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submitted 2 weeks ago by misk@sopuli.xyz to c/technology@lemmy.world
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[-] KingRandomGuy@lemmy.world 16 points 2 weeks ago

Useless is a strong term. I do a fair amount of research on a single 4090. Lots of problems can fit in <32 GB of VRAM. Even my 3060 is good enough to run small scale tests locally.

I'm in CV, and even with enterprise grade hardware, most folks I know are limited to 48GB (A40 and L40S, substantially cheaper and more accessible than A100/H100/H200). My advisor would always say that you should really try to set up a problem where you can iterate in a few days worth of time on a single GPU, and lots of problems are still approachable that way. Of course you're not going to make the next SOTA VLM on a 5090, but not every problem is that big.

[-] brucethemoose@lemmy.world 1 points 1 week ago

Fair. True.

If your workload/test fits in 24GB, that's already a "solved" problem. If it fits in 48GB, it's possibly solved with your institution's workstation or whatever.

But if it takes an 80GB A100, you are likely using very expensive cloud GPU time. I really love the idea of being able to tinker with a "full" 80GB+ workload (even having to deal with ROCM) without having to pay per hour.

[-] KeenFlame@feddit.nu 1 points 2 weeks ago

Exactly, 32 is plenty to develop on, and why would you need to upgrade ram? It was years ago I did that in any computer let alone a tensor workstation. I feel like they made pretty good choices for what it's for

this post was submitted on 25 Feb 2025
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