{"title":"An Energy-Efficient Design-Time Scheduler for FPGAs Leveraging Dynamic Frequency Scaling Emulation (Abstract Only)","authors":"W. Loke, Chin Yang Koay","doi":"10.1145/3020078.3021805","DOIUrl":null,"url":null,"abstract":"We present a design-time tool, EASTA, that combines the feature of reconfigurability in FPGAs and Dynamic Frequency Scaling to realize an efficient multiprocessing scheduler on a single-FPGA system. Multiple deadlines, reconvergent nodes, flow dependency and processor constraints of the multiprocessor problem on general task graphs are rigorously taken into consideration. EASTA is able to determine the minimum number of processing elements required to create a feasible schedule and dynamically adjust the clock speed of each processing element to reclaim slack. The schedule is represented by an efficient tree-based lookup table. We evaluate the EASTA tool using randomly generated task graphs and demonstrate that our framework is able to produce energy savings of 39.41% and 33% for task graphs of size 9.","PeriodicalId":252039,"journal":{"name":"Proceedings of the 2017 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2017 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3020078.3021805","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
We present a design-time tool, EASTA, that combines the feature of reconfigurability in FPGAs and Dynamic Frequency Scaling to realize an efficient multiprocessing scheduler on a single-FPGA system. Multiple deadlines, reconvergent nodes, flow dependency and processor constraints of the multiprocessor problem on general task graphs are rigorously taken into consideration. EASTA is able to determine the minimum number of processing elements required to create a feasible schedule and dynamically adjust the clock speed of each processing element to reclaim slack. The schedule is represented by an efficient tree-based lookup table. We evaluate the EASTA tool using randomly generated task graphs and demonstrate that our framework is able to produce energy savings of 39.41% and 33% for task graphs of size 9.