Cuda + cudnn 在Ubuntu18.04上的手动安装
本文是本人的安装记录，因为想做C语言级的调试，整个过程十分麻烦，而且肯定会有记录忽略的地方，不建议大家使用。仅供参考。一般情况下，还是使用anaconda安装NVIDIA Cuda tool kit吧，非常轻松。
在某些情况下（比如开发的需要）需要手动安装时，可以参考下面的记录。
Step.1 Stop Nouveau
The Nouveau kernel driver is currently in use by your system. This driver is incompatible with the NVIDIA driver,
参考：
https://tutorials.technology/tutorials/85-How-to-remove-Nouveau-kernel-driver-Nvidia-install-error.html
How to remove Nouveau kernel driver (fix Nvidia install error)
#---open a terminal---
sudo apt-get remove nvidia*
sudo apt autoremove
sudo apt-get install dkms build-essential linux-headers-generic
sudo vim /etc/modprobe.d/blacklist.conf
#---save the following info into file blacklist.conf---
blacklist nouveau
blacklist lbm-nouveau
options nouveau modeset=0
alias nouveau off
alias lbm-nouveau off
#---end of the info saved----
#---go back to the terminal---
echo options nouveau modeset=0 | sudo tee -a /etc/modprobe.d/nouveau-kms.conf
sudo update-initramfs -u
rebootStep.2 intall cuda toolkit
然后就可以安装cuda toolkit了
$ sudo sh cuda_10.0.130_410.48_linux.run
blablabla......
-----------------
Do you accept the previously read EULA?
accept/decline/quit: accept
Install NVIDIA Accelerated Graphics Driver for Linux-x86_64 410.48?
(y)es/(n)o/(q)uit: y
Do you want to install the OpenGL libraries?
(y)es/(n)o/(q)uit [ default is yes ]: y
Do you want to run nvidia-xconfig?
This will update the system X configuration file so that the NVIDIA X driver
is used. The pre-existing X configuration file will be backed up.
This option should not be used on systems that require a custom
X configuration, such as systems with multiple GPU vendors.
(y)es/(n)o/(q)uit [ default is no ]: y
Install the CUDA 10.0 Toolkit?
(y)es/(n)o/(q)uit: y
Enter Toolkit Location
[ default is /usr/local/cuda-10.0 ]:
Do you want to install a symbolic link at /usr/local/cuda?
(y)es/(n)o/(q)uit: y
Install the CUDA 10.0 Samples?
(y)es/(n)o/(q)uit: y
Enter CUDA Samples Location
[ default is /home/matthew ]:
Installing the NVIDIA display driver...
Installing the CUDA Toolkit in /usr/local/cuda-10.0 ...
Missing recommended library: libGLU.so
Missing recommended library: libXi.so
Missing recommended library: libXmu.so
Missing recommended library: libGL.so
Installing the CUDA Samples in /home/matthew ...
Copying samples to /home/matthew/NVIDIA_CUDA-10.0_Samples now...
Finished copying samples.
===========
= Summary =
===========
Driver: Installed
Toolkit: Installed in /usr/local/cuda-10.0
Samples: Installed in /home/matthew, but missing recommended libraries
Please make sure that
- PATH includes /usr/local/cuda-10.0/bin
- LD_LIBRARY_PATH includes /usr/local/cuda-10.0/lib64, or, add /usr/local/cuda-10.0/lib64 to /etc/ld.so.conf and run ldconfig as root
To uninstall the CUDA Toolkit, run the uninstall script in /usr/local/cuda-10.0/bin
To uninstall the NVIDIA Driver, run nvidia-uninstall
Please see CUDA_Installation_Guide_Linux.pdf in /usr/local/cuda-10.0/doc/pdf for detailed information on setting up CUDA.
