{"title":"Algorithmic transforms for efficient energy scalable computation","authors":"A. Sinha, Alice Wang, A. Chandrakasan","doi":"10.1145/344166.344188","DOIUrl":null,"url":null,"abstract":"We introduce the notion of energy scalable computation on general purpose processors. The principle idea is to maximize computational quality for a given energy constraint. The desirable energy-quality behavior of algorithms is discussed. Subsequently the energy-quality scalability of three distinct categories of commonly used signal processing algorithms (viz. filtering, frequency domain transforms and classification) are analyzed on the StrongARM SA-1100 processor and transformations are described which obtain significant improvements in the energy-quality scalability of the algorithm.","PeriodicalId":188020,"journal":{"name":"ISLPED'00: Proceedings of the 2000 International Symposium on Low Power Electronics and Design (Cat. No.00TH8514)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"70","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ISLPED'00: Proceedings of the 2000 International Symposium on Low Power Electronics and Design (Cat. No.00TH8514)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/344166.344188","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 70
Abstract
We introduce the notion of energy scalable computation on general purpose processors. The principle idea is to maximize computational quality for a given energy constraint. The desirable energy-quality behavior of algorithms is discussed. Subsequently the energy-quality scalability of three distinct categories of commonly used signal processing algorithms (viz. filtering, frequency domain transforms and classification) are analyzed on the StrongARM SA-1100 processor and transformations are described which obtain significant improvements in the energy-quality scalability of the algorithm.