A parallel implementation of an OL-LOGOS sparse direct solver

John C. Young, R. J. Adams, S. D. Gedney

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Data sparse direct solution methods for electromagnetic simulation problems have proven to be useful for a number of situations, both as standalone direct solvers and as general purpose preconditioners for use with iterative solvers. One set of such direct methods is provided by the LOGOS framework, which is based on expanding the underlying system matrix in a basis of local solutions that satisfy global boundary conditions. A particular subset of the LOGOS-based solution methods is referred to as the overlapped, localizing (OL) LOGOS method. This approach to factoring the system matrix is based on expanding the system matrix in a basis of overlapping sources that localize the scattered field to a spatial region that is also covered by the source functions. It has previously been shown that the computational complexity of such factorizations can scale as well as O(N log N) for low to moderate frequencies when used as a direct solver. The OL-LOGOS method has also been shown to provide an effective, O(N log N) general purpose preconditioner when used to factor the near-neighbor matrix obtained from the multilevel fast multipole method algorithm.

Original languageEnglish
Title of host publication2014 USNC-URSI Radio Science Meeting (Joint with AP-S Symposium), USNC-URSI 2014 - Proceedings
Pages180
Number of pages1
ISBN (Electronic)9781479937462
DOIs
StatePublished - Nov 12 2014
Event2014 USNC-URSI Radio Science Meeting (Joint with AP-S Symposium), USNC-URSI 2014 - Memphis, United States
Duration: Jul 6 2014Jul 11 2014

Publication series

Name2014 USNC-URSI Radio Science Meeting (Joint with AP-S Symposium), USNC-URSI 2014 - Proceedings

Conference

Conference2014 USNC-URSI Radio Science Meeting (Joint with AP-S Symposium), USNC-URSI 2014
Country/TerritoryUnited States
CityMemphis
Period7/6/147/11/14

Bibliographical note

Publisher Copyright:
© 2014 IEEE.

ASJC Scopus subject areas

  • Artificial Intelligence
  • Human-Computer Interaction
  • Electrical and Electronic Engineering

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