A Review of Bayesian Methods in Electronic Design Automation
Abstract
The utilization of Bayesian methods has been widely acknowledged as a viable solution for tackling various challenges in electronic integrated circuit (IC) design under stochastic process variation, including circuit performance modeling, yield/failure rate estimation, and circuit optimization. As the post-Moore era brings about new technologies (such as silicon photonics and quantum circuits), many of the associated issues there are similar to those encountered in electronic IC design and can be addressed using Bayesian methods. Motivated by this observation, we present a comprehensive review of Bayesian methods in electronic design automation (EDA). By doing so, we hope to equip researchers and designers with the ability to apply Bayesian methods in solving stochastic problems in electronic circuits and beyond.
Keywords
Cite
@article{arxiv.2304.09723,
title = {A Review of Bayesian Methods in Electronic Design Automation},
author = {Zhengqi Gao and Duane S. Boning},
journal= {arXiv preprint arXiv:2304.09723},
year = {2023}
}
Comments
24 pages, a draft version. We welcome comments and feedback, which can be sent to [email protected]