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European Conference on Parallel Processing

Euro-Par 2011: Euro-Par 2011: Parallel Processing Workshops pp 146–155Cite as

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Scalable Automatic Performance Analysis on IBM BlueGene/P Systems

Scalable Automatic Performance Analysis on IBM BlueGene/P Systems

  • Yury Oleynik30 &
  • Michael Gerndt30 
  • Conference paper
  • 1068 Accesses

Part of the Lecture Notes in Computer Science book series (LNTCS,volume 7156)

Abstract

Nowadays scientific endeavor becomes more and more hungry for computational power of the state-of-the-art supercomputers. However the current trend in the performance increase comes along with tremendous increase in power consumption. One of the approaches allowing to overcome the issue is tight coupling of the simplified low-frequency cores into massively parallel system, such as IBM BlueGene/P (BG/P) combining hundreds of thousands cores. In addition to revolutionary system design this scale requires new approaches in application development and performance tuning. In this paper we present a new scalable BG/P tailored design for an automatic performance analysis tool - Periscope. In this work we have elicited and implemented a new design for porting Periscope to BG/P which features optimal system utilization, minimal monitoring intrusion and high scalability.

Keywords

  • Performance analysis
  • Scalability of Applications & Tools
  • Supercomputers

This work is partially funded by BMBF under the ISAR project, grant 01IH08005A and the SILC project, grant 6.

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References

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Author information

Authors and Affiliations

  1. Fakultät für Informatik I10, Technische Universität München, Boltzmannstr. 3, 85748, Garching, Germany

    Yury Oleynik & Michael Gerndt

Authors
  1. Yury Oleynik
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  2. Michael Gerndt
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Editor information

Editors and Affiliations

  1. Scilytics, Koellnerhofgasse 3/15A, 1010, Vienna, Austria

    Michael Alexander

  2. ICAR-CNR, Via P. Castellino, 111, 80131, Napoli, Italy

    Pasqua D’Ambra

  3. University of Amsterdam, 1090, Amsterdam, Netherlands

    Adam Belloum

  4. Innovative Computing Laboratory, The University of Tennessee, US

    George Bosilca

  5. Department of Experimental Medicine and Clinic, University Magna Græcia, 88100, Catanzaro, Italy

    Mario Cannataro

  6. Computer Science Department, University of Pisa, Italy

    Marco Danelutto

  7. Second University of Naples, Italy

    Beniamino Di Martino

  8. TUMünchen,, Boltzmannstr. 3, ,, 85748, Garching, Germany

    Michael Gerndt

  9. Equipe Runtime, INRIA Bordeaux Sud-Ouest, 33405, Talence Cedex, France

    Emmanuel Jeannot & Raymond Namyst & 

  10. Equipe HIEPACS, INRIA Bordeaux Sud-Ouest, 33405, Talence Cedex, France

    Jean Roman

  11. Computer Science and Mathematics Division, Oak Ridge National Laboratory, 37831-6164, Oak Ridge, TN, USA

    Stephen L. Scott

  12. Department of Scientific Computing, University of Vienna, Nordbergstr. 15/3C, 1090, Vienna, Austria

    Jesper Larsson Traff

  13. Computer Science and Mathematics Division, Oak Ridge National Laboratory, 37831, Oak Ridge, TN, USA

    Geoffroy Vallée

  14. Technische Universität München, Germany

    Josef Weidendorfer

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© 2012 Springer-Verlag Berlin Heidelberg

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Cite this paper

Oleynik, Y., Gerndt, M. (2012). Scalable Automatic Performance Analysis on IBM BlueGene/P Systems. In: Alexander, M., et al. Euro-Par 2011: Parallel Processing Workshops. Euro-Par 2011. Lecture Notes in Computer Science, vol 7156. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29740-3_18

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  • DOI: https://doi.org/10.1007/978-3-642-29740-3_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29739-7

  • Online ISBN: 978-3-642-29740-3

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