Scaling the ISAM land surface model through parallelization of inter-component data transfer

Phil Miller, Michael Robson, Bassil El-Masri, Rahul Barman, Gengbin Zheng, Atul Jain, Laxmikant V Kale

Research output: Contribution to journalConference article

Abstract

We present the progression of developments necessary to scale the ISAM landsurface model from single nodes and small clusters with unusually largeper-node memory to much larger systems with more common configurations. These efforts include load balancing, conventional library-based output parallelization to reduce memory load, and parallel-in-time data input. OnHopper, a Cray XE6 machine, the result was strong scaling from 256 cores to 16k coreswith an efficiency of 32.9%. On Edison, a Cray XC30 machine, thecode strong scales from 256 cores to 16k coreswith an efficiency of 51.4%. These large-scale gains, and the associated performance increases at smaller scale, enable greater scientific productivity for the users of ISAM and open the possibilities of increased resolution in time and space and greater physical fidelity for the simulated processes while remaining computationally feasible.

Original languageEnglish (US)
Article number6957251
Pages (from-to)422-431
Number of pages10
JournalProceedings of the International Conference on Parallel Processing
Volume2014-November
Issue numberNovember
DOIs
StatePublished - Nov 13 2014
Event43rd International Conference on Parallel Processing, ICPP 2014 - Minneapolis, United States
Duration: Sep 9 2014Sep 12 2014

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ASJC Scopus subject areas

  • Software
  • Mathematics(all)
  • Hardware and Architecture

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