Abstract
In this paper, we describe the process of parallelizing an existing, production level, sequential Synthetic Aperture Radar (SAR) processor based on the Range-Doppler algorithmic approach. We show how, taking into account the constraints imposed by the software architecture and related software engineering costs, it is still possible with a moderate programming effort to parallelize the software and present an message-passing interface (MPI) implementation whose speedup is about 8 on 9 processors, achieving near real-time processing of raw SAR data even on a moderately aged parallel platform. Moreover, we discuss a hybrid two-level parallelization approach that involves the use of both MPI and OpenMP. We also present GridStore, a novel data grid service to manage raw, focused and post-processed SAR data in a grid environment. Indeed, another aim of this work is to show how the processed data can be made available in a grid environment to a wide scientific community, through the adoption of a data grid service providing both metadata and data management functionalities. In this way, along with near real-time processing of SAR images, we provide a data grid-oriented system for data storing, publishing, management, etc.









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Acknowledgments
This work was supported in part by Interreg IIIA Greece, Italy 2000–2006 Grant No I2101005 in the framework of the project “Interstore : decentralized data sharing with applications to biomedical image processing”.
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Cafaro, M., Epicoco, I., Fiore, S. et al. Near real-time parallel processing and advanced data management of SAR images in grid environments. J Real-Time Image Proc 4, 219–227 (2009). https://doi.org/10.1007/s11554-009-0119-z
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DOI: https://doi.org/10.1007/s11554-009-0119-z