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AMD funded a drop-in CUDA implementation built on ROCm: It's now open-source

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1045 points mfiguiere | 2 comments | 12 Feb 24 14:00 UTC | HN request time: 0.535s | source
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Keyframe ◴[12 Feb 24 16:45 UTC] No.39347045[source]▶
This event of release is however a result of AMD stopped funding it per "After two years of development and some deliberation, AMD decided that there is no business case for running CUDA applications on AMD GPUs. One of the terms of my contract with AMD was that if AMD did not find it fit for further development, I could release it. Which brings us to today." from https://github.com/vosen/ZLUDA?tab=readme-ov-file#faq

so, same mistake intel made before.

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tgsovlerkhgsel ◴[12 Feb 24 22:44 UTC] No.39351568[source]▶
How is this not priority #1 for them, with NVIDIA stock shooting to the moon because everyone does machine learning using CUDA-centric tools?

If AMD could get 90% of the CUDA ML stuff to seamlessly run on AMD hardware, and could provide hardware at a competitive cost-per-performance (which I assume they probably could since NVIDIA must have an insane profit margin on their GPUs), wouldn't that be the opportunity to eat NVIDIA's lunch?

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1. make3 ◴[12 Feb 24 22:50 UTC] No.39351635[source]▶
it's a common misconception that deep learning stuff is built in cuda. it's actually built on CUDNN kernels that don't use cuda but are actually gpu assembly written by hand by phds. I'm really not convinced that this project here would be able to be used for this. the ROCm kernels that are analogue to cudnn though, yes
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2. abbra ◴[13 Feb 24 06:05 UTC] No.39354982[source]▶
This project relies on ROCm for all it's CUDNN magic.