Ubuntu 18.10 下安装CUDA10/CUDA10.1

骑猪看日落 2022-04-25 09:32 300阅读 0赞

GPU：GeForce840M  
显卡驱动：预装，版本390  
笔记本  
1.降级gcc 使用gcc5

sudo add-apt-repository ppa:ubuntu-toolchain-r/test
    sudo apt-get update
    sudo apt-get install gcc-5 g++-5
    sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-5 60 --slave /usr/bin/g++ g++ /usr/bin/g++-5

2安装python3.7

sudo apt update
    sudo apt upgrade -y
    sudo apt install software-properties-common
    sudo add-apt-repository ppa:deadsnakes/ppa
    sudo apt install python3.7 -y
    sudo rm -rf  /usr/bin/python3
    sudo ln -s /usr/bin/python3.7 /usr/bin/python3

查找python位置

which python

3.安装n卡驱动  
第一种：

1. 更新apt-get源列表
    sudo apt-get update
    sudo apt-get upgrade
    2. 添加驱动源
    sudo add-apt-repository ppa:graphics-drivers/ppa
    sudo apt-get update
    sudo apt install nvidia-driver-410

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzM0MDY3ODIx_size_16_color_FFFFFF_t_70]  
3.安装cuda10.0

sudo sh  *.run

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzM0MDY3ODIx_size_16_color_FFFFFF_t_70 1]  
一直按Enter直至把声明看完

如果驱动是独立安装了，一定要选择不安装驱动！选择如下：  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzM0MDY3ODIx_size_16_color_FFFFFF_t_70 2]  
有如下信息 可以忽略：  
\*\*\*WARNING: Incomplete installation! This installation did not install the CUDA Driver. A driver of version at least 384.00 is required for CUDA 10.0 functionality to work.

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

4.添加环境变量

sudo gedit ~/.bashrc
    添加到最后
    export PATH=$PATH:/usr/local/cuda/bin  
    export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda/lib64  
    export LIBRARY_PATH=$LIBRARY_PATH:/usr/local/cuda/lib64  
    保存退出
    source ~/.bashrc

5.测试是否成功

sudo rm -rf /usr/local/cuda  
    sudo ln -s /usr/local/cuda-10.0 /usr/local/cuda  
    nvcc --version  
    
    cd /usr/local/cuda/samples/1_Utilities/deviceQuery 
    sudo make
    ./deviceQuery

第二种：

sudo add-apt-repository ppa:graphics-drivers
     sudo apt-get update
     ubuntu-drivers devices

如果系统中有老版本显卡驱动，要先卸载
    sudo apt-get remove --purge nvidia*
    sudo ubuntu-drivers autoinstall
    #这里我安装了430，你可以选择其他的
    sudo apt-get install nvidia-430

重启

#输入
    nvidia-smi

这个图是正确结果  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzM0MDY3ODIx_size_16_color_FFFFFF_t_70 3]

sudo sh cuda_10.1.105_418.39_linux.run

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzM0MDY3ODIx_size_16_color_FFFFFF_t_70 4]  
安装完后，在.bashrc文件末尾添加环境变量

sudo vim ~/.bashrc

export PATH=$PATH:/usr/local/cuda/bin  
    export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda/lib64  
    export LIBRARY_PATH=$LIBRARY_PATH:/usr/local/cuda/lib64

保存退出后，输入以下命名
    source ~/.bashrc

测试是否成功

sudo rm -rf /usr/local/cuda  
    sudo ln -s /usr/local/cuda-10.0 /usr/local/cuda  
    nvcc --version  
    
     cd /usr/local/cuda/samples/1_Utilities/deviceQuery 
    sudo make
    ./deviceQuery

这样的结果就ok 下边有个pass  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzM0MDY3ODIx_size_16_color_FFFFFF_t_70 5]  
在去官网找linux 的cudnn [https://developer.nvidia.com/rdp/cudnn-download][https_developer.nvidia.com_rdp_cudnn-download]  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzM0MDY3ODIx_size_16_color_FFFFFF_t_70 6]

下载完成后，输入以下命令解压文件
    
     tar -zxvf cudnn-10.1-linux-x64-v7.5.1.10.tgz
    
    sudo cp cuda/include/cudnn.h /usr/local/cuda/include/    #解压后的文件夹名为cuda
    sudo cp cuda/lib64/libcudnn* /usr/local/cuda/lib64/ 
    sudo chmod a+r /usr/local/cuda/include/cudnn.h           #增加所有用户对文件的可执行权限
    sudo chmod a+r /usr/local/cuda/lib64/libcudnn*

查看cudnn 版本

cat /usr/local/cuda/include/cudnn.h | grep CUDNN_MAJOR -A 2

至此安装结束  
可以玩玩tensorflow-gpu了

希望能交流更多技术，关注小白的微信公众号吧。  
![在这里插入图片描述][20190703100512270.jpg]

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[https_developer.nvidia.com_rdp_cudnn-download]: https://developer.nvidia.com/rdp/cudnn-download
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[20190703100512270.jpg]: https://img-blog.csdnimg.cn/20190703100512270.jpg