Logfile is /tmp/cuda_install_1832.log
Step.3 supplementary package
如果像前面一样，出现缺少的包：
Missing recommended library: libGLU.so
Missing recommended library: libXi.so
Missing recommended library: libXmu.so
Missing recommended library: libGL.so
不过，这个主要是针对samples，因为报错内容中说了，
Driver: Installed
Toolkit: Installed in /usr/local/cuda-10.0
Samples: Installed in /home/matthew, but missing recommended libraries
如果需要编译使用Samples，那就要补充安装(samples 还需要lglut)：
$ sudo apt-get install libxmu-dev libxi-dev libgl1-mesa-glx libglu1-mesa libglu1-mesa-dev
$ sudo apt-get install freeglut3 freeglut3-dev
Step.4 设置环境变量
sudo gedit ~/.bashrc
添加这两句然后保存：
export PATH=/usr/local/cuda/bin:$PATH
export LD_LIBRARY_PATH=/usr/local/cuda/lib64:$LD_LIBRARY_PATH
保存后, 执行下列命令, 使环境变量立即生效
source ~/.bashrc有的说还要同时需要添加lib库路径(貌似不加也可以)： 在 /etc/ld.so.conf.d/加入文件 cuda.conf,
sudo vim /etc/ld.so.conf.d/cuda.conf
内容如下
/usr/local/cuda/lib64
保存后,执行下列命令使之立刻生效
sudo ldconfig -vStep.5 编译samples并进行测试（optional）
这时候可以对samples进行编译了
cd /usr/local/cuda/samples
然后执行下列命令来build samples
sudo make all -j8测试，如果正常会显示安装成功！
$ cd /usr/local/cuda/samples/1_Utilities/deviceQuery
$ ./deviceQuery
./deviceQuery Starting...
CUDA Device Query (Runtime API) version (CUDART static linking)
Detected 1 CUDA Capable device(s)
Device 0: "GeForce GTX 1080 Ti"
CUDA Driver Version / Runtime Version 10.0 / 10.0
CUDA Capability Major/Minor version number: 6.1
Total amount of global memory: 11175 MBytes (11718230016 bytes)
(28) Multiprocessors, (128) CUDA Cores/MP: 3584 CUDA Cores
GPU Max Clock rate: 1633 MHz (1.63 GHz)
Memory Clock rate: 5505 Mhz
Memory Bus Width: 352-bit
L2 Cache Size: 2883584 bytes
Maximum Texture Dimension Size (x,y,z) 1D=(131072), 2D=(131072, 65536), 3D=(16384, 16384, 16384)
Maximum Layered 1D Texture Size, (num) layers 1D=(32768), 2048 layers
Maximum Layered 2D Texture Size, (num) layers 2D=(32768, 32768), 2048 layers
Total amount of constant memory: 65536 bytes
Total amount of shared memory per block: 49152 bytes
Total number of registers available per block: 65536
Warp size: 32
Maximum number of threads per multiprocessor: 2048
Maximum number of threads per block: 1024
Max dimension size of a thread block (x,y,z): (1024, 1024, 64)
Max dimension size of a grid size (x,y,z): (2147483647, 65535, 65535)
Maximum memory pitch: 2147483647 bytes
Texture alignment: 512 bytes
Concurrent copy and kernel execution: Yes with 2 copy engine(s)
Run time limit on kernels: Yes
Integrated GPU sharing Host Memory: No
Support host page-locked memory mapping: Yes
Alignment requirement for Surfaces: Yes
Device has ECC support: Disabled
