{"title":"逻辑函数求值的广义协分解","authors":"Yunjian Jiang, Slobodan Matic, R. Brayton","doi":"10.1145/775832.775873","DOIUrl":null,"url":null,"abstract":"Logic evaluation of a Boolean function or relation is traditionally done by simulating its gate-level implementation, or creating a branching program using its binary decision diagram (BDD) representation, or using a set of look-up tables. We propose a new approach called generalized cofactoring diagrams, which are a generalization of the above methods. Algorithms are given for finding the optimal cofactoring structure for free-ordered BDD's and generalized cube cofactoring under an average path level (APL) cost criterion. Experiments on multi-valued functions show superior results to previously known methods by an average of 30%. The framework has direct applications in logic simulation, software synthesis for embedded control applications, and functional decomposition in logic synthesis.","PeriodicalId":167477,"journal":{"name":"Proceedings 2003. Design Automation Conference (IEEE Cat. No.03CH37451)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Generalized cofactoring for logic function evaluation\",\"authors\":\"Yunjian Jiang, Slobodan Matic, R. Brayton\",\"doi\":\"10.1145/775832.775873\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Logic evaluation of a Boolean function or relation is traditionally done by simulating its gate-level implementation, or creating a branching program using its binary decision diagram (BDD) representation, or using a set of look-up tables. We propose a new approach called generalized cofactoring diagrams, which are a generalization of the above methods. Algorithms are given for finding the optimal cofactoring structure for free-ordered BDD's and generalized cube cofactoring under an average path level (APL) cost criterion. Experiments on multi-valued functions show superior results to previously known methods by an average of 30%. The framework has direct applications in logic simulation, software synthesis for embedded control applications, and functional decomposition in logic synthesis.\",\"PeriodicalId\":167477,\"journal\":{\"name\":\"Proceedings 2003. Design Automation Conference (IEEE Cat. No.03CH37451)\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2003-06-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings 2003. Design Automation Conference (IEEE Cat. No.03CH37451)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/775832.775873\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 2003. Design Automation Conference (IEEE Cat. No.03CH37451)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/775832.775873","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Generalized cofactoring for logic function evaluation
Logic evaluation of a Boolean function or relation is traditionally done by simulating its gate-level implementation, or creating a branching program using its binary decision diagram (BDD) representation, or using a set of look-up tables. We propose a new approach called generalized cofactoring diagrams, which are a generalization of the above methods. Algorithms are given for finding the optimal cofactoring structure for free-ordered BDD's and generalized cube cofactoring under an average path level (APL) cost criterion. Experiments on multi-valued functions show superior results to previously known methods by an average of 30%. The framework has direct applications in logic simulation, software synthesis for embedded control applications, and functional decomposition in logic synthesis.