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dookiehat t1_iyt3gjg wrote

Reply to comment by Spirit_of_Hogwash in StableDiffusion can generate an image on Apple Silicon Macs in under 18 seconds, thanks to new optimizations in macOS 13.1 by Avieshek

I think it is a software or compiler (?) issue. Stable Diffusion was written for nvidia gpus w cuda cores. Idk what sort of translation happens but it probably leads to inefficiencies not experienced with nvidia.

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sylfy t1_iytgr3x wrote

CUDA and the accompanying cudnn libraries are highly specialised hardware and software libraries for machine learning tasks provided by Nvidia, that they have been working on over the past decade.

It’s the reason Nvidia has such a huge lead in the deep learning community, and the reason that their GPUs are able to command a premium over AMD. Basically all deep learning tools are now designed and benchmarked around Nvidia and CUDA, with some also supporting custom built hardware like Google’s TPUs. AMD is catching up, but the tooling for Nvidia “just works”. This is also the reason people buy those $2000 3090s and 4090s, not for gaming, but for actual work.

Frankly, the two chips are in completely different classes in terms of power draw and what they do (one is a dedicated GPU, the other is a whole SoC), it’s impressive that the M1/M2 even stays competitive.

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