Device supports Unified Addressing (UVA): Yes
Device supports Compute Preemption: Yes
Supports Cooperative Kernel Launch: Yes
Supports MultiDevice Co-op Kernel Launch: Yes
Device PCI Domain ID / Bus ID / location ID: 0 / 1 / 0
Compute Mode:
< Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >
deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 10.0, CUDA Runtime Version = 10.0, NumDevs = 1
Result = PASS
Step.6 CUDNN 的安装
这个我参考了：
http://www.cnblogs.com/empty16/p/4793404.html
https://www.cnblogs.com/jinggege/p/5766146.html
不过原贴有部分路径错误，我在下面有说明。
不过我的系统是cuda10，所以在nvidia网站上下载的是cudnn-10.0-linux-x64-v7.4.2.24.tgz 这个包，注意下载需要注册Nvidia的开发者账号。
安装过程如下，解压会得到一个cuda的文件夹，
cd cuda
#copy到cuda库
sudo cp lib64/libcudnn.* /usr/local/lib/
sudo cp include/cudnn.h /usr/local/include/
#或者，copy到cuda库
sudo cp lib64/libcudnn.* /usr/local/cuda/lib64/
sudo cp include/cudnn.h /usr/local/cuda/include/这两个地方用起来大概没什么区别，不过一般情况下我建议使用/usr/local/cuda/include 和/usr/local/cuda/lib64，比如你要使用pytorch的时候，可以省掉一些手动配置，因为pytorch默认是通过 LD_LIBRARY_PATH来寻找cudnn的（参考：https://github.com/pytorch/pytorch/issues/573）。
下面链接cuDNN的库文件（必须！），这里要特别注意的是，如果前面是将文件拷贝到/usr/local/cuda/lib64和/usr/local/cuda/include,那么下面的操作中也必须做相应的调整，下面的例子中，我假设目录都是/usr/local/lib和/usr/local/include，不再一一说明
$ sudo ln -sf /usr/local/lib/libcudnn.so.7.4.2 /usr/local/lib/libcudnn.so.7
$ sudo ln -sf /usr/local/lib/libcudnn.so.7 /usr/local/lib/libcudnn.so#链接完config更新
$ sudo ldconfig 完成cuda和cudnn的安装
如果在使用cudnn的lib 或者cudnn.h 时出现Permission denied提示，那么说明copy过去的文件当前系统没有权限使用，那么在拷贝过去之前，先对文件授权
修复方式：
cd /usr/local/lib/
sudo su
chmod 777 -R libcudnn.so
chmod 777 -R libcudnn.so.7
chmod 777 -R libcudnn.so.7.4.2
cd ..
cd include
chmod 777 -R cudnn.h
参考：
[1]本参考给出了ubuntu18.04, 16.04, 14.04等版本的nvidia驱动安装
https://askubuntu.com/questions/1077061/how-do-i-install-nvidia-and-cuda-drivers-into-ubuntu
[2]https://blog.csdn.net/tanmx219/article/details/86210023
参考1的安装过程
我按照参考[1]的安装过程，发现安装了大量的开发包，而且由于网络的原因，过程非常缓慢，安装过程如下，
Remove any CUDA PPAs that may be setup and also remove the nvidia-cuda-toolkit if installed:
sudo rm /etc/apt/sources.list.d/cuda* sudo apt remove nvidia-cuda-toolkit
Recommended to also remove all NVIDIA drivers before installing new drivers:
sudo apt remove nvidia-*
Then update the system:
sudo apt update
Install the key:
sudo apt-key adv --fetch-keys http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1404/x86_64/7fa2af80.pub
Add the repo:
sudo bash -c 'echo "deb http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1404/x86_64 /" > /etc/apt/sources.list.d/cuda.list'
Update the system again:
sudo apt update
Install CUDA 10.0.
