An Efficient Parallelization Strategy For The Adaptive Integral Method Based On Graph Partitioning

The adaptive integral method (AIM) is frequently used to efficiently solve scattering problems involving conducting objects immersed in a uniform or stratified medium. We propose an efficient parallelization strategy for AIM suitable for distributed-memory computers. In the proposed approach, a weighted graph is associated to the given mesh, and partitioned in a way that results in an efficient distribution of computations across different processes. Numerical tests show that the proposed algorithm compares favorably to existing techniques to parallelize the AIM.