{"title":"Dynamic minimization of OKFDDs","authors":"R. Drechsler, B. Becker","doi":"10.1109/ICCD.1995.528930","DOIUrl":null,"url":null,"abstract":"We present methods for the construction of small Ordered Kronecker Functional Decision Diagrams (OKFDDs). OKFDDs are a generalization of Ordered Binary Decision Diagrams (OBDDs) and Ordered Functional Decision Diagrams (OFDDs) as well. Our approach is based on dynamic variable ordering and decomposition type choice. For changing the decomposition type we use a new method. We briefly discuss the implementation of PUMA, our OKFDD package. The quality of our methods in comparison with sifting and interleaving for OBDDs is demonstrated based on experiments performed with PUMA.","PeriodicalId":281907,"journal":{"name":"Proceedings of ICCD '95 International Conference on Computer Design. VLSI in Computers and Processors","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1995-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"39","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of ICCD '95 International Conference on Computer Design. VLSI in Computers and Processors","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCD.1995.528930","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 39

Abstract

We present methods for the construction of small Ordered Kronecker Functional Decision Diagrams (OKFDDs). OKFDDs are a generalization of Ordered Binary Decision Diagrams (OBDDs) and Ordered Functional Decision Diagrams (OFDDs) as well. Our approach is based on dynamic variable ordering and decomposition type choice. For changing the decomposition type we use a new method. We briefly discuss the implementation of PUMA, our OKFDD package. The quality of our methods in comparison with sifting and interleaving for OBDDs is demonstrated based on experiments performed with PUMA.
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okfdd的动态最小化
我们提出了构造小有序Kronecker功能决策图(okfdd)的方法。okfdd是有序二元决策图(obdd)和有序功能决策图(ofdd)的推广。我们的方法是基于动态变量排序和分解类型选择。为了改变分解类型,我们使用了一个新方法。我们简要地讨论了我们的OKFDD包PUMA的实现。用PUMA进行的实验证明了我们的方法与筛选和交错处理obdd相比的质量。
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Design and implementation of a 100 MHz centralized instruction window for a superscalar microprocessor Multiprocessor design verification for the PowerPC 620 microprocessor Connection-oriented net model and fuzzy clustering techniques for K-way circuit partitioning Dynamic minimization of OKFDDs Simple tree-construction heuristics for the fanout problem
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