Scalability Issues of In-Situ Visualization in Parallel Simulation of Unsteady Flows

Conference paper

Abstract

Grand challenge applications of 3-dimensional high resolution unsteady computational fluid dynamics result in huge amounts of data. To avoid significant bottlenecks of the storage and communication resources, efficient techniques for data extraction and preprocessing at the source have been realized in the parallel, network-distributed process chain called DSVR. Here the 3D data extraction is implemented as a parallel library and can be done in-situ during the numerical simulations, which avoids the storage of raw data for visualization. In this work we present, evaluate, and compare three techniques of parallel in-situ pathline extraction in distributed memory architectures. The gain in parallel scalability is achieved by an innovative trade-off between parallelization of partial tasks and asynchronous execution of suited serialized tasks. It has been shown that advanced parallelization schemes increase the scalability significantly.

Keywords

Computational Fluid Dynamics Domain Decomposition Split Node Master Process Simulation Application 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgement

Computational support and infrastructure was provided by the North-German Supercomputing Alliance (HLRN). The authors are grateful to Prof. Dr. Siegfried Raasch and his group for sharing the PALM software and for fruitful discussions.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  1. 1.Scientific Visualization and Parallel Processing, Regional Computing Center (RRZ)University of HamburgHamburgGermany

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