Ubuntu18.04上安装cuda10.0

刺骨的言语ヽ痛彻心扉 2022-03-28 08:39 362阅读 0赞

# Ubuntu18.04 + cuda (+ Optional Pytorch) #

### Step1: 检查硬件和系统 ###

检查版本和类型：ubuntu-drivers devices  
$ sudo ubuntu-drivers list  
nvidia-driver-390

$ ubuntu-drivers devices  
== /sys/devices/pci0000:00/0000:00:01.0/0000:01:00.0 ==  
modalias : pci:v000010DEd00001B06sv00001458sd0000374Cbc03sc00i00  
vendor   : NVIDIA Corporation  
model    : GP102 \[GeForce GTX 1080 Ti\]  
driver   : nvidia-driver-390 - distro non-free recommended  
driver   : xserver-xorg-video-nouveau - distro free builtin

这里显示，390是推荐的版本（recommended)

检查自己的GPU是否是CUDA-capable   
$ lspci | grep -i nvidia  
01:00.0 VGA compatible controller: NVIDIA Corporation GP102 \[GeForce GTX 1080 Ti\] (rev a1)  
01:00.1 Audio device: NVIDIA Corporation GP102 HDMI Audio Controller (rev a1)  
然后，可去CUDA的官网查看自己的GPU版本是否在CUDA的支持列表中   
https://developer.nvidia.com/cuda-gpus

### step.2，安装驱动 ###

选择安装所有推荐的驱动，如下命令  
$ sudo ubuntu-drivers autoinstall

也可以选择，只安装其中一个驱动，命令如下  
$ sudo apt install nvidia-390  
OK 驱动安装完成。

这时候，只需要重新启动一下就可以使用NVIDIA的驱动了！  
如何查看到底有没有启动呢？

~$ lsmod | grep nouveau
    #(no response, it means nouveau not running)
    
    ~$ lsmod | grep nvidia
    #(nvidia is running if we get info similar to below)
    nvidia_uvm            757760  0
    nvidia_drm             40960  1
    nvidia_modeset       1110016  9 nvidia_drm
    nvidia              14360576  418 nvidia_uvm,nvidia_modeset
    drm_kms_helper        172032  1 nvidia_drm
    drm                   401408  4 drm_kms_helper,nvidia_drm
    ipmi_msghandler        53248  2 ipmi_devintf,nvidia

关于驱动的安装，给个可供参考的贴子：  
[Linux安装NVIDIA显卡驱动的正确姿势][Linux_NVIDIA]  
[https://blog.csdn.net/wf19930209/article/details/81877822][Linux_NVIDIA]

### step.3, 安装CUDA ###

**----使用anaconda----**

仅仅是使用cuda和cudnn的话，毫无疑问是anaconda比较省事，只需要一条指令，  
conda install cudnn即可大功告成。比如我的机器上，执行完这条指令后，  
１。存放目录：  
anaconda3/pkgs/cudatoolkit-10.0.130-0.tar.bz2  
anaconda3/pkgs/cudnn-7.3.1-cuda10.0\_0.tar.bz2  
２。下载源地址：  
下载源地址最后存放在anaconda3/pkgs/urls.txt中，不过貌似要下载完之后才能看到。[https://repo.anaconda.com/pkgs/main/linux-64/cudatoolkit-10.0.130-0.tar.bz2][https_repo.anaconda.com_pkgs_main_linux-64_cudatoolkit-10.0.130-0.tar.bz2]  
[https://repo.anaconda.com/pkgs/main/linux-64/cudnn-7.3.1-cuda10.0\_0.tar.bz2][https_repo.anaconda.com_pkgs_main_linux-64_cudnn-7.3.1-cuda10.0_0.tar.bz2]