sudo apt install cuda-10-0
It should be installing the nvidia-410 drivers with it as those are what are listed in the repo. See:http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1404/x86_64/
Add the following lines to your ~/.profile file for CUDA 10.0
# set PATH for cuda 10.0 installation
if [ -d "/usr/local/cuda-10.0/bin/" ]; then
export PATH=/usr/local/cuda-10.0/bin${PATH:+:${PATH}}
export LD_LIBRARY_PATH=/usr/local/cuda-10.0/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
fi
Reboot the computer and check your settings when reboot is complete:
Check NVIDIA Cuda Compiler with nvcc --version:
Check NVIDIA driver with nvidia-smi:
参考1的安装结果
====================================================================
sudo apt install nvidia-driver-410
正在读取软件包列表... 完成
正在分析软件包的依赖关系树
正在读取状态信息... 完成
将会同时安装下列软件：
libnvidia-cfg1-410 libnvidia-common-410 libnvidia-compute-410
libnvidia-decode-410 libnvidia-encode-410 libnvidia-fbc1-410
libnvidia-gl-410 libnvidia-ifr1-410 libopengl0 libxnvctrl0
nvidia-compute-utils-410 nvidia-dkms-410 nvidia-kernel-common-410
nvidia-kernel-source-410 nvidia-prime nvidia-settings nvidia-utils-410
screen-resolution-extra xserver-xorg-video-nvidia-410
推荐安装：
libnvidia-compute-410:i386 libnvidia-decode-410:i386
libnvidia-encode-410:i386 libnvidia-ifr1-410:i386 libnvidia-fbc1-410:i386
libnvidia-gl-410:i386
下列软件包将被【卸载】：
libnvidia-compute-390 libnvidia-compute-390:i386
下列【新】软件包将被安装：
libnvidia-cfg1-410 libnvidia-common-410 libnvidia-compute-410
libnvidia-decode-410 libnvidia-encode-410 libnvidia-fbc1-410
libnvidia-gl-410 libnvidia-ifr1-410 libopengl0 libxnvctrl0
nvidia-compute-utils-410 nvidia-dkms-410 nvidia-driver-410
nvidia-kernel-common-410 nvidia-kernel-source-410 nvidia-prime
nvidia-settings nvidia-utils-410 screen-resolution-extra
xserver-xorg-video-nvidia-410
升级了 0 个软件包，新安装了 20 个软件包，要卸载 2 个软件包，有 37 个软件包未被升级。
需要下载 67.1 MB/67.2 MB 的归档。
解压缩后会消耗 130 MB 的额外空间。
您希望继续执行吗？ [Y/n] y
获取:2 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 libopengl0 amd64 1.0.0-2ubuntu2.2 [31.3 kB]
获取:1 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 libnvidia-cfg1-410 410.79-0ubuntu1 [70.2 kB]
获取:3 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 libnvidia-common-410 410.79-0ubuntu1 [9,800 B]
获取:4 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 libnvidia-compute-410 410.79-0ubuntu1 [20.6 MB]
获取:5 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 libnvidia-decode-410 410.79-0ubuntu1 [1,209 kB]
获取:6 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 libnvidia-encode-410 410.79-0ubuntu1 [52.2 kB]
获取:7 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 libnvidia-fbc1-410 410.79-0ubuntu1 [43.6 kB]
获取:8 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 libnvidia-gl-410 410.79-0ubuntu1 [31.4 MB]
获取:9 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 libnvidia-ifr1-410 410.79-0ubuntu1 [68.4 kB]
获取:10 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 libxnvctrl0 410.79-0ubuntu1 [19.3 kB]
获取:11 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 nvidia-compute-utils-410 410.79-0ubuntu1 [72.8 kB]
获取:12 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 nvidia-kernel-source-410 410.79-0ubuntu1 [10.2 MB]
获取:13 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 nvidia-kernel-common-410 410.79-0ubuntu1 [10.3 kB]
获取:14 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 nvidia-dkms-410 410.79-0ubuntu1 [26.0 kB]
获取:15 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 nvidia-utils-410 410.79-0ubuntu1 [333 kB]
获取:16 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 xserver-xorg-video-nvidia-410 410.79-0ubuntu1 [1,652 kB]
获取:17 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 nvidia-driver-410 410.79-0ubuntu1 [395 kB]
获取:18 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 nvidia-settings 410.79-0ubuntu1 [962 kB]
已下载 67.1 MB，耗时 39秒 (1,717 kB/s)
(正在读取数据库 ... 系统当前共安装有 198634 个文件和目录。)
正在卸载 libnvidia-compute-390:amd64 (390.77-0ubuntu0.18.04.1) ...
