{"title":"Extended 0/1 LP formulation for the scheduling problem in high-level synthesis","authors":"H. Achatz","doi":"10.1109/EURDAC.1993.410642","DOIUrl":null,"url":null,"abstract":"An extended zero-one linear programming (O/1 LP) model for the scheduling problem in high-level synthesis is presented. As an extension to former approaches, the 0/1 LP model can handle multifunctional function units as well as different execution times for different instances of the same operation type. These extensions are very important for the applicability of general high-level synthesis tools in real design tasks. The computing time for solving the optimization problems is also acceptable for the new powerful model, since new lower bounds have been introduced that drastically reduce the search space. Some experimental results are shown.<<ETX>>","PeriodicalId":339176,"journal":{"name":"Proceedings of EURO-DAC 93 and EURO-VHDL 93- European Design Automation Conference","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1993-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of EURO-DAC 93 and EURO-VHDL 93- European Design Automation Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EURDAC.1993.410642","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 17
Abstract
An extended zero-one linear programming (O/1 LP) model for the scheduling problem in high-level synthesis is presented. As an extension to former approaches, the 0/1 LP model can handle multifunctional function units as well as different execution times for different instances of the same operation type. These extensions are very important for the applicability of general high-level synthesis tools in real design tasks. The computing time for solving the optimization problems is also acceptable for the new powerful model, since new lower bounds have been introduced that drastically reduce the search space. Some experimental results are shown.<>
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