Takuya Kojima, Hayate Okuhara, Masaaki Kondo, H. Amano
{"title":"Body Bias Control on a CGRA based on Convex Optimization","authors":"Takuya Kojima, Hayate Okuhara, Masaaki Kondo, H. Amano","doi":"10.1109/coolchips54332.2022.9772708","DOIUrl":null,"url":null,"abstract":"Body biasing is one of the critical techniques to realize more energy-efficient computing with reconfigurable devices, such as Coarse-Grained Reconfigurable Architectures (CGRAs). Its benefit depends on the control granularity, whereas fine-grained control makes it challenging to find the best body bias voltage for each domain due to the complexity of the optimization problem. This work reformulates the optimization problem and introduces continuous relaxation to solve it faster than previous work. Experimental result shows the proposed method can solve the problem within 0.5 sec for all benchmarks in any conditions and demonstrates up to 5.65x speed-up compared to the previous method with negligible loss of accuracy.","PeriodicalId":266152,"journal":{"name":"2022 IEEE Symposium in Low-Power and High-Speed Chips (COOL CHIPS)","volume":"317 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE Symposium in Low-Power and High-Speed Chips (COOL CHIPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/coolchips54332.2022.9772708","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
Body biasing is one of the critical techniques to realize more energy-efficient computing with reconfigurable devices, such as Coarse-Grained Reconfigurable Architectures (CGRAs). Its benefit depends on the control granularity, whereas fine-grained control makes it challenging to find the best body bias voltage for each domain due to the complexity of the optimization problem. This work reformulates the optimization problem and introduces continuous relaxation to solve it faster than previous work. Experimental result shows the proposed method can solve the problem within 0.5 sec for all benchmarks in any conditions and demonstrates up to 5.65x speed-up compared to the previous method with negligible loss of accuracy.