Cuda + cudnn 在Ubuntu18.04上的手动安装

迈不过友情╰ 2022-03-25 08:07 204阅读 0赞

本文是本人的安装记录，因为想做C语言级的调试，整个过程十分麻烦，而且肯定会有记录忽略的地方，不建议大家使用。仅供参考。一般情况下，还是使用anaconda安装NVIDIA Cuda tool kit吧，非常轻松。

在某些情况下（比如开发的需要）需要手动安装时，可以参考下面的记录。

## Step.1 Stop Nouveau ##

The Nouveau kernel driver is currently in use by your system.  This driver is incompatible with the NVIDIA driver,

参考：  
[https://tutorials.technology/tutorials/85-How-to-remove-Nouveau-kernel-driver-Nvidia-install-error.html][https_tutorials.technology_tutorials_85-How-to-remove-Nouveau-kernel-driver-Nvidia-install-error.html]  
How to remove Nouveau kernel driver (fix Nvidia install error)

#---open a terminal---
    sudo apt-get remove nvidia*
    sudo apt autoremove
    sudo apt-get install dkms build-essential linux-headers-generic
    
    sudo vim /etc/modprobe.d/blacklist.conf
    #---save the following info into file blacklist.conf---
    blacklist nouveau
    blacklist lbm-nouveau
    options nouveau modeset=0
    alias nouveau off
    alias lbm-nouveau off
    #---end of the info saved----
    
    #---go back to the terminal---
    echo options nouveau modeset=0 | sudo tee -a /etc/modprobe.d/nouveau-kms.conf
    sudo update-initramfs -u
    reboot

# #

## Step.2 intall cuda toolkit ##

然后就可以安装cuda toolkit了  
$ sudo sh cuda\_10.0.130\_410.48\_linux.run

blablabla......

\-----------------

Do you accept the previously read EULA?  
accept/decline/quit: accept

Install NVIDIA Accelerated Graphics Driver for Linux-x86\_64 410.48?  
(y)es/(n)o/(q)uit: y

Do you want to install the OpenGL libraries?  
(y)es/(n)o/(q)uit \[ default is yes \]: y

Do you want to run nvidia-xconfig?  
This will update the system X configuration file so that the NVIDIA X driver  
is used. The pre-existing X configuration file will be backed up.  
This option should not be used on systems that require a custom  
X configuration, such as systems with multiple GPU vendors.  
(y)es/(n)o/(q)uit \[ default is no \]: y

Install the CUDA 10.0 Toolkit?  
(y)es/(n)o/(q)uit: y

Enter Toolkit Location  
 \[ default is /usr/local/cuda-10.0 \]:

Do you want to install a symbolic link at /usr/local/cuda?  
(y)es/(n)o/(q)uit: y

Install the CUDA 10.0 Samples?  
(y)es/(n)o/(q)uit: y

Enter CUDA Samples Location  
 \[ default is /home/matthew \]:

Installing the NVIDIA display driver...  
Installing the CUDA Toolkit in /usr/local/cuda-10.0 ...  
Missing recommended library: libGLU.so  
Missing recommended library: libXi.so  
Missing recommended library: libXmu.so  
Missing recommended library: libGL.so

Installing the CUDA Samples in /home/matthew ...  
Copying samples to /home/matthew/NVIDIA\_CUDA-10.0\_Samples now...  
Finished copying samples.

===========  
= Summary =  
===========

Driver:   Installed  
Toolkit:  Installed in /usr/local/cuda-10.0  
Samples:  Installed in /home/matthew, but missing recommended libraries

Please make sure that  
 -   PATH includes /usr/local/cuda-10.0/bin  
 -   LD\_LIBRARY\_PATH includes /usr/local/cuda-10.0/lib64, or, add /usr/local/cuda-10.0/lib64 to /etc/ld.so.conf and run ldconfig as root

To uninstall the CUDA Toolkit, run the uninstall script in /usr/local/cuda-10.0/bin  
To uninstall the NVIDIA Driver, run nvidia-uninstall

Please see CUDA\_Installation\_Guide\_Linux.pdf in /usr/local/cuda-10.0/doc/pdf for detailed information on setting up CUDA.

