What can go wrong in complex SoCs and how to find the problems.
Bernie DeLay, group director for verification IP R&D at Synopsys, talks about what goes wrong in complex SoCs, how so-called standard pieces play together, and where are the gotchas in re-use.
Companies battle it out to get artificial intelligence to the edge using various chip architectures as their weapons of choice.
Bulk CMOS, FD-SOI and finFETs all on tap as big players vie for differentiation. But where will chipmakers go after 28nm?
Consortiums seek ways to ensure interoperability of hardened IP as way of cutting costs, time-to-market, but it’s not going to be easy.
Experts at the Table, Part 1: Impact on the supply chain, who’s using advanced packaging, and the cost of packaging versus device scaling.
While CPUs continue to evolve, performance is no longer limited to a single processor type or process geometry.
AI-enabled systems are being designed to process more data locally as device scaling benefits decline.
Chips will cost more to design and manufacture even without pushing to the latest node, but that’s not the whole story.
Access to source code makes it attractive for custom applications, but gaps remain in the tool flow and in software.
Growing volume of data and limited improvements in performance create new opportunities for approaches that never got off the ground.
Semiconductor design lags behind other industries in adopting the cloud, but there could be some good reasons for that. Change is difficult.
Behind closed doors: Semiconductor executives talk about the bugs they fear the most and the problems solving them.
While CPUs continue to evolve, performance is no longer limited to a single processor type or process geometry.
New data flow, higher switch density and IP integration create issues across the design flow.
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