Difference between revisions of "Tutorials:Install nVidia CUDA and GPU drivers"
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In case you had the driver or an earlier release of CUDA already installed, my recommendation is to first uninstall them. | 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 .. | + | 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: | 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: | ||
Revision as of 11:37, 18 May 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.
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 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