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NixOS CUDA

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CUDA packages maintenance and support in nixpkgs | https://github.com/orgs/NixOS/projects/27/ | https://nixos.org/manual/nixpkgs/unstable/#cuda63 Servers

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21 May 2026
@81reap:matrix.orgPrayag Bhakar* I see, so at the minimum targeting the $5k budget hardware range with Ampere Altra or a used/refurbished Apple M Series Mac (probably also need Asahi Linux). Is there a donation target/pool for this goal? 00:11:20
@81reap:matrix.orgPrayag Bhakar* I see, so at the minimum targeting the $5k budget hardware range with Ampere Altra Dev Box/Server or a used/refurbished Apple M Series Mac (probably also need Asahi Linux). Is there a donation target/pool for this goal? 00:14:07
@glepage:matrix.orgGaétan Lepage Thanks once again for proposing to help.
Yes, Ampere altra is a solution. Mac + Asahi less so as we want to avoid hacking stuff around more than necessary.
We will be sharing a detailed list of what systems we are looking to get for our CI. However, the budget range is more enterprise-scale than individual-donation scale.
As mentionned before, we're strenghtening our collaboration with companies which are interested to help us on this front.
I hope to be able to update you on our infra soon.
07:45:54
@ss:someonex.netSomeoneSerge (matrix works sometimes)/me goes on to dream about an Asahi cluster for reproducibility studies12:36:34
@81reap:matrix.orgPrayag Bhakar

got it. is there anything I can help with? Sounds like there's an ongoing effort to refactor hostPlatform to be a "polycule". Is there anything I can do there?

I have a lot of machines with Nvidia GPUS that I use nix & nixOS with, so I would still like to help improve the system https://prayag.bhakar.org/000-00-0000/apollo-server.jpg

14:39:34
@marmar22:tchncs.deMarmar Hello, I find that the binary cache doesn't have one for cudaPackages.libnvshmem on my system, which resorts to building from source which I don't have the resources to. Hydra says that the package is there, so I'm not sure on that. Exact name of the package is/nix/store/4nzqdwc370may1ilz6zyy34ym16jlqvn-cuda12.9-libnvshmem-3.6.5-0.drv 15:14:03
@yorik.sar:matrix.orgyorik.sarDoes Asahi work on M2? We could get a Mac Pro that nobody needs for relatively cheap ;)15:23:44
@glepage:matrix.orgGaétan LepageI'd rather use it to build/test packages on darwin16:23:08
@glepage:matrix.orgGaétan Lepage staging-next was merged very recently into master, so our Hydra instance is probably catching up at this moment. 16:23:39
@81reap:matrix.orgPrayag Bhakarimage.png
Download image.png
17:37:08
@81reap:matrix.orgPrayag Bhakarseems like folks have been able to compile Linux on Mac with a few patchs https://seiya.me/blog/building-linux-on-macos-natively17:37:41
@81reap:matrix.orgPrayag Bhakar

Does Asahi work on M2?

also yes! https://asahilinux.org/fedora/#device-support

18:20:25
24 May 2026
@eihqnh:mozilla.orgeihqnh joined the room.15:41:45
@hexa:lossy.networkhexanixos-26.05 has been branched16:26:04
@hexa:lossy.networkhexaprobably time to update the hydra jobsets16:26:12
@hexa:lossy.networkhexahttps://isaiprofitable.com/ lmao16:40:49
@hexa:lossy.networkhexawell played, nvidia16:40:59
@glepage:matrix.orgGaétan LepageYup, will do.19:30:48
@glepage:matrix.orgGaétan Lepage https://github.com/nixos-cuda/hydra-jobsets/pull/31 20:13:09
27 May 2026
@glepage:matrix.orgGaétan Lepage

If anyone has a decent modern GPU to test the flash-attention tests, please ping me.
The CUDA team's infra is not sufficent:

python3.13-flash-attention> FAILED tests/losses/test_cross_entropy.py::test_cross_entropy_loss[128256-0.9-0.7-True-0.01-True-False-dtype2] - torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 1002.00 MiB. GPU 0 has a total capacity of 19.55 GiB of which 360.38 MiB is free. Including non-PyTorch memory, this process has 19.19 GiB memory in use. Of the allocated memory 18.10 GiB is allocated by PyTorch, and 925.39 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)

Thanks in advance for your generosity

15:24:45
@berrij:fairydust.spaceBerriJWould an RTX 6000 Pro with 96GB VRAM be okay? If yes I could run these test but I would need relatively detailed instructions. I'm running a flake based system based on nixos-unstable and I'm running the "latest" Nvidia drivers.15:49:37
@glepage:matrix.orgGaétan Lepage

I'm pretty sure that would fit. Thanks a lot!