正在卸载 libnvidia-compute-390:i386 (390.77-0ubuntu0.18.04.1) ...
正在选中未选择的软件包 libnvidia-cfg1-410:amd64。
(正在读取数据库 ... 系统当前共安装有 198606 个文件和目录。)
正准备解包 ...
A modprobe blacklist file has been created at /etc/modprobe.d to prevent Nouveau
from loading. This can be reverted by deleting the following file:
/etc/modprobe.d/nvidia-graphics-drivers.conf
A new initrd image has also been created. To revert, please regenerate your
initrd by running the following command after deleting the modprobe.d file:
`/usr/sbin/initramfs -u`
*****************************************************************************
*** Reboot your computer and verify that the NVIDIA graphics driver can ***
*** be loaded. ***
*****************************************************************************
INFO:Enable nvidia
DEBUG:Parsing /usr/share/ubuntu-drivers-common/quirks/put_your_quirks_here
DEBUG:Parsing /usr/share/ubuntu-drivers-common/quirks/dell_latitude
DEBUG:Parsing /usr/share/ubuntu-drivers-common/quirks/lenovo_thinkpad
Loading new nvidia-410.79 DKMS files...
Building for 4.15.0-45-generic
Building for architecture x86_64
Building initial module for 4.15.0-45-generic
Done.
nvidia:
Running module version sanity check.
- Original module
- No original module exists within this kernel
- Installation
- Installing to /lib/modules/4.15.0-45-generic/updates/dkms/
nvidia-modeset.ko:
Running module version sanity check.
- Original module
- No original module exists within this kernel
- Installation
- Installing to /lib/modules/4.15.0-45-generic/updates/dkms/
nvidia-drm.ko:
Running module version sanity check.
- Original module
- No original module exists within this kernel
- Installation
- Installing to /lib/modules/4.15.0-45-generic/updates/dkms/
nvidia-uvm.ko:
Running module version sanity check.
- Original module
- No original module exists within this kernel
- Installation
- Installing to /lib/modules/4.15.0-45-generic/updates/dkms/
depmod.....
DKMS: install completed.
...
=====================================================================
$ sudo apt install cuda-10-0
正在读取软件包列表... 完成
正在分析软件包的依赖关系树
正在读取状态信息... 完成
将会同时安装下列软件：
ca-certificates-java cuda-command-line-tools-10-0 cuda-compiler-10-0 cuda-cublas-10-0 cuda-cublas-dev-10-0 cuda-cudart-10-0 cuda-cudart-dev-10-0 cuda-cufft-10-0 cuda-cufft-dev-10-0 cuda-cuobjdump-10-0
cuda-cupti-10-0 cuda-curand-10-0 cuda-curand-dev-10-0 cuda-cusolver-10-0 cuda-cusolver-dev-10-0 cuda-cusparse-10-0 cuda-cusparse-dev-10-0 cuda-demo-suite-10-0 cuda-documentation-10-0
cuda-driver-dev-10-0 cuda-drivers cuda-gdb-10-0 cuda-gpu-library-advisor-10-0 cuda-libraries-10-0 cuda-libraries-dev-10-0 cuda-license-10-0 cuda-memcheck-10-0 cuda-misc-headers-10-0 cuda-npp-10-0
cuda-npp-dev-10-0 cuda-nsight-10-0 cuda-nsight-compute-10-0 cuda-nvcc-10-0 cuda-nvdisasm-10-0 cuda-nvgraph-10-0 cuda-nvgraph-dev-10-0 cuda-nvjpeg-10-0 cuda-nvjpeg-dev-10-0 cuda-nvml-dev-10-0
cuda-nvprof-10-0 cuda-nvprune-10-0 cuda-nvrtc-10-0 cuda-nvrtc-dev-10-0 cuda-nvtx-10-0 cuda-nvvp-10-0 cuda-runtime-10-0 cuda-samples-10-0 cuda-toolkit-10-0 cuda-tools-10-0 cuda-visual-tools-10-0
default-jre default-jre-headless fonts-dejavu-extra freeglut3 freeglut3-dev java-common libatk-wrapper-java libatk-wrapper-java-jni libdrm-dev libgl1-mesa-dev libgles1 libglu1-mesa-dev
libglvnd-core-dev libglvnd-dev libx11-xcb-dev libxcb-dri2-0-dev libxcb-dri3-dev libxcb-glx0-dev libxcb-present-dev libxcb-randr0-dev libxcb-shape0-dev libxcb-sync-dev libxcb-xfixes0-dev libxmu-dev
