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

: Feld, Dustin; Garcke, Jochen; Liu, Jia; Schricker, Eric; Soddemann, Thomas; Xue, Yong


Griebel, Michael; Schüller, Anton; Schweitzer, Marc Alexander:
Scientific Computing and Algorithms in Industrial Simulation : Projects and Products of Fraunhofer SCAI
Cham: Springer International Publishing, 2017
ISBN: 978-3-319-62457-0 (Print)
ISBN: 978-3-319-62458-7 (Online)
Aufsatz in Buch
Fraunhofer SCAI ()

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.