Nika03: Added fitting categories to the page

2026-10-15T10:13:06Z

Added fitting categories to the page

← Older revision		Revision as of 10:13, 15 October 2026
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			[[Category:Software]]
			[[Category:Server]]

Nika03: Created the article

2026-10-15T10:11:25Z

Created the article

New page

== Foreword ==
From Wikipedia:<blockquote>'''Folding@home''' ('''FAH''' or '''F@h''') is a distributed computing project aimed to help scientists develop new therapeutics for a variety of diseases by the means of simulating protein dynamics. This includes the process of protein folding and the movements of proteins, and is reliant on simulations run on volunteers' personal computers. Folding@home is currently based at the University of Pennsylvania and led by Greg Bowman, a former student of Vijay Pande.<ref>https://en.wikipedia.org/wiki/Folding@home</ref></blockquote>

== Installation ==
Basic installation requires following changes to the configuration:<syntaxhighlight lang="nix">
# Enable the Folding@home service.
services.foldingathome.enable = true;

# Create a system user that belongs to a group of the same name.
users.users.foldingathome = {
isSystemUser = true;
group = "foldingathome";
};
# Create a group "foldingathome" for the user
users.groups.foldingathome = {};

# The default service configuration is flawed, as
# DynamicUser doesn't have the necessary permissions
# to execute the cores that live in /var/lib/private
systemd.services.foldingathome.serviceConfig = {
DynamicUser = lib.mkForce false;
User = "foldingathome";
Group = "foldingathome";
};
</syntaxhighlight>The cores are prebuilt generic Linux binaries. '''I’m not sure this is strictly needed:''' I had it already enabled, so I never tested without it. <syntaxhighlight lang="nix">
programs.nix-ld.enable = true;
</syntaxhighlight>

== Using computing power of GPUs ==
If you desire to use compute power of a GPU, then make the following changes to your configuration:

=== Platform independent ===
<syntaxhighlight lang="nix">
users.users.foldingathome.extraGroups = [ "video" "render" ];
</syntaxhighlight>

=== AMD ===
<syntaxhighlight lang="nix">hardware.graphics = {
enable = true;
extraPackages = [ pkgs.rocmPackages.clr.icd ];
};</syntaxhighlight>

=== NVIDIA ===
The following configuration is hypothetical , as I don't have a machine with an Nvidia GPU.

As a hypothetical point of reference, I used the RTX 4070:<syntaxhighlight lang="nix">
hardware.graphics.enable = true;
services.xserver.videoDrivers = [ "nvidia" ]; # needed even if you run headless or Wayland

hardware.nvidia = {
modesetting.enable = true;
open = true; # the 4070 (Ada) supports the open kernel modules
package = config.boot.kernelPackages.nvidiaPackages.stable;
};
</syntaxhighlight>

=== Intel Arc Battlemage (B570, B580) ===
Again, this is also a hypothetical but furthermore, a path rarely trodden. Theoretically possible, but untested.

Folding@home cores need double-precision (FP64) math. '''Intel Arc Alchemist (A310, A380, A750, A770)''' GPUs don't have the hardware implementation for FP64; it's handled by the driver. '''Battlemage (B570 and B580)''' cards do have the FP64 hardware.

One user reported v8.3 recognized the card but showed <code>support: false</code> and couldn’t download GPU work units. Those posts are from 2024-2025, so I don’t know the status today, in October 2026.<ref>https://forum.foldingathome.org/viewtopic.php?p=366886</ref>

If you want to try regardless:<syntaxhighlight lang="nix">
hardware.graphics = {
enable = true;
extraPackages = [ pkgs.intel-compute-runtime ];
};
</syntaxhighlight>

Folding@home - Revision history

Nika03: Added fitting categories to the page

Nika03: Created the article