research-article

The case for sleep states in servers

Authors:

Anshul Gandhi,

Mor Harchol-Balter,

Michael A. KozuchAuthors Info & Claims

HotPower '11: Proceedings of the 4th Workshop on Power-Aware Computing and Systems

Article No.: 2, Pages 1 - 5

https://doi.org/10.1145/2039252.2039254

Published: 23 October 2011 Publication History

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Abstract

While sleep states have existed for mobile devices and workstations for some time, these sleep states have largely not been incorporated into the servers in today's data centers.

Chip designers have been unmotivated to design sleep states because data center administrators haven't expressed any desire to have them. High setup times make administrators fearful of any form of dynamic power management, whereby servers are suspended or shut down when load drops. This general reluctance has stalled research into whether there might be some feasible sleep state (with sufficiently low setup overhead and/or sufficiently low power) that would actually be beneficial in data centers.

This paper uses both experimentation and theory to investigate the regime of sleep states that should be advantageous in data centers. Implementation experiments involve a 24-server multi-tier testbed, serving a web site of the type seen in Facebook or Amazon with key-value workload and a range of hypothetical sleep states. Analytical modeling is used to understand the effect of scaling up to larger data centers. The goal of this research is to encourage data center administrators to consider dynamic power management and to spur chip designers to develop useful sleep states for servers.

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Cited By

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Williams JHarchol-Balter MWang W(2022)The M/M/k with Deterministic Setup TimesProceedings of the ACM on Measurement and Analysis of Computing Systems10.1145/35706176:3(1-45)Online publication date: 8-Dec-2022
https://dl.acm.org/doi/10.1145/3570617
Cao ZZhou XHu HWang ZWen Y(2022)Toward a Systematic Survey for Carbon Neutral Data CentersIEEE Communications Surveys & Tutorials10.1109/COMST.2022.316127524:2(895-936)Online publication date: Oct-2023
https://doi.org/10.1109/COMST.2022.3161275
Phung-Duc T(2020)Batch Arrival Multiserver Queue with State-Dependent Setup for Energy-Saving Data CenterApplied Probability and Stochastic Processes10.1007/978-981-15-5951-8_25(421-440)Online publication date: 30-Aug-2020
https://doi.org/10.1007/978-981-15-5951-8_25
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The case for sleep states in servers

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Published In

HotPower '11: Proceedings of the 4th Workshop on Power-Aware Computing and Systems

October 2011

51 pages

ISBN:9781450309813

DOI:10.1145/2039252

Program Chairs:
Ricardo Bianchini,
Prabal Dutta

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 23 October 2011

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SOSP '11: ACM SIGOPS 23nd Symposium on Operating Systems Principles

October 23, 2011

Cascais, Portugal

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Williams JHarchol-Balter MWang W(2022)The M/M/k with Deterministic Setup TimesProceedings of the ACM on Measurement and Analysis of Computing Systems10.1145/35706176:3(1-45)Online publication date: 8-Dec-2022
https://dl.acm.org/doi/10.1145/3570617
Cao ZZhou XHu HWang ZWen Y(2022)Toward a Systematic Survey for Carbon Neutral Data CentersIEEE Communications Surveys & Tutorials10.1109/COMST.2022.316127524:2(895-936)Online publication date: Oct-2023
https://doi.org/10.1109/COMST.2022.3161275
Phung-Duc T(2020)Batch Arrival Multiserver Queue with State-Dependent Setup for Energy-Saving Data CenterApplied Probability and Stochastic Processes10.1007/978-981-15-5951-8_25(421-440)Online publication date: 30-Aug-2020
https://doi.org/10.1007/978-981-15-5951-8_25
O’Dwyer KCreedon EPurcell MMalone D(2019)Power Saving Proxies for Web ServersThe Computer Journal10.1093/comjnl/bxz08163:2(179-192)Online publication date: 8-Nov-2019
https://doi.org/10.1093/comjnl/bxz081
Larumbe FSanso B(2017)Elastic, on-line and network aware Virtual Machine placement within a data center2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM)10.23919/INM.2017.7987261(28-36)Online publication date: May-2017
https://doi.org/10.23919/INM.2017.7987261
Xuan TDo T(2016)Job Scheduling in a Computational Cluster with Multicore ProcessorsAdvanced Computational Methods for Knowledge Engineering10.1007/978-3-319-38884-7_6(75-84)Online publication date: 23-Apr-2016
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Cheng DGuo YJiang CZhou X(2015)Self-Tuning Batching with DVFS for Performance Improvement and Energy Efficiency in Internet ServersACM Transactions on Autonomous and Adaptive Systems10.1145/272002310:1(1-32)Online publication date: 25-Mar-2015
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Wang KLin MCiucu FWierman ALin C(2015)Characterizing the impact of the workload on the value of dynamic resizing in data centersPerformance Evaluation10.1016/j.peva.2014.12.00185:C(1-18)Online publication date: 1-Mar-2015
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Çavdar DBirke RChen LAlagöz F(2015)A simulation framework for priority scheduling on heterogeneous clustersFuture Generation Computer Systems10.1016/j.future.2015.04.00852:C(37-48)Online publication date: 1-Nov-2015
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Pore MAbbasi ZGupta SVarsamopoulos G(2015)Techniques to Achieve Energy Proportionality in Data Centers: A SurveyHandbook on Data Centers10.1007/978-1-4939-2092-1_4(109-162)Online publication date: 17-Mar-2015
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Are sleep states effective in data centers?

Improving energy efficiency for mobile platforms by exploiting low-power sleep states

Energy-aware task mapping onto heterogeneous platforms using DVFS and sleep states

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