Massively Parallel Approach of Multilevel Fast Multipole Algorithm on DCU Clusters for Large Electromagnetic Scattering problems

We Jia He, Yi Nan Kong, Kai Feng He, Ming Lin Yang, Xin Qing Sheng

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

2 Citations (Scopus)

Abstract

A massively parallel approach of the multilevel fast multipole algorithm (MLFMA) on Deep Computing Unit (DCU) clusters using the Heterogeneous Interface for Portability (HIP) programming model and the Message Passing Interface (MPI) is presented (DCU-MLFMA). The proposed MPI-based multi-DCU parallel implementation is capable of solving challenging problems involving billions of unknowns with a significant speedup, compared with the conventional CPU-based ternary parallelization approach of MLFMA (CPU-MLFMA). Numerical results, including a ship model with length about 6000 wavelengths modeled with 2.6 billion unknowns, are given to demonstrate the capability, as well as the efficiency of the presented method.

Original languageEnglish
Title of host publication2021 International Applied Computational Electromagnetics Society Symposium, ACES-China 2021, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781733509619
DOIs
Publication statusPublished - 28 Jul 2021
Event4th International Applied Computational Electromagnetics Society Symposium in China, ACES-China 2021 - Chengdu, China
Duration: 28 Jul 202131 Jul 2021

Publication series

Name2021 International Applied Computational Electromagnetics Society Symposium, ACES-China 2021, Proceedings

Conference

Conference4th International Applied Computational Electromagnetics Society Symposium in China, ACES-China 2021
Country/TerritoryChina
CityChengdu
Period28/07/2131/07/21

Keywords

  • HIP
  • MPI
  • Multilevel fast multipole algorithm
  • parallelization

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