Generating Layouts of Standard Cells by Implicit Learning on Design Rules for Advanced Processes

Aaron C.W. Liang, Hsuan Ming Huang, Charles H.P. Wen

研究成果: Conference contribution同行評審

4 引文 斯高帕斯(Scopus)

摘要

For the advanced process technologies (e.g, finFET with EUV), the design rules (DRs) are the most challenging issue to the generation of cell layouts and all DR violations must be solved in a legal cell layout. However, most of previous works apply explicit encoding on the selected DRs into the routing engine and cannot accommodate the rapid growth on the size and complexity of DRs as the processes continue to advance. Therefore, in this paper, we propose two implicit-learning techniques, (1) experience-guidance learning (EGL) and (2) constraint-driven learning (CDL) for effectively solving such two problems of DRs, and meanwhile develop an automatic cell-layout generation (ACLG) framework for efficiently generating legal cell layouts. The experimental results show that in a finFET-EUV process [1], EGL and CDL successfully reduce all DR violations on eight target cells where each case takes averagely three minutes. As a result, without manual effort, ACLG is capable of generating legal layouts of standard cells by implicit learning on DRs of advanced processes.

原文English
主出版物標題Proceedings of the 2021 Design, Automation and Test in Europe, DATE 2021
發行者Institute of Electrical and Electronics Engineers Inc.
頁面1829-1834
頁數6
ISBN(電子)9783981926354
DOIs
出版狀態Published - 1 2月 2021
事件2021 Design, Automation and Test in Europe Conference and Exhibition, DATE 2021 - Virtual, Online
持續時間: 1 2月 20215 2月 2021

出版系列

名字Proceedings -Design, Automation and Test in Europe, DATE
2021-February
ISSN(列印)1530-1591

Conference

Conference2021 Design, Automation and Test in Europe Conference and Exhibition, DATE 2021
城市Virtual, Online
期間1/02/215/02/21

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