libxmu-headers libxshmfence-dev libxxf86vm-dev mesa-common-dev nvidia-modprobe openjdk-11-jre openjdk-11-jre-headless x11proto-xf86vidmode-dev
建议安装：
default-java-plugin fonts-ipafont-gothic fonts-ipafont-mincho fonts-wqy-microhei | fonts-wqy-zenhei
下列【新】软件包将被安装：
ca-certificates-java cuda-10-0 cuda-command-line-tools-10-0 cuda-compiler-10-0 cuda-cublas-10-0 cuda-cublas-dev-10-0 cuda-cudart-10-0 cuda-cudart-dev-10-0 cuda-cufft-10-0 cuda-cufft-dev-10-0
cuda-cuobjdump-10-0 cuda-cupti-10-0 cuda-curand-10-0 cuda-curand-dev-10-0 cuda-cusolver-10-0 cuda-cusolver-dev-10-0 cuda-cusparse-10-0 cuda-cusparse-dev-10-0 cuda-demo-suite-10-0
cuda-documentation-10-0 cuda-driver-dev-10-0 cuda-drivers cuda-gdb-10-0 cuda-gpu-library-advisor-10-0 cuda-libraries-10-0 cuda-libraries-dev-10-0 cuda-license-10-0 cuda-memcheck-10-0
cuda-misc-headers-10-0 cuda-npp-10-0 cuda-npp-dev-10-0 cuda-nsight-10-0 cuda-nsight-compute-10-0 cuda-nvcc-10-0 cuda-nvdisasm-10-0 cuda-nvgraph-10-0 cuda-nvgraph-dev-10-0 cuda-nvjpeg-10-0
cuda-nvjpeg-dev-10-0 cuda-nvml-dev-10-0 cuda-nvprof-10-0 cuda-nvprune-10-0 cuda-nvrtc-10-0 cuda-nvrtc-dev-10-0 cuda-nvtx-10-0 cuda-nvvp-10-0 cuda-runtime-10-0 cuda-samples-10-0 cuda-toolkit-10-0
cuda-tools-10-0 cuda-visual-tools-10-0 default-jre default-jre-headless fonts-dejavu-extra freeglut3 freeglut3-dev java-common libatk-wrapper-java libatk-wrapper-java-jni libdrm-dev libgl1-mesa-dev
libgles1 libglu1-mesa-dev libglvnd-core-dev libglvnd-dev libx11-xcb-dev libxcb-dri2-0-dev libxcb-dri3-dev libxcb-glx0-dev libxcb-present-dev libxcb-randr0-dev libxcb-shape0-dev libxcb-sync-dev
libxcb-xfixes0-dev libxmu-dev libxmu-headers libxshmfence-dev libxxf86vm-dev mesa-common-dev nvidia-modprobe openjdk-11-jre openjdk-11-jre-headless x11proto-xf86vidmode-dev
升级了 0 个软件包，新安装了 83 个软件包，要卸载 0 个软件包，有 37 个软件包未被升级。
需要下载 1,407 MB 的归档。
解压缩后会消耗 3,336 MB 的额外空间。
您希望继续执行吗？ [Y/n] y
获取:1 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 java-common all 0.63ubuntu1~02 [7,032 B]
获取:2 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-license-10-0 10.0.130-1 [17.6 kB]
获取:13 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 openjdk-11-jre-headless amd64 10.0.2+13-1ubuntu0.18.04.4 [39.5 MB]
获取:3 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-misc-headers-10-0 10.0.130-1 [640 kB]
获取:4 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-nvcc-10-0 10.0.130-1 [20.0 MB]
获取:5 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-cuobjdump-10-0 10.0.130-1 [130 kB]
获取:6 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-nvprune-10-0 10.0.130-1 [36.8 kB]
获取:7 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-compiler-10-0 10.0.130-1 [2,538 B]
获取:8 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-nvdisasm-10-0 10.0.130-1 [22.1 MB]
获取:9 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-gdb-10-0 10.0.130-1 [2,769 kB]
获取:10 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-nvprof-10-0 10.0.130-1 [5,590 kB]
获取:11 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-memcheck-10-0 10.0.130-1 [139 kB]
获取:12 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-cudart-10-0 10.0.130-1 [109 kB]
获取:14 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-driver-dev-10-0 10.0.130-1 [12.0 kB]
获取:15 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-cudart-dev-10-0 10.0.130-1 [457 kB]
获取:16 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-cupti-10-0 10.0.130-1 [1,564 kB]
