    sudo cp lib* /usr/local/cuda/lib64/
    cd /usr/local/cuda/lib64/ 
    sudo rm -rf libcudnn.so libcudnn.so.5
    sudo ln -s libcudnn.so.5.1.5 libcudnn.so.5 
    sudo ln -s libcudnn.so.5 libcudnn.so 
    

  • 安装python

    • 安装setuptools依赖的zlib库；

    download:http://www.zlib.net/
    ./configure --prefix=/usr/local/zlib/
    make
    make install
    

    添加链接；

    //将--prefix目录添加到zlib.conf中
    sudo vim /etc/ld.so.conf.d/zlib.conf
    ldconfig
    

    • 安装setuptools；

    download:https://pypi.org/project/setuptools/
    sudo python setup.py install
    

    • 安装pip；

    sudo python setup.py install
    

  • 安装tensorflow

    pip安装：

    //gpu-python2
    sudo pip install --ignore-installed --upgrade https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.2.0-cp27-none-linux_x86_64.whl
    //cpu-python2
    sudo pip install --ignore-installed --upgrade https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.2.0-cp27-none-linux_x86_64.whl
    //gpu-python3
    sudo pip install --ignore-installed --upgrade https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.2.0-cp34-cp34m-linux_x86_64.whl
    //cpu-python3
    sudo pip install --ignore-installed --upgrade https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.2.0-cp34-cp34m-linux_x86_64.whl
    

  • 总结

    这样环境就搭好了，可以愉快的烧GPU啦～