{"title":"时间决策表的分解及其在预合成优化中的应用","authors":"Jian Li, Rajesh K. Gupta","doi":"10.1109/ICCAD.1997.643261","DOIUrl":null,"url":null,"abstract":"Presynthesis optimizations transform a behavioral HDL description into an optimized HDL description that results in improved synthesis results. We introduce the decomposition of timed decision tables (TDT), a tabular model of system behavior. The TDT decomposition is based on the kernel extraction algorithm. By experimenting using named benchmarks, we demonstrate how TDT decomposition can be used in presynthesis optimizations.","PeriodicalId":187521,"journal":{"name":"1997 Proceedings of IEEE International Conference on Computer Aided Design (ICCAD)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Decomposition of timed decision tables and its use in presynthesis optimizations\",\"authors\":\"Jian Li, Rajesh K. Gupta\",\"doi\":\"10.1109/ICCAD.1997.643261\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Presynthesis optimizations transform a behavioral HDL description into an optimized HDL description that results in improved synthesis results. We introduce the decomposition of timed decision tables (TDT), a tabular model of system behavior. The TDT decomposition is based on the kernel extraction algorithm. By experimenting using named benchmarks, we demonstrate how TDT decomposition can be used in presynthesis optimizations.\",\"PeriodicalId\":187521,\"journal\":{\"name\":\"1997 Proceedings of IEEE International Conference on Computer Aided Design (ICCAD)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1997-11-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"1997 Proceedings of IEEE International Conference on Computer Aided Design (ICCAD)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCAD.1997.643261\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"1997 Proceedings of IEEE International Conference on Computer Aided Design (ICCAD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCAD.1997.643261","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Decomposition of timed decision tables and its use in presynthesis optimizations
Presynthesis optimizations transform a behavioral HDL description into an optimized HDL description that results in improved synthesis results. We introduce the decomposition of timed decision tables (TDT), a tabular model of system behavior. The TDT decomposition is based on the kernel extraction algorithm. By experimenting using named benchmarks, we demonstrate how TDT decomposition can be used in presynthesis optimizations.