{"title":"HDL optimization using timed decision tables","authors":"Jian Li, Rajesh K. Gupta","doi":"10.1109/DAC.1996.545544","DOIUrl":null,"url":null,"abstract":"System-level presynthesis refers to the optimization of an input HDL description that produces an optimized HDL description suitable for subsequent synthesis tasks. In this paper, we present optimization of control flow in behavioral HDL descriptions using external Don't Care conditions. The optimizations are carried out using a tabular model of system functionality, called Timed Decision Tables or TDTs. TDT based optimization presented here have been implemented in a program called PUMPKIN. Optimization results from several examples show a reduction of 3-88% in the size of synthesized hardware circuits depending upon the external Don't Care information supplied by the user.","PeriodicalId":152966,"journal":{"name":"33rd Design Automation Conference Proceedings, 1996","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1996-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"33rd Design Automation Conference Proceedings, 1996","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DAC.1996.545544","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 16
Abstract
System-level presynthesis refers to the optimization of an input HDL description that produces an optimized HDL description suitable for subsequent synthesis tasks. In this paper, we present optimization of control flow in behavioral HDL descriptions using external Don't Care conditions. The optimizations are carried out using a tabular model of system functionality, called Timed Decision Tables or TDTs. TDT based optimization presented here have been implemented in a program called PUMPKIN. Optimization results from several examples show a reduction of 3-88% in the size of synthesized hardware circuits depending upon the external Don't Care information supplied by the user.