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Analyzing the Performance of Allocation Strategies Based on Space-Filling Curves

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Job Scheduling Strategies for Parallel Processing (JSSPP 2015, JSSPP 2016)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10353))

Abstract

Future exascale supercomputers will be composed of thousands of nodes. In those massive systems, the search for physically close nodes will become essential to deliver an optimal environment to execute parallel applications. Schedulers manage those resources, shared by many users and jobs, searching for partitions in which jobs will run. Significant effort has been devoted to develop allocation strategies that maximize system utilization, while providing partitions that are adequate for the communication demands of applications. In this paper we evaluate a class of strategies based on space-filling curves (SFCs) that search for partitions in which nodes are physically close, compared to other alternatives that relax this requirement (e.g. non-contiguous), or make it even more strict (e.g. contiguous). Several metrics are used to assess the quality of an allocation strategy, some based on system utilization, some others measuring the quality of the resulting partitions. Contiguous allocators suffer from severe degradation in terms of system utilization, while non-contiguous allocators provide inadequate partitions. Somewhere in the middle, SFC allocators offer good system utilization while using quite compact partitions. The final metric to decide which allocator is the best depend on the severity of the slowdown suffered by applications when running in non-optimal partitions.

J.A. Pascual is currently with the APT group in The University of Manchester.

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Acknowledgments

This work has been partially supported by the Research Groups 2013–2018 (IT-609-13) program (Basque Government), TIN2013-41272P (Ministry of Science and Technology). Jose A. Lozano is also supported by BERC program 2014–2017 (Basque government) and Severo Ochoa Program SEV-2013-0323 (Spanish Ministry of Economy and Competitiveness). Jose Miguel-Alonso is member of the HiPEAC European Network.

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Authors and Affiliations

  1. Intelligent Systems Group (ISG), University of the Basque Country UPV/EHU, Donostia-San Sebastian, Spain

    Jose A. Pascual, Jose A. Lozano & Jose Miguel-Alonso

  2. Basque Center for Applied Mathematics (BCAM), Bilbao, Spain

    Jose A. Lozano

Authors
  1. Jose A. Pascual
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  2. Jose A. Lozano
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  3. Jose Miguel-Alonso
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Corresponding author

Correspondence to Jose A. Pascual .

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Editors and Affiliations

  1. Google, Seattle, USA

    Narayan Desai

  2. Google, Mountain View, USA

    Walfredo Cirne

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Pascual, J.A., Lozano, J.A., Miguel-Alonso, J. (2017). Analyzing the Performance of Allocation Strategies Based on Space-Filling Curves. In: Desai, N., Cirne, W. (eds) Job Scheduling Strategies for Parallel Processing. JSSPP JSSPP 2015 2016. Lecture Notes in Computer Science(), vol 10353. Springer, Cham. https://doi.org/10.1007/978-3-319-61756-5_13

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  • DOI: https://doi.org/10.1007/978-3-319-61756-5_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-61755-8

  • Online ISBN: 978-3-319-61756-5

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