CUDA: Difference between revisions

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NixOS supports using NVIDIA GPUs for pure computing purposes, not just for graphics. For example, many users rely on NixOS for machine learning both locally and on cloud instances. These use cases are supported by the [https://github.com/orgs/NixOS/teams/cuda-maintainers @NixOS/cuda-maintainers team] on GitHub. If you have an issue using your NVIDIA GPU for computing purposes [https://github.com/~~nixos~~/nixpkgs/issues/new open an issue] on GitHub and tag @NixOS/cuda-maintainers.

NixOS supports using NVIDIA GPUs for pure computing purposes, not just for graphics. For example, many users rely on NixOS for machine learning both locally and on cloud instances. These use cases are supported by the [https://github.com/orgs/NixOS/teams/cuda-maintainers @NixOS/cuda-maintainers team] on GitHub ([https://github.com/orgs/NixOS/projects/27 project board]). If you have an issue using your NVIDIA GPU for computing purposes [https://github.com/NixOS/nixpkgs/issues/new/choose open an issue] on GitHub and tag <code>@NixOS/cuda-maintainers</code>.

'''Cache''': Using the [https://app.cachix.org/cache/~~cuda~~-~~maintainers#pull cuda~~-~~maintainers~~ cache] is recommended! It will save you valuable time and electrons. Getting set up should be as simple as <code>cachix use ~~cuda~~-~~maintainers~~</code>.

{{tip|1='''Cache''': Using the [https://app.cachix.org/cache/nix-community nix-community cache] is recommended! It will save you valuable time and electrons. Getting set up should be as simple as <code>cachix use nix-community</code>. Click [[#Setting up CUDA Binary Cache|here]] for more details.}}

'''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.}}

== <code>cudatoolkit</code>, <code>cudnn</code>, and related packages ==

{{outdated|scope=section|date=July 2024|reason=Note that these examples have been updated more recently (as of 2024-07-30). May not be the best solution. A better resource is likely the packaging CUDA sample code [https://github.com/NixOS/nixpkgs/tree/master/pkgs/development/cuda-modules/cutensor here].}}

The CUDA toolkit is available in a [https://search.nixos.org/packages?channel=unstable&from=0&size=50&buckets=%7B%22package_attr_set%22%3A%5B%22cudaPackages%22%5D%2C%22package_license_set%22%3A%5B%5D%2C%22package_maintainers_set%22%3A%5B%5D%2C%22package_platforms%22%3A%5B%5D%7D&sort=relevance&type=packages&query=cudatoolkit number of different versions]. Please use the latest major version. You can see where they're defined in nixpkgs [https://github.com/NixOS/nixpkgs/blob/~~4d5b1d6b273fc4acd5dce966d2e9c0ca197b6df2~~/pkgs/development/~~compilers~~/cudatoolkit/~~default~~.nix here].

The CUDA toolkit is available in a [https://search.nixos.org/packages?channel=unstable&from=0&size=50&buckets=%7B%22package_attr_set%22%3A%5B%22cudaPackages%22%5D%2C%22package_license_set%22%3A%5B%5D%2C%22package_maintainers_set%22%3A%5B%5D%2C%22package_platforms%22%3A%5B%5D%7D&sort=relevance&type=packages&query=cudatoolkit number of different versions]. Please use the latest major version. You can see where they're defined in nixpkgs [https://github.com/NixOS/nixpkgs/blob/master/pkgs/development/cuda-modules/cudatoolkit/releases.nix here].

Several "CUDA-X" libraries are packages as well. In particular,

* cuDNN is packaged [https://github.com/NixOS/nixpkgs/~~blob~~/~~634141959076a8ab69ca2cca0f266852256d79ee~~/pkgs/development/~~libraries/science/math~~/cudnn~~/default.nix~~ here].

* cuDNN is packaged [https://github.com/NixOS/nixpkgs/tree/master/pkgs/development/cuda-modules/cudnn here].

* cuTENSOR is packaged [https://github.com/NixOS/nixpkgs/~~blob~~/~~634141959076a8ab69ca2cca0f266852256d79ee~~/pkgs/development/~~libraries/science/math~~/cutensor~~/default.nix~~ here].

