Hongbin Zheng, Qingrui Liu, Junyi Li, Dihu Chen, Zixin Wang
{"title":"A gradual scheduling framework for problem size reduction and cross basic block parallelism exploitation in high-level synthesis","authors":"Hongbin Zheng, Qingrui Liu, Junyi Li, Dihu Chen, Zixin Wang","doi":"10.1109/ASPDAC.2013.6509695","DOIUrl":null,"url":null,"abstract":"In High-level Synthesis, scheduling has a critical impact on the quality of hardware implementation. However, the schedules of different operations are actually having unequal impacts on the Quality of Result. Based on this fact, we propose a novel scheduling framework, which is able to schedule the operations separately according their significance to Quality of Result, to avoid wasting the computational efforts on noncritical operations. Furthermore, the proposed framework supports global code motion, which helps to improve the speed performance of the hardware implementation by distributing the execution time of operations across the their parent BB.","PeriodicalId":297528,"journal":{"name":"2013 18th Asia and South Pacific Design Automation Conference (ASP-DAC)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 18th Asia and South Pacific Design Automation Conference (ASP-DAC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASPDAC.2013.6509695","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
In High-level Synthesis, scheduling has a critical impact on the quality of hardware implementation. However, the schedules of different operations are actually having unequal impacts on the Quality of Result. Based on this fact, we propose a novel scheduling framework, which is able to schedule the operations separately according their significance to Quality of Result, to avoid wasting the computational efforts on noncritical operations. Furthermore, the proposed framework supports global code motion, which helps to improve the speed performance of the hardware implementation by distributing the execution time of operations across the their parent BB.