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Natural Load Indices (NLI) for scientific simulation

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Abstract

We present Natural Load Indices (NLIs) as an alternative to measurement-based load indices. NLIs facilitate further performance improvement and better resource usage. Example NLIs are rainfall amounts in a climate simulation, mass of an atom in a Molecular Dynamics (MD) code and surface fluxes in an ocean model. The process of obtaining an NLI occurs during model development or as a preprocessing step and implementing NLIs minimizes run-time costs associated with dynamic load balancing.

NLIs are investigated in several applications. (A) We implement NLIs in the Community Atmosphere Model and discuss performance. (B) We extend prior Molecular Dynamics work by providing performance analysis using longer simulations. (C) We demonstrate the existence of an NLI in an ocean model. (D) We demonstrate similarities between NLIs in those models and show that NLIs are a general class of load index. Systems investigated include Pentium 4 Xeon, IBM Power5-p575 and IBM BlueGene/L parallel platforms.

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Authors and Affiliations

  1. Tech-X Corporation, Boulder, CO, 80301, USA

    Stefan P. Muszala

  2. University of Colorado at Denver and Health Sciences Center, Computer Science and Engineering, Denver, CO, 80217, USA

    Gita Alaghband

  3. Oak Ridge National Laboratory, National Center for Computational Sciences, P.O. Box 2008, Oak Ridge, TN, 37831, USA

    James Hack

  4. Electrical and Computer Engineering, Colorado State University, Fort Collins, CO, 80523, USA

    Daniel Connors

Authors
  1. Stefan P. Muszala
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  2. Gita Alaghband
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  3. James Hack
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  4. Daniel Connors
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Correspondence to Stefan P. Muszala.

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Muszala, S.P., Alaghband, G., Hack, J. et al. Natural Load Indices (NLI) for scientific simulation. J Supercomput 59, 392–413 (2012). https://doi.org/10.1007/s11227-010-0442-y

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