* cuTENSOR is packaged [https://github.com/NixOS/nixpkgs/tree/master/pkgs/development/cuda-modules/cutensor here].

'''Note that these examples haven't been updated in a while (as of 2022-03-12). May not be the best solution. A better resource is likely the packaging CUDA sample code [https://github.com/NixOS/nixpkgs/blob/634141959076a8ab69ca2cca0f266852256d79ee/pkgs/test/cuda/cuda-library-samples/generic.nix here].'''

There are some possible ways to setup a development environment using CUDA on NixOS. This can be accomplished in the following ways:

There some possible ways to setup a development environment using CUDA on NixOS. This can accomplished in the following ways:

* By making a FHS user env

~~{{file|~~cuda-~~fsh~~.nix~~|nix|<nowiki>~~

<syntaxhighlight lang="nix" line="1" start="1"># flake.nix, run with `nix develop`

{ pkgs ? import <nixpkgs> {} }:

# Run with `nix-shell cuda-fhs.nix`

{ pkgs ? import </nowiki><nixpkgs><nowiki> {} }:

~~let~~

let

~~fhs~~ = pkgs.~~buildFHSUserEnv~~ {

# Change according to the driver used: stable, beta

name = "cuda-env";

nvidiaPackage = pkgs.linuxPackages.nvidiaPackages.stable;

targetPkgs = pkgs: with pkgs; [

in

git

(pkgs.buildFHSEnv {

gitRepo

name = "cuda-env";

gnupg

targetPkgs = pkgs: with pkgs; [

autoconf

git

curl

gitRepo

procps

gnupg

gnumake

autoconf

~~utillinux~~

curl

m4

procps

gperf

gnumake

unzip

util-linux

cudatoolkit

m4

~~linuxPackages.nvidia_x11~~

gperf

libGLU libGL

unzip

xorg.libXi xorg.libXmu freeglut

cudatoolkit

xorg.libXext xorg.libX11 xorg.libXv xorg.libXrandr zlib

nvidiaPackage

ncurses5

libGLU libGL

stdenv.cc

xorg.libXi xorg.libXmu freeglut

binutils

xorg.libXext xorg.libX11 xorg.libXv xorg.libXrandr zlib

];

ncurses5

multiPkgs = pkgs: with pkgs; [ zlib ];

stdenv.cc

runScript = "bash";

binutils

profile = ''

];

export CUDA_PATH=${pkgs.cudatoolkit}

multiPkgs = pkgs: with pkgs; [ zlib ];

# export LD_LIBRARY_PATH=${~~pkgs.linuxPackages.nvidia_x11~~}/lib

runScript = "bash";

export EXTRA_LDFLAGS="-L/lib -L${~~pkgs.linuxPackages.nvidia_x11~~}/lib"

profile = ''

export EXTRA_CCFLAGS="-I/usr/include"

export CUDA_PATH=${pkgs.cudatoolkit}

'';

# export LD_LIBRARY_PATH=${nvidiaPackage}/lib

};

export EXTRA_LDFLAGS="-L/lib -L${nvidiaPackage}/lib"

~~in pkgs.stdenv~~.~~mkDerivation {~~

export EXTRA_CCFLAGS="-I/usr/include"

~~name = "cuda-~~env~~-shell";~~

'';

~~nativeBuildInputs = [ fhs ];~~

}).env

~~shellHook = "exec cuda-env";~~

</syntaxhighlight>

}

</~~nowiki~~>}}

* By making a nix-shell

~~{{file|~~cuda-shell.nix~~|nix|<nowiki>~~

{ pkgs ? import <nixpkgs> {} }:

