Machine Learning in VLSI Computer-Aided Design

Machine Learning in VLSI Computer-Aided Design
by: Ibrahim (Abe) M. Elfadel
ISBN-10: 3030046656
ISBN-13: 9783030046651
Edition: 1st ed. 2019
Released: 2019-03-16
Pages: 694 pages
9
Book Description
This book provides readers with an up-to-date account of the use of machine learning frameworks,methodologies,algorithms and techniques in the context of computer-aided design (CAD) for very-large-scale integrated circuits (VLSI). Coverage includes the various machine learning methods used in lithography,physical design,yield prediction,post-silicon performance analysis,reliability and failure analysis,power and thermal analysis,analog design,logic synthesis,verification,and neuromorphic design.
Provides up-to-date information on machine learning in VLSI CAD for device modeling,layout verifications,yield prediction,post-silicon validation,and reliability;
Discusses the use of machine learning techniques in the context of analog and digital synthesis;
Demonstrates how to formulate VLSI CAD objectives as machine learning problems and provides a comprehensive treatment of their efficient solutions;
Discusses the tradeoff between the cost of collecting data and prediction accuracy and provides a methodology for using prior data to reduce cost of data collection in the design,testing and validation of both analog and digital VLSI designs.