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2017-07-18
A GPU Implementation of the Inverse Fast Multipole Method for Multi-Bistatic Imaging Applications
By
Progress In Electromagnetics Research M, Vol. 58, 159-169, 2017
Abstract
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.
Citation
Luis E. Tirado Galia Ghazi Yuri Alvarez-Lopez Fernando Las-Heras Jose Angel Martinez-Lorenzo , "A GPU Implementation of the Inverse Fast Multipole Method for Multi-Bistatic Imaging Applications," Progress In Electromagnetics Research M, Vol. 58, 159-169, 2017.
doi:10.2528/PIERM17021004
http://www.jpier.org/PIERM/pier.php?paper=17021004
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