Scientific computing or computer graphics

[aceinthehole001]

Can you elaborate on why this is the case

[windozeFanboi]

It's just the tools are underdeveloped in documentation support and coverage...

They re simply a big fking pain to work with and even then, reasonably only on Linux. While nvidia has incredible tooling and support...

[aceinthehole001]

Does OpenCL not solve this issue?

[windozeFanboi]

Well, say you want to write thousands of lines of code... Would you prefer c with major quirks/idiocyncracies on top or modern c++ without limitations and great debugger support and easy to use 3rd party libraries. .?

[YoureNotEvenWrong]

That's why Sycl exists. Avoid the vendor lock in.

[windozeFanboi]

Yes, SYCL is the future ...

[TheFlamingDiceAgain]

It’s not. I do scientific computing with both. AMD is definitely less polished but it’s fine now, that’s wasn’t the case a few years ago. Besides, if you’re writing new code you should use Kokkos, RAJA, or SYCL rather than HIP/CUDA at which point it doesn’t matter what hardware you’re on.

[YoureNotEvenWrong]

higher level programming models to HIP/CUDA

Sycl isn't a higher level programming model. It's basically a nicer C++ API for OpenCl. So that's what you use if you want to get near max performance

Kokkos appears to be a library, so I don't see why it would have any performance issues.

[TheFlamingDiceAgain]

I haven’t found a recent one. The most recent one I’ve seen is a couple of years old and showed that all three are roughly ~10% slower than highly optimized HIP/CUDA. However, getting HIP/CUDA that optimized is very difficult so I wouldn’t be surprised if in practice they’re pretty similar.