{"title":"Synthesis of application-specific memories for power optimization in embedded systems","authors":"L. Benini, A. Macii, E. Macii, M. Poncino","doi":"10.1145/337292.337424","DOIUrl":null,"url":null,"abstract":"This paper presents a novel approach to memory power optimization for embedded systems based on the exploitation of data locality. Locations with highest access frequency are mapped onto a small, low-power application-specific memory which is placed close the processor. Although, in principle, a cache may be used to implement such a memory, more efficient solutions may be adopted. We propose an architecture that outperforms (power-wise) different types of cache memories at no penalty in performance. Power savings (averaged over a number of embedded applications running on ARM processors) range from 12% to 68%.","PeriodicalId":237114,"journal":{"name":"Proceedings 37th Design Automation Conference","volume":"10 3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"34","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 37th Design Automation Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/337292.337424","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 34
Abstract
This paper presents a novel approach to memory power optimization for embedded systems based on the exploitation of data locality. Locations with highest access frequency are mapped onto a small, low-power application-specific memory which is placed close the processor. Although, in principle, a cache may be used to implement such a memory, more efficient solutions may be adopted. We propose an architecture that outperforms (power-wise) different types of cache memories at no penalty in performance. Power savings (averaged over a number of embedded applications running on ARM processors) range from 12% to 68%.