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Determine energy-saving potential in wait-states of large-scale parallel programs

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  • Published: 31 August 2011
  • Volume 27, pages 255–263, (2012)
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Computer Science - Research and Development
Determine energy-saving potential in wait-states of large-scale parallel programs
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  • Michael Knobloch1,
  • Bernd Mohr1 &
  • Timo Minartz2 
  • 781 Accesses

  • 13 Citations

  • Explore all metrics

Abstract

Energy consumption is one of the major topics in high performance computing (HPC) in the last years. However, little effort is put into energy analysis by developers of HPC applications.

We present our approach of combined performance and energy analysis using the performance analysis tool-set Scalasca. Scalascas parallel wait-state analysis is extended by a calculation of the energy-saving potential if a lower power-state can be used.

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Author information

Authors and Affiliations

  1. Jülich Supercomputing Centre (JSC) Forschungszentrum Jülich, 52425, Jülich, Germany

    Michael Knobloch & Bernd Mohr

  2. Department of Informatics, University of Hamburg, 22527, Hamburg, Germany

    Timo Minartz

Authors
  1. Michael Knobloch
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  2. Bernd Mohr
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  3. Timo Minartz
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Corresponding author

Correspondence to Michael Knobloch.

Additional information

This project is funded by the BMBF (German federal ministery for education and science) under grant 01—H08008E within the call: “HPC-Software für skalierbare Parallelrechner”.

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Open Access This is an open access article distributed under the terms of the Creative Commons Attribution Noncommercial License (https://creativecommons.org/licenses/by-nc/2.0), which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.

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Knobloch, M., Mohr, B. & Minartz, T. Determine energy-saving potential in wait-states of large-scale parallel programs. Comput Sci Res Dev 27, 255–263 (2012). https://doi.org/10.1007/s00450-011-0196-7

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  • Published: 31 August 2011

  • Issue Date: November 2012

  • DOI: https://doi.org/10.1007/s00450-011-0196-7

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Keywords

  • Power consumption
  • Energy efficiency
  • Energy
  • Performance
  • Analysis
  • Scalasca
  • MPI

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