Logfile is /tmp/cuda\_install\_1832.log

## Step.3  supplementary package ##

如果像前面一样，出现缺少的包：  
Missing recommended library: libGLU.so  
Missing recommended library: libXi.so  
Missing recommended library: libXmu.so  
Missing recommended library: libGL.so

不过，这个主要是针对samples，因为报错内容中说了，  
Driver:   Installed  
Toolkit:  Installed in /usr/local/cuda-10.0  
Samples:  Installed in /home/matthew, but missing recommended libraries

如果需要编译使用Samples，那就要补充安装(samples 还需要lglut)：

$ sudo apt-get install libxmu-dev libxi-dev libgl1-mesa-glx libglu1-mesa libglu1-mesa-dev
    $ sudo apt-get install freeglut3 freeglut3-dev

## Step.4 设置环境变量 ##

sudo gedit ~/.bashrc
    
    添加这两句然后保存：
    export PATH=/usr/local/cuda/bin:$PATH  
    export LD_LIBRARY_PATH=/usr/local/cuda/lib64:$LD_LIBRARY_PATH
    
    保存后, 执行下列命令, 使环境变量立即生效
    source ~/.bashrc

有的说还要同时需要添加lib库路径(貌似不加也可以)： 在 /etc/ld.so.conf.d/加入文件 cuda.conf,

sudo vim /etc/ld.so.conf.d/cuda.conf
    
    内容如下
    /usr/local/cuda/lib64
    
    保存后,执行下列命令使之立刻生效
    sudo  ldconfig  -v

## Step.5 编译samples并进行测试（optional） ##

这时候可以对samples进行编译了

cd /usr/local/cuda/samples
    
    然后执行下列命令来build samples
    sudo make all -j8

测试，如果正常会显示安装成功！

$ cd /usr/local/cuda/samples/1_Utilities/deviceQuery
    $ ./deviceQuery
    ./deviceQuery Starting...
    
     CUDA Device Query (Runtime API) version (CUDART static linking)
    
    Detected 1 CUDA Capable device(s)
    
    Device 0: "GeForce GTX 1080 Ti"
      CUDA Driver Version / Runtime Version          10.0 / 10.0
      CUDA Capability Major/Minor version number:    6.1
      Total amount of global memory:                 11175 MBytes (11718230016 bytes)
      (28) Multiprocessors, (128) CUDA Cores/MP:     3584 CUDA Cores
      GPU Max Clock rate:                            1633 MHz (1.63 GHz)
      Memory Clock rate:                             5505 Mhz
      Memory Bus Width:                              352-bit
      L2 Cache Size:                                 2883584 bytes
      Maximum Texture Dimension Size (x,y,z)         1D=(131072), 2D=(131072, 65536), 3D=(16384, 16384, 16384)
      Maximum Layered 1D Texture Size, (num) layers  1D=(32768), 2048 layers
      Maximum Layered 2D Texture Size, (num) layers  2D=(32768, 32768), 2048 layers
      Total amount of constant memory:               65536 bytes
      Total amount of shared memory per block:       49152 bytes
      Total number of registers available per block: 65536
      Warp size:                                     32
      Maximum number of threads per multiprocessor:  2048
      Maximum number of threads per block:           1024
      Max dimension size of a thread block (x,y,z): (1024, 1024, 64)
      Max dimension size of a grid size    (x,y,z): (2147483647, 65535, 65535)
      Maximum memory pitch:                          2147483647 bytes
      Texture alignment:                             512 bytes
      Concurrent copy and kernel execution:          Yes with 2 copy engine(s)
      Run time limit on kernels:                     Yes
      Integrated GPU sharing Host Memory:            No
      Support host page-locked memory mapping:       Yes
      Alignment requirement for Surfaces:            Yes
      Device has ECC support:                        Disabled
      Device supports Unified Addressing (UVA):      Yes
      Device supports Compute Preemption:            Yes
      Supports Cooperative Kernel Launch:            Yes
      Supports MultiDevice Co-op Kernel Launch:      Yes
      Device PCI Domain ID / Bus ID / location ID:   0 / 1 / 0
      Compute Mode:
         < Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >
    
    deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 10.0, CUDA Runtime Version = 10.0, NumDevs = 1
    Result = PASS

