An evolution in FPGAs

An evolution in FPGAs
by Tom Simon on 05-24-2019 at 5:00 am

Why does it seem like current FPGA devices work very much like the original telephone systems with exchanges where workers connected calls using cords and plugs? Achronix thinks it is now time to jettison Switch Blocks and adopt a new approach. Their motivation is to improve the suitability of FPGAs to machine learning applications,… Read More


Mentor Extends AI Footprint

Mentor Extends AI Footprint
by Bernard Murphy on 05-23-2019 at 8:00 am

Mentor are stepping up their game in AI/ML. They already had a well-established start through the Solido acquisition in Variation Designer and the ML Characterization Suite, and through Tessent Yield Insight. They have also made progress in prior releases towards supporting design for ML accelerators using Catapult HLS. Now… Read More


Real Time Object Recognition for Automotive Applications

Real Time Object Recognition for Automotive Applications
by Tom Simon on 04-12-2019 at 7:00 am

The basic principles used for neural networks have been understood for decades, what have changed to make them so successful in recent years are increased processing power, storage and training data. Layered on top of this is continued improvement in algorithms, often enabled by dramatic hardware performance improvements.… Read More


Intelligent Electronic Design Exploration with Large System Modeling and Analysis

Intelligent Electronic Design Exploration with Large System Modeling and Analysis
by Camille Kokozaki on 03-07-2019 at 7:00 am

At the recent DesignCon 2019 in Santa Clara, I attended a couple of sessions where Cadence and their research partners provided some insight on machine learning/AI and on large system design analysis; with the first one focused on real-world cloud & machine learning/AI deployment for hardware design and the second one focused… Read More


Building Better ADAS SOCs

Building Better ADAS SOCs
by Tom Simon on 02-07-2019 at 12:00 pm

Ever since we replaced horses in our personal transportation system, folks have been pining for cars that offer some relief from the constant need for supervision, control and management. Indeed, despite their obvious downsides, horses could be counted on to help with steering and obstacle avoidance. There are even cases when… Read More


Improving Library Characterization with Machine Learning!

Improving Library Characterization with Machine Learning!
by Daniel Nenni on 12-04-2018 at 7:00 am

For SOC designers that are waiting for library models the saying “give me liberty or give me death” is especially apropos. Without libraries to support the timing flow, SOC design progress can grind to a halt. As is often the case, more than just a few PVT corners are needed. Years ago, corners were what the term sounded like – the 4 corners… Read More


Machine Learning Meets Scan Diagnosis for Improved Yield Analysis

Machine Learning Meets Scan Diagnosis for Improved Yield Analysis
by Tom Simon on 07-30-2018 at 12:00 pm

Naturally, chips that fail test are a curse, however with the advent of Scan Logic Diagnosis these failures can become a blessing in disguise. Through this technique information gleaned from multiple tester runs can help pin down the locations of defects. Initially tools that did Scan Logic Diagnosis relied on the netlist to filter… Read More


Cadence Selected to Support Major DARPA Program

Cadence Selected to Support Major DARPA Program
by Bernard Murphy on 07-26-2018 at 7:00 am

When DARPA plans programs, they’re known for going big – really big. Which is what they are doing again with their Electronics Resurgence Initiative (ERI). Abstracting from their intro, this is a program “to ensure far-reaching improvements in electronics performance well beyond the limits of traditional scaling”. This isn… Read More


Machine Learning and Embedded FPGA IP

Machine Learning and Embedded FPGA IP
by Tom Dillinger on 07-18-2018 at 12:00 pm

Machine learning-based applications have become prevalent across consumer, medical, and automotive markets. Still, the underlying architecture(s) and implementations are evolving rapidly, to best fit the throughput, latency, and power efficiency requirements of an ever increasing application space. Although ML is … Read More


Cadence’s Smarter and Faster Verification in the Era of Machine Learning, AI, and Big Data Analytics Panel

Cadence’s Smarter and Faster Verification in the Era of Machine Learning, AI, and Big Data Analytics Panel
by Camille Kokozaki on 07-11-2018 at 12:00 pm

I attended on Monday, June 25, DAC’s Opening Day, a Cadence-sponsored Lunch panel. Ann Steffora Mutschler (Semiconductor Engineering) was the Moderator and the Panelists were Jim Hogan (Vista Ventures), David Lacey (HP Enterprise), Shigeo Oshima (Toshiba Memory Corp), Paul Cunningham (Cadence).… Read More