{"title":"Energy-aware memory allocation in heterogeneous non-volatile memory systems","authors":"H. Lee, N. Chang","doi":"10.1145/871506.871609","DOIUrl":null,"url":null,"abstract":"Memory systems consume a significant portion of power in hand-held embedded systems. So far, low-power memory techniques have addressed the power consumption when the system is turned on. In this paper, we consider data retention energy during the power-off period. For this purpose, we first characterize the data retention energy and cycle-accurate active mode energy. of the non-volatile memory systems. Next, we present energy-aware memory allocation for a given task set taking into account arrival rate, execution time, code size, user data size and the number of memory transactions by the use of trace-driven simulation. Experiments demonstrate that our optimal configuration can save up to 26% of the memory system energy compared traditional allocation schemes.","PeriodicalId":355883,"journal":{"name":"Proceedings of the 2003 International Symposium on Low Power Electronics and Design, 2003. ISLPED '03.","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"42","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2003 International Symposium on Low Power Electronics and Design, 2003. ISLPED '03.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/871506.871609","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 42
Abstract
Memory systems consume a significant portion of power in hand-held embedded systems. So far, low-power memory techniques have addressed the power consumption when the system is turned on. In this paper, we consider data retention energy during the power-off period. For this purpose, we first characterize the data retention energy and cycle-accurate active mode energy. of the non-volatile memory systems. Next, we present energy-aware memory allocation for a given task set taking into account arrival rate, execution time, code size, user data size and the number of memory transactions by the use of trace-driven simulation. Experiments demonstrate that our optimal configuration can save up to 26% of the memory system energy compared traditional allocation schemes.