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.
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 80GB, as many projects seem to require these days since the A100 is such a common baseline, 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.
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.
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 80GB, as many projects seem to require these days since the A100 is such a common baseline, 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.