**----手动安装----**

如果你想手动安装呢，就到这里去下载相关的版本，安装包  
https://developer.nvidia.com/cuda-toolkit  
https://developer.nvidia.com/cuda-toolkit-archive  
下载完了再输入命令安装  
sudo sh cuda\_9.2.148\_396.37\_linux.run  
后面还有不少依赖包，一个个装吧！  
这样装的好处是文件比较全，比如cudeSample都会有。

## **----**sudo apt install nvidia-cuda-toolkit**----** ##

**这个安装方法和前面的不一样，会自动完成很多包的安装，我列出来在下面，**

＝＝>>> 不想一个个装可以使用这个试试看，不过这个方法我不推荐，比如下面我提到的pytorch的编译，这种方法就有报错。不清楚是否是ubuntu没整理完整还是啥冲突的问题。另外一种与此不同的安装方法是后面给出了的参考\[1\]的安装方式，是依赖于nvidia官网上的包，貌似会好一些，可参考着看。

$ sudo apt install nvidia-cuda-toolkit
    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 cpp-6 fonts-dejavu-extra g++-6 gcc-6 gcc-6-base
      java-common libaccinj64-9.1 libasan3 libatk-wrapper-java
      libatk-wrapper-java-jni libcublas9.1 libcudart9.1 libcufft9.1 libcufftw9.1
      libcuinj64-9.1 libcurand9.1 libcusolver9.1 libcusparse9.1 libdrm-dev
      libgcc-6-dev libgl1-mesa-dev libgles1 libglvnd-core-dev libglvnd-dev
      libnppc9.1 libnppial9.1 libnppicc9.1 libnppicom9.1 libnppidei9.1 libnppif9.1
      libnppig9.1 libnppim9.1 libnppist9.1 libnppisu9.1 libnppitc9.1 libnpps9.1
      libnvblas9.1 libnvgraph9.1 libnvrtc9.1 libnvtoolsext1 libnvvm3 libopengl0
      libstdc++-6-dev libthrust-dev libvdpau-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 libxshmfence-dev
      libxxf86vm-dev mesa-common-dev nvidia-cuda-dev nvidia-cuda-doc
      nvidia-cuda-gdb nvidia-opencl-dev nvidia-profiler nvidia-visual-profiler
      ocl-icd-libopencl1 ocl-icd-opencl-dev opencl-c-headers openjdk-8-jre
      openjdk-8-jre-headless x11proto-dri2-dev x11proto-gl-dev
      x11proto-xf86vidmode-dev
    建议安装：
      gcc-6-locales g++-6-multilib gcc-6-doc libstdc++6-6-dbg gcc-6-multilib
      libgcc1-dbg libgomp1-dbg libitm1-dbg libatomic1-dbg libasan3-dbg
      liblsan0-dbg libtsan0-dbg libubsan0-dbg libcilkrts5-dbg libmpx2-dbg
      libquadmath0-dbg default-jre libstdc++-6-doc libvdpau-doc libcupti-dev
      nvidia-driver libpoclu-dev icedtea-8-plugin fonts-ipafont-gothic
      fonts-ipafont-mincho fonts-wqy-microhei fonts-wqy-zenhei
    推荐安装：
      libnvcuvid1
    下列【新】软件包将被安装：
      ca-certificates-java cpp-6 fonts-dejavu-extra g++-6 gcc-6 gcc-6-base
      java-common libaccinj64-9.1 libasan3 libatk-wrapper-java
      libatk-wrapper-java-jni libcublas9.1 libcudart9.1 libcufft9.1 libcufftw9.1
      libcuinj64-9.1 libcurand9.1 libcusolver9.1 libcusparse9.1 libdrm-dev
      libgcc-6-dev libgl1-mesa-dev libgles1 libglvnd-core-dev libglvnd-dev
      libnppc9.1 libnppial9.1 libnppicc9.1 libnppicom9.1 libnppidei9.1 libnppif9.1
      libnppig9.1 libnppim9.1 libnppist9.1 libnppisu9.1 libnppitc9.1 libnpps9.1
      libnvblas9.1 libnvgraph9.1 libnvrtc9.1 libnvtoolsext1 libnvvm3 libopengl0
      libstdc++-6-dev libthrust-dev libvdpau-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 libxshmfence-dev
      libxxf86vm-dev mesa-common-dev nvidia-cuda-dev nvidia-cuda-doc
      nvidia-cuda-gdb nvidia-cuda-toolkit nvidia-opencl-dev nvidia-profiler
