Parallelization of Hierarchical Matrix Algorithms for Electromagnetic Scattering Problems

Open Access
Authors
  • E. Larsson
  • A. Zafari
  • M. Righero
  • M.A. Francavilla
  • G. Giordanengo
  • F. Vipiana
  • G. Vecchi
  • C. Kessler
  • C. Ancourt
  • C. Grelck
Publication date 2019
Host editors
  • J. Kołodziej
  • H. González-Vélez
Book title High-Performance Modelling and Simulation for Big Data Applications
Book subtitle Selected Results of the COST Action IC1406 cHiPSet
ISBN
  • 9783030162719
ISBN (electronic)
  • 9783030162726
Series Lecture Notes in Computer Science
Pages (from-to) 36-68
Publisher Cham: Springer Open
Organisations
  • Faculty of Science (FNWI) - Informatics Institute (IVI)
Abstract
Numerical solution methods for electromagnetic scattering problems lead to large systems of equations with millions or even billions of unknown variables. The coefficient matrices are dense, leading to large computational costs and storage requirements if direct methods are used. A commonly used technique is to instead form a hierarchical representation for the parts of the matrix that corresponds to far-field interactions. The overall computational cost and storage requirements can then be reduced to O(NlogN). This still corresponds to a large-scale simulation that requires parallel implementation. The hierarchical algorithms are rather complex, both regarding data dependencies and communication patterns, making parallelization non-trivial. In this chapter, we describe two classes of algorithms in some detail, we provide a survey of existing solutions, we show results for a proof-of-concept implementation, and we provide various perspectives on different aspects of the problem.
Document type Chapter
Language English
Published at https://doi.org/10.1007/978-3-030-16272-6_2
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