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  4. Energy-Efficiency and Performance Comparison of Aerosol Optical Depth Retrieval on Distributed Embedded SoC Architectures
 
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2017
Book Article
Title

Energy-Efficiency and Performance Comparison of Aerosol Optical Depth Retrieval on Distributed Embedded SoC Architectures

Abstract
The Aerosol Optical Depth {(AOD)} is a significant optical property of aerosols and is applied to the atmospheric correction of remotely sensed surface features as well as for monitoring volcanic eruptions, forest fires, and air quality in general, as well as gathering data for climate predictions on the basis of observations from satellites. We have developed an {AOD} retrieval workflow for processing satellite data not only with ordinary {CPUs} but also with parallel processors and {GPU} accelerators in a distributed hardware environment. This workflow includes pre-processing procedures which are followed by the runtime dominating main retrieval method.
Author(s)
Feld, Dustin
Garcke, Jochen  
Liu, Jia
Schricker, Eric
Soddemann, Thomas  
Xue, Yong
Mainwork
Scientific Computing and Algorithms in Industrial Simulations  
DOI
10.1007/978-3-319-62458-7_17
Language
English
Fraunhofer-Institut für Algorithmen und Wissenschaftliches Rechnen SCAI  
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