Sparsification of the Reduced Matrix of the CBFM for a Memory Efficient Solution of Electrically Large EM Scattering Problems

Ines Fenni; Ziad S Haddad; Helene Roussel; Raj Mittra

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Sparsification of the Reduced Matrix of the CBFM for a Memory Efficient Solution of Electrically Large EM Scattering Problems

Ines Fenni, Ziad S Haddad, Helene Roussel and Raj Mittra

The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Conference Proceedings, p.69

01/01/2018

Abstract

Basis functions

Conference Title: 2018 USNC-URSI Radio Science Meeting (Joint with AP-S Symposium) Conference Start Date: 2018, July 8 Conference End Date: 2018, July 13 Conference Location: Boston, MA, USA In this paper a sparsification approach is applied to the compressed matrix resulting from the Characteristic Basis Function Method (CBFM) process in order to significantly reduce the memory cost of this direct solver-based largely used numerical technique. Many efforts have been made in recent years to efficiently calculate this matrix but, all of them have focused on the time cost and have not dealt with the memory resources needed to store it. With the proposed sparsification approach, the present work aims to reduce the computational cost associated to the compressed matrix both in terms of CPU time and memory consumption.

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Title: Sparsification of the Reduced Matrix of the CBFM for a Memory Efficient Solution of Electrically Large EM Scattering Problems
Creators - without role: Ines Fenni
Ziad S Haddad
Helene Roussel
Raj Mittra
Publication Details: The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Conference Proceedings, p.69
Publisher: The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Identifiers: 9940286608331
Academic Unit: King Abdulaziz University
Language: English
Resource Type: Conference proceeding