A parallel algorithm for the dynamic partitioning of particle-mesh computational systems?

Abstract

Particle tracking methods are a versatile computational technique central to the simulation of a wide range of scientific applications. In this paper we present anew parallel approach for the dynamic partitioning of particle-mesh computational systems. The approach uses a framework, the "in-element" particle tracking method, based on the assumption that particle trajectories are computed by problem data localized to individual elements. The parallel efficiency of such particle-mesh systems depends on the partitioning of both the mesh elements and the particles; this distribution can change dramatically because of movement of the particles and adaptive refinement of the mesh. To address this problem we introduce a combined load function that is a function of both the particle and mesh element distributions. We present experiment results that detail the performance of this parallel load balancing approach for a three-dimensional particle-mesh test problem on an unstructured, adaptive mesh. © 2002 Springer-Verlag Berlin Heidelberg.