Improvement and performance of parallel multilevel fast multipole algorithm

The method of establishing data structures plays an important role in the efficiency of parallel multilevel fast multipole algorithm (PMLFMA). Considering the main complements of multilevel fast multipole algorithm (MLFMA) memory, a new parallelization strategy and a modified data octree construction scheme are proposed to further reduce communication in order to improve parallel efficiency. For far interaction, a new scheme called dynamic memory allocation is developed. To analyze the workload balancing performance of a parallel implementation, the original concept of workload balancing factor is introduced and verified by numerical examples. Numerical results show that the above measures improve the parallel efficiency and are suitable for the analysis of electrical large-scale scattering objects.