A Novel Power Management for CMP Systems in Data-Intensive Environment

Pengju Shang, Jun Wang
{"title":"A Novel Power Management for CMP Systems in Data-Intensive Environment","authors":"Pengju Shang, Jun Wang","doi":"10.1109/IPDPS.2011.19","DOIUrl":null,"url":null,"abstract":"The emerging data-intensive applications of today are comprised of non-uniform CPU and I/O intensive workloads, thus imposing a requirement to consider both CPU and I/O effects in the power management strategies. Only scaling down the processor's frequency based on its busy/idle ratio cannot fully exploit opportunities of saving power. Our experiments show that besides the busy and idle status, each processor may also have I/O wait phases waiting for I/O operations to complete. During this period, the completion time is decided by the I/O subsystem rather than the CPU thus scaling the processor to a lower frequency will not affect the performance but save more power. In addition, the CPU's reaction to the I/O operations may be significantly affected by several factors, such as I/O type (sync or unsync), instruction/job level parallelism, it cannot be accurately modeled via physics laws like mechanical or chemical systems. In this paper, we propose a novel power management scheme called MAR (modeless, adaptive, rule-based) in multiprocessor systems to minimize the CPU power consumption under performance constraints. By using richer feedback factors, e.g. the I/O wait, MAR is able to accurately describe the relationships among core frequencies, performance and power consumption. We adopt a modeless control model to reduce the complexity of system modeling. MAR is designed for CMP (Chip Multi Processor) systems by employing multi-input/multi-output (MIMO) theory and per core level DVFS (Dynamic Voltage and Frequency Scaling). Our extensive experiments on a physical test bed demonstrate that, for the SPEC benchmark and data-intensive (TPC-C) benchmark, the efficiency of MAR is 93.6-96.2\\% accurate to the ideal power saving strategy calculated off-line. Compared with baseline solutions, MAR could save 22.5-32.5\\% more power while keeping the comparable performance loss of about 1.8-2.9\\%. In addition, simulation results show the efficiency of our design for various CMP configurations.","PeriodicalId":355100,"journal":{"name":"2011 IEEE International Parallel & Distributed Processing Symposium","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE International Parallel & Distributed Processing Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IPDPS.2011.19","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12

Abstract

The emerging data-intensive applications of today are comprised of non-uniform CPU and I/O intensive workloads, thus imposing a requirement to consider both CPU and I/O effects in the power management strategies. Only scaling down the processor's frequency based on its busy/idle ratio cannot fully exploit opportunities of saving power. Our experiments show that besides the busy and idle status, each processor may also have I/O wait phases waiting for I/O operations to complete. During this period, the completion time is decided by the I/O subsystem rather than the CPU thus scaling the processor to a lower frequency will not affect the performance but save more power. In addition, the CPU's reaction to the I/O operations may be significantly affected by several factors, such as I/O type (sync or unsync), instruction/job level parallelism, it cannot be accurately modeled via physics laws like mechanical or chemical systems. In this paper, we propose a novel power management scheme called MAR (modeless, adaptive, rule-based) in multiprocessor systems to minimize the CPU power consumption under performance constraints. By using richer feedback factors, e.g. the I/O wait, MAR is able to accurately describe the relationships among core frequencies, performance and power consumption. We adopt a modeless control model to reduce the complexity of system modeling. MAR is designed for CMP (Chip Multi Processor) systems by employing multi-input/multi-output (MIMO) theory and per core level DVFS (Dynamic Voltage and Frequency Scaling). Our extensive experiments on a physical test bed demonstrate that, for the SPEC benchmark and data-intensive (TPC-C) benchmark, the efficiency of MAR is 93.6-96.2\% accurate to the ideal power saving strategy calculated off-line. Compared with baseline solutions, MAR could save 22.5-32.5\% more power while keeping the comparable performance loss of about 1.8-2.9\%. In addition, simulation results show the efficiency of our design for various CMP configurations.
数据密集型环境下CMP系统的一种新型电源管理方法
当今新兴的数据密集型应用程序由不统一的CPU和I/O密集型工作负载组成,因此要求在电源管理策略中同时考虑CPU和I/O影响。仅仅根据处理器的忙/空闲比率来降低处理器的频率并不能充分利用节省电力的机会。我们的实验表明,除了繁忙和空闲状态外,每个处理器还可能有等待I/O操作完成的I/O等待阶段。在此期间,完成时间由I/O子系统而不是CPU决定,因此将处理器扩展到较低的频率不会影响性能,但会节省更多的功率。此外,CPU对I/O操作的反应可能会受到几个因素的显著影响,例如I/O类型(同步或不同步),指令/作业级别的并行性,它不能通过机械或化学系统等物理定律精确地建模。在本文中,我们提出了一种新的多处理器系统电源管理方案,称为MAR(无模式,自适应,基于规则),以最大限度地降低CPU功耗。通过使用更丰富的反馈因素,例如I/O等待时间,MAR能够准确地描述核心频率、性能和功耗之间的关系。采用非模态控制模型,降低了系统建模的复杂性。MAR是为CMP(芯片多处理器)系统设计的,采用多输入/多输出(MIMO)理论和每核级DVFS(动态电压和频率缩放)。我们在物理测试平台上的大量实验表明,对于SPEC基准测试和数据密集型(TPC-C)基准测试,MAR的效率与离线计算的理想省电策略的准确率为93.6- 96.2%。与基线解决方案相比,MAR可以节省22.5- 32.5%的功率,同时保持约1.8- 2.9%的性能损失。此外,仿真结果表明了我们的设计在各种CMP配置下的有效性。
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