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
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
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：
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：
或者：
Download Drivers | NVIDIA
ubuntu上查看显示设备信息可以通过以下命令:
选择显卡对应的型号，我的是GetForce->MX200 Series->GetForce MX250->Linxu 64 bit.
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".
然后就是安装进度条：
最后出现的警告不要管它
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 libglvndczl@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：
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。
查看内核模块，发现确实是这样的
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-sminvidia-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。
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：
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.
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]
已下载 45.0 MB，耗时 18秒 (2,549 kB/s)
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sudo apt-get -y install cuda正在选中未选择的软件包 cuda-curand-10-1。
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正在选中未选择的软件包 nsight-compute-2019.4.0。
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正在选中未选择的软件包 libxshmfence-dev:amd64。
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正在选中未选择的软件包 x11proto-xext-dev。
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正在选中未选择的软件包 x11proto-xf86vidmode-dev。
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正在选中未选择的软件包 libgl1-mesa-dev:amd64。
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正在选中未选择的软件包 libglu1-mesa-dev:amd64。
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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。
正准备解包 .../122-cuda-runtime-10-1_10.1.243-1_amd64.deb ...
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。
正准备解包 .../123-cuda-demo-suite-10-1_10.1.243-1_amd64.deb ...
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。
正准备解包 .../124-cuda-10-1_10.1.243-1_amd64.deb ...
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) ...
正在设置 libxcb-dri3-dev:amd64 (1.13-2~ubuntu18.04) ...
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) ...
正在设置 libxcb-xfixes0-dev:amd64 (1.13-2~ubuntu18.04) ...
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 Developer
https://developer.nvidia.com/zh-cn/cudnn
内容： 
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
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：
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。