Distributed Parallel Backprojection for Real-Time Stripmap SAR Imaging on GPU Clusters

Parallelization on a GPU (graphics processing unit) cluster is an effective approach to reducing the huge computation time of backprojection, which is the most accurate SAR (synthetic aperture radar) imaging algorithm for reconstructing images with no errors caused by the platform motion. To obtain...

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Bibliographic Details
Published in2017 IEEE International Conference on Cluster Computing (CLUSTER) pp. 619 - 620
Main Authors Gocho, Masato, Oishi, Noboru, Ozaki, Atsuo
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2017
Subjects
Airplanes
GPU
Graphics processing units
Image reconstruction
Imaging
Real-time systems
SAR
Signal processing algorithms
Synthetic aperture radar
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Summary:Parallelization on a GPU (graphics processing unit) cluster is an effective approach to reducing the huge computation time of backprojection, which is the most accurate SAR (synthetic aperture radar) imaging algorithm for reconstructing images with no errors caused by the platform motion. To obtain accurate imagery in real-time, we developed a distributed parallel backprojection algorithm for stripmap SAR on GPU clusters, which reconstruct the image while receiving signals from the remote platform. In the case of receiving the 1.9 GiB signals from the remote storage through 1GbE, we found that 16 GPUs on the 4 nodes are 11.5 times faster than 1 GPU, and they finished the imaging 1.0s after receiving all signals.
ISSN:2168-9253
DOI:10.1109/CLUSTER.2017.64