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The price of these computers is high now, due to supply constraints, so buying now isnt necessarily the best time for this outcome. You can buy some later... T

The price of these computers is high now, due to supply constraints, so buying now isnt necessarily the best time for this outcome. You can buy some later... The things these can do is (a) memory bandwidth, Nvidia GPUs have been described as "the worlds most expensive memory controller". Generally very useful anywhere. (b) fast low precision floating point. Historically most of the uses of supercomputers wanted high precision, eg for physics etc but people are now experimenting with using lower precision given availability (c) fast networking. generally useful. We were seeing a spread of GPU into other applications pre AI, like GPU driven databases, I think this stopped a bit just because of pricing and availability.

JonChesterfield 2y ago
Lots of memory bandwidth, low latency high bandwidth connections between nodes, lots of floating point. The MI300 looking a bit like HPC being repurposed for AI is probably a win in terms of using the hardware for other things in the future. I've had to double check the low precision point qualifier. I expected MI300X to run f32 and f64 at the same speed (and it does) and nvidia to have slower f64 (which it does). It looks like H100 is 250TF at half, 60TF at float, 30TF at double. MI300X is 650TF at half, 80TF at float or double. Very fast F16 indeed. (sourced from https://www.techpowerup.com/gpu-specs/radeon-instinct-mi300x.c4179 https://www.techpowerup.com/gpu-specs/radeon-instinct-mi300x... and https://www.techpowerup.com/gpu-specs/h100-sxm5-96-gb.c3974 https://www.techpowerup.com/gpu-specs/h100-sxm5-96-gb.c3974, I might have the wrong SKUs for comparison)