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Performance Analysis of a Multiprocessor Coupled Ice–Ocean Model for the Baltic Sea

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  • 1 Rossby Centre, Swedish Meteorological and Hydrological Institute, Norrköping, Sweden
  • | 2 National Supercomputer Centre, Linköping University, Linköping, Sweden
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Abstract

Within the Swedish Regional Climate Modelling Programme (SWECLIM) a 3D coupled ice–ocean model for the Baltic Sea has been developed to simulate physical processes on timescales of hours to decades. The model code is based on the global ocean GCM of the Ocean Circulation Climate Advanced Modelling (OCCAM) project and has been optimized for massively parallel computer architectures. The Hibler-type dynamic–thermodynamic sea ice model utilizes elastic–viscous–plastic rheology resulting in a fully explicit numerical scheme that improves computational efficiency. A detailed performance analysis shows that the ice model causes generic workload imbalance between involved processors. An improved domain partitioning technique minimizes load imbalance, but cannot solve the problem completely. However, it is shown that the total load imbalance is not more than 13% for a mild winter and about 8% for a severe winter. With respect to parallel processor performance, the code makes the best use of available computer resources.

Corresponding author address: Dr. H. E. Markus Meier, Rossby Centre, Swedish Meteorological and Hydrological Institute, SE-60176 Norrköping, Sweden. Email: markus.meier@smhi.se

Abstract

Within the Swedish Regional Climate Modelling Programme (SWECLIM) a 3D coupled ice–ocean model for the Baltic Sea has been developed to simulate physical processes on timescales of hours to decades. The model code is based on the global ocean GCM of the Ocean Circulation Climate Advanced Modelling (OCCAM) project and has been optimized for massively parallel computer architectures. The Hibler-type dynamic–thermodynamic sea ice model utilizes elastic–viscous–plastic rheology resulting in a fully explicit numerical scheme that improves computational efficiency. A detailed performance analysis shows that the ice model causes generic workload imbalance between involved processors. An improved domain partitioning technique minimizes load imbalance, but cannot solve the problem completely. However, it is shown that the total load imbalance is not more than 13% for a mild winter and about 8% for a severe winter. With respect to parallel processor performance, the code makes the best use of available computer resources.

Corresponding author address: Dr. H. E. Markus Meier, Rossby Centre, Swedish Meteorological and Hydrological Institute, SE-60176 Norrköping, Sweden. Email: markus.meier@smhi.se

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