NDLI: Towards a generic power estimator

Content Provider	Springer Nature Link
Author	Cuperti, Leandro Fontoura Costa, Georges Pierson, Jean Marc
Copyright Year	2014
Abstract	Data centers play an important role on worldwide electrical energy consumption. Understanding their power dissipation is a key aspect to achieve energy efficiency. Some application specific models were proposed, while other generic ones lack accuracy. The contributions of this paper are threefold. First we expose the importance of modelling alternating to direct current conversion losses. Second, a weakness of CPU proportional models is evidenced. Finally, a methodology to estimate the power consumed by applications with machine learning techniques is proposed. Since the results of such techniques are deeply data dependent, a study on devices’ power profiles was executed to generate a small set of synthetic benchmarks able to emulate generic applications’ behaviour. Our approach is then compared with two other models, showing that the percentage error of energy estimation of an application can be less than 1 %.
Starting Page	145
Ending Page	153
Page Count	9
File Format	PDF
ISSN	18652034
Journal	Informatik - Forschung und Entwicklung
Volume Number	30
Issue Number	2
e-ISSN	18652042
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2014-07-05
Publisher Place	Berlin, Heidelberg
Access Restriction	Subscribed
Subject Keyword	Power estimation Generic model Data centers Machine learning Neural networks Computer Science Computer Hardware Computer Systems Organization and Communication Networks Software Engineering/Programming and Operating Systems Data Structures, Cryptology and Information Theory Theory of Computation
Content Type	Text
Resource Type	Article
Subject	Computer Science

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