Ubuntu18.04安装CUDA深度学习环境

N卡在深度学习领域具备无可替代的地位,这里记录以下在我这台配备GF MX250 N卡笔记本 上安装cuda以及cuNN的具体步骤。MX250属于低端显卡了,一开始我还担心它会不会不支持CUDA,后面确认了一下,发现可以支持。关于确认N卡是否支持CUDA以及支持版本的具体步骤,可以参考我的这篇博客:

如何确定PC Nvidia显卡是否支持CUDA以及cudaNN?

过程不难,细节很多,下面记录具体步骤:

0:禁用nouveau,将之加入blacklist,然后重启系统

由于我们需要用Nvidia提供的官方驱动,所以需要将写在默认的开源驱动nouveau从系统中卸载掉并避免被再次加载,方法就是将模块名字加入系统黑名单。如果不这样操作,NVIDIA的官方驱动和系统自带的nouveau驱动会产生冲突。

执行 lsmod | grep nouveau 查看当前系统是否在使用nouveau

Ubuntu18.04安装CUDA深度学习环境_第1张图片

在文件:

 /etc/modprobe.d/blacklist.conf

最后一行加上: blacklist nouveau

之后执行如下命令重新生成initramfs,然后重启动

$ sudo update-initramfs -u
$ reboot

重启后,执行

执行命令检测,如果没有任何输出,表示禁用成功,此时,我们用的核显来进行显示。

1.安装显卡驱动:

安装依赖:

sudo apt install make cmake gcc g++ python-pip
sudo apt install make git vim wget cmake

首先使用如下命令查看系统推荐安装的显卡驱动:

ubuntu-drivers devices

Ubuntu18.04安装CUDA深度学习环境_第2张图片

czl@czl-RedmiBook-14:~$ ubuntu-drivers devices
== /sys/devices/pci0000:00/0000:00:14.3 ==
modalias : pci:v00008086d00009DF0sv00008086sd000002A4bc02sc80i00
vendor   : Intel Corporation
manual_install: True
driver   : backport-iwlwifi-dkms - distro free

== /sys/devices/pci0000:00/0000:00:1c.4/0000:02:00.0 ==
modalias : pci:v000010DEd00001D13sv00001D72sd00001814bc03sc02i00
vendor   : NVIDIA Corporation
manual_install: True
driver   : nvidia-driver-460 - distro non-free
driver   : nvidia-driver-450-server - distro non-free
driver   : nvidia-driver-470 - distro non-free
driver   : nvidia-driver-470-server - distro non-free recommended
driver   : nvidia-driver-418-server - distro non-free
driver   : nvidia-driver-460-server - distro non-free
driver   : xserver-xorg-video-nouveau - distro free builtin

czl@czl-RedmiBook-14:~$ 

 系统给我们推荐了一个版本,编号为470的驱动就是我们的目标。

driver   : nvidia-driver-470-server - distro non-free recommended

此命令随着NVIDIA官方显卡驱动的升级会发生变化,比如,再半年后再次执行此命令得到的输入却是下面的样子:

Ubuntu18.04安装CUDA深度学习环境_第3张图片

可见此时推荐的显卡驱动是510版本:

driver   : nvidia-driver-510 - third-party non-free recommended

如果仅仅想知道Nvidia针对所用显卡提供的最新驱动的版本,可以执行nvidia-detector命令,如下图:

Ubuntu18.04安装CUDA深度学习环境_第4张图片
 

或者:

Download Drivers | NVIDIA

ubuntu上查看显示设备信息可以通过以下命令:

Ubuntu18.04安装CUDA深度学习环境_第5张图片

Ubuntu18.04安装CUDA深度学习环境_第6张图片

选择显卡对应的型号,我的是GetForce->MX200 Series->GetForce MX250->Linxu 64 bit.

Ubuntu18.04安装CUDA深度学习环境_第7张图片

 点击搜索并继续,系统会为你搜索到正确的驱动版本,之后点击下载:

主版本号为470,和推荐给我们的一致.

下载过来的驱动默认没有可执行权限,需要我们手动添加:

sudo chmod +x  NVIDIA-Linux-x86_64-470.63.01.run 

之后,执行

sudo ./NVIDIA-Linux-x86_64-470.63.01.run

安装,当出现如下的窗口时,选择 "Continue Installation".

Ubuntu18.04安装CUDA深度学习环境_第8张图片

 然后就是安装进度条:

Ubuntu18.04安装CUDA深度学习环境_第9张图片

最后出现的警告不要管它

Ubuntu18.04安装CUDA深度学习环境_第10张图片

Ubuntu18.04安装CUDA深度学习环境_第11张图片

上图显示没有安装libglvnd,可以选择安装,也可以选择不安装,安装的话,命令是:

sudo apt install libglvnd-dev

安装后,执行

sudo apt search libglvnd
czl@czl-RedmiBook-14:~$ sudo apt search libglvnd
正在排序... 完成
全文搜索... 完成  
libglvnd-core-dev/bionic-updates,now 1.0.0-2ubuntu2.3 amd64 [已安装,自动]
  Vendor neutral GL dispatch library -- core development files

libglvnd-dev/bionic-updates,now 1.0.0-2ubuntu2.3 amd64 [已安装]
  Vendor neutral GL dispatch library -- development files

libglvnd0/bionic-updates,now 1.0.0-2ubuntu2.3 amd64 [已安装,自动]
  Vendor neutral GL dispatch library

czl@czl-RedmiBook-14:~$ 

安装完成:

Ubuntu18.04安装CUDA深度学习环境_第12张图片

不过,可惜的是,安装完libglvnd后,重新在执行安装,会出现下面的错误,因为已经安装过一次了,重新安装会失败。

Ubuntu18.04安装CUDA深度学习环境_第13张图片

 查看内核模块,发现确实是这样的

Ubuntu18.04安装CUDA深度学习环境_第14张图片

重启后,发现还是不成,N卡驱动模块已经加载了,看来只能再次祭出黑名单了,临时禁止N卡驱动挂载,安装后再恢复。

再次重启,发现还是不成,报同样的错误,只是这次模块换成了nvidia,有一个nvidia模块始终被DRM模块引用,即便已经将其加入黑名单。

只能这样了,反正根据信息,libglvnd不重要,可有可无,我们恢复黑名单继续。恢复后,重启,正常的模块加载列表如下图所示。

2.验证驱动:

安装完成后,重启系统,然后输入以下命令验证:

nvidia-smi

nvidia-smi指的是Nvidia System Manager Interface. 如果输出以下信息,表示安装成功,可以开瓶啤酒庆祝了,注意到输出信息包含驱动版本信息。

Ubuntu18.04安装CUDA深度学习环境_第15张图片

czl@czl-RedmiBook-14:~/Downloads$ nvidia-smi
Fri Aug 20 19:18:16 2021       
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 470.63.01    Driver Version: 470.63.01    CUDA Version: 11.4     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|                               |                      |               MIG M. |
|===============================+======================+======================|
|   0  NVIDIA GeForce ...  Off  | 00000000:02:00.0 Off |                  N/A |
| N/A   47C    P0    N/A /  N/A |    496MiB /  2002MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
                                                                               
+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
|    0   N/A  N/A      1478      G   /usr/lib/xorg/Xorg                180MiB |
|    0   N/A  N/A      1590      G   /usr/bin/gnome-shell               81MiB |
|    0   N/A  N/A      1909      G   /usr/lib/firefox/firefox          232MiB |
+-----------------------------------------------------------------------------+
czl@czl-RedmiBook-14:~/Downloads$ 

对于没有安装N卡的PC,也可以安装nvida-smi工具,但执行会报错:

Ubuntu18.04安装CUDA深度学习环境_第16张图片

到此为止,显卡驱动已经安装完成。

3.安装CUDA

根据

如何确定PC Nvidia显卡是否支持CUDA以及cudaNN?

的介绍,确定CUDA的安装版本,根据下方的帮助说明安装.

Ubuntu18.04安装CUDA深度学习环境_第17张图片

安装说明:

$wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-ubuntu1804.pin
$sudo mv cuda-ubuntu1804.pin /etc/apt/preferences.d/cuda-repository-pin-600
$wget https://developer.download.nvidia.com/compute/cuda/10.1/Prod/local_installers/cuda-repo-ubuntu1804-10-1-local-10.1.243-418.87.00_1.0-1_amd64.deb
$sudo dpkg -i cuda-repo-ubuntu1804-10-1-local-10.1.243-418.87.00_1.0-1_amd64.deb
$sudo apt-key add /var/cuda-repo-10-1-local-10.1.243-418.87.00/7fa2af80.pub
$sudo apt-get update
$sudo apt-get -y install cuda
czl@czl-RedmiBook-14:~/cuda$ wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-ubuntu1804.pin
--2021-08-21 10:39:51--  https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-ubuntu1804.pin
正在解析主机 developer.download.nvidia.com (developer.download.nvidia.com)... 129.227.48.133, 129.227.114.197, 129.227.48.130, ...
正在连接 developer.download.nvidia.com (developer.download.nvidia.com)|129.227.48.133|:443... 已连接。
已发出 HTTP 请求,正在等待回应... 301 Moved Permanently
位置:https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64/cuda-ubuntu1804.pin [跟随至新的 URL]
--2021-08-21 10:39:52--  https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64/cuda-ubuntu1804.pin
正在解析主机 developer.download.nvidia.cn (developer.download.nvidia.cn)... 218.98.50.13, 112.84.125.211, 112.84.125.210, ...
正在连接 developer.download.nvidia.cn (developer.download.nvidia.cn)|218.98.50.13|:443... 已连接。
已发出 HTTP 请求,正在等待回应... 200 OK
长度: 190 [application/octet-stream]
正在保存至: “cuda-ubuntu1804.pin”

cuda-ubuntu1804.pin                                100%[================================================================================================================>]     190  --.-KB/s    用时 0s    

2021-08-21 10:39:53 (9.19 MB/s) - 已保存 “cuda-ubuntu1804.pin” [190/190])

czl@czl-RedmiBook-14:~/cuda$ sudo mv cuda-ubuntu1804.pin /etc/apt/preferences.d/cuda-repository-pin-600
czl@czl-RedmiBook-14:~/cuda$ wget https://developer.download.nvidia.com/compute/cuda/10.1/Prod/local_installers/cuda-repo-ubuntu1804-10-1-local-10.1.243-418.87.00_1.0-1_amd64.deb
--2021-08-21 10:40:06--  https://developer.download.nvidia.com/compute/cuda/10.1/Prod/local_installers/cuda-repo-ubuntu1804-10-1-local-10.1.243-418.87.00_1.0-1_amd64.deb
正在解析主机 developer.download.nvidia.com (developer.download.nvidia.com)... 129.227.48.133, 129.227.114.197, 129.227.48.130, ...
正在连接 developer.download.nvidia.com (developer.download.nvidia.com)|129.227.48.133|:443... 已连接。
已发出 HTTP 请求,正在等待回应... 301 Moved Permanently
位置:https://developer.download.nvidia.cn/compute/cuda/10.1/Prod/local_installers/cuda-repo-ubuntu1804-10-1-local-10.1.243-418.87.00_1.0-1_amd64.deb [跟随至新的 URL]
--2021-08-21 10:40:06--  https://developer.download.nvidia.cn/compute/cuda/10.1/Prod/local_installers/cuda-repo-ubuntu1804-10-1-local-10.1.243-418.87.00_1.0-1_amd64.deb
正在解析主机 developer.download.nvidia.cn (developer.download.nvidia.cn)... 218.98.50.13, 112.84.125.211, 112.84.125.210, ...
正在连接 developer.download.nvidia.cn (developer.download.nvidia.cn)|218.98.50.13|:443... 已连接。
已发出 HTTP 请求,正在等待回应... 200 OK
长度: 1859785444 (1.7G) [application/x-deb]
正在保存至: “cuda-repo-ubuntu1804-10-1-local-10.1.243-418.87.00_1.0-1_amd64.deb”

cuda-repo-ubuntu1804-10-1-local-10.1.243-418.87.00 100%[================================================================================================================>]   1.73G  5.28MB/s    用时 7m 7s s

