A framework for hybrid parallel flow simulations with a trillion cells in complex geometries

  • Authors:
  • Christian Godenschwager;Florian Schornbaum;Martin Bauer;Harald Köstler;Ulrich Rüde

  • Affiliations:
  • Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany and Siemens AG, An der Lände, Forchheim;Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany;Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany;Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany;Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany

  • Venue:
  • SC '13 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis
  • Year:
  • 2013

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Abstract

waLBerla is a massively parallel software framework for simulating complex flows with the lattice Boltzmann method (LBM). Performance and scalability results are presented for SuperMUC, the world's fastest x86-based supercomputer ranked number 6 on the Top500 list, and JUQUEEN, a Blue Gene/Q system ranked as number 5. We reach resolutions with more than one trillion cells and perform up to 1.93 trillion cell updates per second using 1.8 million threads. The design and implementation of waLBerla is driven by a careful analysis of the performance on current petascale supercomputers. Our fully distributed data structures and algorithms allow for efficient, massively parallel simulations on these machines. Elaborate node level optimizations and vectorization using SIMD instructions result in highly optimized compute kernels for the single- and two-relaxation-time LBM. Excellent weak and strong scaling is achieved for a complex vascular geometry of the human coronary tree.