Elias Fallon (Engineering Group Director, Cadence Design Systems)
Elias Fallon is currently Engineering Group Director at Cadence Design Systems, a leading Electronic Design Automation company. He has been involved in EDA for more than 20 years from the founding of Neolinear, Inc, which Cadence acquired in 2004. Elias was co-Primary Investigator on the MAGESTIC project, funded by DARPA to investigate the application of Machine Learning to EDA for Package/PCB and Analog IC. Elias also leads an innovation incubation team within the Custom IC R&D group as well as other traditional EDA product teams. Beyond his work developing electronic design automation tools, he has led software quality improvement initiatives within Cadence, partnering with the Carnegie Mellon Software Engineering Institute. Elias graduated from Carnegie Mellon University with an M.S. and B.S. in Electrical and Computer Engineering. Elias, his wife and two children live north of Pittsburgh, PA, USA.
Keynote Title: Accelerating Computational Intelligence with Machine Learning for Electronic Design Automation
Abstract: Electronic Design Automation (EDA) software has delivered semiconductor design productivity improvements for decades. The next generation of intelligent systems in the cloud and at the edge will require another leap in design productivity. EDA software utilizes an advanced toolkit of computational software to provide intelligent system design productivity. The next leap in productivity will come from the addition of machine learning (ML) techniques to the toolbox of computational software capabilities employed by EDA developers. Recent research and development into machine learning for EDA point to clear patterns for how it impacts EDA tools, flows, and design challenges. This development shows how computational intelligence is impacting EDA flows, which in turn will drive the development of new intelligence systems.