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Near Real-Time Multi-GPU omegaK Algorithm for SAR Processing

Davide Tiriticco ; Marco Fratarcangeli (Institutionen för tillämpad informationsteknologi (Chalmers)) ; Riccardo Ferrara ; Stefano Marra
Proceedings of the 2014 conference on Big Data from Space (BiDS'14) (1831-9424). p. 277-280. (2014)
[Konferensbidrag, refereegranskat]

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.

Nyckelord: Remote Sensing, Image Processing, GPGPU, SAR, Real-Time Processing

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Denna post skapades 2015-04-21. Senast ändrad 2015-04-21.
CPL Pubid: 215489


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