A GPU implementation of the inverse fast multipole method for multi-bistatic imaging applications

被引：1

作者：

Tirado L.E. ^{[1
]}

Ghazi G. ^{[1
]}

Álvarez-Lopez Y. ^{[2
]}

Las-Heras F. ^{[2
]}

Martinez-Lorenzo J.Á. ^{[1
]}

机构：

[1] Department of Electrical Engineering, Northeastern University, Boston, 02115, MA

[2] Department of Electrical Engineering, Area of Signal Theory and Communications, University of Oviedo, Gijn, 33203, Asturias

来源：

Martinez-Lorenzo, José Á. (jmartinez@coe.neu.edu) | 1600年 / Electromagnetics Academy卷 / 58期

关键词：

29;

D O I：

10.2528/PIERM17021004

中图分类号：

学科分类号：

摘要：

This paper describes a parallel implementation of the Inverse Fast Multipole Method (IFMM) for multi-bistatic imaging configurations. NVIDIAs Compute Unified Device Architecture (CUDA) is used to parallelize and accelerate the imaging algorithm in a Graphics Processing Unit (GPU). The algorithm is validated with synthetic data generated by the Modified Equivalent Current Approximation (MECA) method and experimental data collected by a Frequency-Modulated Continuous Wave (FMCW) radar system operating in the 70–77 GHz frequency band. The presented results show that the IFMM implementation using the CUDA platform is effective at significantly reducing the algorithm computational time, providing a 300X speedup when compared to the single core OpenMP version of the algorithm. © 2017, Electromagnetics Academy. All rights reserved.

引用

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页码：159 / 169

页数：10

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