[ted_dunning]

Actually, this AI Compute is not very useful for physics, protein folding or many other high performance computing.

The problem is that the connectivity required for much of AI is very different than that required for classic HPC (more emphasis on bandwidth, less on super low latency small payload remote memory operations) and the numeric emphasis is very different (lots of mixed resolution and lots of ridiculously small numeric resolutions like fp8 vs almost all fp64 with some fp32).

The result is that essentially no AI computers reach the high end of the TOP500.

The converse is also true, classic frontier scale super computers don't make the most cost effective AI training platforms because they spend a lot of the budget on making HPC programs fast.

[Glemllksdf]

Alphafold (protein folding) was trained on Googles TPUs which are not GPUs true but very close.

Flow simulation also happens on GPUs and not CPUs though.

El Capitan is the top 1 on top 500 and the flops ratio between CPU and GPU is nearly 1 to 100.