CUDA: Difference between revisions
Replace nix-community binary cache with cache.nixos-cuda.org |
→Enabling CUDA In Packages: Improved tips on installing large CUDA packages without a cache |
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{{tip|1='''Data center GPUs''': Note that you may need to adjust your driver version to use "data center" GPUs like V100/A100s. See [https://discourse.nixos.org/t/how-to-use-nvidia-v100-a100-gpus/17754 this thread] for more info.}} | {{tip|1='''Data center GPUs''': Note that you may need to adjust your driver version to use "data center" GPUs like V100/A100s. See [https://discourse.nixos.org/t/how-to-use-nvidia-v100-a100-gpus/17754 this thread] for more info.}} | ||
== Driver Installation == | |||
Assuming you've followed the [[NVIDIA]] page correctly, and have a CUDA compatible GPU, you shouldn't need to do any further configuration. You can confirm your CUDA version by running the following command in your terminal. | |||
{{code|lang=console|line=no|<nowiki>nvidia-smi | grep CUDA</nowiki>}} | |||
== <code>cudatoolkit</code>, <code>cudnn</code>, and related packages == | == <code>cudatoolkit</code>, <code>cudnn</code>, and related packages == | ||
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<syntaxhighlight lang="nix" line="1" start="1"> | <syntaxhighlight lang="nix" line="1" start="1"> | ||
# flake.nix, run with `nix develop`# Run with `nix-shell cuda-shell.nix` | # flake.nix, run with `nix develop`# Run with `nix-shell cuda-shell.nix` | ||
{ pkgs ? import | { pkgs ? import <nixpkgs> {} }: | ||
let | let | ||
nvidiaPackage = pkgs.linuxPackages.nvidiaPackages.stable; | nvidiaPackage = pkgs.linuxPackages.nvidiaPackages.stable; | ||
| Line 148: | Line 154: | ||
For more information, refer to the [[Binary Cache#Using a binary cache Using a binary cache|Using a binary cache]] page. | For more information, refer to the [[Binary Cache#Using a binary cache Using a binary cache|Using a binary cache]] page. | ||
{{ | {{info|1=You need to rebuild your system at least once after adding the cache, before it can be used.}} | ||
=== NixOS === | === NixOS === | ||
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trusted-substituters = https://cache.nixos-cuda.org | trusted-substituters = https://cache.nixos-cuda.org | ||
</nowiki>|name=~/.config/nix/nix.conf|lang=nix}} | </nowiki>|name=~/.config/nix/nix.conf|lang=nix}} | ||
== Enabling CUDA In Packages == | |||
By default, software packaged in source code form has CUDA support disabled, because of the unfree license. There are multiple options to solve this. | |||
You can enable builds with CUDA support with a nixpkgs wide configuration. | |||
<syntaxhighlight lang="nix"> | |||
nixpkgs.config.cudaSupport = true; | |||
</syntaxhighlight> | |||
Or you can override individual packages. | |||
<syntaxhighlight lang="nix"> | |||
environment.systemPackages = with pkgs; [ | |||
(mlt.override {config.cudaSupport=true;}) | |||
]; | |||
</syntaxhighlight> | |||
Or you can use binary-packaged versions of CUDA compatible software, such as [https://github.com/edolstra/nix-warez/tree/master/blender blender-bin] for Blender. | |||
{{info|If you will be using <code>cudaSupport</code> in packages, it is recommended you utilize a [[#Setting up CUDA Binary Cache|CUDA binary cache]].}} | |||
Without a [[#Setting up CUDA Binary Cache|CUDA cache]], any CUDA compatible package installed with <code>cudaSupport</code> will be compiled from source. This is because NixOS Foundation does not build (and therefore [https://cache.nixos.org/ cache.nixos.org] does not cache) CUDA packages. | |||
For larger programs like Blender, that process can be very resource-intensive. If you are installing large CUDA-enabled package(s) that either are not cached or you are not using a cache, then (especially on older or weaker hardware) it is recommended to reduce the number of cores and/or jobs that the process will take, to prevent a system freeze from resource limits. This can be done with the <code>--max-jobs</code> / <code>-j</code> and <code>--cores</code> flags, for more details see the [https://github.com/NixOS/nix/blob/master/doc/manual/source/advanced-topics/cores-vs-jobs.md Tuning Cores & Jobs] manual page. | |||
If you don't want to deal with the increased time that compilation will take when <code>--max-jobs</code> / <code>-j</code> and <code>--cores</code> are set below maximum, you can also try simply closing other running processes to see if that frees up enough resources for compilation to be successful. | |||
→ For specifics on setting up Blender with CUDA (and OptiX) see: [[Blender#CUDA & OptiX]]. | |||
== Some things to keep in mind when setting up CUDA in NixOS == | == Some things to keep in mind when setting up CUDA in NixOS == | ||
* Some GPUs, like Tesla K80, don't work with the latest drivers, so you must specify them in the option <code>hardware.nvidia.package</code> getting the value from your selected kernel, for example, <code>config.boot.kernelPackages.nvidia_x11_legacy470</code>. You can check which driver version your GPU supports by visiting the [https://www.nvidia.com/Download/index.aspx nvidia site] and checking the driver version. | * Some GPUs, like Tesla K80, don't work with the latest drivers, so you must specify them in the option <code>hardware.nvidia.package</code> getting the value from your selected kernel, for example, <code>config.boot.kernelPackages.nvidia_x11_legacy470</code>. You can check which driver version your GPU supports by visiting the [https://www.nvidia.com/Download/index.aspx nvidia site] and checking the driver version. | ||
* Even with the drivers correctly installed, some software, like Blender, may not see the CUDA GPU. Make sure your system configuration has the option <code>hardware. | * Even with the drivers correctly installed, some software, like Blender, may not see the CUDA GPU. Make sure your system configuration has the option <code>hardware.graphics.enable</code> enabled. | ||
== CUDA under WSL == | == CUDA under WSL == | ||