342 Transistors for Every Person In the World: Cerebras 2nd Gen Wafer Scale Engine Teased
One of the highlights of Hot Chips from 2019 was the startup Cerebras showcasing its product – a large 'wafer-scale' AI chip that was literally the size of a wafer. The chip itself was rectangular, but it was cut from a single wafer, and contained 400,000 cores, 1.2 trillion transistors, 46225 mm2 of silicon, and was built on TSMC's 16 nm process.
[...] Obviously when doing wafer scale, you can't just add more die area, so the only way is to optimize die area per core and take advantage of smaller process nodes. That means for TSMC 7nm, there are now 850,000 cores and 2.6 trillion transistors. Cerebras has had to develop new technologies to deal with multi-reticle designs, but they succeeded with the first gen, and transferred the learnings to the new chip. We're expecting more details about this new product later this year.
Previously: Cerebras "Wafer Scale Engine" Has 1.2 Trillion Transistors, 400,000 Cores
Cerebras Systems' Wafer Scale Engine Deployed at Argonne National Labs
(Score: 2) by takyon on Wednesday August 19 2020, @03:25PM
The design tolerates and routes around defective cores, and the stated core count (400k, now 850k) doesn't include the defective cores, from what I remember.
TSMC is also getting great yields on "7nm". Depending on how much overprovisioning of the cores was done, maybe the yield rate is nearly 100%?
Oh, and from my Wikichip link above, TSMC's "7nm" has 3.3x the density of "16nm". But this is only 2.125x the cores. So they have a lot of margin there. I bet they added more SRAM.
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