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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 | 1 comments | 12 Feb 24 14:00 UTC | HN request time: 0.641s | source
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AndrewKemendo ◴[12 Feb 24 14:53 UTC] No.39345391[source]▶
ROCm is not spelled out anywhere in their documentation and the best answers in search come from Github and not AMD official documents

"Radeon Open Compute Platform"

https://github.com/ROCm/ROCm/issues/1628

And they wonder why they are losing. Branding absolutely matters.

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sorenjan ◴[12 Feb 24 15:27 UTC] No.39345873[source]▶
Funnily enough it doesn't work on their RDNA ("Radeon DNA") hardware (with some exceptions I think), but it's aimed at their CDNA (Compute DNA). If they would come up with a new name today it probably wouldn't include Radeon.

AMD seems to be a firm believer in separating the consumer chips for gaming and the compute chips for everything else. This probably makes a lot of sense from a chip design and current business perspective, but I think it's shortsighted and a bad idea. GPUs are very competent compute devices, and basically wasting all that performance for "only" gaming is strange to me. AI and other compute is getting more and more important for things like image and video processing, language models, etc. Not only for regular consumers, but for enthusiasts and developers it makes a lot of sense to be able to use your 10 TFLOPS chip even when you're not gaming.

While reading through the AMD CDNA whitepaper I saw this and got a good chuckle. "culmination of years of effort by AMD" indeed.

> The computational resources offered by the AMD CDNA family are nothing short of astounding. However, the key to heterogeneous computing is a software stack and ecosystem that easily puts these abilities into the hands of software developers and customers. The AMD ROCm 4.0 software stack is the culmination of years of effort by AMD to provide an open, standards-based, low-friction ecosystem that enables productivity creating portable and efficient high-performance applications for both first- and third-party developers.

https://www.amd.com/content/dam/amd/en/documents/instinct-bu...

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slavik81 ◴[12 Feb 24 15:58 UTC] No.39346337[source]▶
ROCm works fine on the RDNA cards. On Ubuntu 23.10 and Debian Sid, the system packages for the ROCm math libraries have been built to run on every discrete Vega, RDNA 1, RDNA 2, CDNA 1, and CDNA 2 GPU. I've manually tested dozens of cards and every single one worked. There were just a handful of bugs in a couple of the libraries that could easily be fixed by a motivated individual. https://slerp.xyz/rocm/logs/full/

The system package for HIP on Debian has been stuck on ROCm 5.2 / clang-15 for a while, but once I get it updated to ROCm 5.7 / clang-17, I expect that all discrete RDNA 3 GPUs will work.

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1. stonogo ◴[12 Feb 24 19:54 UTC] No.39349534[source]▶
It doesn't matter to my lab whether it technically runs. According to https://rocm.docs.amd.com/projects/install-on-linux/en/lates... it only supports three commercially-available Radeon cards (and four available Radeon Pro) on Linux. Contrast this to CUDA, which supports literally every nVIDIA card in the building, including the crappy NVS series and weirdo laptop GPUs, and it basically becomes impossible to convince anyone to develop for ROCm.