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Generalized Approach to Scalability Analysis of Parallel Applications

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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

This article describes an approach to scalability analysis of parallel applications, which is a major part of the algorithm description used in AlgoWiki, the Open Encyclopedia of Parallel Algorithmic Features. The proposed approach is based on the suggested definition of generalized scalability of a parallel application. This study uses joined and structured data on an application’s execution and supercomputing co-design technologies. Parallel application properties are studied by analyzing data collected from all available sources of its dynamic characteristics and information about the hardware and software platforms corresponding with the features of an algorithm and its implementation. This allows reasonable conclusion to be drawn regarding potential reasons of changes in the execution quality for any parallel applications and to compare the scalability of various programs.

The results were obtained in Moscow State University with the financial support of the Russian Science Foundation, agreement N 14-11-00190, and the Russian Foundation for Basic Research, grant N 16-07-01003 (Sect. 4), and grant N 16-07-00972 (Sect. 5).

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Author information

Authors and Affiliations

  1. Moscow State University, Moscow, Russia

    Alexander Antonov & Alexey Teplov

Authors
  1. Alexander Antonov
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  2. Alexey Teplov
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Corresponding author

Correspondence to Alexander Antonov .

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. DĂ­az-MartĂ­n

  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 FĂĽrlinger

  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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Antonov, A., Teplov, A. (2016). Generalized Approach to Scalability Analysis of Parallel Applications. 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_23

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  • DOI: https://doi.org/10.1007/978-3-319-49956-7_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-49955-0

  • Online ISBN: 978-3-319-49956-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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