Winston Haaswijk, A. Mishchenko, Mathias Soeken, G. Micheli
{"title":"SAT Based Exact Synthesis using DAG Topology Families","authors":"Winston Haaswijk, A. Mishchenko, Mathias Soeken, G. Micheli","doi":"10.1145/3195970.3196111","DOIUrl":null,"url":null,"abstract":"SAT based exact synthesis is a powerful technique, with applications in logic optimization, technology mapping, and synthesis for emerging technologies. However, its runtime behavior can be unpredictable and slow. In this paper, we propose to add a new type of constraint based on families of DAG topologies. Such families restrict the search space considerably and let us partition the synthesis problem in a natural way. Our approach shows significant reductions in runtime as compared to state-of-the-art implementations, by up to 63.43%. Moreover, our implementation has significantly fewer timeouts compared to baseline and reference implementations, and reduces this number by up to 61%. In fact, our topology based implementation dominates the others with respect to the number of solved instances: given a runtime bound, it solves at least as many instances as any other implementation.","PeriodicalId":6491,"journal":{"name":"2018 55th ACM/ESDA/IEEE Design Automation Conference (DAC)","volume":"13 1","pages":"1-6"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"26","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 55th ACM/ESDA/IEEE Design Automation Conference (DAC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3195970.3196111","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 26
Abstract
SAT based exact synthesis is a powerful technique, with applications in logic optimization, technology mapping, and synthesis for emerging technologies. However, its runtime behavior can be unpredictable and slow. In this paper, we propose to add a new type of constraint based on families of DAG topologies. Such families restrict the search space considerably and let us partition the synthesis problem in a natural way. Our approach shows significant reductions in runtime as compared to state-of-the-art implementations, by up to 63.43%. Moreover, our implementation has significantly fewer timeouts compared to baseline and reference implementations, and reduces this number by up to 61%. In fact, our topology based implementation dominates the others with respect to the number of solved instances: given a runtime bound, it solves at least as many instances as any other implementation.