Performance of a Massively Parallel Method of Moment Solver and Its Application

Authors

  • Yan Chen School of Electronic Engineering Xidian University, Xi’an, Shaanxi 710071, China
  • Zhongchao Lin School of Electronic Engineering Xidian University, Xi’an, Shaanxi 710071, China
  • Daniel Garcia-Donoro School of Electronic Engineering Xidian University, Xi’an, Shaanxi 710071, China
  • Xunwang Zhao School of Electronic Engineering Xidian University, Xi’an, Shaanxi 710071, China
  • Yu Zhang School of Electronic Engineering Xidian University, Xi’an, Shaanxi 710071, China

Keywords:

Communication avoiding, high performance, LU decomposition, massively parallel, method of moments

Abstract

A massively parallel Method of Moment (MoM) solver able to run on 200,000 CPU cores and solve matrices larger than 1.3 million unknowns is presented. The solver implements a novel LU decomposition algorithm based on the Communication Avoiding LU (CALU) scheme. By using a new pivoting policy, the communication between processes is improved enhancing the parallel speed up of the algorithm. Solver effectiveness and performance are demonstrated comparing the results with two of the most important math libraries used by direct dense solvers: the commercial MKL and the open source ScaLapack. Results show how simulation time is reduced significantly thanks to this novel LU decomposition algorithm making possible the simulation of incredibility electrically large problems using MoM.

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http://www.netlib.org/benchmark/hpl/scalability.html

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Published

2021-07-30

How to Cite

[1]
Yan Chen, Zhongchao Lin, Daniel Garcia-Donoro, Xunwang Zhao, and Yu Zhang, “Performance of a Massively Parallel Method of Moment Solver and Its Application”, ACES Journal, vol. 32, no. 10, pp. 872–881, Jul. 2021.

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