Carmen Li

If you are naturally short GPU, which is everybody in this room, unless you tell me you have GPUs, then it depends how much you use.

If you want to control your cost volatility, you want to use future to hedge as well.

This is a great question.

So I'm going to flip to slide, if you don't mind.

We have visuals.

More slides, yeah.

So I usually don't like to use slides, but this time, because you mentioned a really good question, so we actually call it GPU lottery.

So we published a paper earlier this year at GPGPU conference with Jefferson Lab on GPU performances.

We actually, so we can have you create a link and, you know, to the audience later on.

This is A100, by the way.

I know we didn't put 10 on.

This is A100, 40 gigabytes memory bandwidth.

We proved there's 38% performance variance for the same chip, and then we decomposed it into the chip itself, intra-provider, and inter-provider.

And there's many reasons for that, right?

And to your point, you don't know until you get your GPUs.

We have a Pletsch for GPU, Carfax for GPU, depends how you look at it.

So in Compute Change, you actually verify the GPU before delivered to you.

So basically, you can RFQ for say, hey, I want a 200 by 200 nodes.

Obviously, it will give you specs back and the commercial back.

At the same time, independently verify the performances on flops, memory bandwidth, tokens, and other information, SLAs and other things.