2021-08-21 10:47:12 (4.16 MB/s) - 已保存 “cuda-repo-ubuntu1804-10-1-local-10.1.243-418.87.00_1.0-1_amd64.deb” [1859785444/1859785444])

czl@czl-RedmiBook-14:~/cuda$ sudo dpkg -i cuda-repo-ubuntu1804-10-1-local-10.1.243-418.87.00_1.0-1_amd64.deb
[sudo] czl 的密码: 
正在选中未选择的软件包 cuda-repo-ubuntu1804-10-1-local-10.1.243-418.87.00。
(正在读取数据库 ... 系统当前共安装有 177536 个文件和目录。)
正准备解包 cuda-repo-ubuntu1804-10-1-local-10.1.243-418.87.00_1.0-1_amd64.deb  ...
正在解包 cuda-repo-ubuntu1804-10-1-local-10.1.243-418.87.00 (1.0-1) ...
正在设置 cuda-repo-ubuntu1804-10-1-local-10.1.243-418.87.00 (1.0-1) ...
czl@czl-RedmiBook-14:~/cuda$ sudo apt-key add /var/cuda-repo-10-1-local-10.1.243-418.87.00/7fa2af80.pub
OK
czl@czl-RedmiBook-14:~/cuda$ sudo apt-get update
获取:1 file:/var/cuda-repo-10-0-local-10.0.130-410.48  InRelease
忽略:1 file:/var/cuda-repo-10-0-local-10.0.130-410.48  InRelease
获取:2 file:/var/cuda-repo-10-0-local-nvjpeg-update-1  InRelease
忽略:2 file:/var/cuda-repo-10-0-local-nvjpeg-update-1  InRelease
获取:3 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  InRelease
忽略:3 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  InRelease
获取:4 file:/var/cuda-repo-10-0-local-10.0.130-410.48  Release [574 B]
获取:5 file:/var/cuda-repo-10-0-local-nvjpeg-update-1  Release [574 B]
获取:6 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  Release [574 B]
获取:4 file:/var/cuda-repo-10-0-local-10.0.130-410.48  Release [574 B]
获取:5 file:/var/cuda-repo-10-0-local-nvjpeg-update-1  Release [574 B]
获取:6 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  Release [574 B]
获取:7 file:/var/cuda-repo-10-0-local-nvjpeg-update-1  Release.gpg [801 B]
获取:7 file:/var/cuda-repo-10-0-local-nvjpeg-update-1  Release.gpg [801 B]
获取:8 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  Release.gpg [833 B]
获取:8 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  Release.gpg [833 B]        
获取:10 file:/var/cuda-repo-10-0-local-nvjpeg-update-1  Packages [689 B]                             
获取:11 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  Packages [25.0 kB]                                                
命中:12 http://cn.archive.ubuntu.com/ubuntu bionic InRelease                                      
获取:13 http://security.ubuntu.com/ubuntu bionic-security InRelease [88.7 kB]
获取:14 http://cn.archive.ubuntu.com/ubuntu bionic-updates InRelease [88.7 kB]       
获取:15 http://security.ubuntu.com/ubuntu bionic-security/main amd64 DEP-11 Metadata [51.3 kB]
获取:16 http://cn.archive.ubuntu.com/ubuntu bionic-backports InRelease [74.6 kB]
获取:17 http://security.ubuntu.com/ubuntu bionic-security/universe amd64 DEP-11 Metadata [57.9 kB]
获取:18 http://security.ubuntu.com/ubuntu bionic-security/multiverse amd64 DEP-11 Metadata [2,464 B]
获取:19 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 DEP-11 Metadata [294 kB]                               
获取:20 http://cn.archive.ubuntu.com/ubuntu bionic-updates/universe amd64 DEP-11 Metadata [295 kB]
获取:21 http://cn.archive.ubuntu.com/ubuntu bionic-updates/multiverse amd64 DEP-11 Metadata [2,468 B]
获取:22 http://cn.archive.ubuntu.com/ubuntu bionic-backports/universe amd64 DEP-11 Metadata [9,272 B]
已下载 964 kB,耗时 3秒 (286 kB/s)                                             
正在读取软件包列表... 完成
czl@czl-RedmiBook-14:~/cuda$ sudo apt-get -y install cuda
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-10-1 cuda-command-line-tools-10-1 cuda-compiler-10-1 cuda-cudart-10-1 cuda-cudart-dev-10-1 cuda-cufft-10-1 cuda-cufft-dev-10-1 cuda-cuobjdump-10-1 cuda-cupti-10-1
  cuda-curand-10-1 cuda-curand-dev-10-1 cuda-cusolver-10-1 cuda-cusolver-dev-10-1 cuda-cusparse-10-1 cuda-cusparse-dev-10-1 cuda-demo-suite-10-1 cuda-documentation-10-1 cuda-driver-dev-10-1 cuda-drivers
  cuda-gdb-10-1 cuda-gpu-library-advisor-10-1 cuda-libraries-10-1 cuda-libraries-dev-10-1 cuda-license-10-1 cuda-memcheck-10-1 cuda-misc-headers-10-1 cuda-npp-10-1 cuda-npp-dev-10-1 cuda-nsight-10-1
  cuda-nsight-compute-10-1 cuda-nsight-systems-10-1 cuda-nvcc-10-1 cuda-nvdisasm-10-1 cuda-nvgraph-10-1 cuda-nvgraph-dev-10-1 cuda-nvjpeg-10-1 cuda-nvjpeg-dev-10-1 cuda-nvml-dev-10-1 cuda-nvprof-10-1
  cuda-nvprune-10-1 cuda-nvrtc-10-1 cuda-nvrtc-dev-10-1 cuda-nvtx-10-1 cuda-nvvp-10-1 cuda-runtime-10-1 cuda-samples-10-1 cuda-sanitizer-api-10-1 cuda-toolkit-10-1 cuda-tools-10-1 cuda-visual-tools-10-1
  default-jre default-jre-headless dkms fonts-dejavu-extra freeglut3 freeglut3-dev java-common libatk-wrapper-java libatk-wrapper-java-jni libcublas-dev libcublas10 libdrm-dev libgif7 libgl1-mesa-dev
  libglu1-mesa-dev libice-dev libnvidia-cfg1-418 libnvidia-common-418 libnvidia-compute-418 libnvidia-decode-418 libnvidia-encode-418 libnvidia-fbc1-418 libnvidia-gl-418 libnvidia-ifr1-418
  libpthread-stubs0-dev libsm-dev libx11-6 libx11-dev libx11-doc libx11-xcb-dev libx11-xcb1 libxau-dev libxcb-dri2-0-dev libxcb-dri3-dev libxcb-glx0-dev libxcb-present-dev libxcb-randr0-dev
  libxcb-render0-dev libxcb-shape0-dev libxcb-sync-dev libxcb-xfixes0-dev libxcb1-dev libxdamage-dev libxdmcp-dev libxext-dev libxfixes-dev libxi-dev libxmu-dev libxmu-headers libxnvctrl0
  libxshmfence-dev libxt-dev libxxf86vm-dev mesa-common-dev nsight-compute-2019.4.0 nsight-systems-2019.3.7 nvidia-compute-utils-418 nvidia-dkms-418 nvidia-driver-418 nvidia-kernel-common-418
  nvidia-kernel-source-418 nvidia-modprobe nvidia-prime nvidia-settings nvidia-utils-418 openjdk-11-jre openjdk-11-jre-headless pkg-config screen-resolution-extra x11proto-core-dev x11proto-damage-dev
  x11proto-dev x11proto-fixes-dev x11proto-input-dev x11proto-xext-dev x11proto-xf86vidmode-dev xorg-sgml-doctools xserver-xorg-video-nvidia-418 xtrans-dev
建议安装:
  menu libice-doc libsm-doc libxcb-doc libxext-doc libxt-doc fonts-ipafont-gothic fonts-ipafont-mincho fonts-wqy-microhei | fonts-wqy-zenhei
推荐安装:
  libnvidia-compute-418:i386 libnvidia-decode-418:i386 libnvidia-encode-418:i386 libnvidia-ifr1-418:i386 libnvidia-fbc1-418:i386 libnvidia-gl-418:i386
下列【新】软件包将被安装:
  ca-certificates-java cuda cuda-10-1 cuda-command-line-tools-10-1 cuda-compiler-10-1 cuda-cudart-10-1 cuda-cudart-dev-10-1 cuda-cufft-10-1 cuda-cufft-dev-10-1 cuda-cuobjdump-10-1 cuda-cupti-10-1
  cuda-curand-10-1 cuda-curand-dev-10-1 cuda-cusolver-10-1 cuda-cusolver-dev-10-1 cuda-cusparse-10-1 cuda-cusparse-dev-10-1 cuda-demo-suite-10-1 cuda-documentation-10-1 cuda-driver-dev-10-1 cuda-drivers
  cuda-gdb-10-1 cuda-gpu-library-advisor-10-1 cuda-libraries-10-1 cuda-libraries-dev-10-1 cuda-license-10-1 cuda-memcheck-10-1 cuda-misc-headers-10-1 cuda-npp-10-1 cuda-npp-dev-10-1 cuda-nsight-10-1
  cuda-nsight-compute-10-1 cuda-nsight-systems-10-1 cuda-nvcc-10-1 cuda-nvdisasm-10-1 cuda-nvgraph-10-1 cuda-nvgraph-dev-10-1 cuda-nvjpeg-10-1 cuda-nvjpeg-dev-10-1 cuda-nvml-dev-10-1 cuda-nvprof-10-1
  cuda-nvprune-10-1 cuda-nvrtc-10-1 cuda-nvrtc-dev-10-1 cuda-nvtx-10-1 cuda-nvvp-10-1 cuda-runtime-10-1 cuda-samples-10-1 cuda-sanitizer-api-10-1 cuda-toolkit-10-1 cuda-tools-10-1 cuda-visual-tools-10-1
  default-jre default-jre-headless dkms fonts-dejavu-extra freeglut3 freeglut3-dev java-common libatk-wrapper-java libatk-wrapper-java-jni libcublas-dev libcublas10 libdrm-dev libgif7 libgl1-mesa-dev
  libglu1-mesa-dev libice-dev libnvidia-cfg1-418 libnvidia-common-418 libnvidia-compute-418 libnvidia-decode-418 libnvidia-encode-418 libnvidia-fbc1-418 libnvidia-gl-418 libnvidia-ifr1-418
  libpthread-stubs0-dev libsm-dev libx11-dev libx11-doc libx11-xcb-dev libxau-dev libxcb-dri2-0-dev libxcb-dri3-dev libxcb-glx0-dev libxcb-present-dev libxcb-randr0-dev libxcb-render0-dev
  libxcb-shape0-dev libxcb-sync-dev libxcb-xfixes0-dev libxcb1-dev libxdamage-dev libxdmcp-dev libxext-dev libxfixes-dev libxi-dev libxmu-dev libxmu-headers libxnvctrl0 libxshmfence-dev libxt-dev
  libxxf86vm-dev mesa-common-dev nsight-compute-2019.4.0 nsight-systems-2019.3.7 nvidia-compute-utils-418 nvidia-dkms-418 nvidia-driver-418 nvidia-kernel-common-418 nvidia-kernel-source-418
  nvidia-modprobe nvidia-prime nvidia-settings nvidia-utils-418 openjdk-11-jre openjdk-11-jre-headless pkg-config screen-resolution-extra x11proto-core-dev x11proto-damage-dev x11proto-dev
  x11proto-fixes-dev x11proto-input-dev x11proto-xext-dev x11proto-xf86vidmode-dev xorg-sgml-doctools xserver-xorg-video-nvidia-418 xtrans-dev
下列软件包将被升级:
  libx11-6 libx11-xcb1
升级了 2 个软件包,新安装了 129 个软件包,要卸载 0 个软件包,有 282 个软件包未被升级。
需要下载 45.0 MB/1,866 MB 的归档。
解压缩后会消耗 4,485 MB 的额外空间。
获取:1 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-license-10-1 10.1.243-1 [16.4 kB]
获取:2 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-misc-headers-10-1 10.1.243-1 [692 kB]
获取:3 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-nvcc-10-1 10.1.243-1 [15.7 MB]  
获取:4 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-cuobjdump-10-1 10.1.243-1 [81.6 kB]
获取:5 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-nvprune-10-1 10.1.243-1 [36.9 kB]
获取:6 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-compiler-10-1 10.1.243-1 [2,534 B]
获取:7 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-nvdisasm-10-1 10.1.243-1 [22.1 MB]
获取:8 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-gdb-10-1 10.1.243-1 [2,773 kB]
获取:9 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-nvprof-10-1 10.1.243-1 [4,016 kB]
获取:10 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-sanitizer-api-10-1 10.1.243-1 [2,153 kB]
获取:11 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-memcheck-10-1 10.1.243-1 [139 kB]
获取:12 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-cudart-10-1 10.1.243-1 [109 kB]
获取:13 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-driver-dev-10-1 10.1.243-1 [11.6 kB]
获取:14 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-cudart-dev-10-1 10.1.243-1 [447 kB]
获取:15 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 java-common all 0.68ubuntu1~18.04.1 [14.5 kB]
获取:16 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-cupti-10-1 10.1.243-1 [11.2 MB]
获取:17 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-gpu-library-advisor-10-1 10.1.243-1 [1,003 kB]
获取:18 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-nvtx-10-1 10.1.243-1 [38.9 kB]
获取:19 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-command-line-tools-10-1 10.1.243-1 [27.3 kB]
获取:20 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-nsight-10-1 10.1.243-1 [2,584 B]
获取:21 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-nvvp-10-1 10.1.243-1 [2,530 B]
获取:22 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-nvrtc-10-1 10.1.243-1 [6,288 kB]
获取:23 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-nvrtc-dev-10-1 10.1.243-1 [8,812 B]
获取:24 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 openjdk-11-jre-headless amd64 11.0.11+9-0ubuntu2~18.04 [37.2 MB]
获取:25 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-cusolver-10-1 10.1.243-1 [71.9 MB]
获取:26 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-cusolver-dev-10-1 10.1.243-1 [14.0 MB]
获取:27 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  libcublas10 10.2.1.243-1 [38.8 MB] 
获取:28 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  libcublas-dev 10.2.1.243-1 [38.9 MB]
获取:29 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-cufft-10-1 10.1.243-1 [84.2 MB]
获取:30 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-cufft-dev-10-1 10.1.243-1 [158 MB]
获取:31 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-curand-10-1 10.1.243-1 [38.9 MB]
获取:32 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-curand-dev-10-1 10.1.243-1 [58.1 MB]
获取:33 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-cusparse-10-1 10.1.243-1 [55.2 MB]                                                                                                         
获取:34 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-cusparse-dev-10-1 10.1.243-1 [55.7 MB]                                                                                                     
获取:35 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-npp-10-1 10.1.243-1 [54.9 MB]                                                                                                              
获取:36 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-npp-dev-10-1 10.1.243-1 [55.7 MB]                                                                                                          
获取:37 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-nvml-dev-10-1 10.1.243-1 [53.1 kB]                                                                                                         
获取:38 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-nvjpeg-10-1 10.1.243-1 [1,213 kB]                                                                                                          
获取:39 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-nvjpeg-dev-10-1 10.1.243-1 [1,153 kB]                                                                                                      
获取:40 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  nsight-compute-2019.4.0 2019.4.0.12-1 [254 MB]                                                                                                  
获取:41 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-nsight-compute-10-1 10.1.243-1 [3,698 B]                                                                                                   
获取:42 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 default-jre-headless amd64 2:1.11-68ubuntu1~18.04.1 [10.9 kB]                                                                        
获取:43 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 ca-certificates-java all 20180516ubuntu1~18.04.1 [12.2 kB]                                                                           
获取:44 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 libgif7 amd64 5.1.4-2ubuntu0.1 [30.9 kB]                                                                                             
获取:45 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 openjdk-11-jre amd64 11.0.11+9-0ubuntu2~18.04 [174 kB]                                                                               
获取:46 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 default-jre amd64 2:1.11-68ubuntu1~18.04.1 [1,076 B]                                                                                 
获取:47 http://cn.archive.ubuntu.com/ubuntu bionic/universe amd64 freeglut3 amd64 2.8.1-3 [73.6 kB]                                                                                                        
获取:48 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 xorg-sgml-doctools all 1:1.11-1 [12.9 kB]                                                                                                    
获取:49 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 x11proto-dev all 2018.4-4 [251 kB]                                                                                                           
获取:50 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 x11proto-core-dev all 2018.4-4 [2,620 B]                                                                                                     
获取:51 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 libxau-dev amd64 1:1.0.8-1ubuntu1 [9,476 B]                                                                                          
获取:52 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libxdmcp-dev amd64 1:1.1.2-3 [25.1 kB]                                                                                                       
获取:53 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 x11proto-input-dev all 2018.4-4 [2,620 B]                                                                                                    
获取:54 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 xtrans-dev all 1.3.5-1 [70.5 kB]                                                                                                             
获取:55 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libpthread-stubs0-dev amd64 0.3-4 [4,068 B]                                                                                                  
获取:56 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 libxcb1-dev amd64 1.13-2~ubuntu18.04 [80.0 kB]                                                                                       
获取:57 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 libx11-dev amd64 2:1.6.4-3ubuntu0.4 [641 kB]                                                                                         
获取:58 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  nsight-systems-2019.3.7 2019.3.7.5-3837e03 [109 MB]                                                                                             
获取:59 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-nsight-systems-10-1 10.1.243-1 [3,130 B]                                                                                                   
获取:60 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 libdrm-dev amd64 2.4.101-2~18.04.1 [126 kB]                                                                                          
获取:61 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 mesa-common-dev amd64 20.0.8-0ubuntu1~18.04.1 [741 kB]                                                                               
获取:62 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 libx11-xcb-dev amd64 2:1.6.4-3ubuntu0.4 [9,764 B]                                                                                    
获取:63 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 libxcb-dri3-dev amd64 1.13-2~ubuntu18.04 [7,384 B]                                                                                   
