{"title":"A General Algorithm for Energy-Aware Dynamic Reconfiguration in Multitasking Systems","authors":"Weixun Wang, S. Ranka, P. Mishra","doi":"10.1109/VLSID.2011.17","DOIUrl":null,"url":null,"abstract":"System optimization techniques based on dynamic reconfiguration are widely adopted for energy conservation. While dynamic voltage scaling (DVS) techniques have been extensively studied for processor energy conservation, dynamic cache reconfiguration (DCR) for reducing cache energy consumption in multitasking systems is still in its infancy. In this paper, we propose a general and flexible algorithm for energy optimization based on dynamic reconfiguration in multitasking systems. Our algorithm is flexibly parameterized and can be used to provide tradeoffs between running time and solution quality. Furthermore, it can easily incorporate variable reconfiguration overhead. Experimental results show that our technique can generate near-optimal solutions with significantly low running time and memory requirements.","PeriodicalId":371062,"journal":{"name":"2011 24th Internatioal Conference on VLSI Design","volume":"78 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 24th Internatioal Conference on VLSI Design","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VLSID.2011.17","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
System optimization techniques based on dynamic reconfiguration are widely adopted for energy conservation. While dynamic voltage scaling (DVS) techniques have been extensively studied for processor energy conservation, dynamic cache reconfiguration (DCR) for reducing cache energy consumption in multitasking systems is still in its infancy. In this paper, we propose a general and flexible algorithm for energy optimization based on dynamic reconfiguration in multitasking systems. Our algorithm is flexibly parameterized and can be used to provide tradeoffs between running time and solution quality. Furthermore, it can easily incorporate variable reconfiguration overhead. Experimental results show that our technique can generate near-optimal solutions with significantly low running time and memory requirements.