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When you follow ROCm's happy path it works well for getting things like PyTorch running, but you do end up putting up with enterprise distros like Ubuntu 22.04
by simfree 4y ago
When you follow ROCm's happy path it works well for getting things like PyTorch running, but you do end up putting up with enterprise distros like Ubuntu 22.04 LTS and its often broken by default network stack.
Enabling ROCm support for unlisted AMD GPUs & APUs is a feature flag away if your running one of these janky enterprise distros that AMD has blessed.
Debian is slowly getting ROCm and PyTorch's packages into the main Debian archive, once complete using AMD hardware for machine learning should be a breezey Apt Install ROCm away, as Debian's machine learning team chooses sane defaults like enabling APU support by default. Derivative distros like PopOS, Linux Mint, Zorin, Kali, Ubuntu and such will inherit this easy support from upstreaming ROCm as well.
- boppo1 4y agohow do I turn on this feature flag? I'm quite happy on xubuntu.
- simfree 4y agoRead their GitHub, there is an issue where they cover the feature flag you need to set to enable ROCm on unsupported platforms.
- kkielhofner 4y agoGenuinely curious - when you say “PyTorch runs” what are you doing with it? When I last tried it a year or so ago it was (more or less) useless. Yes it “ran” but there were weird crashes and edge cases all over the place. Throw in the fact that 95% of documentation, examples, tools, benchmarks, etc are still for CUDA after four years or so of embarking on this journey I think I’ve finally given up for good. I happily and very firmly live in Nvidia/CUDA land now where I can see a story on HN and have it running on my GPU in under 10 minutes. Or 30 seconds if it’s a docker container. You’re brave for running on unsupported GPUs! My experience was bad enough with the “supported” ones :).
- simfree 4y agoIt seems stable with Whisper and a few other models...