获取:64 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 libxcb-render0-dev amd64 1.13-2~ubuntu18.04 [18.4 kB]                                                                                
获取:65 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 libxcb-randr0-dev amd64 1.13-2~ubuntu18.04 [20.4 kB]                                                                                 
获取:66 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 libxcb-shape0-dev amd64 1.13-2~ubuntu18.04 [7,144 B]                                                                                 
获取:67 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 libxcb-xfixes0-dev amd64 1.13-2~ubuntu18.04 [11.7 kB]                                                                                
获取:68 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 libxcb-sync-dev amd64 1.13-2~ubuntu18.04 [10.6 kB]                                                                                   
获取:69 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 libxcb-present-dev amd64 1.13-2~ubuntu18.04 [6,972 B]                                                                                
获取:70 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libxshmfence-dev amd64 1.3-1 [3,692 B]                                                                                                       
获取:71 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-nvgraph-10-1 10.1.243-1 [41.7 MB]                                                                                                          
获取:72 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 libxcb-dri2-0-dev amd64 1.13-2~ubuntu18.04 [8,472 B]                                                                                 
获取:73 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 libxcb-glx0-dev amd64 1.13-2~ubuntu18.04 [27.9 kB]                                                                                   
获取:74 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 x11proto-fixes-dev all 1:2018.4-4 [2,620 B]                                                                                                  
获取:75 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libxfixes-dev amd64 1:5.0.3-1 [11.0 kB]                                                                                                      
获取:76 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 x11proto-damage-dev all 1:2018.4-4 [2,620 B]                                                                                                 
获取:77 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libxdamage-dev amd64 1:1.1.4-3 [5,028 B]                                                                                                     
获取:78 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 x11proto-xext-dev all 2018.4-4 [2,620 B]                                                                                                     
获取:79 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libxext-dev amd64 2:1.3.3-1 [82.1 kB]                                                                                                        
获取:80 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 x11proto-xf86vidmode-dev all 2018.4-4 [2,632 B]                                                                                              
获取:81 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-nvgraph-dev-10-1 10.1.243-1 [34.2 MB]                                                                                                      
获取:82 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libxxf86vm-dev amd64 1:1.1.4-1 [13.3 kB]                                                                                                     
获取:83 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 libgl1-mesa-dev amd64 20.0.8-0ubuntu1~18.04.1 [6,180 B]                                                                              
获取:84 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libglu1-mesa-dev amd64 9.0.0-2.1build1 [206 kB]                                                                                              
获取:85 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libice-dev amd64 2:1.0.9-2 [46.8 kB]                                                                                                         
获取:86 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libsm-dev amd64 2:1.2.2-1 [16.2 kB]                                                                                                          
获取:87 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libxt-dev amd64 1:1.1.5-1 [395 kB]                                                                                                           
获取:88 http://cn.archive.ubuntu.com/ubuntu bionic/universe amd64 freeglut3-dev amd64 2.8.1-3 [124 kB]                                                                                                     
获取:89 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libxmu-headers all 2:1.1.2-2 [54.3 kB]                                                                                                       
获取:90 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libxmu-dev amd64 2:1.1.2-2 [49.0 kB]                                                                                                         
获取:91 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libxi-dev amd64 2:1.7.9-1 [186 kB]                                                                                                           
获取:92 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 dkms all 2.3-3ubuntu9.7 [68.1 kB]                                                                                                    
获取:93 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 pkg-config amd64 0.29.1-0ubuntu2 [45.0 kB]                                                                                                   
获取:94 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 screen-resolution-extra all 0.17.3 [11.7 kB]                                                                                                 
获取:95 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 fonts-dejavu-extra all 2.37-1 [1,953 kB]                                                                                                     
获取:96 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libatk-wrapper-java all 0.33.3-20ubuntu0.1 [34.7 kB]                                                                                         
获取:97 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libatk-wrapper-java-jni amd64 0.33.3-20ubuntu0.1 [28.3 kB]                                                                                   
获取:98 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 libx11-doc all 2:1.6.4-3ubuntu0.4 [2,065 kB]                                                                                         
获取:99 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 nvidia-prime all 0.8.16~0.18.04.1 [9,224 B]                                                                                          
获取:100 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-visual-tools-10-1 10.1.243-1 [398 MB]                                                                                                     
获取:101 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-tools-10-1 10.1.243-1 [2,496 B]                                                                                                           
获取:102 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-samples-10-1 10.1.243-1 [64.5 MB]                                                                                                         
获取:103 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-documentation-10-1 10.1.243-1 [53.5 MB]                                                                                                   
获取:104 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-libraries-dev-10-1 10.1.243-1 [2,612 B]                                                                                                   
获取:105 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-toolkit-10-1 10.1.243-1 [2,828 B]                                                                                                         
获取:106 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  libnvidia-common-418 418.87.00-0ubuntu1 [9,984 B]                                                                                              
获取:107 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  libnvidia-compute-418 418.87.00-0ubuntu1 [19.7 MB]                                                                                             
获取:108 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  libnvidia-decode-418 418.87.00-0ubuntu1 [1,245 kB]                                                                                             
获取:109 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  libnvidia-encode-418 418.87.00-0ubuntu1 [48.4 kB]                                                                                              
获取:110 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  libnvidia-fbc1-418 418.87.00-0ubuntu1 [44.1 kB]                                                                                                
获取:111 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  libnvidia-gl-418 418.87.00-0ubuntu1 [32.2 MB]                                                                                                  
获取:112 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  libnvidia-ifr1-418 418.87.00-0ubuntu1 [68.5 kB]                                                                                                
获取:113 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  nvidia-compute-utils-418 418.87.00-0ubuntu1 [73.2 kB]                                                                                          
获取:114 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  nvidia-kernel-source-418 418.87.00-0ubuntu1 [11.2 MB]                                                                                          
获取:115 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  nvidia-kernel-common-418 418.87.00-0ubuntu1 [9,878 B]                                                                                          
获取:116 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  nvidia-dkms-418 418.87.00-0ubuntu1 [26.0 kB]                                                                                                   
获取:117 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  nvidia-utils-418 418.87.00-0ubuntu1 [334 kB]                                                                                                   
获取:118 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  libnvidia-cfg1-418 418.87.00-0ubuntu1 [70.8 kB]                                                                                                
获取:119 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  xserver-xorg-video-nvidia-418 418.87.00-0ubuntu1 [1,559 kB]                                                                                    
获取:120 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  nvidia-driver-418 418.87.00-0ubuntu1 [401 kB]                                                                                                  
获取:121 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  nvidia-modprobe 418.87.00-0ubuntu1 [19.2 kB]                                                                                                   
获取:122 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  libxnvctrl0 418.87.00-0ubuntu1 [19.4 kB]                                                                                                       
获取:123 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  nvidia-settings 418.87.00-0ubuntu1 [966 kB]                                                                                                    
获取:124 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-drivers 418.87.00-1 [2,588 B]                                                                                                             
获取:125 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-libraries-10-1 10.1.243-1 [2,588 B]                                                                                                       
获取:126 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-runtime-10-1 10.1.243-1 [2,532 B]                                                                                                         
获取:127 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-demo-suite-10-1 10.1.243-1 [3,851 kB]                                                                                                     
获取:128 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda-10-1 10.1.243-1 [2,560 B]                                                                                                                 
获取:129 file:/var/cuda-repo-10-1-local-10.1.243-418.87.00  cuda 10.1.243-1 [2,510 B]                                                                                                                      
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正准备解包 .../081-libxdamage-dev_1%3a1.1.4-3_amd64.deb  ...
正在解包 libxdamage-dev:amd64 (1:1.1.4-3) ...
正在选中未选择的软件包 x11proto-xext-dev。
正准备解包 .../082-x11proto-xext-dev_2018.4-4_all.deb  ...
正在解包 x11proto-xext-dev (2018.4-4) ...
正在选中未选择的软件包 libxext-dev:amd64。
正准备解包 .../083-libxext-dev_2%3a1.3.3-1_amd64.deb  ...
正在解包 libxext-dev:amd64 (2:1.3.3-1) ...
正在选中未选择的软件包 x11proto-xf86vidmode-dev。
正准备解包 .../084-x11proto-xf86vidmode-dev_2018.4-4_all.deb  ...
正在解包 x11proto-xf86vidmode-dev (2018.4-4) ...
正在选中未选择的软件包 libxxf86vm-dev:amd64。
正准备解包 .../085-libxxf86vm-dev_1%3a1.1.4-1_amd64.deb  ...
正在解包 libxxf86vm-dev:amd64 (1:1.1.4-1) ...
正在选中未选择的软件包 libgl1-mesa-dev:amd64。
正准备解包 .../086-libgl1-mesa-dev_20.0.8-0ubuntu1~18.04.1_amd64.deb  ...
正在解包 libgl1-mesa-dev:amd64 (20.0.8-0ubuntu1~18.04.1) ...
正在选中未选择的软件包 libglu1-mesa-dev:amd64。
正准备解包 .../087-libglu1-mesa-dev_9.0.0-2.1build1_amd64.deb  ...
正在解包 libglu1-mesa-dev:amd64 (9.0.0-2.1build1) ...
正在选中未选择的软件包 libice-dev:amd64。
正准备解包 .../088-libice-dev_2%3a1.0.9-2_amd64.deb  ...
正在解包 libice-dev:amd64 (2:1.0.9-2) ...
正在选中未选择的软件包 libsm-dev:amd64。
正准备解包 .../089-libsm-dev_2%3a1.2.2-1_amd64.deb  ...
正在解包 libsm-dev:amd64 (2:1.2.2-1) ...
正在选中未选择的软件包 libxt-dev:amd64。
正准备解包 .../090-libxt-dev_1%3a1.1.5-1_amd64.deb  ...
正在解包 libxt-dev:amd64 (1:1.1.5-1) ...
正在选中未选择的软件包 freeglut3-dev:amd64。
正准备解包 .../091-freeglut3-dev_2.8.1-3_amd64.deb  ...
正在解包 freeglut3-dev:amd64 (2.8.1-3) ...
正在选中未选择的软件包 libxmu-headers。
正准备解包 .../092-libxmu-headers_2%3a1.1.2-2_all.deb  ...
正在解包 libxmu-headers (2:1.1.2-2) ...
正在选中未选择的软件包 libxmu-dev:amd64。
正准备解包 .../093-libxmu-dev_2%3a1.1.2-2_amd64.deb  ...
正在解包 libxmu-dev:amd64 (2:1.1.2-2) ...
正在选中未选择的软件包 libxi-dev:amd64。
正准备解包 .../094-libxi-dev_2%3a1.7.9-1_amd64.deb  ...
正在解包 libxi-dev:amd64 (2:1.7.9-1) ...
正在选中未选择的软件包 cuda-samples-10-1。
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正在解包 cuda-samples-10-1 (10.1.243-1) ...
正在选中未选择的软件包 cuda-documentation-10-1。
正准备解包 .../096-cuda-documentation-10-1_10.1.243-1_amd64.deb  ...
正在解包 cuda-documentation-10-1 (10.1.243-1) ...
正在选中未选择的软件包 cuda-libraries-dev-10-1。
正准备解包 .../097-cuda-libraries-dev-10-1_10.1.243-1_amd64.deb  ...
正在解包 cuda-libraries-dev-10-1 (10.1.243-1) ...
正在选中未选择的软件包 cuda-toolkit-10-1。
正准备解包 .../098-cuda-toolkit-10-1_10.1.243-1_amd64.deb  ...
正在解包 cuda-toolkit-10-1 (10.1.243-1) ...
正在选中未选择的软件包 libnvidia-common-418。
正准备解包 .../099-libnvidia-common-418_418.87.00-0ubuntu1_all.deb  ...
Checking for existing driver runfile install
/var/lib/dpkg/tmp.ci/preinst: 6: /var/lib/dpkg/tmp.ci/preinst: [[: not found
正在解包 libnvidia-common-418 (418.87.00-0ubuntu1) ...
正在选中未选择的软件包 libnvidia-compute-418:amd64。
正准备解包 .../100-libnvidia-compute-418_418.87.00-0ubuntu1_amd64.deb  ...
正在解包 libnvidia-compute-418:amd64 (418.87.00-0ubuntu1) ...
正在选中未选择的软件包 libnvidia-decode-418:amd64。
正准备解包 .../101-libnvidia-decode-418_418.87.00-0ubuntu1_amd64.deb  ...
正在解包 libnvidia-decode-418:amd64 (418.87.00-0ubuntu1) ...
正在选中未选择的软件包 libnvidia-encode-418:amd64。
正准备解包 .../102-libnvidia-encode-418_418.87.00-0ubuntu1_amd64.deb  ...
正在解包 libnvidia-encode-418:amd64 (418.87.00-0ubuntu1) ...
正在选中未选择的软件包 libnvidia-fbc1-418:amd64。
正准备解包 .../103-libnvidia-fbc1-418_418.87.00-0ubuntu1_amd64.deb  ...
正在解包 libnvidia-fbc1-418:amd64 (418.87.00-0ubuntu1) ...
正在选中未选择的软件包 libnvidia-gl-418:amd64。
正准备解包 .../104-libnvidia-gl-418_418.87.00-0ubuntu1_amd64.deb  ...
dpkg-query: 没有找到与 libnvidia-gl-410 相匹配的软件包
正在解包 libnvidia-gl-418:amd64 (418.87.00-0ubuntu1) ...
正在选中未选择的软件包 libnvidia-ifr1-418:amd64。
正准备解包 .../105-libnvidia-ifr1-418_418.87.00-0ubuntu1_amd64.deb  ...
正在解包 libnvidia-ifr1-418:amd64 (418.87.00-0ubuntu1) ...
正在选中未选择的软件包 nvidia-compute-utils-418。
正准备解包 .../106-nvidia-compute-utils-418_418.87.00-0ubuntu1_amd64.deb  ...
正在解包 nvidia-compute-utils-418 (418.87.00-0ubuntu1) ...
正在选中未选择的软件包 dkms。
正准备解包 .../107-dkms_2.3-3ubuntu9.7_all.deb  ...
正在解包 dkms (2.3-3ubuntu9.7) ...
正在选中未选择的软件包 nvidia-kernel-source-418。
正准备解包 .../108-nvidia-kernel-source-418_418.87.00-0ubuntu1_amd64.deb  ...
正在解包 nvidia-kernel-source-418 (418.87.00-0ubuntu1) ...
正在选中未选择的软件包 nvidia-kernel-common-418。
正准备解包 .../109-nvidia-kernel-common-418_418.87.00-0ubuntu1_amd64.deb  ...
正在解包 nvidia-kernel-common-418 (418.87.00-0ubuntu1) ...
正在选中未选择的软件包 nvidia-dkms-418。
正准备解包 .../110-nvidia-dkms-418_418.87.00-0ubuntu1_amd64.deb  ...