## Step.6 **CUDNN 的安装** ##

这个我参考了：  
[http://www.cnblogs.com/empty16/p/4793404.html][http_www.cnblogs.com_empty16_p_4793404.html]  
[https://www.cnblogs.com/jinggege/p/5766146.html][https_www.cnblogs.com_jinggege_p_5766146.html]  
不过原贴有部分路径错误，我在下面有说明。

不过我的系统是cuda10，所以在nvidia网站上下载的是cudnn-10.0-linux-x64-v7.4.2.24.tgz 这个包，注意下载需要注册Nvidia的开发者账号。  
安装过程如下，解压会得到一个cuda的文件夹，

cd cuda
    
    #copy到cuda库
    sudo cp lib64/libcudnn.*    /usr/local/lib/    
    sudo cp include/cudnn.h     /usr/local/include/
    
    #或者，copy到cuda库
    sudo cp lib64/libcudnn.*    /usr/local/cuda/lib64/    
    sudo cp include/cudnn.h     /usr/local/cuda/include/

这两个地方用起来大概没什么区别，不过一般情况下我建议使用/usr/local/cuda/include 和/usr/local/cuda/lib64，比如你要使用pytorch的时候，可以省掉一些手动配置，因为pytorch默认是通过 LD\_LIBRARY\_PATH来寻找cudnn的（参考：[https://github.com/pytorch/pytorch/issues/573][https_github.com_pytorch_pytorch_issues_573]）。

下面链接cuDNN的库文件（必须！），这里要特别注意的是，如果前面是将文件拷贝到/usr/local/cuda/lib64和/usr/local/cuda/include,那么下面的操作中也必须做相应的调整，下面的例子中，我假设目录都是/usr/local/lib和/usr/local/include，不再一一说明

$ sudo ln -sf /usr/local/lib/libcudnn.so.7.4.2  /usr/local/lib/libcudnn.so.7
    $ sudo ln -sf /usr/local/lib/libcudnn.so.7  /usr/local/lib/libcudnn.so

\#链接完config更新

$ sudo ldconfig

完成cuda和cudnn的安装

**如果在使用cudnn的lib 或者cudnn.h 时出现Permission denied提示，那么说明copy过去的文件当前系统没有权限使用，那么在拷贝过去之前，先对文件授权**

**修复方式：**

cd /usr/local/lib/
    sudo su
    chmod 777 -R libcudnn.so
    chmod 777 -R libcudnn.so.7
    chmod 777 -R libcudnn.so.7.4.2
    cd ..
    cd include
    chmod 777 -R cudnn.h

## 参考： ##

\[1\]本参考给出了ubuntu18.04, 16.04, 14.04等版本的nvidia驱动安装  
[https://askubuntu.com/questions/1077061/how-do-i-install-nvidia-and-cuda-drivers-into-ubuntu][https_askubuntu.com_questions_1077061_how-do-i-install-nvidia-and-cuda-drivers-into-ubuntu]  
\[2\][https://blog.csdn.net/tanmx219/article/details/86210023][https_blog.csdn.net_tanmx219_article_details_86210023]

## 参考1的安装过程 ##

我按照参考\[1\]的安装过程，发现安装了大量的开发包，而且由于网络的原因，过程非常缓慢，安装过程如下，

Remove any CUDA PPAs that may be setup and also remove the `nvidia-cuda-toolkit` if installed:

sudo rm /etc/apt/sources.list.d/cuda*
    sudo apt remove nvidia-cuda-toolkit

Recommended to also remove all NVIDIA drivers before installing new drivers:

sudo apt remove nvidia-*

Then update the system:

sudo apt update

Install the key:

sudo apt-key adv --fetch-keys  http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1404/x86_64/7fa2af80.pub

Add the repo:

sudo bash -c 'echo "deb http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1404/x86_64 /" > /etc/apt/sources.list.d/cuda.list'

Update the system again:

sudo apt update

Install CUDA 10.0.

sudo apt install cuda-10-0

It should be installing the nvidia-410 drivers with it as those are what are listed in the repo. See:[http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1404/x86\_64/][http_developer.download.nvidia.com_compute_cuda_repos_ubuntu1404_x86_64]

