Hardware Podcasts

An All Inclusive Journey to HPC/Data Center Silicon Success

EE Times Current · 21 Oct 2022 · 40m

AI in practice: one real use of AI described

What this episode covers

Charlie Matar, Senior Vice President of Systems Solutions at Synopsys, discusses the escalating complexity of High Performance Computing (HPC) and data center silicon design. He highlights critical challenges including engineer shortages, the high cost of advanced nodes, and the shift toward chiplet architectures and 2.5D/3D packaging. Matar also explains how Synopsys is leveraging its DSO.AI platform to optimize power, performance, and area (PPA) while addressing reliability and security concerns in the semiconductor ecosystem.

AI in practice

Where this conversation describes AI being used to build or deliver a product. Part of the AI in practice tracker.

Engineering & simulationDSO.AIsignificant improvement on power performance in area

Synopsys uses reinforcement learning algorithms to automate chip implementation, replacing manual engineering tasks to optimize power, performance, and area (PPA) and reduce time to market.

“So one of the key products that we have released in March of 2020 is DSO.AI, and this technology platform is really around the AI, technology we just discussed a little bit earlier. And with DSO.AI, what we're doing nowadays and it's in production, is we're able to use AI or reinforce learning algorithms, to be able to develop chips and replace some of the capabilities that usually were done manual by engineers with AI engines.”

Charlie Matar · Hear it at 32:44

Most relevant to

large enterprises

Topics

Mentioned

Companies
Synopsys, IRLab, TSMC, ASML, Apple, T-Mobile, SpaceX, Intel, AMD, Qualcomm
Products
DSO.AI
Also
UCIE, PCIe, CXL, DDR

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