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Artificial Intelligence
Ron Lowman, product marketing manager at Synopsys, recently posted an interesting technical bulletin on the Synopsys website entitled How AI in Edge Computing Drives 5G and the IoT. There’s been a lot of discussion recently about the emerging processing hierarchy of edge devices (think cell phone or self-driving car), cloud… Read More
Custom AI acceleration continues to gather steam. In the cloud, Alibaba has launched its own custom accelerator, following Amazon and Google. Facebook is in the game too and Microsoft has a significant stake in Graphcore. Intel/Mobileye have a strong lock on edge AI in cars and wireless infrastructure builders are adding AI capabilities… Read More
I wrote recently on ANSYS and TSMC’s joint work on thermal reliability workflows, as these become much more important in advanced processes and packaging. Xilinx provided their own perspective on thermal reliability analysis for their unquestionably large systems – SoC, memory, SERDES and high-speed I/O – stacked within a … Read More
Machine Learning (ML) has become extremely important for many computing applications, especially ones that involve interacting with the physical world. Along with this trend has come the development of many specialized ML processors for cloud and mobile applications. These chips work fine in the cloud or even in cars or phones,… Read More
This blog is the next in a series in which Paul Cunningham (GM of the Verification Group at Cadence), Jim Hogan and I pick a paper on a novel idea in verification and debate its strengths and opportunities for improvement.
Our goal is to support and appreciate further innovation in this area. Please let us know what you think and please… Read More
I attended a session on 2.5D silicon interposer analysis at DesignCon 2020. Like many presentations at this show, ecosystem collaboration was a focus. In this session, Jinsong Hu (principal application engineer at Cadence) and Yongsong He (senior staff engineer at Enflame Tech) presented approaches for interposer power modeling… Read More
The use of machine learning (ML) to solve complex problems that could not previously be addressed by traditional computing is expanding at an accelerating rate. Even with advances in neural network design, ML’s efficiency and accuracy are highly dependent on the training process. The methods used for training evolved from CPU… Read More
FPGAs, today and throughout the history of semiconductors, play a critical role in design enablement and electronic systems. Which is why we included the history of FPGAs in our book “Fabless: The Transformation of the Semiconductor Industry” and added a new chapter in the 2019 edition on the history of Achronix.
In a recent blog… Read More
I’m kicking off a blog series which should appeal to many of us in functional verification. Paul Cunningham (GM of the Verification Group at Cadence), Jim Hogan (angel investor and board member extraordinaire) and I (sometime blogger) like to noodle from time to time on papers and other verification articles which inspire us.… Read More
It’s clear that blockchain will revolutionize operations and processes in many industries and governments agencies if adopted, but its adoption requires time and efforts, in addition blockchain technology will stimulate people to acquire new skills, and traditional business will have to completely reconsider their processes… Read More
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Bridging the Gap Between Design and Analysis