A Well-Scaling Parallel Algorithm for the Computation of the Translation Operator in the MLFMA

This paper investigates the parallel, distributed-memory computation of the translation operator with L+1 multipoles in the three-dimensional Multilevel Fast Multipole Algorithm (MLFMA). A baseline, communication-free parallel algorithm can compute such a translation operator in O(L) time, using O(L...

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Vydané v:IEEE transactions on antennas and propagation Ročník 62; číslo 5; s. 2679 - 2687
Hlavní autori: Michiels, Bart, Bogaert, Ignace, Fostier, Jan, De Zutter, Daniël
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York, NY IEEE 01.05.2014
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
Algorithms
Antenna radiation patterns
Applied classical electromagnetism
Applied sciences
Complexity
Complexity theory
Computation
Computer science; control theory; systems
Computer systems and distributed systems. User interface
Density functional theory
Distributed-memory architecture
Electromagnetic wave propagation, radiowave propagation
Electromagnetism; electron and ion optics
Exact sciences and technology
Fundamental areas of phenomenology (including applications)
Interpolation
MLFMA
Multilevel
Multipoles
Operators
Parallel algorithms
parallel computing
Physics
Runtime
Software
Three dimensional
translation operator
Translations
Many body theory
Parallel algorithm
Electromagnetism
Memory architecture
Distributed-memory architecture
Distributed computing
Distributed memory
Multipole field
translation operator
Size effect
Parallel computation
Large scale
MLFMA
parallel computing
ISSN:0018-926X, 1558-2221
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Popis
Shrnutí:This paper investigates the parallel, distributed-memory computation of the translation operator with L+1 multipoles in the three-dimensional Multilevel Fast Multipole Algorithm (MLFMA). A baseline, communication-free parallel algorithm can compute such a translation operator in O(L) time, using O(L 2 ) processes. We propose a parallel algorithm that reduces this complexity to O(logL) time. This complexity is theoretically supported and experimentally validated up to 16 384 parallel processes. For realistic cases, the implementation of the proposed algorithm proves to be up to ten times faster than the baseline algorithm. For a large-scale parallel MLFMA simulation with 4096 parallel processes, the runtime for the computation of all translation operators during the setup stage is reduced from roughly one hour to only a few minutes.
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ISSN:0018-926X
1558-2221
DOI:10.1109/TAP.2014.2307338