Olbrich, S.

Vetter, M.

English

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Geophysical Research AbstractsVol. 19, EGU2017-15544, 2017EGU General Assembly 2017© Author(s) 2017. CC Attribution 3.0 License.Efficient in-situ visualization of unsteady flows in climate simulationMichael Vetter (1) and Stephan Olbrich (2)(1) Universität Hamburg, CEN, Hamburg, Germany (michael.vetter@uni-hamburg.de), (2) Universität Hamburg, RRZ,Hamburg, Germany (stephan.olbrich@uni-hamburg.de)The simulation of climate data tends to produce very large data sets, which hardly can be processed in classicalpost-processing visualization applications. Typically, the visualization pipeline consisting of the processes datageneration, visualization mapping and rendering is distributed into two parts over the network or separated via filetransfer. Within most traditional post-processing scenarios the simulation is done on a supercomputer whereas thedata analysis and visualization is done on a graphics workstation. That way temporary data sets with huge volumehave to be transferred over the network, which leads to bandwidth bottlenecks and volume limitations. The solutionto this issue is the avoidance of temporary storage, or at least significant reduction of data complexity.Within the Climate Visualization Lab – as part of the Cluster of Excellence "Integrated Climate System Analy-sis and Prediction" (CliSAP) at the University of Hamburg, in cooperation with the German Climate ComputingCenter (DKRZ) – we develop and integrate an in-situ approach. Our software framework DSVR is based on theseparation of the process chain between the mapping and the rendering processes. It couples the mapping processdirectly to the simulation by calling methods of a parallelized data extraction library, which create a time-basedsequence of geometric 3D scenes. This sequence is stored on a special streaming server with an interactive post-filtering option and then played-out asynchronously in a separate 3D viewer application. Since the rendering is partof this viewer application, the scenes can be navigated interactively. In contrast to other in-situ approaches where2D images are created as part of the simulation or synchronous co-visualization takes place, our method supportsinteraction in 3D space and in time, as well as fixed frame rates.To integrate in-situ processing based on our DSVR framework and methods in the ICON climate model, we arecontinuously evolving the data structures and mapping algorithms of the framework to support the ICON model’snative grid structures, since DSVR originally was designed for rectilinear grids only. We now have implemented anew output module to ICON to take advantage of the DSVR visualization. The visualization can be configured asmost output modules by using a specific namelist and is exemplarily integrated within the non-hydrostatic atmo-spheric model time loop. With the integration of a DSVR based in-situ pathline extraction within ICON, a furthermilestone is reached. The pathline algorithm as well as the grid data structures have been optimized for the domaindecomposition used for the parallelization of ICON based on MPI and OpenMP. The software implementationand evaluation is done on the supercomputers at DKRZ. In principle, the data complexity is reduced from O(n3)to O(m), where n is the grid resolution and m the number of supporting point of all pathlines. The stability andscalability evaluation is done using Atmospheric Model Intercomparison Project (AMIP) runs.We will give a short introduction in our software framework, as well as a short overview on the implementationand usage of DSVR within ICON. Furthermore, we will present visualization and evaluation results of sampleapplications.

Efficient in-situ visualization of unsteady flows in climate simulation

https://pure.mpg.de/pubman/item/item_2473241_1/component/file_2473240/EGU2017-15544.pdf

Efficient in-situ visualization of unsteady flows in climate simulation

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