Add the following lines to your `~/.profile` file for CUDA 10.0

# set PATH for cuda 10.0 installation
    if [ -d "/usr/local/cuda-10.0/bin/" ]; then
        export PATH=/usr/local/cuda-10.0/bin${PATH:+:${PATH}}
        export LD_LIBRARY_PATH=/usr/local/cuda-10.0/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
    fi

Reboot the computer and check your settings when reboot is complete:  
Check NVIDIA Cuda Compiler with `nvcc --version`:  
Check NVIDIA driver with `nvidia-smi`:

## 参考1的安装结果 ##

====================================================================
    sudo apt install nvidia-driver-410
    正在读取软件包列表... 完成
    正在分析软件包的依赖关系树       
    正在读取状态信息... 完成       
    将会同时安装下列软件：
      libnvidia-cfg1-410 libnvidia-common-410 libnvidia-compute-410
      libnvidia-decode-410 libnvidia-encode-410 libnvidia-fbc1-410
      libnvidia-gl-410 libnvidia-ifr1-410 libopengl0 libxnvctrl0
      nvidia-compute-utils-410 nvidia-dkms-410 nvidia-kernel-common-410
      nvidia-kernel-source-410 nvidia-prime nvidia-settings nvidia-utils-410
      screen-resolution-extra xserver-xorg-video-nvidia-410
    推荐安装：
      libnvidia-compute-410:i386 libnvidia-decode-410:i386
      libnvidia-encode-410:i386 libnvidia-ifr1-410:i386 libnvidia-fbc1-410:i386
      libnvidia-gl-410:i386
    下列软件包将被【卸载】：
      libnvidia-compute-390 libnvidia-compute-390:i386
    下列【新】软件包将被安装：
      libnvidia-cfg1-410 libnvidia-common-410 libnvidia-compute-410
      libnvidia-decode-410 libnvidia-encode-410 libnvidia-fbc1-410
      libnvidia-gl-410 libnvidia-ifr1-410 libopengl0 libxnvctrl0
      nvidia-compute-utils-410 nvidia-dkms-410 nvidia-driver-410
      nvidia-kernel-common-410 nvidia-kernel-source-410 nvidia-prime
      nvidia-settings nvidia-utils-410 screen-resolution-extra
      xserver-xorg-video-nvidia-410
    升级了 0 个软件包，新安装了 20 个软件包，要卸载 2 个软件包，有 37 个软件包未被升级。
    需要下载 67.1 MB/67.2 MB 的归档。
    解压缩后会消耗 130 MB 的额外空间。
    您希望继续执行吗？ [Y/n] y
    获取:2 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 libopengl0 amd64 1.0.0-2ubuntu2.2 [31.3 kB]
    获取:1 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  libnvidia-cfg1-410 410.79-0ubuntu1 [70.2 kB]
    获取:3 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  libnvidia-common-410 410.79-0ubuntu1 [9,800 B]
    获取:4 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  libnvidia-compute-410 410.79-0ubuntu1 [20.6 MB]
    获取:5 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  libnvidia-decode-410 410.79-0ubuntu1 [1,209 kB]
    获取:6 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  libnvidia-encode-410 410.79-0ubuntu1 [52.2 kB]
    获取:7 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  libnvidia-fbc1-410 410.79-0ubuntu1 [43.6 kB]
    获取:8 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  libnvidia-gl-410 410.79-0ubuntu1 [31.4 MB]
    获取:9 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  libnvidia-ifr1-410 410.79-0ubuntu1 [68.4 kB]
    获取:10 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  libxnvctrl0 410.79-0ubuntu1 [19.3 kB]
    获取:11 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  nvidia-compute-utils-410 410.79-0ubuntu1 [72.8 kB]
    获取:12 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  nvidia-kernel-source-410 410.79-0ubuntu1 [10.2 MB]
    获取:13 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  nvidia-kernel-common-410 410.79-0ubuntu1 [10.3 kB]
    获取:14 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  nvidia-dkms-410 410.79-0ubuntu1 [26.0 kB]
    获取:15 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  nvidia-utils-410 410.79-0ubuntu1 [333 kB]
    获取:16 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  xserver-xorg-video-nvidia-410 410.79-0ubuntu1 [1,652 kB]
    获取:17 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  nvidia-driver-410 410.79-0ubuntu1 [395 kB]
    获取:18 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  nvidia-settings 410.79-0ubuntu1 [962 kB]
    已下载 67.1 MB，耗时 39秒 (1,717 kB/s)                                         
    (正在读取数据库 ... 系统当前共安装有 198634 个文件和目录。)
    正在卸载 libnvidia-compute-390:amd64 (390.77-0ubuntu0.18.04.1) ...
    正在卸载 libnvidia-compute-390:i386 (390.77-0ubuntu0.18.04.1) ...
    正在选中未选择的软件包 libnvidia-cfg1-410:amd64。
    (正在读取数据库 ... 系统当前共安装有 198606 个文件和目录。)
    正准备解包 ...
    