      nvidia-visual-profiler ocl-icd-libopencl1 ocl-icd-opencl-dev
      opencl-c-headers openjdk-8-jre openjdk-8-jre-headless x11proto-dri2-dev
      x11proto-gl-dev x11proto-xf86vidmode-dev
    升级了 0 个软件包，新安装了 73 个软件包，要卸载 0 个软件包，有 305 个软件包未被升级。
    需要下载 827 MB 的归档。
    解压缩后会消耗 1,990 MB 的额外空间。
    获取:1 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 java-common all 0.63ubuntu1~02 [7,032 B]
    获取:2 http://cn.archive.ubuntu.com/ubuntu bionic-updates/universe amd64 openjdk-8-jre-headless amd64 8u191-b12-0ubuntu0.18.04.1 [27.3 MB]
    获取:3 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 ca-certificates-java all 20180516ubuntu1~18.04.1 [12.2 kB]
    获取:4 http://cn.archive.ubuntu.com/ubuntu bionic-updates/universe amd64 gcc-6-base amd64 6.5.0-2ubuntu1~18.04 [16.7 kB]
    获取:5 http://cn.archive.ubuntu.com/ubuntu bionic-updates/universe amd64 cpp-6 amd64 6.5.0-2ubuntu1~18.04 [6,396 kB]
    获取:6 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 fonts-dejavu-extra all 2.37-1 [1,953 kB]
    获取:7 http://cn.archive.ubuntu.com/ubuntu bionic-updates/universe amd64 libasan3 amd64 6.5.0-2ubuntu1~18.04 [313 kB]
    获取:8 http://cn.archive.ubuntu.com/ubuntu bionic-updates/universe amd64 libgcc-6-dev amd64 6.5.0-2ubuntu1~18.04 [2,308 kB]
    获取:9 http://cn.archive.ubuntu.com/ubuntu bionic-updates/universe amd64 gcc-6 amd64 6.5.0-2ubuntu1~18.04 [7,067 kB]
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    获取:11 http://cn.archive.ubuntu.com/ubuntu bionic-updates/universe amd64 g++-6 amd64 6.5.0-2ubuntu1~18.04 [7,213 kB]
    获取:12 http://cn.archive.ubuntu.com/ubuntu bionic/multiverse amd64 libaccinj64-9.1 amd64 9.1.85-3ubuntu1 [1,748 kB]
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    获取:14 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libatk-wrapper-java-jni amd64 0.33.3-20ubuntu0.1 [28.3 kB]
    获取:15 http://cn.archive.ubuntu.com/ubuntu bionic/multiverse amd64 libcublas9.1 amd64 9.1.85-3ubuntu1 [25.0 MB]
    获取:16 http://cn.archive.ubuntu.com/ubuntu bionic/multiverse amd64 libcudart9.1 amd64 9.1.85-3ubuntu1 [121 kB]
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    获取:19 http://cn.archive.ubuntu.com/ubuntu bionic/multiverse amd64 libcuinj64-9.1 amd64 9.1.85-3ubuntu1 [1,878 kB]               获取:20 http://cn.archive.ubuntu.com/ubuntu bionic/multiverse amd64 libcurand9.1 amd64 9.1.85-3ubuntu1 [38.9 MB]                 获取:21 http://cn.archive.ubuntu.com/ubuntu bionic/multiverse amd64 libcusolver9.1 amd64 9.1.85-3ubuntu1 [28.2 MB]              获取:22 http://cn.archive.ubuntu.com/ubuntu bionic/multiverse amd64 libcusparse9.1 amd64 9.1.85-3ubuntu1 [25.2 MB]           获取:23 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libdrm-dev amd64 2.4.91-2 [238 kB]                                           获取:24 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 libgles1 amd64 1.0.0-2ubuntu2.2 [11.2 kB]                   获取:25 http://cn.archive.ubuntu.com/ubuntu