| 20 May 2026 |
Prayag Bhakar | I see, so at the minimum targeting the $5k budget hardware range with Ampere Altra or an Apple M Series Mac (probably also need Asahi Linux). Is there a donation target/pool for this goal? | 23:59:21 |
| 21 May 2026 |
Prayag 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 |
Prayag 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 |
Gaétan 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 |
SomeoneSerge (matrix works sometimes) | /me goes on to dream about an Asahi cluster for reproducibility studies | 12:36:34 |
Prayag 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 |
Marmar | 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 | Does Asahi work on M2? We could get a Mac Pro that nobody needs for relatively cheap ;) | 15:23:44 |
Gaétan Lepage | I'd rather use it to build/test packages on darwin | 16:23:08 |
Gaétan Lepage | staging-next was merged very recently into master, so our Hydra instance is probably catching up at this moment. | 16:23:39 |
Prayag Bhakar |  Download image.png | 17:37:08 |
Prayag Bhakar | seems like folks have been able to compile Linux on Mac with a few patchs https://seiya.me/blog/building-linux-on-macos-natively | 17:37:41 |
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 |