High Performance Evaluation of Helmholtz Potentials Using the Multi-Level Fast Multipole Algorithm

Evaluation of pair potentials is critical in a number of areas of physics. The classical
$N$
-body problem has its root in evaluating the Laplace potential, and has spawned tree-algorithms, the fast multipole method (FMM), as well as kernel independent approaches. Over the years, FMM for Laplace potential has had a profound impact on a number of disciplines as it has been possible to develop highly scalable parallel versions of these algorithms. This is in stark contrast to parallel algorithms for oscillatory potentials such as the Helmholtz potential. The principal bottlenecks to scalable parallelism are the computation and communication costs of operations necessary to traverse up, across, and down the tree. In this article, we analyze asymptotic costs for both computation and communication in a parallel implementation, and describe techniques to overcome bottlenecks and achieve high performance evaluation of the Helmholtz potential for different distributions of particles. We demonstrate that the resulting implementation has a load balancing effect that significantly reduces the time-to-solution and enhances the scale of problems that can be treated using full wave physics.