bionic/multiverse amd64 libnppc9.1 amd64 9.1.85-3ubuntu1 [127 kB]                     获取:26 http://cn.archive.ubuntu.com/ubuntu bionic/multiverse amd64 libnppial9.1 amd64 9.1.85-3ubuntu1 [3,169 kB]                 获取:27 http://cn.archive.ubuntu.com/ubuntu bionic/multiverse amd64 libnppicc9.1 amd64 9.1.85-3ubuntu1 [1,376 kB]               获取:28 http://cn.archive.ubuntu.com/ubuntu bionic/multiverse amd64 libnppicom9.1 amd64 9.1.85-3ubuntu1 [497 kB]                获取:29 http://cn.archive.ubuntu.com/ubuntu bionic/multiverse amd64 libnppidei9.1 amd64 9.1.85-3ubuntu1 [1,673 kB]             获取:30 http://cn.archive.ubuntu.com/ubuntu bionic/multiverse amd64 libnppif9.1 amd64 9.1.85-3ubuntu1 [20.9 MB]                   获取:31 http://cn.archive.ubuntu.com/ubuntu bionic/multiverse amd64 libnppig9.1 amd64 9.1.85-3ubuntu1 [9,960 kB]                 获取:32 http://cn.archive.ubuntu.com/ubuntu bionic/multiverse amd64 libnppim9.1 amd64 9.1.85-3ubuntu1 [2,295 kB]                 获取:33 http://cn.archive.ubuntu.com/ubuntu bionic/multiverse amd64 libnppist9.1 amd64 9.1.85-3ubuntu1 [4,910 kB]                 获取:34 http://cn.archive.ubuntu.com/ubuntu bionic/multiverse amd64 libnppisu9.1 amd64 9.1.85-3ubuntu1 [120 kB]                   获取:35 http://cn.archive.ubuntu.com/ubuntu bionic/multiverse amd64 libnppitc9.1 amd64 9.1.85-3ubuntu1 [714 kB]                   获取:36 http://cn.archive.ubuntu.com/ubuntu bionic/multiverse amd64 libnpps9.1 amd64 9.1.85-3ubuntu1 [2,568 kB]                   获取:37 http://cn.archive.ubuntu.com/ubuntu bionic/multiverse amd64 libnvblas9.1 amd64 9.1.85-3ubuntu1 [132 kB]                   获取:38 http://cn.archive.ubuntu.com/ubuntu bionic/multiverse amd64 libnvgraph9.1 amd64 9.1.85-3ubuntu1 [6,252 kB]             
    获取:39 http://cn.archive.ubuntu.com/ubuntu bionic/multiverse amd64 libnvrtc9.1 amd64 9.1.85-3ubuntu1 [6,309 kB]                   
    获取:40 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libvdpau-dev amd64 1.1.1-3ubuntu1 [35.8 kB]                             获取:41 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 libx11-xcb-dev amd64 2:1.6.4-3ubuntu0.1 [9,764 B]     获取:42 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libxcb-dri2-0-dev amd64 1.13-1 [8,476 B]                                   获取:43 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libxcb-dri3-dev amd64 1.13-1 [7,368 B]                                     
    获取:44 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libxcb-glx0-dev amd64 1.13-1 [27.9 kB]    
    获取:45 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libxcb-randr0-dev amd64 1.13-1 [20.4 kB]     
    获取:46 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libxcb-shape0-dev amd64 1.13-1 [7,144 B]   
    获取:47 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libxcb-xfixes0-dev amd64 1.13-1 [11.7 kB]       
    获取:48 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libxcb-sync-dev amd64 1.13-1 [10.6 kB]      
