Parallel Implementations of Multilevel Fast Multipole Algorithm on Graphical Processing Unit Cluster for Large-scale Electromagnetics Objects

Authors

  • Nghia Tran Department of Electrical Engineering and Computer Science The Catholic University of America, Washington, DC, 20064, USA
  • Ozlem Kilic Department of Electrical Engineering and Computer Science The Catholic University of America, Washington, DC, 20064, USA

Keywords:

Graphics Processing Unit (GPU), Multilevel Fast Multipole Algorithm (MLFMA)

Abstract

This paper investigates solving large-scale electromagnetic scattering problems by using the Multilevel Fast Multipole Algorithm (MLFMA). A parallel implementation for MLFMA is performed on a 12-node Graphics Processing Unit (GPU) cluster that populates NVidia Tesla M2090 GPUs. The details of the implementations and the performance achievements in terms of accuracy, speed up, and scalability are shown and analyzed. The experimental results demonstrate that our MLFMA implementation on GPUs is much faster than (up to 37x) that of the CPU implementation.

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References

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Published

2021-07-25

How to Cite

[1]
Nghia Tran and Ozlem Kilic, “Parallel Implementations of Multilevel Fast Multipole Algorithm on Graphical Processing Unit Cluster for Large-scale Electromagnetics Objects”, ACES Journal, vol. 33, no. 02, pp. 180–183, Jul. 2021.

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