    A modprobe blacklist file has been created at /etc/modprobe.d to prevent Nouveau
    from loading. This can be reverted by deleting the following file:
    /etc/modprobe.d/nvidia-graphics-drivers.conf
    
    A new initrd image has also been created. To revert, please regenerate your
    initrd by running the following command after deleting the modprobe.d file:
    `/usr/sbin/initramfs -u`
    
    *****************************************************************************
    *** Reboot your computer and verify that the NVIDIA graphics driver can   ***
    *** be loaded.                                                            ***
    *****************************************************************************
    
    INFO:Enable nvidia
    DEBUG:Parsing /usr/share/ubuntu-drivers-common/quirks/put_your_quirks_here
    DEBUG:Parsing /usr/share/ubuntu-drivers-common/quirks/dell_latitude
    DEBUG:Parsing /usr/share/ubuntu-drivers-common/quirks/lenovo_thinkpad
    Loading new nvidia-410.79 DKMS files...
    Building for 4.15.0-45-generic
    Building for architecture x86_64
    Building initial module for 4.15.0-45-generic
    Done.
    
    nvidia:
    Running module version sanity check.
     - Original module
       - No original module exists within this kernel
     - Installation
       - Installing to /lib/modules/4.15.0-45-generic/updates/dkms/
    
    nvidia-modeset.ko:
    Running module version sanity check.
     - Original module
       - No original module exists within this kernel
     - Installation
       - Installing to /lib/modules/4.15.0-45-generic/updates/dkms/
    
    nvidia-drm.ko:
    Running module version sanity check.
     - Original module
       - No original module exists within this kernel
     - Installation
       - Installing to /lib/modules/4.15.0-45-generic/updates/dkms/
    
    nvidia-uvm.ko:
    Running module version sanity check.
     - Original module
       - No original module exists within this kernel
     - Installation
       - Installing to /lib/modules/4.15.0-45-generic/updates/dkms/
    
    depmod.....
    
    DKMS: install completed.
     ...
    
