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SAOU: safe adaptive overclocking and undervolting for energy-efficient GPU computing

Authors:

Devashree Tripathy,

Zizhong ChenAuthors Info & Claims

ISLPED '20: Proceedings of the ACM/IEEE International Symposium on Low Power Electronics and Design

Pages 205 - 210

https://doi.org/10.1145/3370748.3406553

Published: 10 August 2020 Publication History

Abstract

The current trend of ever-increasing performance in scientific applications comes with tremendous growth in energy consumption. In this paper, we present a framework for GPU applications, which reduces energy consumption in GPUs through Safe Overclocking and Undervolting (SAOU) without sacrificing performance. The idea is to increase the frequency beyond the safe frequency f_{sa f eMax} and undervolt below V_{sa f eMin} to get maximum energy saving. Since such overclocking and undervolting may give rise to faults, we employ an enhanced checkpoint-recovery technique to cover the possible errors. Empirically, we explore different errors and derive a fault model that can set the undervolting and overclocking level for maximum energy saving. We target cuBLAS Matrix Multiplication (cuBLAS-MM) kernel for error correction using the checkpoint and recovery (CR) technique as an example of scientific applications. In case of cuBLAS, SAOU achieves up to 22% energy reduction through undervolting and overclocking without sacrificing the performance.

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Information

Published In

cover image ACM Conferences

ISLPED '20: Proceedings of the ACM/IEEE International Symposium on Low Power Electronics and Design

August 2020

263 pages

ISBN:9781450370530

DOI:10.1145/3370748

Conference Chairs:
David Atienza Alonso
EPFL
,
Qinru Qiu
Syracuse Univ.
,
Program Chairs:
Sherief Reda
Brown Univ.
,
Yiran Chen
Duke Univ.

Copyright © 2020 Owner/Author.

This work is licensed under a Creative Commons Attribution International 4.0 License.

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New York, NY, United States

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Published: 10 August 2020

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ISLPED '20

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ISLPED '20: ACM/IEEE International Symposium on Low Power Electronics and Design

August 10 - 12, 2020

Massachusetts, Boston

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Overall Acceptance Rate 398 of 1,159 submissions, 34%

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https://doi.org/10.3390/su16041519
Wang YHao MHe HZhang WTang QSun XWang Z(2024)DRLCAP: Runtime GPU Frequency Capping With Deep Reinforcement LearningIEEE Transactions on Sustainable Computing10.1109/TSUSC.2024.33626979:5(712-726)Online publication date: Sep-2024
https://doi.org/10.1109/TSUSC.2024.3362697
Chen JLiang XZhao KSabzi HBhuyan LChen ZDehnavi MKulkarni MKrishnamoorthy S(2023)Improving Energy Saving of One-Sided Matrix Decompositions on CPU-GPU Heterogeneous SystemsProceedings of the 28th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming10.1145/3572848.3577496(274-287)Online publication date: 25-Feb-2023
https://dl.acm.org/doi/10.1145/3572848.3577496
Yari-Karin SSiyadatzadeh RAnsari MEjlali A(2023)Passive Primary/Backup-Based Scheduling for Simultaneous Power and Reliability Management on Heterogeneous Embedded SystemsIEEE Transactions on Sustainable Computing10.1109/TSUSC.2022.31866568:1(82-93)Online publication date: 1-Jan-2023
https://doi.org/10.1109/TSUSC.2022.3186656
Ou ZChen JSun YXu TJiang GTan ZQi X(2023)AOA: Adaptive Overclocking Algorithm on CPU-GPU Heterogeneous PlatformsAlgorithms and Architectures for Parallel Processing10.1007/978-3-031-22677-9_14(253-272)Online publication date: 11-Jan-2023
https://doi.org/10.1007/978-3-031-22677-9_14
Ranganath KSuetterlein JManzano JSong SWong Dde Supinski BHall MGamblin T(2021)MAPAProceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis10.1145/3458817.3480853(1-14)Online publication date: 14-Nov-2021
https://dl.acm.org/doi/10.1145/3458817.3480853
Tripathy DAbdolrashidi ABhuyan LZhou LWong D(2021)PAVERACM Transactions on Architecture and Code Optimization10.1145/345116418:3(1-26)Online publication date: 8-Jun-2021
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Zamani HTripathy DJahanshahi AWong D(2021)ICAP: Designing Inrush Current Aware Power Gating Switch for GPGPU2021 IEEE International Conference on Networking, Architecture and Storage (NAS)10.1109/NAS51552.2021.9605434(1-8)Online publication date: Oct-2021
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Tripathy DAbdolrashidi AFan QWong DSatpathy M(2021)LocalityGuru: A PTX Analyzer for Extracting Thread Block-level Locality in GPGPUs2021 IEEE International Conference on Networking, Architecture and Storage (NAS)10.1109/NAS51552.2021.9605411(1-8)Online publication date: Oct-2021
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