Near Real-Time Multi-GPU omegaK Algorithm for SAR Processing
Paper in proceedings, 2014

This paper presents a Near-Real-Time multi-GPU accelerated solution of the ωk Algorithm for Synthetic Aperture Radar (SAR) data focusing, obtained in Stripmap SAR mode. Starting from an input raw data, the algorithm subdivides it in a grid of a configurable number of bursts along track. A multithreading CPU-side support is made available in order to handle each graphic device in parallel. Then each burst is assigned to a separate GPU and processed including Range Compression, Stolt Mapping via ChirpZ and Azimuth Compression steps. We prove the efficiency of our algorithm by using Sentinel-1 raw data (approx. 3.3 GB) on a commodity graphics card; the single-GPU solution is approximately 4x faster than the industrial multi-core CPU implementation (General ACS SAR Processor, GASP), without significant loss of quality. Using a multi-GPU system, the algorithm is approximately 6x faster with respect to the CPU processor.


Remote Sensing


Image Processing

Real-Time Processing


Davide Tiriticco

Marco Fratarcangeli

Chalmers, Applied Information Technology (Chalmers)

Riccardo Ferrara

Stefano Marra

Proceedings of the 2014 conference on Big Data from Space (BiDS'14)

1831-9424 (ISSN)


Areas of Advance

Information and Communication Technology

Subject Categories

Computer Science



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