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Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
}
TY - GEN
T1 - Power capping
T2 - what works, what does not
AU - Petoumenos, Pavlos
AU - Mukhanov, Lev
AU - Wang, Zheng
AU - Leather, Hugh
AU - Nikolopoulos, Dimitrios
N1 - ©2015 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
PY - 2015/12/14
Y1 - 2015/12/14
N2 - Peak power consumption is the first order design constraint of data centers. Though peak power consumption is rarely, if ever, observed, the entire data center facility must prepare for it, leading to inefficient usage of its resources. The most prominent way for addressing this issue is to limit the power consumption of the data center IT facility far below its theoretical peak value. Many approaches have been proposed to achieve that, based on the same small set of enforcement mechanisms, but there has been no corresponding work on systematically examining the advantages and disadvantages of each such mechanism. In the absence of such a study, it is unclear what is the optimal mechanism for a given computing environment, which can lead to unnecessarily poor performance if an inappropriate scheme is used. This paper fills this gap by comparing for the first time five widely used power capping mechanisms under the same hardware/software setting. We also explore possible alternative power capping mechanisms beyond what has been previously proposed and evaluate them under the same setup. We systematically analyze the strengths and weaknesses of each mechanism, in terms of energy efficiency, overhead, and predictable behavior. We show how these mechanisms can be combined in order to implement an optimal power capping mechanism which reduces the slowdown compared to the most widely used mechanism by up to 88%. Our results provide interesting insights regarding the different trade-offs of power capping techniques, which will be useful for designing and implementing highly efficient power capping in the future.
AB - Peak power consumption is the first order design constraint of data centers. Though peak power consumption is rarely, if ever, observed, the entire data center facility must prepare for it, leading to inefficient usage of its resources. The most prominent way for addressing this issue is to limit the power consumption of the data center IT facility far below its theoretical peak value. Many approaches have been proposed to achieve that, based on the same small set of enforcement mechanisms, but there has been no corresponding work on systematically examining the advantages and disadvantages of each such mechanism. In the absence of such a study, it is unclear what is the optimal mechanism for a given computing environment, which can lead to unnecessarily poor performance if an inappropriate scheme is used. This paper fills this gap by comparing for the first time five widely used power capping mechanisms under the same hardware/software setting. We also explore possible alternative power capping mechanisms beyond what has been previously proposed and evaluate them under the same setup. We systematically analyze the strengths and weaknesses of each mechanism, in terms of energy efficiency, overhead, and predictable behavior. We show how these mechanisms can be combined in order to implement an optimal power capping mechanism which reduces the slowdown compared to the most widely used mechanism by up to 88%. Our results provide interesting insights regarding the different trade-offs of power capping techniques, which will be useful for designing and implementing highly efficient power capping in the future.
KW - Power optimization
KW - Power capping
KW - Compiler
KW - DVFS
KW - RAPL
U2 - 10.1109/ICPADS.2015.72
DO - 10.1109/ICPADS.2015.72
M3 - Conference contribution/Paper
SN - 9780769557854
SP - 525
EP - 534
BT - Parallel and Distributed Systems (ICPADS), 2015 IEEE 21st International Conference on
PB - IEEE
ER -