WARNING: Your driver installation has been altered since it was initially installed; this may happen, for example, if you have since installed the NVIDIA driver through a mechanism other than
         nvidia-installer (such as your distribution's native package management system).  nvidia-installer will attempt to uninstall as best it can.  Please see the file '/var/log/nvidia-uninstall.log'
         for details.


WARNING: Failed to delete some directories. See /var/log/nvidia-uninstall.log for details.

正在解包 nvidia-dkms-418 (418.87.00-0ubuntu1) ...
正在选中未选择的软件包 nvidia-utils-418。
正准备解包 .../111-nvidia-utils-418_418.87.00-0ubuntu1_amd64.deb  ...
正在解包 nvidia-utils-418 (418.87.00-0ubuntu1) ...
正在选中未选择的软件包 libnvidia-cfg1-418:amd64。
正准备解包 .../112-libnvidia-cfg1-418_418.87.00-0ubuntu1_amd64.deb  ...
正在解包 libnvidia-cfg1-418:amd64 (418.87.00-0ubuntu1) ...
正在选中未选择的软件包 xserver-xorg-video-nvidia-418。
正准备解包 .../113-xserver-xorg-video-nvidia-418_418.87.00-0ubuntu1_amd64.deb  ...
正在解包 xserver-xorg-video-nvidia-418 (418.87.00-0ubuntu1) ...
正在选中未选择的软件包 nvidia-driver-418。
正准备解包 .../114-nvidia-driver-418_418.87.00-0ubuntu1_amd64.deb  ...
正在解包 nvidia-driver-418 (418.87.00-0ubuntu1) ...
正在选中未选择的软件包 nvidia-modprobe。
正准备解包 .../115-nvidia-modprobe_418.87.00-0ubuntu1_amd64.deb  ...
正在解包 nvidia-modprobe (418.87.00-0ubuntu1) ...
正在选中未选择的软件包 pkg-config。
正准备解包 .../116-pkg-config_0.29.1-0ubuntu2_amd64.deb  ...
正在解包 pkg-config (0.29.1-0ubuntu2) ...
正在选中未选择的软件包 screen-resolution-extra。
正准备解包 .../117-screen-resolution-extra_0.17.3_all.deb  ...
正在解包 screen-resolution-extra (0.17.3) ...
正在选中未选择的软件包 libxnvctrl0:amd64。
正准备解包 .../118-libxnvctrl0_418.87.00-0ubuntu1_amd64.deb  ...
正在解包 libxnvctrl0:amd64 (418.87.00-0ubuntu1) ...
正在选中未选择的软件包 nvidia-settings。
正准备解包 .../119-nvidia-settings_418.87.00-0ubuntu1_amd64.deb  ...
正在解包 nvidia-settings (418.87.00-0ubuntu1) ...
正在选中未选择的软件包 cuda-drivers。
正准备解包 .../120-cuda-drivers_418.87.00-1_amd64.deb  ...
正在解包 cuda-drivers (418.87.00-1) ...
正在选中未选择的软件包 cuda-libraries-10-1。
正准备解包 .../121-cuda-libraries-10-1_10.1.243-1_amd64.deb  ...
正在解包 cuda-libraries-10-1 (10.1.243-1) ...
正在选中未选择的软件包 cuda-runtime-10-1。
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正在解包 cuda-runtime-10-1 (10.1.243-1) ...
正在选中未选择的软件包 cuda-demo-suite-10-1。
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正在解包 cuda-demo-suite-10-1 (10.1.243-1) ...
正在选中未选择的软件包 cuda-10-1。
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正在解包 cuda-10-1 (10.1.243-1) ...
正在选中未选择的软件包 cuda。
正准备解包 .../125-cuda_10.1.243-1_amd64.deb  ...
正在解包 cuda (10.1.243-1) ...
正在选中未选择的软件包 fonts-dejavu-extra。
正准备解包 .../126-fonts-dejavu-extra_2.37-1_all.deb  ...
正在解包 fonts-dejavu-extra (2.37-1) ...
正在选中未选择的软件包 libatk-wrapper-java。
正准备解包 .../127-libatk-wrapper-java_0.33.3-20ubuntu0.1_all.deb  ...
正在解包 libatk-wrapper-java (0.33.3-20ubuntu0.1) ...
正在选中未选择的软件包 libatk-wrapper-java-jni:amd64。
正准备解包 .../128-libatk-wrapper-java-jni_0.33.3-20ubuntu0.1_amd64.deb  ...
正在解包 libatk-wrapper-java-jni:amd64 (0.33.3-20ubuntu0.1) ...
正在选中未选择的软件包 libx11-doc。
正准备解包 .../129-libx11-doc_2%3a1.6.4-3ubuntu0.4_all.deb  ...
正在解包 libx11-doc (2:1.6.4-3ubuntu0.4) ...
正在选中未选择的软件包 nvidia-prime。
正准备解包 .../130-nvidia-prime_0.8.16~0.18.04.1_all.deb  ...
正在解包 nvidia-prime (0.8.16~0.18.04.1) ...
正在设置 libnvidia-common-418 (418.87.00-0ubuntu1) ...
正在设置 nvidia-kernel-source-418 (418.87.00-0ubuntu1) ...
正在设置 nvidia-prime (0.8.16~0.18.04.1) ...
正在设置 nsight-compute-2019.4.0 (2019.4.0.12-1) ...
正在设置 libxshmfence-dev:amd64 (1.3-1) ...
正在设置 libpthread-stubs0-dev:amd64 (0.3-4) ...
正在设置 libnvidia-compute-418:amd64 (418.87.00-0ubuntu1) ...
正在设置 libdrm-dev:amd64 (2.4.101-2~18.04.1) ...
正在设置 xorg-sgml-doctools (1:1.11-1) ...
正在设置 java-common (0.68ubuntu1~18.04.1) ...
正在设置 nvidia-utils-418 (418.87.00-0ubuntu1) ...
正在设置 libx11-6:amd64 (2:1.6.4-3ubuntu0.4) ...
正在设置 nvidia-kernel-common-418 (418.87.00-0ubuntu1) ...
update-initramfs: deferring update (trigger activated)
正在设置 libgif7:amd64 (5.1.4-2ubuntu0.1) ...
正在设置 cuda-license-10-1 (10.1.243-1) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and 
conditions of the EULA (End User License Agreement). The EULA is located
at /usr/local/cuda-10.1/doc/EULA.txt. The EULA can also be found at
http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the
terms and conditions of the EULA, do not use the software.

