research-article

Evaluating and modeling power consumption of multi-core processors

Authors:

Robert Basmadjian,

Hermann de MeerAuthors Info & Claims

e-Energy '12: Proceedings of the 3rd International Conference on Future Energy Systems: Where Energy, Computing and Communication Meet

Article No.: 12, Pages 1 - 10

https://doi.org/10.1145/2208828.2208840

Published: 09 May 2012 Publication History

Abstract

Recently, energy-efficient computing has become a major interest, both in the mobile and IT sectors. With the advent of multi-core processors and their energy-saving mechanisms, there is a necessity to model their power consumption. The existing models for multi-core processors are based on the assumption that the power consumption of multiple cores performing parallel computations is equal to the sum of the power of each of those active cores. In this paper, we analyze this assumption and show that it leads to lack of accuracy when applied to modern processors such as quad-core. Based on our analysis, we present a methodology for estimating the power consumption of multi-core processors. Unlike existing models, we take into account resource sharing and power saving mechanisms. We show that our approach provides an accuracy within a maximum error of 5%.

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Cited By

Niaz HManumachu RLastovetsky A(2025)Accurate and Reliable Energy Measurement and Modelling of Data Transfer Between CPU and GPU in Parallel Applications on Heterogeneous Hybrid PlatformsIEEE Transactions on Computers10.1109/TC.2024.350426274:3(1011-1024)Online publication date: 1-Mar-2025
https://dl.acm.org/doi/10.1109/TC.2024.3504262
Priya AChoudhury RPatni SSharma HMohanty MNarayanam KDevi UMoogi PPatil PParag P(2024)Energy-minimizing workload splitting and frequency selection for guaranteed performance over heterogeneous coresProceedings of the 15th ACM International Conference on Future and Sustainable Energy Systems10.1145/3632775.3661968(308-322)Online publication date: 4-Jun-2024
https://dl.acm.org/doi/10.1145/3632775.3661968
Zhang TDipanzan STahmooresnejad LEzzati-Jivan N(2024)Assessing Predictive Models for Energy Consumption Across Varied Software Environments2024 IEEE International Conference on Big Data (BigData)10.1109/BigData62323.2024.10825500(5233-5242)Online publication date: 15-Dec-2024
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Evaluating and modeling power consumption of multi-core processors

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Published In

cover image ACM Other conferences

e-Energy '12: Proceedings of the 3rd International Conference on Future Energy Systems: Where Energy, Computing and Communication Meet

May 2012

250 pages

ISBN:9781450310550

DOI:10.1145/2208828

General Chairs:
Marco Ajmone Marsan
Politecnico di Torino, Italy, and Institute IMDEA Networks, Spain
,
Suresh Goyal
Alcatel-Lucent Bell Labs
,
Shugong Xu
Huawei Technologies, China
,
Program Chairs:
Antonio Fernández
Anta Institute IMDEA Networks, Spain
,
Milan Prodanovic
Institute IMDEA Energy, Spain
,
Ken Christensen
University of South Florida

Copyright © 2012 ACM.

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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New York, NY, United States

Publication History

Published: 09 May 2012

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e-Energy'12

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IEEE-CS\DATC

e-Energy'12: 3rd International Conference on Energy-Efficient Computing and Networking

May 9 - 11, 2012

Madrid, Spain

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Overall Acceptance Rate 160 of 446 submissions, 36%

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Cited By

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https://dl.acm.org/doi/10.1109/TC.2024.3504262
Priya AChoudhury RPatni SSharma HMohanty MNarayanam KDevi UMoogi PPatil PParag P(2024)Energy-minimizing workload splitting and frequency selection for guaranteed performance over heterogeneous coresProceedings of the 15th ACM International Conference on Future and Sustainable Energy Systems10.1145/3632775.3661968(308-322)Online publication date: 4-Jun-2024
https://dl.acm.org/doi/10.1145/3632775.3661968
Zhang TDipanzan STahmooresnejad LEzzati-Jivan N(2024)Assessing Predictive Models for Energy Consumption Across Varied Software Environments2024 IEEE International Conference on Big Data (BigData)10.1109/BigData62323.2024.10825500(5233-5242)Online publication date: 15-Dec-2024
https://doi.org/10.1109/BigData62323.2024.10825500
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Prihozhy AKarasik O(2023)Influence of shortest path algorithms on energy consumption of multi-core processors«System analysis and applied information science»10.21122/2309-4923-2023-2-4-12(4-12)Online publication date: 4-Oct-2023
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Yi SKim TKim JDutt N(2023)EASYR: Energy-Efficient Adaptive System Reconfiguration for Dynamic Deadlines in Autonomous Driving on Multicore ProcessorsACM Transactions on Embedded Computing Systems10.1145/357050322:3(1-29)Online publication date: 20-Apr-2023
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Li HWen LLiu YShen Y(2022)More than Meets One Core: An Energy-Aware Cost Optimization in Dynamic Multi-Core Processor Server Consolidation for Cloud Data CenterElectronics10.3390/electronics1120337711:20(3377)Online publication date: 19-Oct-2022
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Hou ZShen HZhou XGu JWang YZhao T(2022)Prediction of job characteristics for intelligent resource allocation in HPC systems: a survey and future directionsFrontiers of Computer Science: Selected Publications from Chinese Universities10.1007/s11704-022-0625-816:5Online publication date: 1-Oct-2022
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Rumyantsev ABasmadjian RAstafiev SGolovin A(2022)Three-level modeling of a speed-scaling supercomputerAnnals of Operations Research10.1007/s10479-022-04830-0331:2(649-677)Online publication date: 21-Jun-2022
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