    =====================================================================
    $ sudo apt install cuda-10-0
    正在读取软件包列表... 完成
    正在分析软件包的依赖关系树       
    正在读取状态信息... 完成       
    将会同时安装下列软件：
      ca-certificates-java cuda-command-line-tools-10-0 cuda-compiler-10-0 cuda-cublas-10-0 cuda-cublas-dev-10-0 cuda-cudart-10-0 cuda-cudart-dev-10-0 cuda-cufft-10-0 cuda-cufft-dev-10-0 cuda-cuobjdump-10-0
      cuda-cupti-10-0 cuda-curand-10-0 cuda-curand-dev-10-0 cuda-cusolver-10-0 cuda-cusolver-dev-10-0 cuda-cusparse-10-0 cuda-cusparse-dev-10-0 cuda-demo-suite-10-0 cuda-documentation-10-0
      cuda-driver-dev-10-0 cuda-drivers cuda-gdb-10-0 cuda-gpu-library-advisor-10-0 cuda-libraries-10-0 cuda-libraries-dev-10-0 cuda-license-10-0 cuda-memcheck-10-0 cuda-misc-headers-10-0 cuda-npp-10-0
      cuda-npp-dev-10-0 cuda-nsight-10-0 cuda-nsight-compute-10-0 cuda-nvcc-10-0 cuda-nvdisasm-10-0 cuda-nvgraph-10-0 cuda-nvgraph-dev-10-0 cuda-nvjpeg-10-0 cuda-nvjpeg-dev-10-0 cuda-nvml-dev-10-0
      cuda-nvprof-10-0 cuda-nvprune-10-0 cuda-nvrtc-10-0 cuda-nvrtc-dev-10-0 cuda-nvtx-10-0 cuda-nvvp-10-0 cuda-runtime-10-0 cuda-samples-10-0 cuda-toolkit-10-0 cuda-tools-10-0 cuda-visual-tools-10-0
      default-jre default-jre-headless fonts-dejavu-extra freeglut3 freeglut3-dev java-common libatk-wrapper-java libatk-wrapper-java-jni libdrm-dev libgl1-mesa-dev libgles1 libglu1-mesa-dev
      libglvnd-core-dev libglvnd-dev libx11-xcb-dev libxcb-dri2-0-dev libxcb-dri3-dev libxcb-glx0-dev libxcb-present-dev libxcb-randr0-dev libxcb-shape0-dev libxcb-sync-dev libxcb-xfixes0-dev libxmu-dev
      libxmu-headers libxshmfence-dev libxxf86vm-dev mesa-common-dev nvidia-modprobe openjdk-11-jre openjdk-11-jre-headless x11proto-xf86vidmode-dev
    建议安装：
      default-java-plugin fonts-ipafont-gothic fonts-ipafont-mincho fonts-wqy-microhei | fonts-wqy-zenhei
    下列【新】软件包将被安装：
      ca-certificates-java cuda-10-0 cuda-command-line-tools-10-0 cuda-compiler-10-0 cuda-cublas-10-0 cuda-cublas-dev-10-0 cuda-cudart-10-0 cuda-cudart-dev-10-0 cuda-cufft-10-0 cuda-cufft-dev-10-0
      cuda-cuobjdump-10-0 cuda-cupti-10-0 cuda-curand-10-0 cuda-curand-dev-10-0 cuda-cusolver-10-0 cuda-cusolver-dev-10-0 cuda-cusparse-10-0 cuda-cusparse-dev-10-0 cuda-demo-suite-10-0
      cuda-documentation-10-0 cuda-driver-dev-10-0 cuda-drivers cuda-gdb-10-0 cuda-gpu-library-advisor-10-0 cuda-libraries-10-0 cuda-libraries-dev-10-0 cuda-license-10-0 cuda-memcheck-10-0
      cuda-misc-headers-10-0 cuda-npp-10-0 cuda-npp-dev-10-0 cuda-nsight-10-0 cuda-nsight-compute-10-0 cuda-nvcc-10-0 cuda-nvdisasm-10-0 cuda-nvgraph-10-0 cuda-nvgraph-dev-10-0 cuda-nvjpeg-10-0
      cuda-nvjpeg-dev-10-0 cuda-nvml-dev-10-0 cuda-nvprof-10-0 cuda-nvprune-10-0 cuda-nvrtc-10-0 cuda-nvrtc-dev-10-0 cuda-nvtx-10-0 cuda-nvvp-10-0 cuda-runtime-10-0 cuda-samples-10-0 cuda-toolkit-10-0
      cuda-tools-10-0 cuda-visual-tools-10-0 default-jre default-jre-headless fonts-dejavu-extra freeglut3 freeglut3-dev java-common libatk-wrapper-java libatk-wrapper-java-jni libdrm-dev libgl1-mesa-dev
      libgles1 libglu1-mesa-dev libglvnd-core-dev libglvnd-dev libx11-xcb-dev libxcb-dri2-0-dev libxcb-dri3-dev libxcb-glx0-dev libxcb-present-dev libxcb-randr0-dev libxcb-shape0-dev libxcb-sync-dev
      libxcb-xfixes0-dev libxmu-dev libxmu-headers libxshmfence-dev libxxf86vm-dev mesa-common-dev nvidia-modprobe openjdk-11-jre openjdk-11-jre-headless x11proto-xf86vidmode-dev
    升级了 0 个软件包，新安装了 83 个软件包，要卸载 0 个软件包，有 37 个软件包未被升级。
    需要下载 1,407 MB 的归档。
    解压缩后会消耗 3,336 MB 的额外空间。
    您希望继续执行吗？ [Y/n] y
    获取:1 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 java-common all 0.63ubuntu1~02 [7,032 B]
    获取:2 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-license-10-0 10.0.130-1 [17.6 kB]
    获取:13 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 openjdk-11-jre-headless amd64 10.0.2+13-1ubuntu0.18.04.4 [39.5 MB]
    获取:3 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-misc-headers-10-0 10.0.130-1 [640 kB]
    获取:4 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-nvcc-10-0 10.0.130-1 [20.0 MB]
    获取:5 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-cuobjdump-10-0 10.0.130-1 [130 kB]
    获取:6 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-nvprune-10-0 10.0.130-1 [36.8 kB]
    获取:7 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-compiler-10-0 10.0.130-1 [2,538 B]
    获取:8 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-nvdisasm-10-0 10.0.130-1 [22.1 MB]
    获取:9 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-gdb-10-0 10.0.130-1 [2,769 kB]                                                                                      
    获取:10 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-nvprof-10-0 10.0.130-1 [5,590 kB]                                                                                  
    获取:11 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-memcheck-10-0 10.0.130-1 [139 kB]                                                                                  
    获取:12 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-cudart-10-0 10.0.130-1 [109 kB]                                                                                    
    获取:14 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-driver-dev-10-0 10.0.130-1 [12.0 kB]                                                                               
    获取:15 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-cudart-dev-10-0 10.0.130-1 [457 kB]                                                                                