# flake.nix, run with `nix develop`# Run with `nix-shell cuda-shell.nix`

{ pkgs ? import </nowiki><nixpkgs><nowiki> {} }:

pkgs.~~stdenv~~.~~mkDerivation~~ {

let

nvidiaPackage = pkgs.linuxPackages.nvidiaPackages.stable;

in

pkgs.mkShell {

name = "cuda-env-shell";

buildInputs = with pkgs; [

git gitRepo gnupg autoconf curl

procps gnumake ~~utillinux~~ m4 gperf unzip

procps gnumake util-linux m4 gperf unzip

cudatoolkit ~~linuxPackages.nvidia_x11~~

cudatoolkit nvidiaPackage

libGLU libGL

xorg.libXi xorg.libXmu freeglut

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shellHook = ''

export CUDA_PATH=${pkgs.cudatoolkit}

# export LD_LIBRARY_PATH=${pkgs.linuxPackages.nvidia_x11}/lib:${pkgs.ncurses5}/lib

# export LD_LIBRARY_PATH=${nvidiaPackage}/lib:${pkgs.ncurses}/lib

export EXTRA_LDFLAGS="-L/lib -L${nvidiaPackage}/lib"

export EXTRA_CCFLAGS="-I/usr/include"

'';

}

</syntaxhighlight>

* By making a flake.nix

<syntaxhighlight lang="nix" line="1" start="1"># flake.nix, run with `nix develop`

{

description = "CUDA development environment";

outputs = {

self,

nixpkgs,

}: let

system = "x86_64-linux";

pkgs = import nixpkgs {

inherit system;

config.allowUnfree = true;

config.cudaSupport = true;

config.cudaVersion = "12";

};

# Change according to the driver used: stable, beta

nvidiaPackage = pkgs.linuxPackages.nvidiaPackages.stable;

in {

# alejandra is a nix formatter with a beautiful output

formatter."${system}" = nixpkgs.legacyPackages.${system}.alejandra;

devShells.${system}.default = pkgs.mkShell {

buildInputs = with pkgs; [

ffmpeg

fmt.dev

cudaPackages.cuda_cudart

cudatoolkit

nvidiaPackage

cudaPackages.cudnn

libGLU

libGL

xorg.libXi

xorg.libXmu

freeglut

xorg.libXext

xorg.libX11

xorg.libXv

xorg.libXrandr

zlib

ncurses

stdenv.cc

binutils

uv

];

shellHook = ''

export LD_LIBRARY_PATH="${nvidiaPackage}/lib:$LD_LIBRARY_PATH"

export CUDA_PATH=${pkgs.cudatoolkit}

export EXTRA_LDFLAGS="-L/lib -L${nvidiaPackage}/lib"

export EXTRA_CCFLAGS="-I/usr/include"

export CMAKE_PREFIX_PATH="${pkgs.fmt.dev}:$CMAKE_PREFIX_PATH"

export PKG_CONFIG_PATH="${pkgs.fmt.dev}/lib/pkgconfig:$PKG_CONFIG_PATH"

'';

};

}</syntaxhighlight>

== Setting up CUDA Binary Cache ==

The [https://nix-community.org/cache/ Nix-community cache] contains pre-built CUDA packages. By adding it to your system, Nix will fetch these packages instead of building them, saving valuable time and processing power.

For more information, refer to the [[Binary Cache#Using a binary cache Using a binary cache|Using a binary cache]] page.

{{warning|1=You need to rebuild your system at least once after adding the cache, before it can be used.}}

=== NixOS ===

Add the cache to <code>substituters</code> and <code>trusted-public-keys</code> inside your system configuration:

{{file|/etc/nixos/configuration.nix|nix|<nowiki>

nix.settings = {

substituters = [

"https://nix-community.cachix.org"

];

trusted-public-keys = [

"nix-community.cachix.org-1:mB9FSh9qf2dCimDSUo8Zy7bkq5CX+/rkCWyvRCYg3Fs="

];

};

</nowiki>}}

=== Non-NixOS ===

If you have [https://www.cachix.org cachix] installed and set up, all you need to do is run:

$ cachix use nix-community

</syntaxHighlight>

Else, you have to add <code>substituters</code> and <code>trusted-public-keys</code> to <code>/etc/nix/nix.conf</code>:

{{file|/etc/nix/nix.conf|nix|<nowiki>

trusted-public-keys = nix-community.cachix.org-1:mB9FSh9qf2dCimDSUo8Zy7bkq5CX+/rkCWyvRCYg3Fs=

trusted-substituters = https://nix-community.cachix.org

trusted-users = root @wheel

</nowiki>}}

If your user is in <code>trusted-users</code>, you can also add the cache in your home directory:

{{file|~/.config/nix/nix.conf|nix|<nowiki>

substituters = https://nix-community.cachix.org

</nowiki>}}

== 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.

