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NickLucche / stable-diffusion-nvidia-docker

GPU-ready Dockerfile to run Stability.AI stable-diffusion model v2 with a simple web interface. Includes multi-GPUs support.
MIT License
357 stars 43 forks source link

Can we pool cpu and gpu? Or is that impossible? #25

Open DuckersMcQuack opened 1 year ago

DuckersMcQuack commented 1 year ago

I plan to get another 3090, but if it is possible to "pool" cpu and gpu performance and allocate 24GB ram as well as a "shared same amount each", i'd love to try that! Might be dreadfully slow due to "potato cpu vs gpu performance", but worth an experimentation!

Cpu in question here is a 5900x.

NickLucche commented 1 year ago

Hey, sorry for the late reply, this is possible although a bit unconventional due to the huge speed differences. You would want to have two models, one on cpu and the other on gpu did I get that right?

DuckersMcQuack commented 1 year ago

Hey, sorry for the late reply, this is possible although a bit unconventional due to the huge speed differences. You would want to have two models, one on cpu and the other on gpu did I get that right?

If that's what it takes to get the pooling of cpu as well, sure! Got 64GB ram, so plenty to take from :) As i wanna see for myself what "speed increase" that would achieve.

NickLucche commented 1 year ago

RAM wouldn't be the bottleneck here tho, what would happen is that you get the GPU model output in a few seconds for say image_0 and then you're stuck waiting for the CPU models to finish computation for image_1, image_2...

What I would rather consider is adding an optimized model for CPU inference only..