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An Experimental Study of Data Transfer Strategies for Execution of Scientific Workflows

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Parallel Computing Technologies (PaCT 2019)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11657))

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Abstract

The paper studies the impact of data transfer strategies on the execution of scientific workflows. Five strategies are described, which define when and in what order data transfers are performed during the workflow execution. The strategies are experimentally evaluated by means of simulation using a realistic network model. It is demonstrated that the execution time of data-intensive workflows significantly depends on the used strategy. In particular, Eager and Lazy strategies, often used in theory and practice of workflow scheduling, demonstrate the poor results in most cases. The alternative strategies provide up to 36% makespan improvement by overlapping communications and computations, prioritizing data transfers and reducing network contention.

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Notes

  1. 1.

    https://github.com/alexmnazarenko/pysimgrid.

  2. 2.

    https://github.com/osukhoroslov/pysimgrid-experiments/tree/master/pact2019.

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Acknowledgments

This work is supported by the Russian Science Foundation (project 16-11-10352).

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Authors and Affiliations

  1. Institute for Information Transmission Problems of the Russian Academy of Sciences, Moscow, Russia

    Oleg Sukhoroslov

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  1. Oleg Sukhoroslov
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Correspondence to Oleg Sukhoroslov .

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Editors and Affiliations

  1. Institute of Computational Mathematics and Mathematical Geophysics SB RAS, Novosibirsk State University, Novosibirsk State Technical University, Novosibirsk, Russia

    Victor Malyshkin

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Sukhoroslov, O. (2019). An Experimental Study of Data Transfer Strategies for Execution of Scientific Workflows. In: Malyshkin, V. (eds) Parallel Computing Technologies. PaCT 2019. Lecture Notes in Computer Science(), vol 11657. Springer, Cham. https://doi.org/10.1007/978-3-030-25636-4_6

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  • DOI: https://doi.org/10.1007/978-3-030-25636-4_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-25635-7

  • Online ISBN: 978-3-030-25636-4

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