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They’re not ignoring it, they’re eroding it. The API that matters is Torch, and only the API. Letting NVIDIA charge famine prices is both a bad idea and a huge
by benreesman 3y ago
They’re not ignoring it, they’re eroding it.
The API that matters is Torch, and only the API. Letting NVIDIA charge famine prices is both a bad idea and a huge incentive to write software bridging the gap.
- kkielhofner 3y agoI don’t know if you do work in this space but this wasn’t accurate several years ago and it certainly isn’t accurate now. The amount of extremely CUDA specific handwritten compute architecture code, custom kernels, etc has exploded and other than a few things here and there (yes, like torch SDPA) we’re waaaay past vanilla torch for anything beyond a toy. The pricing and theoretical hardware specs of these novelties doesn’t matter when an inferior on paper Nvidia product will wipe the floor with the other in the real world. People have spent 15 years wringing every last penny out of CUDA on Nvidia hardware. There is some light shining through but you’ll still see things like “Woo-hoo FlashAttention finally supports ROCm! Oh wait, what’s that, FlashAttention2 has been running on CUDA for six months?” Don’t even get me started on the “alternative” software stacks and drivers.
- pjmlp 3y agoAlso the anti-CUDA folks keep forgetting the polyglot nature of the ecosystem, made possible since PTX was introduced on CUDA 3.0. The graphical debugging tools that allows stepping through GPU code just like with on the CPU.
- pjmlp 3y agoFor those like myself Torch means nothing, I don't use GPU for machine learning rather graphics programming and general purpose compute.