DesignCon is part of the Informa Markets Division of Informa PLC

This site is operated by a business or businesses owned by Informa PLC and all copyright resides with them. Informa PLC's registered office is 5 Howick Place, London SW1P 1WG. Registered in England and Wales. Number 8860726.


Welcome to the DesignCon 2020 agenda and presentation download site. Here you can view and download conference and/or Chiphead Theater presentations before, during, and after the event. If you’re looking for a presentation from a specific session that you’re unable to find here, it is likely because the presenter has not provided permission for external use or has not yet shared their presentation with us. Please check back after the event for a more complete catalogue of available presentations.

Panel – Electronic Design Automation Roadmap for Machine Learning & AI Standardization

Leigh Anne Clevenger (Design Automation Data Scientist, Silicon Integration Initiative, Inc.)

Rhett Davis (Professor, Electrical and Computer Engineering, North Carolina State University)

Leon Stok (Vice President, Electronic Design Automation, IBM)

John Ellis (President and CEO, Silicon Integration Initiative, Inc.)

Norman Chang (Chief Technologist at Semiconductor BU, ANSYS)

Ramond Rodríguez (Director of Strategic CAD Capabilities, Intel)

Location: Ballroom D

Date: Thursday, January 30

Time: 3:45pm - 5:00pm

Track: 14. Machine Learning for Microelectronics, Signaling & System Design

Format: Panel Discussion

Pass Type: 2-Day Pass, All-Access Pass, Alumni All-Access Pass, Boot Camp Pass, Expo Pass - Get your pass now!

Vault Recording: TBD

Audience Level: All

A roadmap is "a plan or strategy intended to achieve a particular goal." Currently, EDA has no roadmap for ML/AI with a time-table to meet design and manufacturing needs. A roadmap would provide a framework to study targeted ML/AI functions and describe dependencies between industry organizations. Defining functional needs with business goals will identify methodology gaps for new R&D from industry and academia.

Industry and academic experts will discuss and debate the following areas critical to developing an EDA ML/AI roadmap: concept unification, software interoperability, high-volume data handling and exchange, and learning from other disciplines.

Takeaway

In this panel, industry and academic experts will discuss and debate the following areas critical to developing an EDA ML/AI roadmap: concept unification, software interoperability, high-volume data handling and exchange, and learning from other disciplines.