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Review: Energy-aware performance analysis methodologies for HPC architectures-An exploratory study

Author:

Shajulin BenedictAuthors Info & Claims

Journal of Network and Computer Applications, Volume 35, Issue 6

Pages 1709 - 1719

https://doi.org/10.1016/j.jnca.2012.08.003

Published: 01 November 2012 Publication History

Abstract

Performance analysis is a crucial step in HPC architectures including clouds. Traditional performance analysis methodologies that were proposed, implemented, and enacted are functional with the objective of identifying bottlenecks or issues related to memory, programming languages, hardware, and virtualization aspects. However, the need for energy efficient architectures in highly scalable computing environments, such as, Grid or Cloud, has widened the research thrust on developing performance analysis methodologies that analyze the energy inefficiency of HPC applications or their associated hardware. This paper surveys the performance analysis methodologies that investigates into the available energy monitoring and energy awareness mechanisms for HPC architectures. In addition, the paper validates the existing tools in terms of overhead, portability, and user-friendly parameters by conducting experiments at HPCCLoud Research Laboratory at our premise. This research work will promote HPC application developers to select an apt monitoring mechanism and HPC tool developers to augment required energy monitoring mechanisms which fit well with their basic monitoring infrastructures.

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Cited By

Hilgers TLiem R(2024)Comparability and Reproducibility in HPC Applications' Energy Consumption CharacterizationProceedings of the 15th ACM International Conference on Future and Sustainable Energy Systems10.1145/3632775.3662162(560-568)Online publication date: 4-Jun-2024
https://dl.acm.org/doi/10.1145/3632775.3662162
Zhang ABhalachandra SDeng SZhao Z(2023)NPAT - A Power Analysis Tool at NERSCProceedings of the SC '23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis10.1145/3624062.3624149(712-719)Online publication date: 12-Nov-2023
https://dl.acm.org/doi/10.1145/3624062.3624149
Czarnul PProficz JKrzywaniak A(2019)Energy-Aware High-Performance ComputingScientific Programming10.1155/2019/83487912019Online publication date: 1-Jan-2019
https://dl.acm.org/doi/10.1155/2019/8348791
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Review: Energy-aware performance analysis methodologies for HPC architectures-An exploratory study

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Published In

cover image Journal of Network and Computer Applications

Journal of Network and Computer Applications Volume 35, Issue 6

November, 2012

449 pages

ISSN:1084-8045

Issue’s Table of Contents

Copyright © Elsevier Ltd © 2012.

Publisher

Academic Press Ltd.

United Kingdom

Publication History

Published: 01 November 2012

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Cited By

Hilgers TLiem R(2024)Comparability and Reproducibility in HPC Applications' Energy Consumption CharacterizationProceedings of the 15th ACM International Conference on Future and Sustainable Energy Systems10.1145/3632775.3662162(560-568)Online publication date: 4-Jun-2024
https://dl.acm.org/doi/10.1145/3632775.3662162
Zhang ABhalachandra SDeng SZhao Z(2023)NPAT - A Power Analysis Tool at NERSCProceedings of the SC '23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis10.1145/3624062.3624149(712-719)Online publication date: 12-Nov-2023
https://dl.acm.org/doi/10.1145/3624062.3624149
Czarnul PProficz JKrzywaniak A(2019)Energy-Aware High-Performance ComputingScientific Programming10.1155/2019/83487912019Online publication date: 1-Jan-2019
https://dl.acm.org/doi/10.1155/2019/8348791
Beneventi FBartolini ACavazzoni CBenini L(2017)Continuous learning of HPC infrastructure models using big data analytics and in-memory processing toolsProceedings of the Conference on Design, Automation & Test in Europe10.5555/3130379.3130626(1038-1043)Online publication date: 27-Mar-2017
https://dl.acm.org/doi/10.5555/3130379.3130626
(2017)Energy analysis of code regions of HPC applications using EnergyAnalyzer toolInternational Journal of Computational Science and Engineering10.1504/IJCSE.2017.1000502414:3(267-278)Online publication date: 1-Jan-2017
https://dl.acm.org/doi/10.1504/IJCSE.2017.10005024
O’brien KPietri IReddy RLastovetsky ASakellariou R(2017)A Survey of Power and Energy Predictive Models in HPC Systems and ApplicationsACM Computing Surveys10.1145/307881150:3(1-38)Online publication date: 29-Jun-2017
https://dl.acm.org/doi/10.1145/3078811
Bareford MJohnson NWeiland M(2016)On the trade-offs between energy to solution and runtime for real-world CFD test-casesProceedings of the Exascale Applications and Software Conference 201610.1145/2938615.2938619(1-8)Online publication date: 26-Apr-2016
https://dl.acm.org/doi/10.1145/2938615.2938619
Almeida FArteaga JBlanco VCabrera A(2015)Energy Measurement Tools for Ultrascale ComputingSupercomputing Frontiers and Innovations: an International Journal10.14529/jsfi1502042:2(64-76)Online publication date: 6-Apr-2015
https://dl.acm.org/doi/10.14529/jsfi150204
Zhang ZSu SLin YCheng XShuang KXu P(2015)Adaptive multi-objective artificial immune system based virtual network embeddingJournal of Network and Computer Applications10.1016/j.jnca.2015.03.00753:C(140-155)Online publication date: 1-Jul-2015
https://dl.acm.org/doi/10.1016/j.jnca.2015.03.007
Lent R(2015)Grid Scheduling with Makespan and Energy-Based GoalsJournal of Grid Computing10.1007/s10723-015-9349-413:4(527-546)Online publication date: 1-Dec-2015
https://dl.acm.org/doi/10.1007/s10723-015-9349-4
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