    获取:49 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libxcb-present-dev amd64 1.13-1 [6,968 B]   
    获取:50 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libxshmfence-dev amd64 1.3-1 [3,692 B]   
    获取:51 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 x11proto-xf86vidmode-dev all 2018.4-4 [2,632 B]  
    获取:52 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libxxf86vm-dev amd64 1:1.1.4-1 [13.3 kB]               
    获取:53 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 mesa-common-dev amd64 18.0.5-0ubuntu0~18.04.1 [536 kB]
    获取:54 http://cn.archive.ubuntu.com/ubuntu bionic-updates/universe amd64 openjdk-8-jre amd64 8u191-b12-0ubuntu0.18.04.1 [69.7 kB]    
    获取:55 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 x11proto-dri2-dev all 2018.4-4 [2,620 B]  
    获取:56 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 x11proto-gl-dev all 2018.4-4 [2,612 B]    
    获取:57 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 libglvnd-core-dev amd64 1.0.0-2ubuntu2.2 [12.9 kB]   
    获取:58 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 libopengl0 amd64 1.0.0-2ubuntu2.2 [31.3 kB]   
    获取:59 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 libglvnd-dev amd64 1.0.0-2ubuntu2.2 [3,408 B]  
    获取:60 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 libgl1-mesa-dev amd64 18.0.5-0ubuntu0~18.04.1 [4,444 B]
    获取:61 http://cn.archive.ubuntu.com/ubuntu bionic/multiverse amd64 libnvtoolsext1 amd64 9.1.85-3ubuntu1 [31.3 kB]     
    获取:62 http://cn.archive.ubuntu.com/ubuntu bionic/multiverse amd64 libnvvm3 amd64 9.1.85-3ubuntu1 [4,274 kB]   
    获取:63 http://cn.archive.ubuntu.com/ubuntu bionic/multiverse amd64 libthrust-dev all 1.9.1~9.1.85-3ubuntu1 [461 kB]  
    获取:64 http://cn.archive.ubuntu.com/ubuntu bionic/multiverse amd64 nvidia-cuda-dev amd64 9.1.85-3ubuntu1 [263 MB]   
    获取:65 http://cn.archive.ubuntu.com/ubuntu bionic/multiverse amd64 nvidia-cuda-doc all 9.1.85-3ubuntu1 [95.2 MB]    
    获取:66 http://cn.archive.ubuntu.com/ubuntu bionic/multiverse amd64 nvidia-cuda-gdb amd64 9.1.85-3ubuntu1 [2,724 kB]  
    获取:67 http://cn.archive.ubuntu.com/ubuntu bionic/multiverse amd64 nvidia-profiler amd64 9.1.85-3ubuntu1 [2,672 kB]     
    获取:68 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 opencl-c-headers all 2.2~2018.02.21-gb5c3680-1 [28.5 kB] 
    获取:69 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 ocl-icd-libopencl1 amd64 2.2.11-1ubuntu1 [30.3 kB]   
    获取:70 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 ocl-icd-opencl-dev amd64 2.2.11-1ubuntu1 [2,512 B]    
    获取:71 http://cn.archive.ubuntu.com/ubuntu bionic/multiverse amd64 nvidia-opencl-dev amd64 9.1.85-3ubuntu1 [22.6 kB]   
    获取:72 http://cn.archive.ubuntu.com/ubuntu bionic/multiverse amd64 nvidia-cuda-toolkit amd64 9.1.85-3ubuntu1 [30.4 MB]  
    获取:73 http://cn.archive.ubuntu.com/ubuntu bionic/multiverse amd64 nvidia-visual-profiler amd64 9.1.85-3ubuntu1 [115 MB]