* 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.opengl.enable</code> enabled.

* By default, software packaged in source code form has CUDA support disabled, because of the unfree license. To solve this, you can enable builds with CUDA support with a nixpkgs wide configuration, or use binary packaged CUDA compatible software such as [https://github.com/edolstra/nix-warez/tree/master/blender blender-bin].

== CUDA under WSL ==

This (surprisingly) works just fine using nixpkgs 23.05 provided that you prefix the <code>LD_LIBRARY_PATH</code> in your interactive environment with the WSL library directory. For nix shell this looks like:

{{file|cuda-shell.nix|nix|<nowiki>

shellHook = ''

export CUDA_PATH=${pkgs.cudatoolkit}

export LD_LIBRARY_PATH=/usr/lib/wsl/lib:${pkgs.linuxPackages.nvidia_x11}/lib:${pkgs.ncurses5}/lib

export EXTRA_LDFLAGS="-L/lib -L${pkgs.linuxPackages.nvidia_x11}/lib"

export EXTRA_CCFLAGS="-I/usr/include"

'';

}

</nowiki>}}

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* [https://discourse.nixos.org/t/cuda-setup-on-nixos/1118 CUDA setup on NixOS]

* [https://github.com/NixOS/nixpkgs/issues/131608 eGPU with nvidia-docker on intel-xserver]

* [https://discourse.nixos.org/t/cuda-in-nixos-on-gcp-for-a-tesla-k80/ Tesla K80 based CUDA setup with Terraform on GCP]

[[Category:Server]]

