Performance evaluation of a parallel sparse lattice Boltzmann solver

Authors:
L. Axner;J. Bernsdorf;T. Zeiser;P. Lammers;J. Linxweiler;A. G. Hoekstra
Affiliations:
Section Computational Science, Faculty of Science, University of Amsterdam, Kruislaan 403, 1098 SJ, Amsterdam, The Netherlands;NEC Laboratories Europe, NEC Europe Ltd., Rathausallee 10, D-53757 St. Augustin, Germany;Regionales Rechenzentrum Erlangen, University of Erlangen-Nuremberg, Martensstr.1, D-91058 Erlangen, Germany;HLRS, Nobelstrasse 19, D-70569 Stuttgart, Germany;Institute for Computational Modeling in Civil Engineering, Pockelstrasse 3, D-38106 Braunschweig, Germany;Section Computational Science, Faculty of Science, University of Amsterdam, Kruislaan 403, 1098 SJ, Amsterdam, The Netherlands
Venue:
Journal of Computational Physics
Year:
2008

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Abstract

We develop a performance prediction model for a parallelized sparse lattice Boltzmann solver and present performance results for simulations of flow in a variety of complex geometries. A special focus is on partitioning and memory/load balancing strategy for geometries with a high solid fraction and/or complex topology such as porous media, fissured rocks and geometries from medical applications. The topology of the lattice nodes representing the fluid fraction of the computational domain is mapped on a graph. Graph decomposition is performed with both multilevel recursive-bisection and multilevel k-way schemes based on modified Kernighan-Lin and Fiduccia-Mattheyses partitioning algorithms. Performance results and optimization strategies are presented for a variety of platforms, showing a parallel efficiency of almost 80% for the largest problem size. A good agreement between the performance model and experimental results is demonstrated.