Fast Variation-aware Circuit Sizing Approach for Analog Design with ML-Assisted Evolutionary Algorithm

Ling Yen Song, Tung Chieh Kuo, Ming Hung Wang, Chien Nan Jimmy Liu, Juinn Dar Huang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Evolutionary algorithm (EA) based on circuit simulation is one of the popular approaches for analog circuit sizing because of its high accuracy and adaptability on different cases. However, if process variation is also considered, the huge number of simulations becomes almost infeasible for large circuits. Although there are some recent works that adopt machine learning (ML) techniques to speed up the optimization process, the variation effects are still hard to be considered in those approaches. In this paper, we propose a fast variation-aware evolutionary algorithm for analog circuit sizing with a ML-assisted prediction model. By predicting the likelihood for a design that has worse performance, our EA process is able to skip many unnecessary simulations to reduce the convergence time. Moreover, a novel force-directed model is proposed to guide the optimization toward better yield. Based on the performance of prior circuit samples in the EA optimization, the proposed force model is able to predict the likelihood of a design that has better yield without time-consuming Monte Carlo simulations. Compared with prior works, the proposed approach significantly reduces the number of simulations in the yield-aware EA optimization, which helps to generate more practical designs with high reliability and low cost.

Original languageEnglish
Title of host publicationASP-DAC 2022 - 27th Asia and South Pacific Design Automation Conference, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages80-85
Number of pages6
ISBN (Electronic)9781665421355
DOIs
StatePublished - 2022
Event27th Asia and South Pacific Design Automation Conference, ASP-DAC 2022 - Virtual, Online, Taiwan
Duration: 17 Jan 202220 Jan 2022

Publication series

NameProceedings of the Asia and South Pacific Design Automation Conference, ASP-DAC
Volume2022-January

Conference

Conference27th Asia and South Pacific Design Automation Conference, ASP-DAC 2022
Country/TerritoryTaiwan
CityVirtual, Online
Period17/01/2220/01/22

Keywords

  • Analog circuit sizing
  • Evolutionary algorithm
  • Machine learning
  • Process variation

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