It will be perfect for stuff like GPU-accelerated query engines, "classical ML" and every other CPU-based workload that could conceivably be offloaded to GPU
You can get used 16GB P100s on AliExpress for ~$100 if you want obsolete GPUs. Allegedly new AMD BC 250s are only slightly more.
I've looked at this some but I already have a GTX1070 which is only supported upto CUDA 11.9.
That's precludes some interesting modern optimizations out of the box. I've spend a lot of LLM tokens backporting some things, but I'm really not sure the hassle is worth it.
New hardware is just better. I think in maybe 5 years when supply and demand are back in equilibrium we are going to have some killer technology for decent prices, and 15yo H100s won't look attractive.
This is assuming that there is no big, big disruption to the semiconductor industry (e.g. TSMC getting attacked), in which case... well, I am gonna treat each stick of RAM I currently have like it's a faberge egg.
In a recent Gamer Nexus video with Level 1 Tech, they mention V100s are also quite useful for many applications that use FP64: stuff four in a workstation, and many PhD candidates would be quite happy with the throughput they can get for certain scenarios.
Is the idea that previously maintaining GPU programs was expensive whereas now AI makes it cheap? If so, I could buy that line of reasoning.
Maybe relatedly, I expect (hope) the hardware manufacturers will ramp up supply in the meanwhile which would also put downward pressure on GPUs. Right now though this hardware crunch is making me sad, not even because of GPUs but also because of general memory / disk.
TL;DR.
> I, for one, welcome the coming age of the post-LLM-datacenter-overinvestment-bust-fueled backyard GPU supercomputer revolution.
> The Big Question is…
> Who is cultivating the option to snap up and repurpose vapourised datacenter investments at fire sale prices, soon as the "datacenter debt" cometh calling?