An OpenMP-CUDA implementation of multilevel fast multipole algorithm for electromagnetic simulation on multi-GPU computing systems

Jian Guan, Su Yan, Jian Ming Jin

Research output: Contribution to journalArticle

Abstract

A multi-GPU implementation of the multilevel fast multipole algorithm (MLFMA) based on the hybrid OpenMP-CUDA parallel programming model (OpenMP-CUDA-MLFMA) is presented for computing electromagnetic scattering of a three-dimensional conducting object. The proposed hierarchical parallelization strategy ensures a high computational throughput for the GPU calculation. The resulting OpenMP-based multi-GPU implementation is capable of solving real-life problems with over one million unknowns with a remarkable speed-up. The radar cross sections of a few benchmark objects are calculated to demonstrate the accuracy of the solution. The results are compared with those from the CPU-based MLFMA and measurements. The capability and efficiency of the presented method are analyzed through the examples of a sphere, an aerocraft, and a missile-like object. Compared with the 8-threaded CPU-based MLFMA, the OpenMP-CUDA-MLFMA method can achieve from 5 to 20 total speed-up ratios.

Original languageEnglish (US)
Article number6504730
Pages (from-to)3607-3616
Number of pages10
JournalIEEE Transactions on Antennas and Propagation
Volume61
Issue number7
DOIs
StatePublished - Jan 1 2013

Keywords

  • CUDA
  • OpenMP
  • electromagnetic scattering
  • hybrid parallel programming model
  • multi-GPU
  • multilevel fast multipole algorithm
  • radar cross section

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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