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Scalable Algorithms for the Solution of Higher-Dimensional PDEs

  • Mario HeeneEmail author
  • Dirk Pflüger
Conference paper
Part of the Lecture Notes in Computational Science and Engineering book series (LNCSE, volume 113)

Abstract

The solution of higher-dimensional problems, such as the simulation of plasma turbulence in a fusion device as described by the five-dimensional gyrokinetic equations, is a grand challenge for current and future high-performance computing. The sparse grid combination technique is a promising approach to the solution of these problems on large-scale distributed memory systems. The combination technique numerically decomposes a single large problem into multiple moderately-sized partial problems that can be computed in parallel, independently and asynchronously of each other. The ability to efficiently combine the individual partial solutions to a common sparse grid solution is a key to the overall performance of such large-scale computations. In this work, we present new algorithms for the recombination of distributed component grids and demonstrate their scalability to 180, 225 cores on the supercomputer Hazel Hen.

Keywords

Grid Point Domain Decomposition Process Group Sparse Grid Combine Solution 
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

Acknowledgements

This work was supported by the German Research Foundation (DFG) through the Priority Program 1648 “Software for Exascale Computing” (SPPEXA).

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Institute for Parallel and Distributed SystemsUniversity of StuttgartStuttgartGermany

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