@Article{IJNAM-9-2,
author = {},
title = {Parallel Data Partitioning Strategy in Solving Large Scale Electromagnetic Scattering Problems},
journal = {International Journal of Numerical Analysis and Modeling},
year = {2012},
volume = {9},
number = {2},
pages = {257--269},
abstract = {<p style="text-align: justify;">The multilevel fast multipole algorithm (MLFMA) has shown great efficiency in
solving large scale electromagnetic scattering problems. However, when unknowns become up to
tens of millions, it is not trivial to keep high performance because of the complicated structure
and calculation of MLFMA. In order to get rid of the bottleneck caused by load balancing, a
parallel data partitioning strategy is proposed based on the hierarchical structure of an oct-tree
of MLFMA. We present our data partitioning strategy in the light of different layers&#39; properties
including the processing of three kinds of layers in the tree and a fine-grained decomposition.
We also put forward a solution of a coexisting data correlating problem, using a transition layer.
Meanwhile, with the purpose of minimizing communication time in distributed memory system, a
redundant technique is applied in the distributed layer. Parallel efficiency analysis demonstrates
that the computational cost in parallelization of MLFMA can be asymptotically cut, and a high
parallel efficiency can be obtained in our implementation.</p>},
issn = {2617-8710},
doi = {https://doi.org/2012-IJNAM-625},
url = {https://global-sci.com/article/83466/parallel-data-partitioning-strategy-in-solving-large-scale-electromagnetic-scattering-problems}
}