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System Monitoring-Based Holistic Resource Utilization Analysis for Every User of a Large HPC Center

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Algorithms and Architectures for Parallel Processing (ICA3PP 2016)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10049))

Abstract

The problem of effective resource utilization is very challenging nowadays, especially for HPC centers running top-level supercomputing facilities with high energy consumption and significant number of workgroups. The weakness of many system monitoring based approaches to efficiency study is the basic orientation on professionals and analysis of specific jobs with low availability for regular users. The proposed all-round performance analysis approach, covering single application performance, project-level and overall system resource utilization based on system monitoring data that promises to be an effective and low cost technique aimed at all types of HPC center users. Every user of HPC center can access details on any of his executed jobs to better understand application behavior and sequences of job runs including scalability study, helping in turn to perform appropriate optimizations and implement co-design techniques. Taking into consideration all levels (user, project manager, administrator), the approach aids to improve output of HPC centers.

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Author information

Authors and Affiliations

  1. Research Computing Center of Moscow State University, Moscow, Russia

    Dmitry Nikitenko, Konstantin Stefanov, Sergey Zhumatiy, Vadim Voevodin, Alexey Teplov & Pavel Shvets

Authors
  1. Dmitry Nikitenko
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  2. Konstantin Stefanov
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  3. Sergey Zhumatiy
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  4. Vadim Voevodin
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  5. Alexey Teplov
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  6. Pavel Shvets
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Corresponding author

Correspondence to Dmitry Nikitenko .

Editor information

Editors and Affiliations

  1. Carlos III University of Madrid, Getafe, Spain

    Jesus Carretero

  2. Carlos III University of Madrid, Getafe, Spain

    Javier Garcia-Blas

  3. Mathematical Support for Computers, N. I. Lobachevsky State University of Nizhny Novgorod, Nizhniy Novgorod, Russia

    Victor Gergel

  4. Research Computing Center (RCC), Moscow State University, Moscow, Russia

    Vladimir Voevodin

  5. Research Computing Center (RCC), Moscow State University, Moscow, Russia

    Iosif Meyerov

  6. E.U. Politécnica, Universidad de Extremaddura, Cáceres, Spain

    Juan A. Rico-Gallego

  7. Ingenieria de Sistemas Informáticos, Universidad de Extremaddura, Cáceres, Spain

    Juan C. Díaz-Martín

  8. Universitat Politécnica de València, Valencia, Spain

    Pedro Alonso

  9. Distributed and Parallel Systems Group, Institute for Computer Science, Innsbruck, Austria

    Juan Durillo

  10. Carlos III University of Madrid, Getafe, Spain

    José Daniel Garcia Sánchez

  11. UCD School of Computer Science, University College Dublin, Dublin, Ireland

    Alexey L. Lastovetsky

  12. University of Calabria, Rende (CS), Italy

    Fabrizio Marozzo

  13. Information Science and Engineering, Central South University, Changsha, Hunan, China

    Qin Liu

  14. Information Science and Engineering, Central South University, Changsha, Hunan, China

    Zakirul Alam Bhuiyan

  15. Ludwig Maximilian University of Munich, Munich, Germany

    Karl Fürlinger

  16. Informatik 10 - Rechnertechnik, Technische Universität München, Munich, Germany

    Josef Weidendorfer

  17. High Performance Computing Center (HLRS), Stuttgart, Germany

    José Gracia

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Nikitenko, D., Stefanov, K., Zhumatiy, S., Voevodin, V., Teplov, A., Shvets, P. (2016). System Monitoring-Based Holistic Resource Utilization Analysis for Every User of a Large HPC Center. In: Carretero, J., et al. Algorithms and Architectures for Parallel Processing. ICA3PP 2016. Lecture Notes in Computer Science(), vol 10049. Springer, Cham. https://doi.org/10.1007/978-3-319-49956-7_24

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  • DOI: https://doi.org/10.1007/978-3-319-49956-7_24

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-49955-0

  • Online ISBN: 978-3-319-49956-7

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