| 21 May 2026 |
Prayag Bhakar |
Does Asahi work on M2?
also yes! https://asahilinux.org/fedora/#device-support
| 18:20:25 |
| 24 May 2026 |
| eihqnh joined the room. | 15:41:45 |
hexa | nixos-26.05 has been branched | 16:26:04 |
hexa | probably time to update the hydra jobsets | 16:26:12 |
hexa | https://isaiprofitable.com/ lmao | 16:40:49 |
hexa | well played, nvidia | 16:40:59 |
Gaétan Lepage | Yup, will do. | 19:30:48 |
Gaétan Lepage | https://github.com/nixos-cuda/hydra-jobsets/pull/31 | 20:13:09 |
| 27 May 2026 |
Gaétan 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 | Would 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 |
Gaétan 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 |
Gaétan 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 |
Gaétan Lepage | Hmm. Wait, you need to set cudaSupport. | 16:02:39 |
BerriJ | I 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 | in this economy?! | 16:04:38 |
Gaétan 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 |
Gaétan 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 | 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 |
Gaétan 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 |
hexa | makes you wonder who we are building cuda support for | 16:12:00 |
Gaétan Lepage | Not for the owners of those GPUs unfortunately 🥲 | 16:20:08 |
BerriJ | In my case I'm working at a German University and the server is used by a team of around 9 researchers :) | 16:33:56 |
hexa | pretty sure Gaetan works at some French university 😆 | 16:37:26 |
Gaétan Lepage | Not anymore. (French universities don't have such fancy GPUs) 🫠 | 16:38:38 |
BerriJ | The build is running now :) | 17:16:42 |
SomeoneSerge (matrix works sometimes) | Can't you nix in container? | 18:26:52 |
SomeoneSerge (matrix works sometimes) | Not TUM? | 18:27:57 |
SomeoneSerge (matrix works sometimes) | Not the OS group? I'd be hyped yo learn that somebody in academia/hpc/rse community actually uses nixpkgs cuda, because so far I've been getting the vibes that only the enterprise cares, and all these eurohpc/CSC/yada yada are completely unapproachable and dead set on their easybuild lmod workflows... | 18:33:29 |
BerriJ | University of Duisburg-Essen, not TUM
But it's really not that big of a deal. The economics faculty has its own little IT department, they bought some servers for machine learning of which our Chair was able to get one and we asked them to install nixos on that for us cause we use nixos since 2 years on all of our machines.
That's essentially the full story, there is not that much support for NixOS besides me pushing it and my Boss seeing the advantages and sometimes proudly talking about our infra 😅 | 18:55:53 |
SomeoneSerge (matrix works sometimes) | Shooting in the dark but anything that could be done or reprioritized on our side to potentially help the lab's story? | 19:48:31 |