获取:17 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-gpu-library-advisor-10-0 10.0.130-1 [1,003 kB]
获取:18 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-nvtx-10-0 10.0.130-1 [38.9 kB]
获取:19 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-command-line-tools-10-0 10.0.130-1 [26.9 kB]
获取:20 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-nsight-10-0 10.0.130-1 [2,590 B]
获取:21 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-nvvp-10-0 10.0.130-1 [2,536 B]
获取:22 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-nvrtc-10-0 10.0.130-1 [5,925 kB]
获取:23 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-nvrtc-dev-10-0 10.0.130-1 [9,344 B]
获取:24 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-cusolver-10-0 10.0.130-1 [38.4 MB]
获取:25 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-cusolver-dev-10-0 10.0.130-1 [13.2 MB]
获取:26 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-cublas-10-0 10.0.130-1 [30.3 MB]
获取:27 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-cublas-dev-10-0 10.0.130-1 [30.8 MB]
获取:28 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-cufft-10-0 10.0.130-1 [60.7 MB]
获取:29 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-cufft-dev-10-0 10.0.130-1 [124 MB]
获取:30 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-curand-10-0 10.0.130-1 [38.9 MB]
获取:31 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-curand-dev-10-0 10.0.130-1 [58.1 MB]
获取:32 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-cusparse-10-0 10.0.130-1 [27.1 MB]
获取:33 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-cusparse-dev-10-0 10.0.130-1 [27.2 MB]
获取:34 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-npp-10-0 10.0.130-1 [54.2 MB]
获取:35 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-npp-dev-10-0 10.0.130-1 [55.0 MB]
获取:36 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-nvml-dev-10-0 10.0.130-1 [51.6 kB]
获取:37 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-nvgraph-10-0 10.0.130-1 [12.8 MB]
获取:38 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-nvgraph-dev-10-0 10.0.130-1 [33.4 MB]
获取:39 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-nvjpeg-10-0 10.0.130-1 [281 kB]
获取:40 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-nvjpeg-dev-10-0 10.0.130-1 [192 kB]
获取:41 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-nsight-compute-10-0 10.0.130-1 [188 MB]
获取:42 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-visual-tools-10-0 10.0.130-1 [394 MB]
获取:43 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-tools-10-0 10.0.130-1 [2,498 B]
获取:44 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-samples-10-0 10.0.130-1 [61.5 MB]
获取:45 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-documentation-10-0 10.0.130-1 [52.0 MB]
获取:46 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-libraries-dev-10-0 10.0.130-1 [2,606 B]
获取:47 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-toolkit-10-0 10.0.130-1 [2,834 B]
获取:48 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 nvidia-modprobe 410.79-0ubuntu1 [19.1 kB]
获取:49 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-drivers 410.79-1 [2,568 B]
获取:50 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-libraries-10-0 10.0.130-1 [2,586 B]
获取:51 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-runtime-10-0 10.0.130-1 [2,540 B]
获取:52 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-demo-suite-10-0 10.0.130-1 [3,868 kB]
获取:53 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64 cuda-10-0 10.0.130-1 [2,562 B]