### 卸载 ###

卸载过程比较简单，就是一个命令：sudo apt-get --purge remove nvidia-cuda-toolkit  
注意执行本语句过程中，有一个提示：'sudo apt autoremove'，就是那些不需要再用的依赖也可以删除掉（我一般都保留不删，只要不冲突就行，免得其他程序还得再安装）。

$ sudo apt-get --purge remove nvidia-cuda-toolkit  
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         
下列软件包是自动安装的并且现在不需要了：  
  debugedit g++-6 libaccinj64-9.1 libcublas9.1 libcudart9.1 libcufft9.1 libcufftw9.1 libcuinj64-9.1 libcurand9.1 libcusolver9.1 libcusparse9.1 libdrm-dev libgl1-mesa-dev libgles1 libglvnd-core-dev  
  libglvnd-dev libnppc9.1 libnppial9.1 libnppicc9.1 libnppicom9.1 libnppidei9.1 libnppif9.1 libnppig9.1 libnppim9.1 libnppist9.1 libnppisu9.1 libnppitc9.1 libnpps9.1 libnvblas9.1 libnvgraph9.1  
  libnvrtc9.1 libnvtoolsext1 libnvvm3 libopengl0 librpmbuild8 librpmsign8 libsqlite0 libthrust-dev libvdpau-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 libxshmfence-dev libxxf86vm-dev mesa-common-dev nvidia-cuda-dev nvidia-cuda-doc nvidia-cuda-gdb nvidia-opencl-dev nvidia-profiler  
  nvidia-visual-profiler ocl-icd-opencl-dev opencl-c-headers python-libxml2 python-lzma python-pycurl python-rpm python-sqlite python-sqlitecachec python-urlgrabber rpm x11proto-dri2-dev x11proto-gl-dev  
  x11proto-xf86vidmode-dev  
使用'sudo apt autoremove'来卸载它(它们)。  
下列软件包将被【卸载】：  
  nvidia-cuda-toolkit\*  
升级了 0 个软件包，新安装了 0 个软件包，要卸载 1 个软件包，有 14 个软件包未被升级。  
解压缩后将会空出 61.0 MB 的空间。  
您希望继续执行吗？ \[Y/n\] y  
(正在读取数据库 ... 系统当前共安装有 188653 个文件和目录。)  
正在卸载 nvidia-cuda-toolkit (9.1.85-3ubuntu1) ...  
正在处理用于 man-db (2.8.3-2ubuntu0.1) 的触发器 ...  
(正在读取数据库 ... 系统当前共安装有 188613 个文件和目录。)  
正在清除 nvidia-cuda-toolkit (9.1.85-3ubuntu1) 的配置文件 ...

另外提一下pytorch的编译与安装，

根据[https://github.com/pytorch/pytorch][https_github.com_pytorch_pytorch]的说法，

采用下面这几步就够了，  
conda install numpy pyyaml mkl mkl-include setuptools cmake cffi typing

\# Add LAPACK support for the GPU if needed  
conda install -c pytorch magma-cuda92 \# or \[magma-cuda80 | magma-cuda91\] depending on your cuda version

\# Get the PyTorch Source  
git clone --recursive https://github.com/pytorch/pytorch  
cd pytorch

\#Install PyTorch  
export CMAKE\_PREFIX\_PATH=$\{CONDA\_PREFIX:-"$(dirname $(which conda))/../"\}  
python setup.py install

而实际上，我发现Ubuntu18.04上也有不少冲突，主要是缺少安装包什么的，或者是不兼容，具体报错内容没记住，其中有一个cuda的问题

CMake Error at cmake/public/cuda.cmake:318 (message):  
  CUDA 9.1 is not compatible with std::tuple from GCC version >= 6.  Please  
  upgrade to CUDA 9.2 or use the following option to use another version (for  
  example):  
    -DCUDA\_HOST\_COMPILER=/usr/bin/gcc-5  
.....  
\-- Configuring incomplete, errors occurred!  
See also "/home/matthew/dev/pytorch/build/CMakeFiles/CMakeOutput.log".  
See also "/home/matthew/dev/pytorch/build/CMakeFiles/CMakeError.log".  
Failed to run 'bash ../tools/build\_pytorch\_libs.sh --use-cuda --use-fbgemm --use-nnpack --use-mkldnn --use-qnnpack caffe2'

