{"title":"Exploiting dynamic phase distance mapping for phase-based tuning of embedded systems","authors":"Tosiron Adegbija, A. Gordon-Ross","doi":"10.1109/ICCD.2013.6657066","DOIUrl":null,"url":null,"abstract":"Phase-based tuning increases optimization potential by configuring system parameters for application execution phases. Previous work proposed phase distance mapping (PDM), which relied on extensive a priori analysis of executing applications to dynamically estimate the best configuration using the correlation between phases. We propose DynaPDM, a new dynamic phase distance mapping methodology that eliminates a priori designer effort, dynamically analyzes phases, and determines the best configurations, yielding average energy delay product savings of 28%-an 8% improvement on PDM-and configurations within 1% of the optimal.","PeriodicalId":398811,"journal":{"name":"2013 IEEE 31st International Conference on Computer Design (ICCD)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE 31st International Conference on Computer Design (ICCD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCD.2013.6657066","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Phase-based tuning increases optimization potential by configuring system parameters for application execution phases. Previous work proposed phase distance mapping (PDM), which relied on extensive a priori analysis of executing applications to dynamically estimate the best configuration using the correlation between phases. We propose DynaPDM, a new dynamic phase distance mapping methodology that eliminates a priori designer effort, dynamically analyzes phases, and determines the best configurations, yielding average energy delay product savings of 28%-an 8% improvement on PDM-and configurations within 1% of the optimal.