A Database Dependent Framework for K-Input Maximum Fanout-Free Window Rewriting

Xuliang Zhu, Ruofei Tang, Lei Chen, Xing Li, Xin Huang, Mingxuan Yuan, Weihua Sheng, Jianliang Xu

Research output: Contribution to conferenceConference paperpeer-review

Abstract

Rewriting is a widely used logic optimization approach incorporated in most commercial logic synthesis tools. In this paper, we present a new rewriting method based on AndInverted Graph (AIG). Rather than focusing on cut rewriting, it considers a novel sub-structure called Maximum Fanout-Free Window (MFFW) and rewrites with a more compact implementation. Both exact synthesis and heuristic methods can be adopted to optimize MFFWs. A database dependent framework is proposed to store the optimal sub-structures to accelerate the processing. We further propose the semi-canonicalization to reduce the scale of the database, which could reduce more than 98% of the 4-input MFFW database. Extensive experiments on benchmark datasets demonstrate both the effectiveness and efficiency of our proposed framework.
Original languageEnglish
Publication statusPublished - Jul 2023
EventThe 60th ACM/IEEE Design Automation Conference, DAC 2023 - Moscone West, San Francisco, United States
Duration: 9 Jul 202313 Jul 2023
https://www.dac.com/
https://60dac.conference-program.com/

Competition

CompetitionThe 60th ACM/IEEE Design Automation Conference, DAC 2023
Country/TerritoryUnited States
CitySan Francisco
Period9/07/2313/07/23
Internet address

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