Difference between revisions of "Tutorials:Install nVidia CUDA and GPU drivers"

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== Overview ==
 
== Overview ==
  
−
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.
+
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/bash
 +
sudo apt-get update
 +
sudo apt-get upgrade
 +
</syntaxhighlight>
 +
 
  
  
 
== Guide ==
 
== Guide ==
  
−
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:
+
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/bash
 +
wget http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-repo-ubuntu1804_10.1.168-1_amd64.deb
 +
dpkg -i cuda-repo-ubuntu1804_10.1.168-1_amd64.deb
 +
apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/7fa2af80.pub
 +
apt-get update
 +
apt-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.
  
 +
If you cannot get the script to run or have a different linux version, head over to [https://developer.nvidia.com/cuda-downloads the nVidia CUDA download page] and install CUDA 10.1 by following their instructions. I strongy recommend the networked ".deb" package installation. Make sure to explain any problems you encounter on the discussion page so that we can troubleshoot this guide.
  
 +
Post installation, you should reboot your system to make sure it still works. Run the following commands in a shell to test installation, which should produce a similar output than what is shown:
  
−
In case you had the driver or an earlier release of CUDA already installed, my recommendation is to first uninstall them.
+
<syntaxhighlight lang="bash">
 +
# show version of the nVidia driver
 +
> glxinfo | grep NVIDIA
 +
TODO: copy reference output
 +
 
 +
# show version of the CUDA compiler toolchain
 +
> /usr/local/cuda/nvcc --version
 +
nvcc: NVIDIA (R) Cuda compiler driver
 +
Copyright (c) 2005-2019 NVIDIA Corporation
 +
Built on Wed_Apr_24_19:10:27_PDT_2019
 +
Cuda compilation tools, release 10.1, V10.1.168
 +
 
 +
# show detected GPUs
 +
> nvidia-smi
 +
Sat 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>
 +
 
 +
 
 +
You should also add the path for the binaries and libraries to your environment so that all tools are able to find them. For example, add the following two lines to your ".bashrc" in your home folder:
  
−
Note that the string "bionic" 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.
+
<syntaxhighlight lang="bash">
 +
export PATH=/usr/local/cuda/bin:$PATH
 +
export LD_LIBRARY_PATH=/usr/local/cuda/lib64:$LD_LIBRARY_PATH
 +
</syntaxhighlight>
  
−
If you cannot get the script to run, head over to ... and install CUDA 10.1 by following their instructions. Make sure to explain your problems on the discussion page so that we can troubleshoot this guide.
 
  
−
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]]

Latest revision as of 13:40, 18 June 2019

Overview

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, 

#!/bin/bash
sudo apt-get update
sudo apt-get upgrade


Guide

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): 

#!/bin/bash
wget http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-repo-ubuntu1804_10.1.168-1_amd64.deb
dpkg -i cuda-repo-ubuntu1804_10.1.168-1_amd64.deb
apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/7fa2af80.pub
apt-get update
apt-get install -y cuda

In case you had the driver or an earlier release of CUDA already installed, my recommendation is to first uninstall them.

If you cannot get the script to run or have a different linux version, head over to the nVidia CUDA download page and install CUDA 10.1 by following their instructions. I strongy recommend the networked ".deb" package installation. Make sure to explain any problems you encounter on the discussion page so that we can troubleshoot this guide.

Post installation, you should reboot your system to make sure it still works. Run the following commands in a shell to test installation, which should produce a similar output than what is shown: 

# show version of the nVidia driver
> glxinfo | grep NVIDIA
TODO: copy reference output

# show version of the CUDA compiler toolchain
> /usr/local/cuda/nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2019 NVIDIA Corporation
Built on Wed_Apr_24_19:10:27_PDT_2019
Cuda compilation tools, release 10.1, V10.1.168

# show detected GPUs
> nvidia-smi
Sat 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>                                                        |
|=============================================================================|


You should also add the path for the binaries and libraries to your environment so that all tools are able to find them. For example, add the following two lines to your ".bashrc" in your home folder: 

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