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Understanding Resource Selection Requirements for Computationally Intensive Tasks on Heterogeneous Computing Infrastructure

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Economics of Grids, Clouds, Systems, and Services (GECON 2016)

Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 10382))

Abstract

Scientists and researchers face challenges in efficiently configuring their scientific computing tasks so that they can be run in a timely and cost-effective manner. While the increasing availability of different types of computing platforms provides many opportunities to users, it can further complicate the job configuration process. In this paper we present work-in-progress to develop an approach to assist with identifying the most suitable computing platform and configuration for a computational task based on a user’s financial and temporal constraints, using a decision support system. We use Nekkloud, a web-based tool for running computations via the Nektar++ spectral/hp element framework, as an exemplar and build a table that scores a range of properties for four example computing platforms to help select the most suitable platform for a job. We demonstrate our approach using three sample task scenarios.

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Acknowledgements

The authors wish to acknowledge the Nektar++ team for their advice, particularly in relation to the scenarios and solvers. JC and JD acknowledge Imperial College London for funding the Pathways to Impact project “Simplifying High Performance Computing Access for the Nektar++ Framework” under Imperial’s EPSRC Impact Acceleration Account. JC and JD also acknowledge EPSRC for their support of the completed libhpc (EP/I030239/1) and libhpc Stage II (EP/K038788/1) projects where Nekkloud and TemPSS were initially developed.

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Authors and Affiliations

  1. Department of Computing, Imperial College London, London, UK

    Jeremy Cohen & John Darlington

  2. Novancia Business School Paris, Paris, France

    Thierry Rayna

Authors
  1. Jeremy Cohen
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  2. Thierry Rayna
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  3. John Darlington
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Corresponding author

Correspondence to Jeremy Cohen .

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Editors and Affiliations

  1. Department of Computer Science, University of Zaragoza, Zaragoza, Spain

    José Ángel Bañares

  2. Harokopio University, Tavros, Greece

    Konstantinos Tserpes

  3. Seoul National University, Seoul, Korea (Republic of)

    Jörn Altmann

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Cohen, J., Rayna, T., Darlington, J. (2017). Understanding Resource Selection Requirements for Computationally Intensive Tasks on Heterogeneous Computing Infrastructure. In: Bañares, J., Tserpes, K., Altmann, J. (eds) Economics of Grids, Clouds, Systems, and Services. GECON 2016. Lecture Notes in Computer Science(), vol 10382. Springer, Cham. https://doi.org/10.1007/978-3-319-61920-0_18

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  • DOI: https://doi.org/10.1007/978-3-319-61920-0_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-61919-4

  • Online ISBN: 978-3-319-61920-0

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