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There's more in common with other GPU architectures than there are differences, so a CUDA consultant should be able to pivot if/when the other players are a goi
by Philpax 1y ago
There's more in common with other GPU architectures than there are differences, so a CUDA consultant should be able to pivot if/when the other players are a going concern. It's more about the mindset than the specifics.
- dotancohen 1y agoI've been hearing that for over a decade. I can't even name off hand any CUDA competitors, none of them are likely to gain enough traction to upset CUDA in the coming decade.
- Philpax 1y agoHence the "if" :-) ROCm is getting some adoption, especially as some of the world's largest public supercomputers have AMD GPUs. Some of this is also being solved by working at a different abstraction layer; you can sometimes be ignorant to the hardware you're running on with PyTorch. It's still leaky, but it's something.
- physicsguy 1y agoI still don't see ROCm as that serious a threat, they're still a long way behind in library support. I used to use ROCFFT as an example, it was missing core functionality that cuFFT has had since like 2008. It looks like they've finally caught up now, but that's one library among many.
- Q6T46nT668w6i3m 1y agoLook at the state of PyTorch’s CI pipelines and you’ll immediately see that ROCm is a nightmare. Especially nowadays when TPU and MPS, while missing features, rarely create cascading failures throughout the stack.
- j45 1y agoWaiting just adds more dust to the skills pile. Programming languages are groups of syntax.
- einpoklum 1y agoTalking about hardware rather than software, you have AMD and Intel. And - if your platform is not x86_64, NVIDIA is probably not even one of the competitors; and you have ARM, Qualcomm, Apple, Samsung and probably some others.
- sdenton4 1y ago...Well, the article compares GPUs to tpus, made by a competitor you probably know the name of...