@@ Line 1: / Line 1: @@
-NixOS supports using NVIDIA GPUs for pure computing purposes, not just for graphics. For example, many users rely on NixOS for machine learning both locally and on cloud instances. These use cases are supported by the [https://github.com/orgs/NixOS/teams/cuda-maintainers @NixOS/cuda-maintainers team] on GitHub. If you have an issue using your NVIDIA GPU for computing purposes [https://github.com/nixos/nixpkgs/issues/new open an issue] on GitHub and tag @NixOS/cuda-maintainers.
+NixOS supports using NVIDIA GPUs for pure computing purposes, not just for graphics. For example, many users rely on NixOS for machine learning both locally and on cloud instances. These use cases are supported by the [https://github.com/orgs/NixOS/teams/cuda-maintainers @NixOS/cuda-maintainers team] on GitHub ([https://github.com/orgs/NixOS/projects/27 project board]). If you have an issue using your NVIDIA GPU for computing purposes [https://github.com/NixOS/nixpkgs/issues/new/choose open an issue] on GitHub and tag <code>@NixOS/cuda-maintainers</code>.
-'''Cache''': Using the [https://app.cachix.org/cache/cuda-maintainers#pull cuda-maintainers cache] is recommended! It will save you valuable time and electrons. Getting set up should be as simple as <code>cachix use cuda-maintainers</code>.
+{{tip|1='''Cache''': Using the [https://app.cachix.org/cache/nix-community nix-community cache] is recommended! It will save you valuable time and electrons. Getting set up should be as simple as <code>cachix use nix-community</code>. Click [[#Setting up CUDA Binary Cache|here]] for more details.}}
-'''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.}}
 == <code>cudatoolkit</code>, <code>cudnn</code>, and related packages ==
+{{outdated|scope=section|date=July 2024|reason=Note that these examples have been updated more recently (as of 2024-07-30). May not be the best solution. A better resource is likely the packaging CUDA sample code [https://github.com/NixOS/nixpkgs/tree/master/pkgs/development/cuda-modules/cutensor here].}}
-The CUDA toolkit is available in a [https://search.nixos.org/packages?channel=unstable&from=0&size=50&buckets=%7B%22package_attr_set%22%3A%5B%22cudaPackages%22%5D%2C%22package_license_set%22%3A%5B%5D%2C%22package_maintainers_set%22%3A%5B%5D%2C%22package_platforms%22%3A%5B%5D%7D&sort=relevance&type=packages&query=cudatoolkit number of different versions]. Please use the latest major version. You can see where they're defined in nixpkgs [https://github.com/NixOS/nixpkgs/blob/4d5b1d6b273fc4acd5dce966d2e9c0ca197b6df2/pkgs/development/compilers/cudatoolkit/default.nix here].
+The CUDA toolkit is available in a [https://search.nixos.org/packages?channel=unstable&from=0&size=50&buckets=%7B%22package_attr_set%22%3A%5B%22cudaPackages%22%5D%2C%22package_license_set%22%3A%5B%5D%2C%22package_maintainers_set%22%3A%5B%5D%2C%22package_platforms%22%3A%5B%5D%7D&sort=relevance&type=packages&query=cudatoolkit number of different versions]. Please use the latest major version. You can see where they're defined in nixpkgs [https://github.com/NixOS/nixpkgs/blob/master/pkgs/development/cuda-modules/cudatoolkit/releases.nix here].
 Several "CUDA-X" libraries are packages as well. In particular,
-* cuDNN is packaged [https://github.com/NixOS/nixpkgs/blob/634141959076a8ab69ca2cca0f266852256d79ee/pkgs/development/libraries/science/math/cudnn/default.nix here].
+* cuDNN is packaged [https://github.com/NixOS/nixpkgs/tree/master/pkgs/development/cuda-modules/cudnn here].
-* cuTENSOR is packaged [https://github.com/NixOS/nixpkgs/blob/634141959076a8ab69ca2cca0f266852256d79ee/pkgs/development/libraries/science/math/cutensor/default.nix here].
+* cuTENSOR is packaged [https://github.com/NixOS/nixpkgs/tree/master/pkgs/development/cuda-modules/cutensor here].
-'''Note that these examples haven't been updated in a while (as of 2022-03-12). May not be the best solution. A better resource is likely the packaging CUDA sample code [https://github.com/NixOS/nixpkgs/blob/634141959076a8ab69ca2cca0f266852256d79ee/pkgs/test/cuda/cuda-library-samples/generic.nix here].'''