正在设置 cuda-cusparse-10-1 (10.1.243-1) ...
正在设置 nsight-systems-2019.3.7 (2019.3.7.5-3837e03) ...
update-alternatives: 使用 /opt/nvidia/nsight-systems/2019.3.7/Target-x86_64/x86_64/nsys 来在自动模式中提供 /usr/local/bin/nsys (nsys)
update-alternatives: 使用 /opt/nvidia/nsight-systems/2019.3.7/Host-x86_64/nsight-sys 来在自动模式中提供 /usr/local/bin/nsight-sys (nsight-sys)
update-alternatives: 使用 /opt/nvidia/nsight-systems/2019.3.7/Host-x86_64/nsys-exporter 来在自动模式中提供 /usr/local/bin/nsys-exporter (nsys-exporter)
正在设置 cuda-nvjpeg-10-1 (10.1.243-1) ...
正在设置 x11proto-dev (2018.4-4) ...
正在设置 cuda-nvdisasm-10-1 (10.1.243-1) ...
正在设置 cuda-nvml-dev-10-1 (10.1.243-1) ...
正在设置 cuda-sanitizer-api-10-1 (10.1.243-1) ...
正在设置 cuda-nvjpeg-dev-10-1 (10.1.243-1) ...
正在设置 cuda-cufft-10-1 (10.1.243-1) ...
正在设置 cuda-nvprof-10-1 (10.1.243-1) ...
正在设置 x11proto-damage-dev (1:2018.4-4) ...
正在设置 pkg-config (0.29.1-0ubuntu2) ...
正在设置 cuda-nvrtc-10-1 (10.1.243-1) ...
正在设置 libx11-xcb1:amd64 (2:1.6.4-3ubuntu0.4) ...
正在设置 xtrans-dev (1.3.5-1) ...
正在设置 x11proto-xext-dev (2018.4-4) ...
正在设置 dkms (2.3-3ubuntu9.7) ...
正在设置 libcublas10 (10.2.1.243-1) ...
正在设置 libcublas-dev (10.2.1.243-1) ...
正在设置 libxdmcp-dev:amd64 (1:1.1.2-3) ...
正在设置 libnvidia-gl-418:amd64 (418.87.00-0ubuntu1) ...
正在设置 cuda-npp-10-1 (10.1.243-1) ...
正在设置 libice-dev:amd64 (2:1.0.9-2) ...
正在设置 nvidia-compute-utils-418 (418.87.00-0ubuntu1) ...
警告:您指定的主目录 /nonexistent 不能够访问:No such file or directory
正在添加系统用户"nvidia-persistenced" (UID 122)...
正在添加新组"nvidia-persistenced" (GID 127)...
正在将新用户"nvidia-persistenced" (UID 122)添加到组"nvidia-persistenced"...
无法创建主目录"/nonexistent"
Created symlink /etc/systemd/system/multi-user.target.wants/nvidia-persistenced.service → /lib/systemd/system/nvidia-persistenced.service.
正在设置 cuda-cufft-dev-10-1 (10.1.243-1) ...
正在设置 libnvidia-cfg1-418:amd64 (418.87.00-0ubuntu1) ...
正在设置 screen-resolution-extra (0.17.3) ...
正在设置 nvidia-modprobe (418.87.00-0ubuntu1) ...
正在设置 libx11-doc (2:1.6.4-3ubuntu0.4) ...
正在设置 nvidia-dkms-418 (418.87.00-0ubuntu1) ...
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/lenovo_thinkpad
DEBUG:Parsing /usr/share/ubuntu-drivers-common/quirks/put_your_quirks_here
DEBUG:Parsing /usr/share/ubuntu-drivers-common/quirks/dell_latitude
Loading new nvidia-418.87.00 DKMS files...
Building for 5.4.0-81-generic
Building for architecture x86_64
Building initial module for 5.4.0-81-generic
Error! Bad return status for module build on kernel: 5.4.0-81-generic (x86_64)
Consult /var/lib/dkms/nvidia/418.87.00/build/make.log for more information.
正在设置 fonts-dejavu-extra (2.37-1) ...
正在设置 cuda-driver-dev-10-1 (10.1.243-1) ...
正在设置 cuda-cuobjdump-10-1 (10.1.243-1) ...
正在设置 libatk-wrapper-java (0.33.3-20ubuntu0.1) ...
正在设置 libnvidia-ifr1-418:amd64 (418.87.00-0ubuntu1) ...
正在设置 cuda-nsight-systems-10-1 (10.1.243-1) ...
正在设置 cuda-gdb-10-1 (10.1.243-1) ...
正在设置 x11proto-input-dev (2018.4-4) ...
正在设置 libxnvctrl0:amd64 (418.87.00-0ubuntu1) ...
正在设置 cuda-nsight-compute-10-1 (10.1.243-1) ...
正在设置 libnvidia-fbc1-418:amd64 (418.87.00-0ubuntu1) ...
正在设置 cuda-cudart-10-1 (10.1.243-1) ...
正在设置 freeglut3:amd64 (2.8.1-3) ...
正在设置 libsm-dev:amd64 (2:1.2.2-1) ...
正在设置 cuda-npp-dev-10-1 (10.1.243-1) ...
正在设置 xserver-xorg-video-nvidia-418 (418.87.00-0ubuntu1) ...
正在设置 libnvidia-decode-418:amd64 (418.87.00-0ubuntu1) ...
正在设置 x11proto-core-dev (2018.4-4) ...
正在设置 cuda-cusolver-10-1 (10.1.243-1) ...
正在设置 cuda-misc-headers-10-1 (10.1.243-1) ...
正在设置 cuda-nvtx-10-1 (10.1.243-1) ...
正在设置 cuda-curand-10-1 (10.1.243-1) ...
正在设置 cuda-cusparse-dev-10-1 (10.1.243-1) ...
正在设置 cuda-gpu-library-advisor-10-1 (10.1.243-1) ...
正在设置 cuda-nvgraph-10-1 (10.1.243-1) ...
正在设置 x11proto-fixes-dev (1:2018.4-4) ...
正在设置 cuda-nvprune-10-1 (10.1.243-1) ...
正在设置 cuda-memcheck-10-1 (10.1.243-1) ...
正在设置 cuda-cudart-dev-10-1 (10.1.243-1) ...
正在设置 x11proto-xf86vidmode-dev (2018.4-4) ...
正在设置 libxau-dev:amd64 (1:1.0.8-1ubuntu1) ...
正在设置 cuda-nvrtc-dev-10-1 (10.1.243-1) ...
正在设置 nvidia-settings (418.87.00-0ubuntu1) ...
正在设置 cuda-curand-dev-10-1 (10.1.243-1) ...
正在设置 libatk-wrapper-java-jni:amd64 (0.33.3-20ubuntu0.1) ...
正在设置 cuda-cusolver-dev-10-1 (10.1.243-1) ...
正在设置 libxcb1-dev:amd64 (1.13-2~ubuntu18.04) ...
正在设置 libxcb-glx0-dev:amd64 (1.13-2~ubuntu18.04) ...
正在设置 libx11-dev:amd64 (2:1.6.4-3ubuntu0.4) ...
正在设置 libxxf86vm-dev:amd64 (1:1.1.4-1) ...
正在设置 libxfixes-dev:amd64 (1:5.0.3-1) ...
正在设置 cuda-nvgraph-dev-10-1 (10.1.243-1) ...
正在设置 libxcb-sync-dev:amd64 (1.13-2~ubuntu18.04) ...
正在设置 libx11-xcb-dev:amd64 (2:1.6.4-3ubuntu0.4) ...
正在设置 libnvidia-encode-418:amd64 (418.87.00-0ubuntu1) ...
正在设置 libxt-dev:amd64 (1:1.1.5-1) ...
正在设置 cuda-libraries-10-1 (10.1.243-1) ...
正在设置 cuda-nvcc-10-1 (10.1.243-1) ...
正在设置 mesa-common-dev:amd64 (20.0.8-0ubuntu1~18.04.1) ...
正在设置 libxmu-headers (2:1.1.2-2) ...
正在设置 nvidia-driver-418 (418.87.00-0ubuntu1) ...
正在设置 libxdamage-dev:amd64 (1:1.1.4-3) ...
正在设置 cuda-compiler-10-1 (10.1.243-1) ...
正在设置 libxcb-dri2-0-dev:amd64 (1.13-2~ubuntu18.04) ...
正在设置 libxcb-render0-dev:amd64 (1.13-2~ubuntu18.04) ...
正在设置 cuda-drivers (418.87.00-1) ...
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正在设置 libxext-dev:amd64 (2:1.3.3-1) ...
正在设置 libxcb-shape0-dev:amd64 (1.13-2~ubuntu18.04) ...
正在设置 cuda-libraries-dev-10-1 (10.1.243-1) ...
正在设置 libxi-dev:amd64 (2:1.7.9-1) ...
正在设置 cuda-cupti-10-1 (10.1.243-1) ...
正在设置 libxcb-randr0-dev:amd64 (1.13-2~ubuntu18.04) ...
正在设置 libxmu-dev:amd64 (2:1.1.2-2) ...
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正在设置 cuda-runtime-10-1 (10.1.243-1) ...
正在设置 cuda-command-line-tools-10-1 (10.1.243-1) ...
正在设置 cuda-demo-suite-10-1 (10.1.243-1) ...
正在设置 libxcb-present-dev:amd64 (1.13-2~ubuntu18.04) ...
正在设置 libgl1-mesa-dev:amd64 (20.0.8-0ubuntu1~18.04.1) ...
正在设置 libglu1-mesa-dev:amd64 (9.0.0-2.1build1) ...
正在设置 freeglut3-dev:amd64 (2.8.1-3) ...
正在设置 cuda-samples-10-1 (10.1.243-1) ...
正在设置 cuda-documentation-10-1 (10.1.243-1) ...
正在设置 openjdk-11-jre-headless:amd64 (11.0.11+9-0ubuntu2~18.04) ...
update-alternatives: 使用 /usr/lib/jvm/java-11-openjdk-amd64/bin/java 来在自动模式中提供 /usr/bin/java (java)
update-alternatives: 使用 /usr/lib/jvm/java-11-openjdk-amd64/bin/jjs 来在自动模式中提供 /usr/bin/jjs (jjs)
update-alternatives: 使用 /usr/lib/jvm/java-11-openjdk-amd64/bin/keytool 来在自动模式中提供 /usr/bin/keytool (keytool)
update-alternatives: 使用 /usr/lib/jvm/java-11-openjdk-amd64/bin/rmid 来在自动模式中提供 /usr/bin/rmid (rmid)
update-alternatives: 使用 /usr/lib/jvm/java-11-openjdk-amd64/bin/rmiregistry 来在自动模式中提供 /usr/bin/rmiregistry (rmiregistry)
update-alternatives: 使用 /usr/lib/jvm/java-11-openjdk-amd64/bin/pack200 来在自动模式中提供 /usr/bin/pack200 (pack200)
update-alternatives: 使用 /usr/lib/jvm/java-11-openjdk-amd64/bin/unpack200 来在自动模式中提供 /usr/bin/unpack200 (unpack200)
update-alternatives: 使用 /usr/lib/jvm/java-11-openjdk-amd64/lib/jexec 来在自动模式中提供 /usr/bin/jexec (jexec)
