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

研究成果: Conference contribution同行評審

摘要

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.

原文English
主出版物標題ASP-DAC 2022 - 27th Asia and South Pacific Design Automation Conference, Proceedings
發行者Institute of Electrical and Electronics Engineers Inc.
頁面80-85
頁數6
ISBN(電子)9781665421355
DOIs
出版狀態Published - 2022
事件27th Asia and South Pacific Design Automation Conference, ASP-DAC 2022 - Virtual, Online, Taiwan
持續時間: 17 1月 202220 1月 2022

出版系列

名字Proceedings of the Asia and South Pacific Design Automation Conference, ASP-DAC
2022-January

Conference

Conference27th Asia and South Pacific Design Automation Conference, ASP-DAC 2022
國家/地區Taiwan
城市Virtual, Online
期間17/01/2220/01/22

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