MLFMA optimal decomposing strategy

Author

Yue Hu

Author_Institution

Dept. of Inf. Technol. & Mechatron. Eng., Shang Hai XingJian Coll., Shanghai, China

fYear

2013

fDate

20-22 Dec. 2013

Firstpage

2527

Lastpage

2530

Abstract

To decompose the far-neighborhood and near-neighborhood data domains of Multi-Level Fast Multi-Pole Algorithm (MLFMA), an optimal parallel implementation is discussed in this paper. To solve this problem, the characteristics of the two fields are respectively considered. Especially in the near-neighborhood decomposing, the clustering property of data is applied. The effectiveness of the optimized strategy is demonstrated by experimental results. Comparing with the former strategy, a higher parallel efficiency is obtained.

Keywords

electrical engineering computing; electromagnetic wave scattering; parallel processing; pattern clustering; MLFMA optimal decomposing strategy; data clustering property; electromagnetic scattering; far-neighborhood data decomposition; multilevel fast multipole algorithm; near-neighborhood data decomposition; optimal parallel implementation; Computers; Electromagnetic scattering; Geometry; Impedance; MLFMA; Mathematical model; Matrix decomposition; MLFMA; clustering property; far-neighborhood; near-neighborhood; optimal; parallel implementation;

fLanguage

English

Publisher

ieee

Conference_Titel

Mechatronic Sciences, Electric Engineering and Computer (MEC), Proceedings 2013 International Conference on

Conference_Location

Shengyang

Print_ISBN

978-1-4799-2564-3

Type

conf

DOI

10.1109/MEC.2013.6885461

Filename

6885461