    获取:16 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-cupti-10-0 10.0.130-1 [1,564 kB]                                                                                   
    获取:17 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-gpu-library-advisor-10-0 10.0.130-1 [1,003 kB]                                                                     
    获取:18 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-nvtx-10-0 10.0.130-1 [38.9 kB]                                                                                     
    获取:19 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-command-line-tools-10-0 10.0.130-1 [26.9 kB]                                                                       
    获取:20 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-nsight-10-0 10.0.130-1 [2,590 B]                                                                                   
    获取:21 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-nvvp-10-0 10.0.130-1 [2,536 B]                                                                                     
    获取:22 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-nvrtc-10-0 10.0.130-1 [5,925 kB]                                                                                   
    获取:23 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-nvrtc-dev-10-0 10.0.130-1 [9,344 B]                                                                                
    获取:24 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-cusolver-10-0 10.0.130-1 [38.4 MB]                                                                                 
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    获取:26 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-cublas-10-0 10.0.130-1 [30.3 MB]                                                                                   
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    获取:28 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-cufft-10-0 10.0.130-1 [60.7 MB]                                                                                    
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    获取:30 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-curand-10-0 10.0.130-1 [38.9 MB]                                                                                   
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    获取:32 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-cusparse-10-0 10.0.130-1 [27.1 MB]                                                                                 
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    获取:34 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-npp-10-0 10.0.130-1 [54.2 MB]                                                                                      
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    获取:36 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-nvml-dev-10-0 10.0.130-1 [51.6 kB]                                                                                 
    获取:37 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-nvgraph-10-0 10.0.130-1 [12.8 MB]                                                                                  
    获取:38 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-nvgraph-dev-10-0 10.0.130-1 [33.4 MB]                                                                              
    获取:39 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-nvjpeg-10-0 10.0.130-1 [281 kB]                                                                                    
    获取:40 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-nvjpeg-dev-10-0 10.0.130-1 [192 kB]                                                                                
    获取:41 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-nsight-compute-10-0 10.0.130-1 [188 MB]                                                                            
    获取:42 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-visual-tools-10-0 10.0.130-1 [394 MB]                                                                              
    获取:43 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-tools-10-0 10.0.130-1 [2,498 B]                                                                                    
    获取:44 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-samples-10-0 10.0.130-1 [61.5 MB]                                                                                  
    获取:45 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-documentation-10-0 10.0.130-1 [52.0 MB]                                                                            
    获取:46 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-libraries-dev-10-0 10.0.130-1 [2,606 B]                                                                            
    获取:47 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-toolkit-10-0 10.0.130-1 [2,834 B]                                                                                  
    获取:48 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  nvidia-modprobe 410.79-0ubuntu1 [19.1 kB]                                                                               
    获取:49 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-drivers 410.79-1 [2,568 B]                                                                                         
    获取:50 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-libraries-10-0 10.0.130-1 [2,586 B]                                                                                
