Re:Nvidia announces its most powerful AI chip as it seeks to...
by YetAnotherNick on Monday March 18, 2024 @06:03PM
(#39750592)
How is 2.5x disappointing in one generation?
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Re:Nvidia announces its most powerful AI chip as it seeks to...
by dagmx on Monday March 18, 2024 @07:11PM
(#39751169)
Did you skip the sentence immediately after that one?
It’s two fused chips. So 1.25x per chip. 25% uplift. Not 2.5x uplift. The 2.5x is for the whole package.
Re:Nvidia announces its most powerful AI chip as it seeks to...
by throwaway11460 on Monday March 18, 2024 @09:32PM
(#39752126)
Is that how it works? Why don't we just put many chips in one computer?
Re:Nvidia announces its most powerful AI chip as it seeks to...
by dagmx on Monday March 18, 2024 @10:55PM
(#39752498)
the massive blackwell SoC he showed is two Blackwell dies with an interconnect. It’s very similar to what Apple does with their Ultra series.
Then the B200 package is 2 of these plus a CPU. So a total of 4 GPU dies in each unit.
Re:Nvidia announces its most powerful AI chip as it seeks to...
by abhinavk on Monday March 18, 2024 @11:10PM
(#39752579)
> Then the B200 package is 2 of these plus a CPU.
That's GB200.
Re:Nvidia announces its most powerful AI chip as it seeks to...
by downvotetruth on Monday March 18, 2024 @09:42PM
(#39752179)
> two fused chips
Jensen's comment about being first was such a dig to Emerald Rapids.
Re:Nvidia announces its most powerful AI chip as it seeks to...
by dagmx on Monday March 18, 2024 @10:53PM
(#39752489)
Is it the first? The Apple Ultra series chips are two Max’s fused with an interconnect. In which case it’s both CPU and GPU.
I believe this is just the first for a GPU only product.
Re:Nvidia announces its most powerful AI chip as it seeks to...
by chimney on Monday March 18, 2024 @06:06PM
(#39750638)
Compare to the 10x that was Hopper uplift.
Re:Nvidia announces its most powerful AI chip as it seeks to...
by YetAnotherNick on Monday March 18, 2024 @06:21PM
(#39750770)
Because it involved scaling in chip area needed for FP8. AI community realized that FP8 training is possible few years back so the transistors given for FP8 was scaled. Overall I think transistors grow just by ~50% per generation so most of the gains comes from removing FP32/FP64 share which were dominant 10 years back, but there is only some point it could go to.