A scalable RBF--FD method for atmospheric flow

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.