+There are some possible ways to setup a development environment using CUDA on NixOS. This can be accomplished in the following ways:
-There some possible ways to setup a development environment using CUDA on NixOS. This can accomplished in the following ways:
 * By making a FHS user env
-{{file|cuda-fsh.nix|nix|<nowiki>
+<syntaxhighlight lang="nix" line="1" start="1"># flake.nix, run with `nix develop`
-{ pkgs ? import <nixpkgs> {} }:
+# Run with `nix-shell cuda-fhs.nix`
+{ pkgs ? import </nowiki><nixpkgs><nowiki> {} }:
 let
-  fhs = pkgs.buildFHSUserEnv {
+   # Change according to the driver used: stable, beta
-    name = "cuda-env";
+   nvidiaPackage = pkgs.linuxPackages.nvidiaPackages.stable;
-    targetPkgs = pkgs: with pkgs; [
+in
-      git
+(pkgs.buildFHSEnv {
-      gitRepo
+  name = "cuda-env";
-      gnupg
+  targetPkgs = pkgs: with pkgs; [
-      autoconf
+    git
-      curl
+    gitRepo
-      procps
+    gnupg
-      gnumake
+    autoconf
-      utillinux
+    curl
-      m4
+    procps
-      gperf
+    gnumake
-      unzip
+    util-linux
-      cudatoolkit
+    m4
-      linuxPackages.nvidia_x11
+    gperf
-      libGLU libGL
+    unzip
-      xorg.libXi xorg.libXmu freeglut
+    cudatoolkit
-      xorg.libXext xorg.libX11 xorg.libXv xorg.libXrandr zlib
+    nvidiaPackage
-      ncurses5
+    libGLU libGL
-      stdenv.cc
+    xorg.libXi xorg.libXmu freeglut
-      binutils
+    xorg.libXext xorg.libX11 xorg.libXv xorg.libXrandr zlib
-    ];
+    ncurses5
-    multiPkgs = pkgs: with pkgs; [ zlib ];
+    stdenv.cc
-    runScript = "bash";
+    binutils
-    profile = ''
+  ];
-       export CUDA_PATH=${pkgs.cudatoolkit}
+  multiPkgs = pkgs: with pkgs; [ zlib ];
-       # export LD_LIBRARY_PATH=${pkgs.linuxPackages.nvidia_x11}/lib
+  runScript = "bash";
-       export EXTRA_LDFLAGS="-L/lib -L${pkgs.linuxPackages.nvidia_x11}/lib"
+  profile = ''
-       export EXTRA_CCFLAGS="-I/usr/include"
+    export CUDA_PATH=${pkgs.cudatoolkit}
-     '';
+    # export LD_LIBRARY_PATH=${nvidiaPackage}/lib
-  };
+    export EXTRA_LDFLAGS="-L/lib -L${nvidiaPackage}/lib"
-in pkgs.stdenv.mkDerivation {
+    export EXTRA_CCFLAGS="-I/usr/include"
-   name = "cuda-env-shell";
+  '';
-   nativeBuildInputs = [ fhs ];
+}).env
-   shellHook = "exec cuda-env";
+</syntaxhighlight>
-}
-</nowiki>}}
 * By making a nix-shell
-{{file|cuda-shell.nix|nix|<nowiki>
+<syntaxhighlight lang="nix" line="1" start="1">
-{ pkgs ? import <nixpkgs> {} }:
+# flake.nix, run with `nix develop`# Run with `nix-shell cuda-shell.nix`
+{ pkgs ? import </nowiki><nixpkgs><nowiki> {} }:
-pkgs.stdenv.mkDerivation {
+let
+   nvidiaPackage = pkgs.linuxPackages.nvidiaPackages.stable;
+in
+pkgs.mkShell {
     name = "cuda-env-shell";
     buildInputs = with pkgs; [
       git gitRepo gnupg autoconf curl
-      procps gnumake utillinux m4 gperf unzip
+      procps gnumake util-linux m4 gperf unzip
-      cudatoolkit linuxPackages.nvidia_x11
+      cudatoolkit nvidiaPackage
       libGLU libGL
       xorg.libXi xorg.libXmu freeglut
@@ Line 80: / Line 79: @@
     shellHook = ''
        export CUDA_PATH=${pkgs.cudatoolkit}
-       # export LD_LIBRARY_PATH=${pkgs.linuxPackages.nvidia_x11}/lib:${pkgs.ncurses5}/lib
+       # export LD_LIBRARY_PATH=${nvidiaPackage}/lib:${pkgs.ncurses}/lib
+      export EXTRA_LDFLAGS="-L/lib -L${nvidiaPackage}/lib"
+      export EXTRA_CCFLAGS="-I/usr/include"
+   '';
+}
+</syntaxhighlight>
+* By making a flake.nix
+<syntaxhighlight lang="nix" line="1" start="1"># flake.nix, run with `nix develop`
+{
+  description = "CUDA development environment";
+  outputs = {
+    self,
+    nixpkgs,
+  }: let
+    system = "x86_64-linux";
+    pkgs = import nixpkgs {
+      inherit system;
+      config.allowUnfree = true;
+      config.cudaSupport = true;
+      config.cudaVersion = "12";
+    };
+    # Change according to the driver used: stable, beta
+    nvidiaPackage = pkgs.linuxPackages.nvidiaPackages.stable;
+  in {
+    # alejandra is a nix formatter with a beautiful output
