GPUs for Deep Learning in 2023 – An In-depth Analysis

Re:GPUs for Deep Learning in 2023 – An In-depth Analysis by jszymborski on Wednesday January 18, 2023 @03:03PM (#34432251)

> It doesn't have enough RAM for most problems.

It might not be as glamorous or make as many headlines, but there is plenty of research that goes on below 40Gb.

While I most commonly use A100s for my research, all my models fit on my personal RTX 2080.

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Re:GPUs for Deep Learning in 2023 – An In-depth Analysis by ngcc_hk on Wednesday January 18, 2023 @06:10PM (#34434451)

Wonder are you trying to walk around the limit or it just happen like this?

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Re:GPUs for Deep Learning in 2023 – An In-depth Analysis by jszymborski on Wednesday January 18, 2023 @06:43PM (#34434777)

We're trying to walk around to limits:

I) My research involves biological data (protein-protein interactions) and my datasets are tiny (about 30K high-confidence samples). We have to regularize aggressively and use a pretty tiny network to get something that doesn't over-fit horrendously.

II) We want to accommodate many inferences (10^3 to 10^12) inferences on a personal desktop or cheap OVH server in little time so we can serve the model on an online portal.

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