Optimized hybrid parallel lattice boltzmann fluid flow simulations on complex geometries

  • Authors:
  • Jonas Fietz;Mathias J. Krause;Christian Schulz;Peter Sanders;Vincent Heuveline

  • Affiliations:
  • Engineering Mathematics and Computing Lab (EMCL), Karlsruhe Institute of Technology (KIT), Germany;Engineering Mathematics and Computing Lab (EMCL), Karlsruhe Institute of Technology (KIT), Germany;Institute for Theoretical Informatics, Algorithmics II, Karlsruhe Institute of Technology (KIT), Germany;Institute for Theoretical Informatics, Algorithmics II, Karlsruhe Institute of Technology (KIT), Germany;Engineering Mathematics and Computing Lab (EMCL), Karlsruhe Institute of Technology (KIT), Germany

  • Venue:
  • Euro-Par'12 Proceedings of the 18th international conference on Parallel Processing
  • Year:
  • 2012

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Abstract

Computational fluid dynamics (CFD) have become more and more important in the last decades, accelerating research in many different areas for a variety of applications. In this paper, we present an optimized hybrid parallelization strategy capable of solving large-scale fluid flow problems on complex computational domains. The approach relies on the combination of lattice Boltzmann methods (LBM) for the fluid flow simulation, octree data structures for a sparse block-wise representation and decomposition of the geometry as well as graph partitioning methods optimizing load balance and communication costs. The approach is realized in the framework of the open source library OpenLB and evaluated for the simulation of respiration in a subpart of a human lung. The efficiency gains are discussed by comparing the results of the full optimized approach with those of more simpler ones realized prior.