research-article

A survey on software methods to improve the energy efficiency of parallel computing

Authors:

Bronis R de Supinski,

David Abramson,

Minh Ngoc Dinh,

Elizabeth R JessupAuthors Info & Claims

International Journal of High Performance Computing Applications, Volume 31, Issue 6

Pages 517 - 549

https://doi.org/10.1177/1094342016665471

Published: 01 November 2017 Publication History

Abstract

Energy consumption is one of the top challenges for achieving the next generation of supercomputing. Codesign of hardware and software is critical for improving energy efficiency EE for future large-scale systems. Many architectural power-saving techniques have been developed, and most hardware components are approaching physical limits. Accordingly, parallel computing software, including both applications and systems, should exploit power-saving hardware innovations and manage efficient energy use. In addition, new power-aware parallel computing methods are essential to decrease energy usage further. This article surveys software-based methods that aim to improve EE for parallel computing. It reviews the methods that exploit the characteristics of parallel scientific applications, including load imbalance and mixed precision of floating-point FP calculations, to improve EE. In addition, this article summarizes widely used methods to improve power usage at different granularities, such as the whole system and per application. In particular, it describes the most important techniques to measure and to achieve energy-efficient usage of various parallel computing facilities, including processors, memories, and networks. Overall, this article reviews the state-of-the-art of energy-efficient methods for parallel computing to motivate researchers to achieve optimal parallel computing under a power budget constraint.

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Cabrera AAlmeida FCastellanos-Nieves DOleksiak ABlanco V(2024)Energy efficient power cap configurations through Pareto front analysis and machine learning categorizationCluster Computing10.1007/s10586-023-04151-227:3(3433-3449)Online publication date: 1-Jun-2024
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Cabrera AAlmeida FCastellanos-Nieves DOleksiak ABlanco V(2024)Energy efficient power cap configurations through Pareto front analysis and machine learning categorizationCluster Computing10.1007/s10586-023-04151-227:3(3433-3449)Online publication date: 1-Jun-2024
https://dl.acm.org/doi/10.1007/s10586-023-04151-2
Tabaeiaghdaei SScherrer SKwon JPerrig A(2023)Carbon-Aware Global Routing in Path-Aware NetworksProceedings of the 14th ACM International Conference on Future Energy Systems10.1145/3575813.3595192(144-158)Online publication date: 20-Jun-2023
https://dl.acm.org/doi/10.1145/3575813.3595192
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
https://dl.acm.org/doi/10.1007/s11704-022-0625-8
Galante Gda Rosa Righi R(2022)Adaptive parallel applications: from shared memory architectures to fog computing (2002–2022)Cluster Computing10.1007/s10586-022-03692-225:6(4439-4461)Online publication date: 1-Dec-2022
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Simbeye DMakweba D(2021)Improvement of Energy-Efficiency in High Performance Computing (HPC)International Journal of ICT Research in Africa and the Middle East10.4018/IJICTRAME.29083510:2(30-51)Online publication date: 1-Jul-2021
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D’Agostino DMerelli IAldinucci MCesini D(2021)Hardware and Software Solutions for Energy-Efficient Computing in Scientific ProgrammingScientific Programming10.1155/2021/55142842021Online publication date: 1-Jan-2021
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Warade MSchneider JLee K(2021)FEPAC: A Framework for Evaluating Parallel Algorithms on Cluster ArchitecturesProceedings of the 2021 Australasian Computer Science Week Multiconference10.1145/3437378.3444363(1-10)Online publication date: 1-Feb-2021
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Crespo JSánchez JAlfaro-Cortés FFlich JDuato J(2021)UPR: deadlock-free dynamic network reconfiguration by exploiting channel dependency graph compatibilityThe Journal of Supercomputing10.1007/s11227-021-03791-877:11(12826-12856)Online publication date: 1-Nov-2021
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Ogbebor JImoize AAtayero A(2020)Energy Efficient Design Techniques in Next-Generation Wireless Communication NetworksWireless Communications & Mobile Computing10.1155/2020/72353622020Online publication date: 1-Jan-2020
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Heldens SHijma PWerkhoven BMaassen JBelloum AVan Nieuwpoort R(2020)The Landscape of Exascale ResearchACM Computing Surveys10.1145/337239053:2(1-43)Online publication date: 20-Mar-2020
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