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Comment by PeterisP | Hacker News Reader

This is a bit of a chicken and egg problem, because the developers of these projects probably don't even have relevant AMD devices to test that, because why would they?

The only reasonable way to break the cycle would be proactive intervention by AMD to contribute code and testing and easy "works out of the box" installation to all the major popular projects to add AMD support so they can sell more their hardware later, but I'm not seeing AMD doing that.

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CUDA is just way to good in terms of UX with nothing platform-independent coming close to it. I wish there was a competitor, but there simply isn't.

I wish AMD&Intel would extend compute shaders with pointers&pointer casting, arbitrary large buffers instead of just 4GB, device-wide sync, and function pointers. Those are kinda my must-have functionality. Even better, just use C++ for compute shaders.

Freestanding C++ can be compiled to amdgpu or nvptx using clang. There are rough edges but it's usable.

Like the pytorch one? Or the onnx? Or Triton? There's loads of these machine learning things, each of which built their thing assuming Nvidia, to which AMD is stoically working to implement support for their hardware. It's a task of unbounded scope with unclear return on investment and they're doing it anyway.

Maybe the AMD device will just have to announce it's (KHTML, like Gecko).

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