A scalable RBF--FD method for atmospheric flow
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.
document
https://n2t.org/ark:/85065/d76111j9
eng
geoscientificInformation
Text
publication
2016-01-01T00:00:00Z
publication
2015-10-01T00:00:00Z
Copyright 2015 Elsevier.
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