An Efficient Asynchronous Batch Bayesian Optimization Approach for Analog Circuit Synthesis

Autor:	Zhang, Shuhan, Yang, Fan, Zhou, Dian, Zeng, Xuan
Rok vydání:	2021
Předmět:	Electrical Engineering and Systems Science - Systems and Control
Druh dokumentu:	Working Paper
DOI:	10.1109/DAC18072.2020.9218592
Popis:	In this paper, we propose EasyBO, an Efficient ASYnchronous Batch Bayesian Optimization approach for analog circuit synthesis. In this proposed approach, instead of waiting for the slowest simulations in the batch to finish, we accelerate the optimization procedure by asynchronously issuing the next query points whenever there is an idle worker. We introduce a new acquisition function that can better explore the design space for asynchronous batch Bayesian optimization. A new strategy is proposed to better balance the exploration and exploitation and guarantee the diversity of the query points. And a penalization scheme is proposed to further avoid redundant queries during the asynchronous batch optimization. The efficiency of optimization can thus be further improved. Compared with the state-of-the-art batch Bayesian optimization algorithm, EasyBO achieves up to 7.35 times speed-up without sacrificing the optimization results. Comment: 6 pages, 6 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2106.14683 Zobrazit plný text záznamu View this record from Arxiv