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Cerebras More than Doubles Core and Transistor Count with 2nd-Generation Wafer Scale Engine

posted by martyb on Wednesday August 19 2020, @01:36AM   
from the Amdahl's-law? dept.

takyon writes:

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

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Original Submission

• Fighting COVID (Score: 3, Interesting) by takyon on Wednesday August 19 2020, @01:36AM

  by takyon (881) <takyonNO@SPAMsoylentnews.org> on Wednesday August 19 2020, @01:36AM (#1038634) Journal

  https://www.hpcwire.com/2020/05/13/cerebras-argonne-supercomputer-fighting-covid-19/ [hpcwire.com]

  For Argonne and CS-1, brute force was not the name of the game. Instead, Argonne applied the CS-1’s AI capabilities to train machine learning models to churn through the lab’s massive molecular datasets (comprising existing FDA-approved drugs) and predict which of those molecules would have the best docking scores. The result, according to Cerebras: “hundreds of times” faster turnaround on the datasets at a fraction of the computational cost.

  The first iteration of the CS-1’s battle against COVID-19 was completed over the last few weeks. Now, Argonne and Cerebras are working on a new ML process for CS-1 that would treat the process as a computer vision problem, representing viral proteins and drug molecules as images rather than numbers.

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