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Nvidia will build 700-petaflop supercomputer for University of Florida

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Re: Nvidia will build 700-petaflop supercomputer for University of Florida

#111
post #76

Does anyone know why everyone is still buying Nvidia instead of custom AI accelerators from other vendors? For example, on paper the new Graphcore machines look like an easy win, or at least a risk worth taking. (I see this particular supercomputer was funded by Nvidia but my question is about the general trend).

The only non-NVidia device you can actually use that has broad support outside basic models in software is Google's TPUs. Graphcore looks great! But no one outside Graphcore has used them so who knows. Intel's Nervana looked great on paper, right up until they dumped it. There are some interesting accelerator options around for inference. But for training it's NVidia for almost everything, and TPUs as a good option i…

> But no one outside Graphcore has used them so who knows.

This part really confuses me. I'd love to try out their hardware, but the only cloud offering they had last time I checked made you rent a whole month's worth (for many thousands of dollars).

It seems like getting it in the hands of devs should be a top priority.

Re: Nvidia will build 700-petaflop supercomputer for University of Florida

#112
post #48

Earlier quoted context omitted.

Cars generate closer to 122g of CO2 per km [1]. 122,000kg would be ~1 million km or ~50 cars. 1 - https://ec.europa.eu/clima/policies/transport/vehicles/cars_...

Damn. I was confused by the fuel consumption being in per 100 km units. I've edited my post. Thanks.

lol - https://old.reddit.com/r/Metric/comments/hytuja/how_does_the...
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