Breaking News

Gaps And Opportunities For AI/ML Techniques In The EDA Domain – SemiEngineering

Systems & Design


Understand the challenges to adoption and potential improvements to AI and ML techniques in EDA.

January 27th, 2021 –

By: Si2

Semiconductor industry awareness of AI/ML in EDA has progressed such that results from a user survey can drive industry-wide standards and improvements. Silicon Integration Initiative conducted such a survey in April 2020 identifying gaps, opportunities, and current practice for incorporation of AI/ML into the EDA domain. This paper presents and analyzes the findings of the survey. Areas explored include the current state of ML adoption in EDA at the respondents’ organizations and areas for potential improvement where respondents felt a certain level of dissatisfaction with the current state of ML availability and adoption within their organizations as well as their fields. Each respondent identified his or her areas of interest related to EDA.  The goal of this analysis is to understand the challenges to adoption and potential improvements to AI and ML techniques in EDA. This will benefit EDA tool vendors and end-user engineers as well as individuals from academia, industrial design houses, and national laboratories. Future work by research and development groups can support these efforts through the development of a common AI/ML in EDA ecosystem.
Click here to continue reading.
Authors: Joydip Das, Samsung Austin R&D Center (SARC); Akhilesh Kumar, Ansys; Aparna Dey, Cadence Design Systems; Sashi Obilisetty, Google LLC; Prateek Bhansali, Intel Corporation; Srinivas Bodapati, Intel Corporation; Hui Fu, Intel Corporation; Anoop Saha, Mentor, a Siemens Business; Rhett Davis, NC State University; Ryan Carey, Qualcomm; Rajeev Jain, Qualcomm; Karthik V. Aadithya, Sandia National Laboratory; and Leigh Anne Clevenger, Si2