91% [13 openjdk-11-jre-headless 11.0 MB/39.5 MB 28%] 17.8 kB/s 29分 52秒
获取:54 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 default-jre-headless amd64 2:1.10-63ubuntu1~02 [3,412 B]
获取:55 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 ca-certificates-java all 20180516ubuntu1~18.04.1 [12.2 kB]
获取:56 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 openjdk-11-jre amd64 10.0.2+13-1ubuntu0.18.04.4 [53.1 kB]
获取:57 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 default-jre amd64 2:1.10-63ubuntu1~02 [1,092 B]
获取:58 http://cn.archive.ubuntu.com/ubuntu bionic/universe amd64 freeglut3 amd64 2.8.1-3 [73.6 kB]
获取:59 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 libdrm-dev amd64 2.4.95-1~18.04.1 [121 kB]
获取:60 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 mesa-common-dev amd64 18.2.2-0ubuntu1~18.04.1 [551 kB]
获取:61 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 libglvnd-core-dev amd64 1.0.0-2ubuntu2.2 [12.9 kB]
获取:62 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 libgles1 amd64 1.0.0-2ubuntu2.2 [11.2 kB]
获取:63 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 libglvnd-dev amd64 1.0.0-2ubuntu2.2 [3,408 B]
获取:64 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 libx11-xcb-dev amd64 2:1.6.4-3ubuntu0.1 [9,764 B]
获取:65 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libxcb-dri3-dev amd64 1.13-1 [7,368 B]
获取:66 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libxcb-randr0-dev amd64 1.13-1 [20.4 kB]
获取:67 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libxcb-shape0-dev amd64 1.13-1 [7,144 B]
获取:68 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libxcb-xfixes0-dev amd64 1.13-1 [11.7 kB]
获取:69 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libxcb-sync-dev amd64 1.13-1 [10.6 kB]
获取:70 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libxcb-present-dev amd64 1.13-1 [6,968 B]
获取:71 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libxshmfence-dev amd64 1.3-1 [3,692 B]
获取:72 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libxcb-dri2-0-dev amd64 1.13-1 [8,476 B]
获取:73 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libxcb-glx0-dev amd64 1.13-1 [27.9 kB]
获取:74 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 x11proto-xf86vidmode-dev all 2018.4-4 [2,632 B]
获取:75 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libxxf86vm-dev amd64 1:1.1.4-1 [13.3 kB]
获取:76 http://cn.archive.ubuntu.com/ubuntu bionic-updates/main amd64 libgl1-mesa-dev amd64 18.2.2-0ubuntu1~18.04.1 [4,432 B]
获取:77 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libglu1-mesa-dev amd64 9.0.0-2.1build1 [206 kB]
获取:78 http://cn.archive.ubuntu.com/ubuntu bionic/universe amd64 freeglut3-dev amd64 2.8.1-3 [124 kB]
获取:79 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libxmu-headers all 2:1.1.2-2 [54.3 kB]
获取:80 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libxmu-dev amd64 2:1.1.2-2 [49.0 kB]
获取:81 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 fonts-dejavu-extra all 2.37-1 [1,953 kB]
获取:82 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libatk-wrapper-java all 0.33.3-20ubuntu0.1 [34.7 kB]
获取:83 http://cn.archive.ubuntu.com/ubuntu bionic/main amd64 libatk-wrapper-java-jni amd64 0.33.3-20ubuntu0.1 [28.3 kB]
已下载 1,407 MB，耗时 26分 38秒 (880 kB/s)
正在从软件包中解出模板：100%
正在选中未选择的软件包 java-common。
(正在读取数据库 ... 系统当前共安装有 199217 个文件和目录。)
正准备解包 ...
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done.
done.
