research-article

Prediction models for multi-dimensional power-performance optimization on many cores

Authors:

Matthew Curtis-Maury,

Filip Blagojevic,

Dimitrios S. Nikolopoulos,

Bronis R. de Supinski,

Martin SchulzAuthors Info & Claims

PACT '08: Proceedings of the 17th international conference on Parallel architectures and compilation techniques

Pages 250 - 259

https://doi.org/10.1145/1454115.1454151

Published: 25 October 2008 Publication History

Abstract

Power has become a primary concern for HPC systems. Dynamic voltage and frequency scaling (DVFS) and dynamic concurrency throttling (DCT) are two software tools (or knobs) for reducing the dynamic power consumption of HPC systems. To date, few works have considered the synergistic integration of DVFS and DCT in performance-constrained systems, and, to the best of our knowledge, no prior research has developed application-aware simultaneous DVFS and DCT controllers in real systems and parallel programming frameworks. We present a multi-dimensional, online performance predictor, which we deploy to address the problem of simultaneous runtime optimization of DVFS and DCT on multi-core systems. We present results from an implementation of the predictor in a runtime library linked to the Intel OpenMP environment and running on an actual dual-processor quad-core system. We show that our predictor derives near-optimal settings of the power-aware program adaptation knobs that we consider. Our overall framework achieves significant reductions in energy (19% mean) and ED² (40% mean), through simultaneous power savings (6% mean) and performance improvements (14% mean). We also find that our framework outperforms earlier solutions that adapt only DVFS or DCT, as well as one that sequentially applies DCT then DVFS. Further, our results indicate that prediction-based schemes for runtime adaptation compare favorably and typically improve upon heuristic search-based approaches in both performance and energy savings.

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Cited By

Buduleci CGellert AFlorea ABrad R(2024)Architectural and Technological Approaches for Efficient Energy Management in Multicore ProcessorsComputers10.3390/computers1304008413:4(84)Online publication date: 22-Mar-2024
https://doi.org/10.3390/computers13040084
Alnori ADjemame KAlsenani Y(2024)Agnostic Energy Consumption Models for Heterogeneous GPUs in Cloud ComputingApplied Sciences10.3390/app1406238514:6(2385)Online publication date: 12-Mar-2024
https://doi.org/10.3390/app14062385
Dutta AChoi JJannesari A(2023)Power Constrained Autotuning using Graph Neural Networks2023 IEEE International Parallel and Distributed Processing Symposium (IPDPS)10.1109/IPDPS54959.2023.00060(535-545)Online publication date: May-2023
https://doi.org/10.1109/IPDPS54959.2023.00060
Show More Cited By

Index Terms

Prediction models for multi-dimensional power-performance optimization on many cores
1. Computer systems organization
  1. Architectures
    1. Parallel architectures
2. Software and its engineering
  1. Software creation and management
    1. Software development process management
      1. Software development methods
  2. Software organization and properties
    1. Contextual software domains
      1. Operating systems
        Process management
        Concurrency control

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Published In

cover image ACM Conferences

PACT '08: Proceedings of the 17th international conference on Parallel architectures and compilation techniques

October 2008

328 pages

ISBN:9781605582825

DOI:10.1145/1454115

General Chair:
Andreas Moshovos
University of Toronto, Canada
,
Program Chairs:
David Tarditi
Microsoft, USA
,
Kunle Olukotun
Stanford University, USA

Copyright © 2008 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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Publication History

Published: 25 October 2008

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dynamic concurrency throttling

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PACT '08

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PACT '08: International Conference on Parallel Architectures and Compilation Techniques

October 25 - 29, 2008

Ontario, Toronto, Canada

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Overall Acceptance Rate 121 of 471 submissions, 26%

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Cited By

Buduleci CGellert AFlorea ABrad R(2024)Architectural and Technological Approaches for Efficient Energy Management in Multicore ProcessorsComputers10.3390/computers1304008413:4(84)Online publication date: 22-Mar-2024
https://doi.org/10.3390/computers13040084
Alnori ADjemame KAlsenani Y(2024)Agnostic Energy Consumption Models for Heterogeneous GPUs in Cloud ComputingApplied Sciences10.3390/app1406238514:6(2385)Online publication date: 12-Mar-2024
https://doi.org/10.3390/app14062385
Dutta AChoi JJannesari A(2023)Power Constrained Autotuning using Graph Neural Networks2023 IEEE International Parallel and Distributed Processing Symposium (IPDPS)10.1109/IPDPS54959.2023.00060(535-545)Online publication date: May-2023
https://doi.org/10.1109/IPDPS54959.2023.00060
Cabrera AAlmeida FCastellanos-Nieves DOleksiak ABlanco V(2023)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: 10-Oct-2023
https://doi.org/10.1007/s10586-023-04151-2
Liu JNicolae BLi D(2022)Lobster: Load Balance-Aware I/O for Distributed DNN TrainingProceedings of the 51st International Conference on Parallel Processing10.1145/3545008.3545090(1-11)Online publication date: 29-Aug-2022
https://dl.acm.org/doi/10.1145/3545008.3545090
Cho YPark JNegele FJo CGross TEgger BLee JAgrawal KSpear M(2022)DopiaProceedings of the 27th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming10.1145/3503221.3508421(32-45)Online publication date: 2-Apr-2022
https://dl.acm.org/doi/10.1145/3503221.3508421
Wu NXie Y(2022)A Survey of Machine Learning for Computer Architecture and SystemsACM Computing Surveys10.1145/349452355:3(1-39)Online publication date: 3-Feb-2022
https://dl.acm.org/doi/10.1145/3494523
Navarro Muñoz AF. Lorenzon AAyguadé Parra EBeltran Querol V(2021)Combining Dynamic Concurrency Throttling with Voltage and Frequency Scaling on Task-based Programming ModelsProceedings of the 50th International Conference on Parallel Processing10.1145/3472456.3472471(1-11)Online publication date: 9-Aug-2021
https://dl.acm.org/doi/10.1145/3472456.3472471
Knorst TJordan MLorenzon ARutzig MBeck A(2021)ETCF – Energy-Aware CPU Thread Throttling and Workload Balancing Framework for CPU-FPGA Collaborative Environments2021 XI Brazilian Symposium on Computing Systems Engineering (SBESC)10.1109/SBESC53686.2021.9628345(1-8)Online publication date: 22-Nov-2021
https://doi.org/10.1109/SBESC53686.2021.9628345
Wu KPeng IRen JLi DSarkar VKim H(2020)RibbonProceedings of the ACM International Conference on Parallel Architectures and Compilation Techniques10.1145/3410463.3414625(427-439)Online publication date: 30-Sep-2020
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