网上有不少解决办法，参考：[https://github.com/pytorch/pytorch/issues/14152][https_github.com_pytorch_pytorch_issues_14152]

我的办法是

step1: remove the previous cuda  
sudo apt-get --purge remove nvidia-cuda-toolkit  
conda remove cudnn (if has installed a different version needed)

step2: install cudnn  (this will install cudnn7\_cuda9.2  
conda install pybind11  
conda install cudnn

$ conda install cudnn
    Solving environment: done
    
    ## Package Plan ##
      environment location: /home/matthew/anaconda3/envs/torchdev
      added / updated specs: 
        - cudnn
    
    The following packages will be downloaded:
        package                    |            build
        ---------------------------|-----------------
        cudatoolkit-9.2            |                0       351.0 MB
        cudnn-7.2.1                |        cuda9.2_0       322.8 MB
        ------------------------------------------------------------
                                               Total:       673.8 MB
    
    The following NEW packages will be INSTALLED:
        cudatoolkit: 9.2-0          
        cudnn:       7.2.1-cuda9.2_0
    Proceed ([y]/n)? y

这一步之后，就可以正常执行python setup.py install了。

## 参考安装方式\[1\] ##

[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]  
本安装方式的缺点是：看运气，网络上有些包比较卡顿！！！

### 安装过程 ###

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/ubuntu1804/x86_64/7fa2af80.pub

Add the repo:

sudo bash -c 'echo "deb http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64 /" > /etc/apt/sources.list.d/cuda.list'

Update the system again:

sudo apt update

If you only want the NVIDIA 410 driver run, if not, skip this step:

sudo apt install nvidia-driver-410

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/ubuntu1804/x86\_64/][http_developer.download.nvidia.com_compute_cuda_repos_ubuntu1804_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`:  
...

### 安装结果（列出全部的安装包） ###

~$ 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 ...
    ...
    update-initramfs: deferring update (trigger activated)
    
    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]                                                                                 
    获取:25 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-cusolver-dev-10-0 10.0.130-1 [13.2 MB]                                                                             
    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]                                                                                   
    获取:27 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-cublas-dev-10-0 10.0.130-1 [30.8 MB]                                                                               
    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]                                                                                    
    获取:29 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-cufft-dev-10-0 10.0.130-1 [124 MB]                                                                                 
    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]                                                                                   
    获取:31 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-curand-dev-10-0 10.0.130-1 [58.1 MB]                                                                               
    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]                                                                                 
    获取:33 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-cusparse-dev-10-0 10.0.130-1 [27.2 MB]                                                                             
    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]                                                                                      
    获取:35 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64  cuda-npp-dev-10-0 10.0.130-1 [55.0 MB]                                                                                  
    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]                                                                                          
    91% [13 openjdk-11-jre-headless 11.0 MB/39.5 MB 28%]                                                                                                                                  17.8 kB/s 29分 52秒 
    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]                                                                                   
    获取:62 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 libgles1 amd64 1.0.0-2ubuntu2.2 [11.2 kB]                                                                                            
    获取:63 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 libglvnd-dev amd64 1.0.0-2ubuntu2.2 [3,408 B]                                                                                        
    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]                                                                                    
    获取:65 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libxcb-dri3-dev amd64 1.13-1 [7,368 B]                                                                                                       
    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]                                                                                                    
    获取:69 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libxcb-sync-dev amd64 1.13-1 [10.6 kB]                                                                                                       
    获取:70 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libxcb-present-dev amd64 1.13-1 [6,968 B]                                                                                                    
    获取:71 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libxshmfence-dev amd64 1.3-1 [3,692 B]                                                                                                       
    获取:72 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libxcb-dri2-0-dev amd64 1.13-1 [8,476 B]                                                                                                     
    获取:73 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libxcb-glx0-dev amd64 1.13-1 [27.9 kB]                                                                                                       
    获取:74 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 x11proto-xf86vidmode-dev all 2018.4-4 [2,632 B]                                                                                              
    获取:75 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libxxf86vm-dev amd64 1:1.1.4-1 [13.3 kB]                                                                                                     
    获取:76 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 libgl1-mesa-dev amd64 18.2.2-0ubuntu1~18.04.1 [4,432 B]                                                                              
    获取:77 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libglu1-mesa-dev amd64 9.0.0-2.1build1 [206 kB]                                                                                              
    获取:78 http://cn.archive.ubuntu.com/ubuntu bionic/universe amd64 freeglut3-dev amd64 2.8.1-3 [124 kB]                                                                                                     
    获取:79 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libxmu-headers all 2:1.1.2-2 [54.3 kB]                                                                                                       
    获取:80 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libxmu-dev amd64 2:1.1.2-2 [49.0 kB]                                                                                                         
    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]                                                                                         
    获取:83 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libatk-wrapper-java-jni amd64 0.33.3-20ubuntu0.1 [28.3 kB]                                                                                   
    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 ...
    