正在设置 default-jre-headless (2:1.11-68ubuntu1~18.04.1) ...
正在设置 openjdk-11-jre:amd64 (11.0.11+9-0ubuntu2~18.04) ...
正在设置 ca-certificates-java (20180516ubuntu1~18.04.1) ...
head: 无法打开'/etc/ssl/certs/java/cacerts' 读取数据: 没有那个文件或目录
Adding debian:GlobalSign_Root_CA_-_R6.pem
Adding debian:IdenTrust_Commercial_Root_CA_1.pem
Adding debian:GeoTrust_Universal_CA.pem
Adding debian:ssl-cert-snakeoil.pem
Adding debian:Security_Communication_RootCA2.pem
Adding debian:TrustCor_ECA-1.pem
Adding debian:Starfield_Class_2_CA.pem
Adding debian:Trustis_FPS_Root_CA.pem
Adding debian:GeoTrust_Global_CA.pem
Adding debian:thawte_Primary_Root_CA_-_G2.pem
Adding debian:D-TRUST_Root_Class_3_CA_2_2009.pem
Adding debian:SSL.com_Root_Certification_Authority_RSA.pem
Adding debian:QuoVadis_Root_CA_3.pem
Adding debian:TrustCor_RootCert_CA-2.pem
Adding debian:Certum_Trusted_Network_CA.pem
Adding debian:CA_Disig_Root_R2.pem
Adding debian:NetLock_Arany_=Class_Gold=_Főtanúsítvány.pem
Adding debian:ePKI_Root_Certification_Authority.pem
Adding debian:DigiCert_Assured_ID_Root_G3.pem
Adding debian:Security_Communication_Root_CA.pem
Adding debian:EC-ACC.pem
Adding debian:TWCA_Root_Certification_Authority.pem
Adding debian:GDCA_TrustAUTH_R5_ROOT.pem
Adding debian:Amazon_Root_CA_3.pem
Adding debian:Hellenic_Academic_and_Research_Institutions_RootCA_2011.pem
Adding debian:VeriSign_Class_3_Public_Primary_Certification_Authority_-_G4.pem
Adding debian:TUBITAK_Kamu_SM_SSL_Kok_Sertifikasi_-_Surum_1.pem
Adding debian:OISTE_WISeKey_Global_Root_GB_CA.pem
Adding debian:Network_Solutions_Certificate_Authority.pem
Adding debian:Secure_Global_CA.pem
Adding debian:Actalis_Authentication_Root_CA.pem
Adding debian:Hellenic_Academic_and_Research_Institutions_ECC_RootCA_2015.pem
Adding debian:DigiCert_Global_Root_G2.pem
Adding debian:AffirmTrust_Networking.pem
Adding debian:T-TeleSec_GlobalRoot_Class_3.pem
Adding debian:Amazon_Root_CA_4.pem
Adding debian:GeoTrust_Primary_Certification_Authority_-_G2.pem
Adding debian:DigiCert_Assured_ID_Root_CA.pem
Adding debian:Entrust_Root_Certification_Authority_-_EC1.pem
Adding debian:TWCA_Global_Root_CA.pem
Adding debian:Staat_der_Nederlanden_EV_Root_CA.pem
Adding debian:Entrust.net_Premium_2048_Secure_Server_CA.pem
Adding debian:QuoVadis_Root_CA_2.pem
Adding debian:USERTrust_RSA_Certification_Authority.pem
Adding debian:Hongkong_Post_Root_CA_1.pem
Adding debian:LuxTrust_Global_Root_2.pem
Adding debian:GeoTrust_Universal_CA_2.pem
Adding debian:IdenTrust_Public_Sector_Root_CA_1.pem
Adding debian:SecureSign_RootCA11.pem
Adding debian:D-TRUST_Root_Class_3_CA_2_EV_2009.pem
Adding debian:Buypass_Class_3_Root_CA.pem
Adding debian:Certum_Trusted_Network_CA_2.pem
Adding debian:OISTE_WISeKey_Global_Root_GA_CA.pem
Adding debian:Entrust_Root_Certification_Authority.pem
Adding debian:SSL.com_EV_Root_Certification_Authority_RSA_R2.pem
Adding debian:Verisign_Class_3_Public_Primary_Certification_Authority_-_G3.pem
Adding debian:Taiwan_GRCA.pem
Adding debian:DigiCert_Global_Root_CA.pem
Adding debian:Entrust_Root_Certification_Authority_-_G2.pem
Adding debian:Buypass_Class_2_Root_CA.pem
Adding debian:AffirmTrust_Premium.pem
Adding debian:Amazon_Root_CA_1.pem
Adding debian:Staat_der_Nederlanden_Root_CA_-_G3.pem
Adding debian:E-Tugra_Certification_Authority.pem
Adding debian:Izenpe.com.pem
Adding debian:Certplus_Class_2_Primary_CA.pem
Adding debian:certSIGN_ROOT_CA.pem
Adding debian:GlobalSign_Root_CA_-_R3.pem
Adding debian:Amazon_Root_CA_2.pem
Adding debian:SSL.com_Root_Certification_Authority_ECC.pem
Adding debian:GlobalSign_Root_CA.pem
Adding debian:Comodo_AAA_Services_root.pem
Adding debian:Certinomis_-_Root_CA.pem
Adding debian:thawte_Primary_Root_CA.pem
Adding debian:AffirmTrust_Commercial.pem
Adding debian:Microsec_e-Szigno_Root_CA_2009.pem
Adding debian:AffirmTrust_Premium_ECC.pem
Adding debian:DigiCert_Trusted_Root_G4.pem
Adding debian:Go_Daddy_Root_Certificate_Authority_-_G2.pem
Adding debian:Staat_der_Nederlanden_Root_CA_-_G2.pem
Adding debian:ACCVRAIZ1.pem
Adding debian:QuoVadis_Root_CA_1_G3.pem
Adding debian:Starfield_Services_Root_Certificate_Authority_-_G2.pem
Adding debian:QuoVadis_Root_CA_3_G3.pem
Adding debian:Sonera_Class_2_Root_CA.pem
Adding debian:SwissSign_Gold_CA_-_G2.pem
Adding debian:Baltimore_CyberTrust_Root.pem
Adding debian:Chambers_of_Commerce_Root_-_2008.pem
Adding debian:OISTE_WISeKey_Global_Root_GC_CA.pem
Adding debian:GlobalSign_Root_CA_-_R2.pem
Adding debian:SSL.com_EV_Root_Certification_Authority_ECC.pem
Adding debian:VeriSign_Universal_Root_Certification_Authority.pem
Adding debian:DigiCert_High_Assurance_EV_Root_CA.pem
Adding debian:DigiCert_Global_Root_G3.pem
Adding debian:AC_RAIZ_FNMT-RCM.pem
Adding debian:Autoridad_de_Certificacion_Firmaprofesional_CIF_A62634068.pem
Adding debian:COMODO_Certification_Authority.pem
Adding debian:thawte_Primary_Root_CA_-_G3.pem
Adding debian:T-TeleSec_GlobalRoot_Class_2.pem
Adding debian:GeoTrust_Primary_Certification_Authority_-_G3.pem
Adding debian:QuoVadis_Root_CA.pem
Adding debian:COMODO_ECC_Certification_Authority.pem
Adding debian:Cybertrust_Global_Root.pem
Adding debian:GlobalSign_ECC_Root_CA_-_R5.pem
Adding debian:TrustCor_RootCert_CA-1.pem
Adding debian:SwissSign_Silver_CA_-_G2.pem
Adding debian:Deutsche_Telekom_Root_CA_2.pem
Adding debian:Certigna.pem
Adding debian:USERTrust_ECC_Certification_Authority.pem
Adding debian:COMODO_RSA_Certification_Authority.pem
Adding debian:Starfield_Root_Certificate_Authority_-_G2.pem
Adding debian:VeriSign_Class_3_Public_Primary_Certification_Authority_-_G5.pem
Adding debian:XRamp_Global_CA_Root.pem
Adding debian:CFCA_EV_ROOT.pem
Adding debian:SecureTrust_CA.pem
Adding debian:DST_Root_CA_X3.pem
Adding debian:DigiCert_Assured_ID_Root_G2.pem
Adding debian:ISRG_Root_X1.pem
Adding debian:Hellenic_Academic_and_Research_Institutions_RootCA_2015.pem
Adding debian:EE_Certification_Centre_Root_CA.pem
Adding debian:QuoVadis_Root_CA_2_G3.pem
Adding debian:GlobalSign_ECC_Root_CA_-_R4.pem
Adding debian:Global_Chambersign_Root_-_2008.pem
Adding debian:SZAFIR_ROOT_CA2.pem
Adding debian:TeliaSonera_Root_CA_v1.pem
Adding debian:Atos_TrustedRoot_2011.pem
Adding debian:Go_Daddy_Class_2_CA.pem
Adding debian:GeoTrust_Primary_Certification_Authority.pem
done.
正在设置 default-jre (2:1.11-68ubuntu1~18.04.1) ...
正在设置 cuda-nsight-10-1 (10.1.243-1) ...
正在设置 cuda-nvvp-10-1 (10.1.243-1) ...
正在设置 cuda-visual-tools-10-1 (10.1.243-1) ...
正在设置 cuda-tools-10-1 (10.1.243-1) ...
正在设置 cuda-toolkit-10-1 (10.1.243-1) ...
正在设置 cuda-10-1 (10.1.243-1) ...
正在设置 cuda (10.1.243-1) ...
正在处理用于 man-db (2.8.3-2ubuntu0.1) 的触发器 ...
正在处理用于 gnome-menus (3.13.3-11ubuntu1.1) 的触发器 ...
正在处理用于 dbus (1.12.2-1ubuntu1.2) 的触发器 ...
正在处理用于 ca-certificates (20190110~18.04.1) 的触发器 ...
Updating certificates in /etc/ssl/certs...
0 added, 0 removed; done.
Running hooks in /etc/ca-certificates/update.d...