    获取:51 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-runtime-10-0 10.0.130-1 [2,540 B]                                                                                  
    获取:52 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-demo-suite-10-0 10.0.130-1 [3,868 kB]                                                                              
    获取:53 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-10-0 10.0.130-1 [2,562 B]                                                                                          
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    获取:54 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 default-jre-headless amd64 2:1.10-63ubuntu1~02 [3,412 B]                                                                                     
    获取:55 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 ca-certificates-java all 20180516ubuntu1~18.04.1 [12.2 kB]                                                                           
    获取:56 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 openjdk-11-jre amd64 10.0.2+13-1ubuntu0.18.04.4 [53.1 kB]                                                                            
    获取:57 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 default-jre amd64 2:1.10-63ubuntu1~02 [1,092 B]                                                                                              
    获取:58 http://cn.archive.ubuntu.com/ubuntu bionic/universe amd64 freeglut3 amd64 2.8.1-3 [73.6 kB]                                                                                                        
    获取:59 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 libdrm-dev amd64 2.4.95-1~18.04.1 [121 kB]                                                                                           
    获取:60 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 mesa-common-dev amd64 18.2.2-0ubuntu1~18.04.1 [551 kB]                                                                               
    获取:61 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 libglvnd-core-dev amd64 1.0.0-2ubuntu2.2 [12.9 kB]                                                                                   
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    获取:64 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 libx11-xcb-dev amd64 2:1.6.4-3ubuntu0.1 [9,764 B]                                                                                    
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    获取:66 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libxcb-randr0-dev amd64 1.13-1 [20.4 kB]                                                                                                     
    获取:67 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libxcb-shape0-dev amd64 1.13-1 [7,144 B]                                                                                                     
    获取:68 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libxcb-xfixes0-dev amd64 1.13-1 [11.7 kB]                                                                                                    
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    获取:74 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 x11proto-xf86vidmode-dev all 2018.4-4 [2,632 B]                                                                                              
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    获取:78 http://cn.archive.ubuntu.com/ubuntu bionic/universe amd64 freeglut3-dev amd64 2.8.1-3 [124 kB]                                                                                                     
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    获取:81 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 fonts-dejavu-extra all 2.37-1 [1,953 kB]                                                                                                     
    获取:82 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libatk-wrapper-java all 0.33.3-20ubuntu0.1 [34.7 kB]                                                                                         
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    已下载 1,407 MB，耗时 26分 38秒 (880 kB/s)                                                                                                                                                                 
    正在从软件包中解出模板：100%
    正在选中未选择的软件包 java-common。
    (正在读取数据库 ... 系统当前共安装有 199217 个文件和目录。)
    正准备解包 ...
    ...
    
    done.
    done.

[https_tutorials.technology_tutorials_85-How-to-remove-Nouveau-kernel-driver-Nvidia-install-error.html]: https://tutorials.technology/tutorials/85-How-to-remove-Nouveau-kernel-driver-Nvidia-install-error.html
[http_www.cnblogs.com_empty16_p_4793404.html]: http://www.cnblogs.com/empty16/p/4793404.html
[https_www.cnblogs.com_jinggege_p_5766146.html]: https://www.cnblogs.com/jinggege/p/5766146.html
[https_github.com_pytorch_pytorch_issues_573]: https://github.com/pytorch/pytorch/issues/573
[https_askubuntu.com_questions_1077061_how-do-i-install-nvidia-and-cuda-drivers-into-ubuntu]: https://askubuntu.com/questions/1077061/how-do-i-install-nvidia-and-cuda-drivers-into-ubuntu
[https_blog.csdn.net_tanmx219_article_details_86210023]: https://blog.csdn.net/tanmx219/article/details/86210023
[http_developer.download.nvidia.com_compute_cuda_repos_ubuntu1404_x86_64]: http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1404/x86_64/