Domain knowledge based energy management in handhelds

N. Nachiappan, Praveen Yedlapalli, N. Soundararajan, A. Sivasubramaniam, M. Kandemir, Ravishankar R. Iyer, C. Das
{"title":"Domain knowledge based energy management in handhelds","authors":"N. Nachiappan, Praveen Yedlapalli, N. Soundararajan, A. Sivasubramaniam, M. Kandemir, Ravishankar R. Iyer, C. Das","doi":"10.1109/HPCA.2015.7056029","DOIUrl":null,"url":null,"abstract":"Energy management in handheld devices is becoming a daunting task with the growing number of accelerators, increasing memory demands and high computing capacities required to support applications with stringent QoS needs. Current DVFS techniques that modulate power states of a single hardware component, or even recent proposals that manage multiple components, can lose out opportunities for attaining high energy efficiencies that may be possible by leveraging application domain knowledge. Thus, this paper proposes a coordinated multi-component energy optimization mechanism for handheld devices, where the energy profile of different components such as CPU, memory, GPU and IP cores are considered in unison to trigger the appropriate DVFS state by exploiting the application domain knowledge. Specifically, we show that for the important class of frame-based applications, the domain knowledge - frame processing rates, component utilization and available slack - can be used to decide effective DVFS states for each component from among the numerous choices. With such knowledge, rather than a brute force search of all speed setting choices, we propose two simpler heuristics, called Greedy policy and Kaldor-Hicks compensation policy, to make the decisions at frame boundaries. Our evaluations with 7 commonly-used Android apps show that our domain-aware coordinated DVFS policies have 23% better energy efficiency than the conventionally used Android governors, and are within ~9% of an optimal policy that does not drop any frames.","PeriodicalId":6593,"journal":{"name":"2015 IEEE 21st International Symposium on High Performance Computer Architecture (HPCA)","volume":"1 1","pages":"150-160"},"PeriodicalIF":0.0000,"publicationDate":"2015-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"37","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE 21st International Symposium on High Performance Computer Architecture (HPCA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HPCA.2015.7056029","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 37

Abstract

Energy management in handheld devices is becoming a daunting task with the growing number of accelerators, increasing memory demands and high computing capacities required to support applications with stringent QoS needs. Current DVFS techniques that modulate power states of a single hardware component, or even recent proposals that manage multiple components, can lose out opportunities for attaining high energy efficiencies that may be possible by leveraging application domain knowledge. Thus, this paper proposes a coordinated multi-component energy optimization mechanism for handheld devices, where the energy profile of different components such as CPU, memory, GPU and IP cores are considered in unison to trigger the appropriate DVFS state by exploiting the application domain knowledge. Specifically, we show that for the important class of frame-based applications, the domain knowledge - frame processing rates, component utilization and available slack - can be used to decide effective DVFS states for each component from among the numerous choices. With such knowledge, rather than a brute force search of all speed setting choices, we propose two simpler heuristics, called Greedy policy and Kaldor-Hicks compensation policy, to make the decisions at frame boundaries. Our evaluations with 7 commonly-used Android apps show that our domain-aware coordinated DVFS policies have 23% better energy efficiency than the conventionally used Android governors, and are within ~9% of an optimal policy that does not drop any frames.
基于领域知识的手持设备能量管理
随着加速器数量的增加、内存需求的增加以及支持具有严格QoS需求的应用程序所需的高计算能力的增加,手持设备中的能量管理正在成为一项艰巨的任务。当前的DVFS技术是调制单个硬件组件的电源状态,甚至最近提出的管理多个组件的建议,都可能失去通过利用应用程序领域知识实现高能效的机会。为此,本文提出了一种针对手持设备的协调多组件能量优化机制,该机制统一考虑CPU、内存、GPU和IP核等不同组件的能量分布,利用应用领域知识触发适当的DVFS状态。具体来说,我们表明,对于一类重要的基于帧的应用,领域知识-帧处理速率,组件利用率和可用空闲-可以用于从众多选择中确定每个组件的有效DVFS状态。有了这些知识,我们提出了两种更简单的启发式方法,称为贪心策略和卡尔多-希克斯补偿策略,以在帧边界做出决策,而不是对所有速度设置选择进行暴力搜索。我们对7个常用的Android应用程序的评估表明,我们的域感知协调DVFS策略比传统使用的Android调控器的能源效率高23%,并且在不丢失任何帧的最优策略的约9%之内。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信