PTPT: Physical Design Tool Parameter Tuning via Multi-Objective Bayesian Optimization-Reference-Cited by-同舟云学术

PTPT: Physical Design Tool Parameter Tuning via Multi-Objective Bayesian Optimization

Published:2023-01 Issue:1 Volume:42 Page:178-189
ISSN:0278-0070
Container-title:IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
language:
Short-container-title:IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst.

Author:

Geng Hao¹^ORCID,Chen Tinghuan²^ORCID,Ma Yuzhe³^ORCID,Zhu Binwu²^ORCID,Yu Bei¹^ORCID

Affiliation:

1. School of Information Science and Technology, ShanghaiTech University, Shanghai, China

2. Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong

3. Microelectronics Thrust, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, China

Funder

Hisilicon Technologies Company, AI Chip Center for Emerging Smart Systems (ACCESS), Hong Kong

Research Grants Council of Hong Kong

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Graphics and Computer-Aided Design,Software

Link

Reference24 articles.

4. Predictive entropy search for multiobjective Bayesian optimization;hernández-lobato;Proc Int Conf Mach Learn (ICML),2016

5. Multi-task Gaussian process prediction;bonilla;Proc Annu Conf Neural Inf Process Syst (NeurIPS),2007

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