Comment by ben_w

> quick edit to add: At it's peak Folding@Home was utilizing 2.4 EXAflops worth of silicon. At that moment that one single distributed computational project had more compute than easily the top 100 data centers at the time. Let that sink in: The first exa-scale compute was achieved with smartphones, PS3s, and clunky old HP laptops; not a "hyperscaler"

A DGX B200 has a power draw of 14.3 kW and will do 72-144 petaFLOP of AI workload depending on how many bits of accuracy is asked for; this is 5-10 petaFLOP/kW: https://www.nvidia.com/en-us/data-center/dgx-b200/

Data centres are now getting measured in gigawatts. Some of that's cooling and so on. I don't know the exact percent, so let's say 50% of that is compute. It doesn't matter much.

That means 1GW of DC -> 500 MW of compute -> 5e5 kW -> 5e5 * [5-10] PFLOP/s -> 2500 - 5000 exaFLOP/s.

I'm not sure how many B200s have been sold to date?