+    formatter."${system}" = nixpkgs.legacyPackages.${system}.alejandra;
+    devShells.${system}.default = pkgs.mkShell {
+      buildInputs = with pkgs; [
+        ffmpeg
+        fmt.dev
+        cudaPackages.cuda_cudart
+        cudatoolkit
+        nvidiaPackage
+        cudaPackages.cudnn
+        libGLU
+        libGL
+        xorg.libXi
+        xorg.libXmu
+        freeglut
+        xorg.libXext
+        xorg.libX11
+        xorg.libXv
+        xorg.libXrandr
+        zlib
+        ncurses
+        stdenv.cc
+        binutils
+        uv
+      ];
+      shellHook = ''
+        export LD_LIBRARY_PATH="${nvidiaPackage}/lib:$LD_LIBRARY_PATH"
+        export CUDA_PATH=${pkgs.cudatoolkit}
+        export EXTRA_LDFLAGS="-L/lib -L${nvidiaPackage}/lib"
+        export EXTRA_CCFLAGS="-I/usr/include"
+        export CMAKE_PREFIX_PATH="${pkgs.fmt.dev}:$CMAKE_PREFIX_PATH"
+        export PKG_CONFIG_PATH="${pkgs.fmt.dev}/lib/pkgconfig:$PKG_CONFIG_PATH"
+      '';
+    };
+  };
+}</syntaxhighlight>
+== Setting up CUDA Binary Cache ==
+The [https://nix-community.org/cache/ Nix-community cache] contains pre-built CUDA packages. By adding it to your system, Nix will fetch these packages instead of building them, saving valuable time and processing power.
+For more information, refer to the [[Binary Cache#Using a binary cache Using a binary cache|Using a binary cache]] page.
+{{warning|1=You need to rebuild your system at least once after adding the cache, before it can be used.}}
+=== NixOS ===
+Add the cache to <code>substituters</code> and <code>trusted-public-keys</code> inside your system configuration:
+{{file|/etc/nixos/configuration.nix|nix|<nowiki>
+nix.settings = {
+  substituters = [
+    "https://nix-community.cachix.org"
+  ];
+  trusted-public-keys = [
+    "nix-community.cachix.org-1:mB9FSh9qf2dCimDSUo8Zy7bkq5CX+/rkCWyvRCYg3Fs="
+  ];
+};
+</nowiki>}}
+=== Non-NixOS ===
+If you have [https://www.cachix.org cachix] installed and set up, all you need to do is run:
+<syntaxHighlight lang="console">
+$ cachix use nix-community
+</syntaxHighlight>
+Else, you have to add <code>substituters</code> and <code>trusted-public-keys</code> to <code>/etc/nix/nix.conf</code>:
+{{file|/etc/nix/nix.conf|nix|<nowiki>
+trusted-public-keys = nix-community.cachix.org-1:mB9FSh9qf2dCimDSUo8Zy7bkq5CX+/rkCWyvRCYg3Fs=
+trusted-substituters = https://nix-community.cachix.org
+trusted-users = root @wheel
+</nowiki>}}
+If your user is in <code>trusted-users</code>, you can also add the cache in your home directory:
+{{file|~/.config/nix/nix.conf|nix|<nowiki>
+substituters = https://nix-community.cachix.org
+</nowiki>}}
+== 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.
+* 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.opengl.enable</code> enabled.
+* By default, software packaged in source code form has CUDA support disabled, because of the unfree license. To solve this, you can enable builds with CUDA support with a nixpkgs wide configuration, or use binary packaged CUDA compatible software such as [https://github.com/edolstra/nix-warez/tree/master/blender blender-bin].
+== CUDA under WSL ==
+This (surprisingly) works just fine using nixpkgs 23.05 provided that you prefix the <code>LD_LIBRARY_PATH</code> in your interactive environment with the WSL library directory. For nix shell this looks like:
+{{file|cuda-shell.nix|nix|<nowiki>
+   shellHook = ''
+      export CUDA_PATH=${pkgs.cudatoolkit}
+      export LD_LIBRARY_PATH=/usr/lib/wsl/lib:${pkgs.linuxPackages.nvidia_x11}/lib:${pkgs.ncurses5}/lib
        export EXTRA_LDFLAGS="-L/lib -L${pkgs.linuxPackages.nvidia_x11}/lib"
        export EXTRA_CCFLAGS="-I/usr/include"
     '';
-}
 </nowiki>}}
@@ Line 93: / Line 210: @@
 * [https://discourse.nixos.org/t/cuda-setup-on-nixos/1118 CUDA setup on NixOS]
 * [https://github.com/NixOS/nixpkgs/issues/131608 eGPU with nvidia-docker on intel-xserver]
+* [https://discourse.nixos.org/t/cuda-in-nixos-on-gcp-for-a-tesla-k80/ Tesla K80 based CUDA setup with Terraform on GCP]
+[[Category:Server]]