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http://hdl.handle.net/2122/9032
Authors: | Bilotta, G.* Sanchez, R.* Ganci, G.* |
Title: | Optimizing Satellite Monitoring of Volcanic Areas Through GPUs and Multi-Core CPUs Image Processing: An OpenCL Case Study | Journal: | IEEE journal of selected topics in applied Earth observations and remote sensing | Series/Report no.: | 6/6 (2013) | Publisher: | IEEE / Institute of Electrical and Electronics Engineers Incorporated | Issue Date: | Dec-2013 | DOI: | 10.1109/JSTARS.2013.2255261 | Keywords: | Image processing, parallel programming, remote sensing, satellites. | Subject Classification: | 04. Solid Earth::04.08. Volcanology::04.08.06. Volcano monitoring 04. Solid Earth::04.08. Volcanology::04.08.07. Instruments and techniques |
Abstract: | Satellite 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: | Article published / in press |
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