Please use this identifier to cite or link to this item: http://hdl.handle.net/2122/9032
AuthorsBilotta, G.* 
Sanchez, R.* 
Ganci, G.* 
TitleOptimizing Satellite Monitoring of Volcanic Areas Through GPUs and Multi-Core CPUs Image Processing: An OpenCL Case Study
Issue DateDec-2013
Series/Report no.6/6 (2013)
DOI10.1109/JSTARS.2013.2255261
URIhttp://hdl.handle.net/2122/9032
KeywordsImage processing, parallel programming, remote sensing, satellites.
Subject Classification04. Solid Earth::04.08. Volcanology::04.08.06. Volcano monitoring 
04. Solid Earth::04.08. Volcanology::04.08.07. Instruments and techniques 
AbstractSatellite image processing algorithms often offer a very high degree of parallelism (e.g., pixel-by-pixel processing) that make them optimal candidates for execution on high-performance parallel computing hardware such as modern graphic processing units (GPUs) and multicore CPUs with vector processing capabilities. By using the OpenCL computing standard, a single implementation of a parallel algorithm can be deployed on a wide range of hardware platforms. However, achieving the best performance on each individual platform may still require a custom implementation. We show some possible approaches to the optimization of satellite image processing algorithms on a range of different platforms, discussing the implementation in OpenCL of the classic Brightness Temperature Difference ash-cloud detection algorithm.
Appears in Collections:Papers Published / Papers in press

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