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426 points benchmarkist | 3 comments | | HN request time: 0.423s | source
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zackangelo ◴[] No.42179476[source]
This is astonishingly fast. I’m struggling to get over 100 tok/s on my own Llama 3.1 70b implementation on an 8x H100 cluster.

I’m curious how they’re doing it. Obviously the standard bag of tricks (eg, speculative decoding, flash attention) won’t get you close. It seems like at a minimum you’d have to do multi-node inference and maybe some kind of sparse attention mechanism?

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simonw ◴[] No.42180035[source]
They have a chip the size of a dinner plate. Take a look at the pictures: https://cerebras.ai/product-chip/
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1. ekianjo ◴[] No.42180490[source]
what kind of yield do they get on that size?
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2. bufferoverflow ◴[] No.42180600[source]
It's near 100%. Discussed here:

https://youtu.be/f4Dly8I8lMY?t=95

3. petra ◴[] No.42180601[source]
Part of their technology is managing/bypassing defects.