research-article

An adaptive task creation strategy for work-stealing scheduling

Authors:

Pen-Chung YewAuthors Info & Claims

CGO '10: Proceedings of the 8th annual IEEE/ACM international symposium on Code generation and optimization

Pages 266 - 277

https://doi.org/10.1145/1772954.1772992

Published: 24 April 2010 Publication History

Abstract

Work-stealing is a key technique in many multi-threading programming languages to get good load balancing. The current work-stealing techniques have a high implementation overhead in some applications and require a large amount of memory space for data copying to assure correctness. They also cannot handle many application programs that have an unbalanced call tree or have no definitive working sets.

In this paper, we propose a new adaptive task creation strategy, called AdaptiveTC, which supports effective work-stealing schemes and also handles the above mentioned problems effectively. As shown in some experimental results, AdaptiveTC runs 2.71x faster than Cilk and 1.72x faster than Tascell for the 16-queen problem with 8 threads.

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Cited By

Nakashima RYasugi MYoritaka HHiraishi TUmatani S(2021)Work-stealing Strategies That Consider Work Amount and HierarchyJournal of Information Processing10.2197/ipsjjip.29.47829(478-489)Online publication date: 2021
https://doi.org/10.2197/ipsjjip.29.478
Finnerty PKamada TOhta C(2021)A self‐adjusting task granularity mechanism for the Java lifeline‐based global load balancer library on many‐core clustersConcurrency and Computation: Practice and Experience10.1002/cpe.622434:2Online publication date: 18-Feb-2021
https://doi.org/10.1002/cpe.6224
Finnerty PKamada TOhta C(2020)Self-adjusting task granularity for Global load balancer library on clusters of many-core processorsProceedings of the Eleventh International Workshop on Programming Models and Applications for Multicores and Manycores10.1145/3380536.3380539(1-10)Online publication date: 22-Feb-2020
https://dl.acm.org/doi/10.1145/3380536.3380539
Show More Cited By

Index Terms

An adaptive task creation strategy for work-stealing scheduling
1. Software and its engineering
  1. Software notations and tools
    1. Compilers
      1. Runtime environments
    2. General programming languages
      1. Language features
        Concurrent programming structures

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Published In

cover image ACM Conferences

CGO '10: Proceedings of the 8th annual IEEE/ACM international symposium on Code generation and optimization

April 2010

300 pages

ISBN:9781605586359

DOI:10.1145/1772954

General Chairs:
Andreas Moshovos
University of Toronto
,
Greg Steffan
University of Toronto
,
Program Chairs:
Kim Hazelwood
University of Virginia
,
David Kaeli
Northeastern University

Copyright © 2010 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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Published: 24 April 2010

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CGO '10: 8th Annual IEEE/ ACM International Symposium on Code Generation and Optimization

April 24 - 28, 2010

Ontario, Toronto, Canada

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Overall Acceptance Rate 312 of 1,061 submissions, 29%

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Cited By

Nakashima RYasugi MYoritaka HHiraishi TUmatani S(2021)Work-stealing Strategies That Consider Work Amount and HierarchyJournal of Information Processing10.2197/ipsjjip.29.47829(478-489)Online publication date: 2021
https://doi.org/10.2197/ipsjjip.29.478
Finnerty PKamada TOhta C(2021)A self‐adjusting task granularity mechanism for the Java lifeline‐based global load balancer library on many‐core clustersConcurrency and Computation: Practice and Experience10.1002/cpe.622434:2Online publication date: 18-Feb-2021
https://doi.org/10.1002/cpe.6224
Finnerty PKamada TOhta C(2020)Self-adjusting task granularity for Global load balancer library on clusters of many-core processorsProceedings of the Eleventh International Workshop on Programming Models and Applications for Multicores and Manycores10.1145/3380536.3380539(1-10)Online publication date: 22-Feb-2020
https://dl.acm.org/doi/10.1145/3380536.3380539
Wang MTa TCheng LBatten C(2020)Efficiently Supporting Dynamic Task Parallelism on Heterogeneous Cache-Coherent Systems2020 ACM/IEEE 47th Annual International Symposium on Computer Architecture (ISCA)10.1109/ISCA45697.2020.00025(173-186)Online publication date: May-2020
https://doi.org/10.1109/ISCA45697.2020.00025
Nakashima RYoritaka HYasugi MHiraishi TUmatani S(2019)Extending a Work-Stealing Framework with Priorities and Weights2019 IEEE/ACM 9th Workshop on Irregular Applications: Architectures and Algorithms (IA3)10.1109/IA349570.2019.00008(9-16)Online publication date: Nov-2019
https://doi.org/10.1109/IA349570.2019.00008
Yoritaka HMatsui KYasugi MHiraishi TUmatani S(2019)Probabilistic guardsParallel Computing10.1016/j.parco.2018.06.00382:C(19-36)Online publication date: 1-Feb-2019
https://dl.acm.org/doi/10.1016/j.parco.2018.06.003
Yang JHe Q(2018)Scheduling Parallel Computations by Work StealingInternational Journal of Parallel Programming10.1007/s10766-016-0484-846:2(173-197)Online publication date: 1-Apr-2018
https://dl.acm.org/doi/10.1007/s10766-016-0484-8
Farooqui NRoy IChen YTalwar VBarik RLewis BShpeisman TSchwan K(2018)Accelerating Data Analytics on Integrated GPU Platforms via Runtime SpecializationInternational Journal of Parallel Programming10.1007/s10766-016-0482-x46:2(336-375)Online publication date: 1-Apr-2018
https://dl.acm.org/doi/10.1007/s10766-016-0482-x
Pinto GCanino ACastor FXu GLiu YRosu GDi Penta MNguyen T(2017)Understanding and overcoming parallelism bottlenecks in ForkJoin applicationsProceedings of the 32nd IEEE/ACM International Conference on Automated Software Engineering10.5555/3155562.3155657(765-775)Online publication date: 30-Oct-2017
https://dl.acm.org/doi/10.5555/3155562.3155657
Pinto GCanino ACastor FXu GLiu Y(2017)Understanding and overcoming parallelism bottlenecks in ForkJoin applications2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE)10.1109/ASE.2017.8115687(765-775)Online publication date: Oct-2017
https://doi.org/10.1109/ASE.2017.8115687
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