Acceleration of FDTD Method Using Deep Computing Unit

  • You Shen Tian
  • , Lixiao Wang
  • , Qing Huo Liu
  • , Wen Chen
  • , Qingtao Sun

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

Parallel computing finds extensive applications in numerical modeling of large-scale electromagnetic problems. We present a method for accelerating finite-difference time-domain (FDTD) method using deep computing unit (DCU). Simulation results show that the proposed method provides a significant improvement in efficiency compared to serial FDTD and parallel FDTD using multicore CPU. It offers a potential improvement for FDTD method in solving large-scale electromagnetic (EM) problems combining with high-performance computing (HPC) technology.

Original languageEnglish
Title of host publicationISAPE 2024 - 14th International Symposium on Antennas, Propagation and EM Theory
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-3
ISBN (Electronic)9798350353129
DOIs
Publication statusPublished - Oct 2024
Event14th International Symposium on Antennas, Propagation and EM Theory, ISAPE 2024 - Hefei, China
Duration: 23 Oct 202426 Oct 2024

Publication series

NameISAPE 2024 - 14th International Symposium on Antennas, Propagation and EM Theory

Conference

Conference14th International Symposium on Antennas, Propagation and EM Theory, ISAPE 2024
Country/TerritoryChina
CityHefei
Period23/10/2426/10/24

Keywords

  • deep computing unit (DCU)
  • finite-difference time-domain (FDTD) method
  • high-performance computing (HPC)
  • parallel computing

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Signal Processing
  • Instrumentation

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