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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 | 4 comments | 12 Feb 24 14:00 UTC | HN request time: 0s | source
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btown ◴[12 Feb 24 14:37 UTC] No.39345221[source]▶
Why would this not be AMD’s top priority among priorities? Someone recently likened the situation to an Iron Age where NVIDIA owns all the iron. And this sounds like AMD knowing about a new source of ore and not even being willing to sink a single engineer’s salary into exploration.

My only guess is they have a parallel skunkworks working on the same thing, but in a way that they can keep it closed-source - that this was a hedge they think they no longer need, and they are missing the forest for the trees on the benefits of cross-pollination and open source ethos to their business.

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izacus ◴[12 Feb 24 14:54 UTC] No.39345400[source]▶
Why do you think running after nVidia for this submarket is a good idea for them? The AMD GPU team isn't especially big and the development investment is massive. Moreover, they'll have the opportunity cost for projects they're now dominating in (all game consoles for example).

Do you expect them to be able to capitalize on the AI fad so much (and quickly enough!) that it's worth dropping the ball on projects they're now doing well in? Or perhaps continue investing into the part of the market where they're doing much better than nVidia?

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1. throwawaymaths ◴[12 Feb 24 15:04 UTC] No.39345522[source]▶
IIRC (this could be old news) AMD GPUs are preferred in the supercomputer segment because they offer better flops/unit energy. However without a cuda-like you're missing out on the AI part of supercompute, which is increasing proportion.

The margins on supercompute-related sales are very high. Simplifying, but you can basically take a consumer chip, unlock a few things, add more memory capacity, relicense, and your margin goes up by a huge factor.

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2. Symmetry ◴[12 Feb 24 15:19 UTC] No.39345747[source]▶
It's more that the resource balance in AMD's compute line of GPUs (the CDNA ones) has been more focused on the double precision operations that most supercomputer code makes heavy use of.
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3. anonylizard ◴[12 Feb 24 15:39 UTC] No.39346067[source]▶
They are preferred not because of inherent superiority of AMD GPUs. But simply because they have to price lower and have lower margins.

Nvidia could always just half their prices one day, and wipe out every non-state-funded competitor. But Nvidia prefers to collect their extreme margins and funnel it into even more R&D in AI.

4. throwawaymaths ◴[12 Feb 24 22:03 UTC] No.39351166[source]▶
Thanks for clarifying! I had a feeling I had my story slightly wrong