A scalable RBF--FD method for atmospheric flow

AMS Citation:
Tillenius, M., E. Larsson, E. Lehto, and N. Flyer, 2015: A scalable RBF--FD method for atmospheric flow. Journal of Computational Physics, 298, 406-422, doi:10.1016/j.jcp.2015.06.003.
Resource Type:article
Title:A scalable RBF--FD method for atmospheric flow
Abstract: Radial basis function-generated finite difference (RBF--FD) methods have recently been proposed as very interesting for global scale geophysical simulations, and have been shown to outperform established pseudo-spectral and discontinuous Galerkin methods for shallow water test problems. In order to be competitive for very large scale simulations, the RBF--FD methods needs to be efficiently implemented for modern multicore based computer architectures. This is a challenging assignment, because the main computational operations are unstructured sparse matrix-vector multiplications, which in general scale poorly on multicore computers due to bandwidth limitations. However, with the task parallel implementation described here we achieve 60-100% of theoretical speedup within a shared memory node, and 80-100% of linear speedup across nodes. We present results for global shallow water benchmark problems with a 30 km resolution.
Peer Review:Refereed
Copyright Information:Copyright 2015 Elsevier.
OpenSky citable URL: ark:/85065/d76111j9
Publisher's Version: 10.1016/j.jcp.2015.06.003
  • Martin Tillenius
  • Elisabeth Larsson
  • Erik Lehto
  • Natasha Flyer - NCAR/UCAR
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