Changes

This tutorial will walk you through the necessary steps to set up nVidia CUDA and the correct corresponding version of GPU drivers, as well as a bunch of libraries needed for development.Note, before you do anything else, you should first update your system packages to the latest versions, <syntaxhighlight lang="bash">#!/bin/bashsudo apt-get updatesudo apt-get upgrade</syntaxhighlight> 

If you have a freshly installed Ubuntu 18.04 or some derivative (such as Linux Mint 19), this should be simply a matter of running the following script(run with sudo): <syntaxhighlight lang="bash">#!/bin/bashwget http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-repo-ubuntu1804_10.1.168-1_amd64.debdpkg -i cuda-repo-ubuntu1804_10.1.168-1_amd64.debapt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/7fa2af80.pubapt-get updateapt-get install -y cuda</syntaxhighlight> In case you had the driver or an earlier release of CUDA already installed, my recommendation is to first uninstall them.

#!show version of the nVidia driver> glxinfo | grep NVIDIATODO: copy reference output # show version of the CUDA compiler toolchain> /binusr/bashlocal/cuda/nvcc --versionnvcc: NVIDIA (R) Cuda compiler driverCopyright (c) 2005-2019 NVIDIA CorporationBuilt on Wed_Apr_24_19:10:27_PDT_2019Cuda compilation tools, release 10.1, V10.1.168 # show detected GPUs> nvidia-smiSat May 18 12:51:46 2019+-----------------------------------------------------------------------------+| NVIDIA-SMI 418.39 Driver Version: 418.39 CUDA Version: 10.1 ||-------------------------------+----------------------+----------------------+| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC || Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. ||===============================+======================+======================|| 0 Quadro GV100 On | 00000000:03:00.0 On | Off || 35% 48C P0 27W / 250W | 1490MiB / 32475MiB | 0% Default |+-------------------------------+----------------------+----------------------+ +-----------------------------------------------------------------------------+| Processes: GPU Memory || GPU PID Type Process name Usage ||=============================================================================|| 0 1354 G /usr/lib/xorg/Xorg 800MiB || 0 1762 G cinnamon 331MiB || 0 10767 G /usr/lib/firefox/firefox 6MiB || <... more processes> ||=============================================================================|</syntaxhighlight> 

</syntaxhighlight>In case you had You should also add the driver or an earlier release of CUDA already installedpath for the binaries and libraries to your environment so that all tools are able to find them. For example, my recommendation is add the following two lines to first uninstall themyour ".bashrc" in your home folder:

Note that the string <syntaxhighlight lang="bionicbash" is the output of the command "lsb_release -cs". If you have an older version of Ubuntu, you can try to replace "bionic" with the output of this command, but it might not be supported. On a derivative Linux, this does not work, and you need to find out the correct Ubuntu lsb release by consulting their documentation.>export PATH=/usr/local/cuda/bin:$PATHexport LD_LIBRARY_PATH=/usr/local/cuda/lib64:$LD_LIBRARY_PATH</syntaxhighlight>

Post installation, you should reboot your system to make sure it still works. Run the following commands in a shell to test installation[[Category:Tutorials]]