JUNE 18–22, 2017
FRANKFURT AM MAIN, GERMANY

Presentation Details
 
Name: (PP23) i_SSS - integrated Support System for Sustainability
 
Time: Tuesday, June 20, 2017
03:15 pm - 03:45 pm
 
Room:   Booth #L-212  
 
Breaks:03:15 pm - 03:45 pm Coffee Break
 
Presenter:   Jannek Squar, University of Hamburg
 
Abstract:   The target of our project is the development of a realtime digital decision system to optimise farming with regard to an increase of crop yield and minimal damage to the environment. Basis for this decision system is SAGA, which is an open-source geographic information system. During our development we add new SAGA tools, which analyse local circumstances provided through a combination of on-site measurements and remote sensing and allow to assess potential risks. Risks like runoff, erosion and mass transport may be inferred from ICON weather-forecasts, which we get from Deutscher Wetterdienst. To handle the huge amount of data from weather forecasts, remote sensing and measurement stations but also from SAGA tools, the use of HPC is essential to ensure that the decision system may deliver realtime results in the end. Therefore we build an infrastructure for a HPC cluster which allows to download and preprocess weather-forecasts automatically and in parallel. The preprocessing offers the opportunity to reduce the amount of data (currently up to 90%) and prepare the data before it is loaded into SAGA. SAGA can be executed on a cluster but makes currently only use of OpenMP. Besides from optimising the new tools we want to expand its potential by introducing MPI parallelisation - this would result in a significant gain in performance.

Authors: 
Christoph Beck, Universität Hamburg
Michael Bock, Universität Hamburg
Jürgen Böhner, Universität Hamburg
Olaf Conrad, Universität Hamburg
Tobias Kawohl, Universität Hamburg
Michael Kuhn, Universität Hamburg
Lars Landschreiber, Universität Hamburg
Hermann Lenhart, Universität Hamburg
Thomas Ludwig, German Climate Computing Center
Jannek Squar, Universität Hamburg
Sandra Wendland, Universität Hamburg
  
 
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PP23_Squar.pdf (1442 KB)