done.
done.
正在处理用于 hicolor-icon-theme (0.17-2) 的触发器 ...
正在处理用于 fontconfig (2.12.6-0ubuntu2) 的触发器 ...
正在处理用于 mime-support (3.60ubuntu1) 的触发器 ...
正在处理用于 desktop-file-utils (0.23-1ubuntu3.18.04.2) 的触发器 ...
正在处理用于 libc-bin (2.27-3ubuntu1.2) 的触发器 ...
正在处理用于 initramfs-tools (0.130ubuntu3.9) 的触发器 ...
update-initramfs: Generating /boot/initrd.img-5.4.0-81-generic
I: The initramfs will attempt to resume from /dev/sda7
I: (UUID=0defca3c-fb26-472d-b207-45c7cfb2fb2e)
I: Set the RESUME variable to override this.
czl@czl-RedmiBook-14:~/cuda$ 

在.bashrc中添加环境变量:

export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda-10.1/lib64
export PATH=$PATH:/usr/local/cuda-10.1/bin
export CUDA_HOME=$CUDA_HOME:/usr/local/cuda-10.1

之后执行source .bashrc

验证:

进入目录

/usr/local/cuda-10.1/samples/1_Utilities/deviceQuery

执行编译

czl@czl-RedmiBook-14:/usr/local/cuda-10.1/samples/1_Utilities/deviceQuery$ sudo make
[sudo] czl 的密码: 
/usr/local/cuda-10.1/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-10.1/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
czl@czl-RedmiBook-14:/usr/local/cuda-10.1/samples/1_Utilities/deviceQuery$

运行./deviceQuery

czl@czl-RedmiBook-14:/usr/local/cuda-10.1/samples/1_Utilities/deviceQuery$ ./deviceQuery 
./deviceQuery Starting...

 CUDA Device Query (Runtime API) version (CUDART static linking)

Detected 1 CUDA Capable device(s)

Device 0: "NVIDIA GeForce MX250"
  CUDA Driver Version / Runtime Version          11.4 / 10.1
  CUDA Capability Major/Minor version number:    6.1
  Total amount of global memory:                 2003 MBytes (2099904512 bytes)
  ( 3) Multiprocessors, (128) CUDA Cores/MP:     384 CUDA Cores
  GPU Max Clock rate:                            1582 MHz (1.58 GHz)
  Memory Clock rate:                             3504 Mhz
  Memory Bus Width:                              64-bit
  L2 Cache Size:                                 524288 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 / 2 / 0
  Compute Mode:
     < Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >

deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 11.4, CUDA Runtime Version = 10.1, NumDevs = 1
Result = PASS
czl@czl-RedmiBook-14:/usr/local/cuda-10.1/samples/1_Utilities/deviceQuery$ 

安装CUDANN

除了要保证和CUDA的版本匹配之外,没有什么需要注意的,下载链接在:

NVIDIA cuDNN | NVIDIA Developerhttps://developer.nvidia.com/zh-cn/cudnn

Ubuntu18.04安装CUDA深度学习环境_第18张图片

内容: Ubuntu18.04安装CUDA深度学习环境_第19张图片

增加头文件目录和库目录的可读属性

czl@czl-RedmiBook-14:~/下载/cuda$ ls
include  lib64  NVIDIA_SLA_cuDNN_Support.txt
czl@czl-RedmiBook-14:~/下载/cuda$ cd include/
czl@czl-RedmiBook-14:~/下载/cuda/include$ ls
cudnn_adv_infer.h  cudnn_adv_train.h  cudnn_backend.h  cudnn_cnn_infer.h  cudnn_cnn_train.h  cudnn.h  cudnn_ops_infer.h  cudnn_ops_train.h  cudnn_version.h
czl@czl-RedmiBook-14:~/下载/cuda/include$ sudo chmod a+r *
czl@czl-RedmiBook-14:~/下载/cuda/include$ cd ..
czl@czl-RedmiBook-14:~/下载/cuda$ ls
include  lib64  NVIDIA_SLA_cuDNN_Support.txt
czl@czl-RedmiBook-14:~/下载/cuda$ cd lib64/
czl@czl-RedmiBook-14:~/下载/cuda/lib64$ sudo chmod a+r *
czl@czl-RedmiBook-14:~/下载/cuda/lib64$ cd ..
czl@czl-RedmiBook-14:~/下载/cuda$ ls
include  lib64  NVIDIA_SLA_cuDNN_Support.txt
czl@czl-RedmiBook-14:~/下载/cuda$ 

 安装,手工将头文件和库文件拷贝到/usr/local/cuda-10.1/目录下的include和lib64目录中。

czl@czl-RedmiBook-14:~/下载/cuda/include$ sudo cp * /usr/local/cuda-10.1/include/
czl@czl-RedmiBook-14:~/下载/cuda/include$ cd ..
czl@czl-RedmiBook-14:~/下载/cuda$ cd lib64/  
czl@czl-RedmiBook-14:~/下载/cuda/lib64$ sudo cp * /usr/local/cuda-10.1/lib64/
czl@czl-RedmiBook-14:~/下载/cuda/lib64$ 

查看版本,cudnn_version.h

Ubuntu18.04安装CUDA深度学习环境_第20张图片

基础验证:

用例在/usr/local/cuda-10.1/samples/1_Utilities目录下

czl@czl-RedmiBook-14:/usr/local/cuda-10.1/samples/1_Utilities$ ls
bandwidthTest  deviceQuery  deviceQueryDrv  p2pBandwidthLatencyTest  topologyQuery  UnifiedMemoryPerf
czl@czl-RedmiBook-14:/usr/local/cuda-10.1/samples/1_Utilities$ cd topologyQuery/
czl@czl-RedmiBook-14:/usr/local/cuda-10.1/samples/1_Utilities/topologyQuery$ ls
Makefile  NsightEclipse.xml  readme.txt  topologyQuery.cu
czl@czl-RedmiBook-14:/usr/local/cuda-10.1/samples/1_Utilities/topologyQuery$ sudo make
[sudo] czl 的密码: 
/usr/local/cuda-10.1/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 topologyQuery.o -c topologyQuery.cu

/usr/local/cuda-10.1/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 topologyQuery topologyQuery.o 
mkdir -p ../../bin/x86_64/linux/release
cp topologyQuery ../../bin/x86_64/linux/release
czl@czl-RedmiBook-14:/usr/local/cuda-10.1/samples/1_Utilities/topologyQuery$ 
czl@czl-RedmiBook-14:/usr/local/cuda-10.1/samples/1_Utilities/topologyQuery$ ./topologyQuery 
GPU0 <-> CPU:
  * Atomic Supported: no
czl@czl-RedmiBook-14:/usr/local/cuda-10.1/samples/1_Utilities/topologyQuery$ cd ..
czl@czl-RedmiBook-14:/usr/local/cuda-10.1/samples/1_Utilities$ ls
bandwidthTest  deviceQuery  deviceQueryDrv  p2pBandwidthLatencyTest  topologyQuery  UnifiedMemoryPerf
czl@czl-RedmiBook-14:/usr/local/cuda-10.1/samples/1_Utilities$ cd bandwidthTest/
czl@czl-RedmiBook-14:/usr/local/cuda-10.1/samples/1_Utilities/bandwidthTest$ sudo make
/usr/local/cuda-10.1/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 bandwidthTest.o -c bandwidthTest.cu
/usr/local/cuda-10.1/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 bandwidthTest bandwidthTest.o 
mkdir -p ../../bin/x86_64/linux/release
cp bandwidthTest ../../bin/x86_64/linux/release
czl@czl-RedmiBook-14:/usr/local/cuda-10.1/samples/1_Utilities/bandwidthTest$ sudo ./bandwidthTest 
[CUDA Bandwidth Test] - Starting...
Running on...

 Device 0: NVIDIA GeForce MX250
 Quick Mode

 Host to Device Bandwidth, 1 Device(s)
 PINNED Memory Transfers
   Transfer Size (Bytes)	Bandwidth(GB/s)
   32000000			2.9

 Device to Host Bandwidth, 1 Device(s)
 PINNED Memory Transfers
   Transfer Size (Bytes)	Bandwidth(GB/s)
   32000000			3.2

 Device to Device Bandwidth, 1 Device(s)
 PINNED Memory Transfers
   Transfer Size (Bytes)	Bandwidth(GB/s)
   32000000			48.8

Result = PASS

NOTE: The CUDA Samples are not meant for performance measurements. Results may vary when GPU Boost is enabled.
czl@czl-RedmiBook-14:/usr/local/cuda-10.1/samples/1_Utilities/bandwidthTest$ cd ..
czl@czl-RedmiBook-14:/usr/local/cuda-10.1/samples/1_Utilities$ ls
bandwidthTest  deviceQuery  deviceQueryDrv  p2pBandwidthLatencyTest  topologyQuery  UnifiedMemoryPerf
czl@czl-RedmiBook-14:/usr/local/cuda-10.1/samples/1_Utilities$ cd deviceQueryDrv/
czl@czl-RedmiBook-14:/usr/local/cuda-10.1/samples/1_Utilities/deviceQueryDrv$ ls
deviceQueryDrv.cpp  Makefile  NsightEclipse.xml  readme.txt
czl@czl-RedmiBook-14:/usr/local/cuda-10.1/samples/1_Utilities/deviceQueryDrv$ sudo make
/usr/local/cuda-10.1/bin/nvcc -ccbin g++ -I../../common/inc  -m64    -gencode arch=compute_30,code=compute_30 -o deviceQueryDrv.o -c deviceQueryDrv.cpp
/usr/local/cuda-10.1/bin/nvcc -ccbin g++   -m64      -gencode arch=compute_30,code=compute_30 -o deviceQueryDrv deviceQueryDrv.o  -L/usr/local/cuda-10.1/lib64/stubs -lcuda
mkdir -p ../../bin/x86_64/linux/release
cp deviceQueryDrv ../../bin/x86_64/linux/release
czl@czl-RedmiBook-14:/usr/local/cuda-10.1/samples/1_Utilities/deviceQueryDrv$ sudo ./deviceQueryDrv 
./deviceQueryDrv Starting...