You'd need to add the following to your config:

      programs.nix-required-mounts = {
        enable = true;
        presets.nvidia-gpu.enable = true;
      };

Then

nix build github:GaetanLepage/nixpkgs/flash-attn#python3Packages.flash-attn.gpuCheck --cores 10
16:00:23
@glepage:matrix.orgGaétan Lepage Watch out for RAM consumption though. It's terribly hungry. I need to set it to 15 max on a 128GB system. 16:01:16
@glepage:matrix.orgGaétan Lepage Hmm. Wait, you need to set cudaSupport. 16:02:39
@berrij:fairydust.spaceBerriJI could also jump into a dev shell if you provide me a flake if that's easier. Anyway I can try when I'm back home in about an hour. And the machine in question has 760gb of ram so we should be fine I guess 😇16:04:05
@hexa:lossy.networkhexain this economy?!16:04:38
@glepage:matrix.orgGaétan Lepage
nix build --impure --cores 2 --expr '
    (import (builtins.getFlake "github:GaetanLepage/nixpkgs/flash-attn") {
      system = builtins.currentSystem;
      config = { allowUnfree = true; cudaSupport = true; };
    }).python3Packages.flash-attn.gpuCheck
  '

This should do it.

16:05:28
@glepage:matrix.orgGaétan Lepage *
nix build --impure --expr '
    (import (builtins.getFlake "github:GaetanLepage/nixpkgs/flash-attn") {
      system = builtins.currentSystem;
      config = { allowUnfree = true; cudaSupport = true; };
    }).python3Packages.flash-attn.gpuCheck
  '

This should do it.

16:05:59
@berrij:fairydust.spaceBerriJ
In reply to @hexa:lossy.network
in this economy?!
It's not my private one unfortunately 😅
But I'm the admin and currently there is no workload on that thing.
16:07:57
@glepage:matrix.orgGaétan Lepage

I mean... If only I had nix installed...

root@p4-r01-ct18:~# nvidia-smi
Wed May 27 16:10:23 2026
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 580.126.21             Driver Version: 580.126.21     CUDA Version: 13.2     |
+-----------------------------------------+------------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |
|                                         |                        |               MIG M. |
|=========================================+========================+======================|
|   0  NVIDIA GB200                   On  |   00000008:01:00.0 Off |                    0 |
| N/A   45C    P0            170W / 1200W |       0MiB / 189471MiB |      0%      Default |
|                                         |                        |             Disabled |
+-----------------------------------------+------------------------+----------------------+
|   1  NVIDIA GB200                   On  |   00000009:01:00.0 Off |                    0 |
| N/A   45C    P0            153W / 1200W |       0MiB / 189471MiB |      0%      Default |
|                                         |                        |             Disabled |
+-----------------------------------------+------------------------+----------------------+
|   2  NVIDIA GB200                   On  |   00000018:01:00.0 Off |                    0 |
| N/A   45C    P0            153W / 1200W |       0MiB / 189471MiB |      0%      Default |
|                                         |                        |             Disabled |
+-----------------------------------------+------------------------+----------------------+
|   3  NVIDIA GB200                   On  |   00000019:01:00.0 Off |                    0 |
| N/A   45C    P0            176W / 1200W |       0MiB / 189471MiB |      0%      Default |
|                                         |                        |             Disabled |
+-----------------------------------------+------------------------+----------------------+

+-----------------------------------------------------------------------------------------+
| Processes:                                                                              |
|  GPU   GI   CI              PID   Type   Process name                        GPU Memory |
|        ID   ID                                                               Usage      |
|=========================================================================================|
|  No running processes found                                                             |
+-----------------------------------------------------------------------------------------+
16:10:33

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