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

(www.phoronix.com)
1045 points mfiguiere | 4 comments | 12 Feb 24 14:00 UTC | HN request time: 0.911s | source
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lambdaone ◴[12 Feb 24 15:32 UTC] No.39345937[source]▶
It seems to me that AMD are crazy to stop funding this. CUDA-on-ROCm breaks NVIDIA's moat, and would also act as a disincentive for NVIDIA to make breaking changes to CUDA; what more could AMD want?

When you're #1, you can go all-in on your own proprietary stack, knowing that network effects will drive your market share higher and higher for you for free.

When you're #2, you need to follow de-facto standards and work on creating and following truly open ones, and try to compete on actual value, rather than rent-seeking. AMD of all companies should know this.

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1. saboot ◴[12 Feb 24 15:55 UTC] No.39346284[source]▶
Yep, I develop several applications that use CUDA. I see AMD/Radeon powered computers for sale and want to buy one, but I am not going to risk not being able to run those applications or having to rewrite them.

If they want me as a customer, and they have not created a viable alternative to CUDA, they need to pursue this.

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2. weebull ◴[12 Feb 24 21:53 UTC] No.39351051[source]▶
Define "viable"?
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3. croutons ◴[13 Feb 24 02:23 UTC] No.39353549[source]▶
A backend that runs PyTorch out of the box and is as easy to setup / use as nvidia stack.
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4. weebull ◴[14 Feb 24 21:02 UTC] No.39375285{3}[source]▶
Installing PyTorch with the PyTorch website instructions for AMD was pretty painless for me on Linux. I know everybodies experience is different, but install wasn't the issue for me.

For me the issue on AMD was stability in situations when VRAM was getting tight.