A resynthesis approach for network optimization

Kuang Chien Chen, Yusuke Matsunaga, Masahiro Fujita, Saburo Muroga

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)


An algorithm, RENO (resynthesis for network optimization), for the optimization of multilevel combinational networks is presented. In RENO, a given network is minimized for area by optimally resynthesizing each gate, using other existing gates in the network. The resynthesis process is based on a covering-set algorithm, which enables one to resynthesize using complex gates instead of only simple gates (e.g., NAND and NOR), thereby exploring more reconfiguration possibilities. Due to the reconfiguration ability of the RENO algorithm, networks optimized by RENO have good quality, even if no network don't-care is used. The RENO algorithm has been implemented in both cube and shared-OBDD data structures. Experimental results obtained by RENO for benchmark functions and comparison with the optimization algorithm used in MIS 2.2 show that RENO is effective for multilevel network optimization.

Original languageEnglish
Title of host publicationProceedings - Design Automation Conference
PublisherPubl by IEEE
Number of pages6
ISBN (Print)0818691492, 9780818691492
Publication statusPublished - 1991
Externally publishedYes
EventProceedings of the 28th ACM/IEEE Design Automation Conference - San Francisco, CA, USA
Duration: Jun 17 1991Jun 21 1991

Publication series

NameProceedings - Design Automation Conference
ISSN (Print)0146-7123


OtherProceedings of the 28th ACM/IEEE Design Automation Conference
CitySan Francisco, CA, USA

All Science Journal Classification (ASJC) codes

  • Engineering(all)


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