{"title":"Battery-efficient task execution on portable reconfigurable computing","authors":"B. Sethuraman, J. Khan, R. Vemuri","doi":"10.1109/SOCC.2004.1362420","DOIUrl":null,"url":null,"abstract":"We present a battery-efficient task execution methodology for portable reconfigurable computing (RC) platforms. We implement a given algorithm with varying power-performance levels: we call these implementations, Cores and each core is characterized in terms of its power and performance levels. Core change and/or the frequency change are the two mechanisms used to vary the battery consumption. We consider two cases for single task execution: one increasing the performance with a battery life constraint and the other prolonging the battery' life with a performance constraint. The execution time of each task is divided into equal time intervals, called slots. A simulated annealing based algorithm is used to find the best constraint-satisfying sequence of cores offline. Our results show a 50% increase in the total work done (case 1) and 61% increase in battery life (case 2), by using this methodology when compared to a system not using it. The combined effect of both cases is applied to a multiple task execution and the results are reported.","PeriodicalId":184894,"journal":{"name":"IEEE International SOC Conference, 2004. Proceedings.","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE International SOC Conference, 2004. Proceedings.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SOCC.2004.1362420","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
We present a battery-efficient task execution methodology for portable reconfigurable computing (RC) platforms. We implement a given algorithm with varying power-performance levels: we call these implementations, Cores and each core is characterized in terms of its power and performance levels. Core change and/or the frequency change are the two mechanisms used to vary the battery consumption. We consider two cases for single task execution: one increasing the performance with a battery life constraint and the other prolonging the battery' life with a performance constraint. The execution time of each task is divided into equal time intervals, called slots. A simulated annealing based algorithm is used to find the best constraint-satisfying sequence of cores offline. Our results show a 50% increase in the total work done (case 1) and 61% increase in battery life (case 2), by using this methodology when compared to a system not using it. The combined effect of both cases is applied to a multiple task execution and the results are reported.