    Running hooks in /etc/ca-certificates/update.d...
    
    done.

### Step.4 检查cuda是否安装成功 ###

检查 CUDA Toolkit是否安装成功 终端输入 ：  
$ nvcc -V  
会输出CUDA的版本信息（V要大写）   
$ nvidia-smi

一般安装完后，cuda还有一些可供测试的samples，位置一般是在/usr/local/cuda-10.0下面，我们可以检测一下效果，如下

~$ cd /usr/local/cuda-10.0/samples/1_Utilities/deviceQuery
    
    ==>>>
    ...deviceQuery$ sudo make
    /usr/local/cuda-10.0/bin/nvcc -ccbin g++ -I../../common/inc  -m64    -gencode arch=compute_30,code=sm_30 -gencode arch=compute_35,code=sm_35 -gencode arch=compute_37,code=sm_37 -gencode arch=compute_50,code=sm_50 -gencode arch=compute_52,code=sm_52 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_61,code=sm_61 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_75,code=compute_75 -o deviceQuery.o -c deviceQuery.cpp
    /usr/local/cuda-10.0/bin/nvcc -ccbin g++   -m64      -gencode arch=compute_30,code=sm_30 -gencode arch=compute_35,code=sm_35 -gencode arch=compute_37,code=sm_37 -gencode arch=compute_50,code=sm_50 -gencode arch=compute_52,code=sm_52 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_61,code=sm_61 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_75,code=compute_75 -o deviceQuery deviceQuery.o 
    mkdir -p ../../bin/x86_64/linux/release
    cp deviceQuery ../../bin/x86_64/linux/release
    
    ==>>>
    ...deviceQuery$ ls
    deviceQuery      deviceQuery.o  NsightEclipse.xml
    deviceQuery.cpp  Makefile       readme.txt
    
    ==>>>
    ...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:                 11177 MBytes (11720130560 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

[Linux_NVIDIA]: https://blog.csdn.net/wf19930209/article/details/81877822
[https_repo.anaconda.com_pkgs_main_linux-64_cudatoolkit-10.0.130-0.tar.bz2]: https://repo.anaconda.com/pkgs/main/linux-64/cudatoolkit-10.0.130-0.tar.bz2
[https_repo.anaconda.com_pkgs_main_linux-64_cudnn-7.3.1-cuda10.0_0.tar.bz2]: https://repo.anaconda.com/pkgs/main/linux-64/cudnn-7.3.1-cuda10.0_0.tar.bz2
[https_github.com_pytorch_pytorch]: https://github.com/pytorch/pytorch
[https_github.com_pytorch_pytorch_issues_14152]: https://github.com/pytorch/pytorch/issues/14152
[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
[http_developer.download.nvidia.com_compute_cuda_repos_ubuntu1804_x86_64]: http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/