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DWS: Demand-aware Work-Stealing in Multi-programmed Multi-core Architectures

Authors:

Minyi GuoAuthors Info & Claims

PMAM'14: Proceedings of Programming Models and Applications on Multicores and Manycores

Pages 131 - 139

https://doi.org/10.1145/2578948.2560696

Published: 07 February 2014 Publication History

Abstract

Traditional work-stealing schedulers perform poorly in multi-programmed multi-core architectures, because all the programs tend to use all the cores and thus incur serious core contention. To relieve this problem, this paper proposes a Demand-aware Work-Stealing (DWS) task scheduler, with which a work-stealing program uses cores according to its realtime demand on the cores. If multiple programs scheduled by DWS run in a multi-core architecture concurrently, the cores are first evenly allocated to the co-running programs. At runtime, if a program cannot fully utilize its cores, it releases some of its allocated cores. Otherwise, if a program demands more cores, it tries to use the free cores released by its co-running programs. Experimental results show that DWS can achieve up to 32.3% performance gain for co-running programs compared to traditional work-stealing schedulers with the ABP yielding mechanism.

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Cited By

Parikh HDeodhar VGavrilovska APande S(2021)Distributed Work Stealing at Scale via Matchmaking2021 IEEE International Conference on Cluster Computing (CLUSTER)10.1109/Cluster48925.2021.00040(250-260)Online publication date: Sep-2021
https://doi.org/10.1109/Cluster48925.2021.00040
Zhang JWu CYang DChen YMeng XXu LGuo M(2018)HSCSFrontiers of Computer Science: Selected Publications from Chinese Universities10.1007/s11704-017-6349-512:6(1090-1104)Online publication date: 1-Dec-2018
https://dl.acm.org/doi/10.1007/s11704-017-6349-5
Zhang JGuo MWu CChen Y(2017)Toward multi-programmed workloads with different memory footprints: a self-adaptive last level cache scheduling schemeScience China Information Sciences10.1007/s11432-016-0408-161:1Online publication date: 14-Jul-2017
https://doi.org/10.1007/s11432-016-0408-1

Index Terms

DWS: Demand-aware Work-Stealing in Multi-programmed Multi-core Architectures
1. Software and its engineering
  1. Software notations and tools
    1. Compilers

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Published In

cover image ACM Conferences

PMAM'14: Proceedings of Programming Models and Applications on Multicores and Manycores

February 2014

156 pages

ISBN:9781450326575

DOI:10.1145/2578948

Conference Chairs:
Pavan Balaji
Argonne National Laboratory, USA
,
Minyi Guo
Shanghai Jiao Tong, University, China
,
Zhiyi Huang
University of Otago, New Zealand

Copyright © 2014 ACM.

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Published: 07 February 2014

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February 15 - 19, 2014

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Overall Acceptance Rate 53 of 97 submissions, 55%

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Cited By

Parikh HDeodhar VGavrilovska APande S(2021)Distributed Work Stealing at Scale via Matchmaking2021 IEEE International Conference on Cluster Computing (CLUSTER)10.1109/Cluster48925.2021.00040(250-260)Online publication date: Sep-2021
https://doi.org/10.1109/Cluster48925.2021.00040
Zhang JWu CYang DChen YMeng XXu LGuo M(2018)HSCSFrontiers of Computer Science: Selected Publications from Chinese Universities10.1007/s11704-017-6349-512:6(1090-1104)Online publication date: 1-Dec-2018
https://dl.acm.org/doi/10.1007/s11704-017-6349-5
Zhang JGuo MWu CChen Y(2017)Toward multi-programmed workloads with different memory footprints: a self-adaptive last level cache scheduling schemeScience China Information Sciences10.1007/s11432-016-0408-161:1Online publication date: 14-Jul-2017
https://doi.org/10.1007/s11432-016-0408-1

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