An efficient parallel implementation of the multilevel fast multipole algorithm for rigorous solutions of large-scale scattering problems
Date
2010
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Abstract
We present the solution of large-scale scattering problems discretized with hundreds of millions of unknowns. The multilevel fast multipole algorithm (MLFMA) is parallelized using the hierarchical partitioning strategy on distributed-memory architectures. Optimizations and load-balancing algorithms are extensively used to improve parallel MLFMA solutions. The resulting implementation is successfully employed on modest parallel computers to solve scattering problems involving metallic objects larger than 1000λ and discretized with more than 300 million unknowns. © 2010 IEEE.
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2010 URSI International Symposium on Electromagnetic Theory
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IEEE
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Distributed memory, Hierarchical partitioning, Large-scale scattering, Load-balancing algorithm, Metallic objects, Multi-level fast multi-pole algorithm, Multilevel fast multipole algorithms, Parallel computer, Parallel implementations, Rigorous solution, Scattering problems, Algorithms, Electric fields, Electromagnetism, Scattering, Problem solving
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English