Using Machine Learning Clustering To Find Large Coverage Holes

Identifying large and important coverage holes is a time-consuming process that requires expertise in the design and its verification environment. This paper describes a novel machine learning-based technique for finding large coverage holes when the coverage events are individually defined. The tec...

Full description

Bibliographic Details

Published in:	Proceedings of the 2020 ACM/IEEE Workshop on Machine Learning for CAD pp. 139 - 144
Main Authors:	Gal, Raviv, Simchoni, Giora, Ziv, Avi
Format:	Conference Proceeding
Language:	English
Published:	ACM 16.11.2020
Subjects:	Analytical models clustering Conferences functional coverage hole analysis Machine learning Servers Solid modeling
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!