CUDA Device Query (Driver API) statically linked version 
Detected 1 CUDA Capable device(s)

Device 0: "NVIDIA GeForce MX250"
  CUDA Driver Version:                           11.4
  CUDA Capability Major/Minor version number:    6.1
  Total amount of global memory:                 2003 MBytes (2099904512 bytes)
  ( 3) Multiprocessors, (128) CUDA Cores/MP:     384 CUDA Cores
  GPU Max Clock rate:                            1582 MHz (1.58 GHz)
  Memory Clock rate:                             3504 Mhz
  Memory Bus Width:                              64-bit
  L2 Cache Size:                                 524288 bytes
  Max Texture Dimension Sizes                    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)
  Texture alignment:                             512 bytes
  Maximum memory pitch:                          2147483647 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
  Concurrent kernel execution:                   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 / 2 / 0
  Compute Mode:
     < Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >
Result = PASS
czl@czl-RedmiBook-14:/usr/local/cuda-10.1/samples/1_Utilities/deviceQueryDrv$ cd ..
czl@czl-RedmiBook-14:/usr/local/cuda-10.1/samples/1_Utilities$ ls
bandwidthTest  deviceQuery  deviceQueryDrv  p2pBandwidthLatencyTest  topologyQuery  UnifiedMemoryPerf
czl@czl-RedmiBook-14:/usr/local/cuda-10.1/samples/1_Utilities$ cd p2pBandwidthLatencyTest/
czl@czl-RedmiBook-14:/usr/local/cuda-10.1/samples/1_Utilities/p2pBandwidthLatencyTest$ sudo make
/usr/local/cuda-10.1/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 p2pBandwidthLatencyTest.o -c p2pBandwidthLatencyTest.cu
/usr/local/cuda-10.1/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 p2pBandwidthLatencyTest p2pBandwidthLatencyTest.o 
mkdir -p ../../bin/x86_64/linux/release
cp p2pBandwidthLatencyTest ../../bin/x86_64/linux/release
czl@czl-RedmiBook-14:/usr/local/cuda-10.1/samples/1_Utilities/p2pBandwidthLatencyTest$ sudo ./p2pBandwidthLatencyTest 
[P2P (Peer-to-Peer) GPU Bandwidth Latency Test]
Device: 0, NVIDIA GeForce MX250, pciBusID: 2, pciDeviceID: 0, pciDomainID:0

***NOTE: In case a device doesn't have P2P access to other one, it falls back to normal memcopy procedure.
So you can see lesser Bandwidth (GB/s) and unstable Latency (us) in those cases.

P2P Connectivity Matrix
     D\D     0
     0	     1
Unidirectional P2P=Disabled Bandwidth Matrix (GB/s)
   D\D     0 
     0  45.41 
Unidirectional P2P=Enabled Bandwidth (P2P Writes) Matrix (GB/s)
   D\D     0 
     0  48.97 
Bidirectional P2P=Disabled Bandwidth Matrix (GB/s)
   D\D     0 
     0  40.32 
Bidirectional P2P=Enabled Bandwidth Matrix (GB/s)
   D\D     0 
     0  44.13 
P2P=Disabled Latency Matrix (us)
   GPU     0 
     0   1.36 

   CPU     0 
     0   1.59 
P2P=Enabled Latency (P2P Writes) Matrix (us)
   GPU     0 
     0   1.36 

   CPU     0 
     0   1.52 

NOTE: The CUDA Samples are not meant for performance measurements. Results may vary when GPU Boost is enabled.
czl@czl-RedmiBook-14:/usr/local/cuda-10.1/samples/1_Utilities/p2pBandwidthLatencyTest$ ls
Makefile  NsightEclipse.xml  p2pBandwidthLatencyTest  p2pBandwidthLatencyTest.cu  p2pBandwidthLatencyTest.o  readme.txt
czl@czl-RedmiBook-14:/usr/local/cuda-10.1/samples/1_Utilities/p2pBandwidthLatencyTest$ cd ..
czl@czl-RedmiBook-14:/usr/local/cuda-10.1/samples/1_Utilities$ ls
bandwidthTest  deviceQuery  deviceQueryDrv  p2pBandwidthLatencyTest  topologyQuery  UnifiedMemoryPerf
czl@czl-RedmiBook-14:/usr/local/cuda-10.1/samples/1_Utilities$ cd UnifiedMemoryPerf/
czl@czl-RedmiBook-14:/usr/local/cuda-10.1/samples/1_Utilities/UnifiedMemoryPerf$ ls
commonDefs.hpp  commonKernels.cu  commonKernels.hpp  helperFunctions.cpp  Makefile  matrixMultiplyPerf.cu  NsightEclipse.xml  readme.txt
czl@czl-RedmiBook-14:/usr/local/cuda-10.1/samples/1_Utilities/UnifiedMemoryPerf$ sudo make
/usr/local/cuda-10.1/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 commonKernels.o -c commonKernels.cu
/usr/local/cuda-10.1/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 helperFunctions.o -c helperFunctions.cpp
/usr/local/cuda-10.1/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 matrixMultiplyPerf.o -c matrixMultiplyPerf.cu
/usr/local/cuda-10.1/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 UnifiedMemoryPerf commonKernels.o helperFunctions.o matrixMultiplyPerf.o 
mkdir -p ../../bin/x86_64/linux/release
cp UnifiedMemoryPerf ../../bin/x86_64/linux/release
czl@czl-RedmiBook-14:/usr/local/cuda-10.1/samples/1_Utilities/UnifiedMemoryPerf$ sudo ./UnifiedMemoryPerf 
GPU Device 0: "NVIDIA GeForce MX250" with compute capability 6.1

Running ........................................................

Overall Time For matrixMultiplyPerf 

Printing Average of 20 measurements in (ms)
Size_KB	 UMhint	UMhntAs	 UMeasy	  0Copy	MemCopy	CpAsync	CpHpglk	CpPglAs
4	  0.241	  0.184	  0.342	  0.019	  0.032	  0.025	  0.034	  0.036
16	  0.274	  0.223	  0.613	  0.048	  0.062	  0.055	  0.063	  0.068
64	  0.572	  0.414	  0.985	  0.300	  0.258	  0.179	  0.176	  0.165
256	  1.484	  1.213	  1.883	  1.765	  0.772	  0.885	  0.808	  0.693
1024	  5.258	  5.079	  5.939	 12.261	  3.910	  3.698	  3.560	  3.531
4096	 25.862	 24.730	 28.311	 96.461	 23.153	 22.382	 21.748	 21.319
16384	167.280	154.706	180.784	750.827	135.102	134.785	133.111	132.947

NOTE: The CUDA Samples are not meant for performance measurements. Results may vary when GPU Boost is enabled.
czl@czl-RedmiBook-14:/usr/local/cuda-10.1/samples/1_Utilities/UnifiedMemoryPerf$ 

CUDA BLAS验证:

/usr/local/cuda-10.1/samples/7_CUDALibraries/batchCUBLAS

czl@czl-RedmiBook-14:/usr/local/cuda-10.1/samples/7_CUDALibraries/batchCUBLAS$ sudo make
/usr/local/cuda-10.1/bin/nvcc -ccbin g++ -I../../common/inc  -m64    -gencode arch=compute_30,code=compute_30 -o batchCUBLAS.o -c batchCUBLAS.cpp
/usr/local/cuda-10.1/bin/nvcc -ccbin g++   -m64      -gencode arch=compute_30,code=compute_30 -o batchCUBLAS batchCUBLAS.o  -lcublas
mkdir -p ../../bin/x86_64/linux/release
cp batchCUBLAS ../../bin/x86_64/linux/release
czl@czl-RedmiBook-14:/usr/local/cuda-10.1/samples/7_CUDALibraries/batchCUBLAS$ sudo ./batchCUBLAS 
batchCUBLAS Starting...

GPU Device 0: "NVIDIA GeForce MX250" with compute capability 6.1


 ==== Running single kernels ==== 

Testing sgemm
#### args: ta=0 tb=0 m=128 n=128 k=128  alpha = (0xbf800000, -1) beta= (0x40000000, 2)
#### args: lda=128 ldb=128 ldc=128
^^^^ elapsed = 0.00004292 sec  GFLOPS=97.7344
@@@@ sgemm test OK
Testing dgemm
#### args: ta=0 tb=0 m=128 n=128 k=128  alpha = (0x0000000000000000, 0) beta= (0x0000000000000000, 0)
#### args: lda=128 ldb=128 ldc=128
^^^^ elapsed = 0.00020099 sec  GFLOPS=20.8685
@@@@ dgemm test OK

 ==== Running N=10 without streams ==== 

Testing sgemm
#### args: ta=0 tb=0 m=128 n=128 k=128  alpha = (0xbf800000, -1) beta= (0x00000000, 0)
#### args: lda=128 ldb=128 ldc=128
^^^^ elapsed = 0.00015092 sec  GFLOPS=277.918
@@@@ sgemm test OK
Testing dgemm
#### args: ta=0 tb=0 m=128 n=128 k=128  alpha = (0xbff0000000000000, -1) beta= (0x0000000000000000, 0)
#### args: lda=128 ldb=128 ldc=128
^^^^ elapsed = 0.00163698 sec  GFLOPS=25.6222
@@@@ dgemm test OK

 ==== Running N=10 with streams ==== 

Testing sgemm
#### args: ta=0 tb=0 m=128 n=128 k=128  alpha = (0x40000000, 2) beta= (0x40000000, 2)
#### args: lda=128 ldb=128 ldc=128
^^^^ elapsed = 0.00013089 sec  GFLOPS=320.441
@@@@ sgemm test OK
Testing dgemm
#### args: ta=0 tb=0 m=128 n=128 k=128  alpha = (0xbff0000000000000, -1) beta= (0x0000000000000000, 0)
#### args: lda=128 ldb=128 ldc=128
^^^^ elapsed = 0.00167584 sec  GFLOPS=25.028
@@@@ dgemm test OK

 ==== Running N=10 batched ==== 

Testing sgemm
#### args: ta=0 tb=0 m=128 n=128 k=128  alpha = (0x3f800000, 1) beta= (0xbf800000, -1)
#### args: lda=128 ldb=128 ldc=128
^^^^ elapsed = 0.00010204 sec  GFLOPS=411.032
@@@@ sgemm test OK
Testing dgemm
#### args: ta=0 tb=0 m=128 n=128 k=128  alpha = (0xbff0000000000000, -1) beta= (0x4000000000000000, 2)
#### args: lda=128 ldb=128 ldc=128
^^^^ elapsed = 0.00167203 sec  GFLOPS=25.0851
@@@@ dgemm test OK

Test Summary
0 error(s)
czl@czl-RedmiBook-14:/usr/local/cuda-10.1/samples/7_CUDALibraries/batchCUBLAS$ 

工具:

用到的编译器工具是nvcc,信息如下:

czl@czl-RedmiBook-14:/usr/local/cuda-10.1/samples/7_CUDALibraries/batchCUBLAS$ nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2019 NVIDIA Corporation
Built on Sun_Jul_28_19:07:16_PDT_2019
Cuda compilation tools, release 10.1, V10.1.243
czl@czl-RedmiBook-14:/usr/local/cuda-10.1/samples/7_CUDALibraries/batchCUBLAS$ which nvcc
/usr/local/cuda-10.1/bin/nvcc
czl@czl-RedmiBook-14:/usr/local/cuda-10.1/samples/7_CUDALibraries/batchCUBLAS$ 

nvidia-detector

Nvidia OpenGL Driver

OpenGL Driver Support | NVIDIA Developer

OPENGL库的变化:

分别记录安装Nvidia 驱动前后,以根目录为基础的查找文件libgl*的信息,发现差异如下:

Ubuntu18.04安装CUDA深度学习环境_第21张图片

Ubuntu18.04安装CUDA深度学习环境_第22张图片

Ubuntu18.04安装CUDA深度学习环境_第23张图片

libglvnd应该是驱动安装前通过命令行安装的,派出在外,其余的差别应该来源于N卡的驱动安装。

注意:

安装完成后,不需要恢复黑名单列表,保持nouveau禁用即可。

结束!

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