ALPS: A framework for parallel adaptive PDE solution

Adaptive mesh refinement and coarsening (AMR) is essential for the numerical solution of partial differential equations (PDEs) that exhibit behavior over a wide range of length and time scales. Because of the complex dynamic data structures and communication patterns and frequent data exchange and r...

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Bibliographic Details
Published in:Journal of physics. Conference series 2009-07, Vol.180 (1), p.012009
Main Authors: Burstedde, Carsten, Burtscher, Martin, Ghattas, Omar, Stadler, Georg, Tu, Tiankai, Wilcox, Lucas C
Format: Article
Language:English
Subjects:
Data exchange
Data structures
Dynamic loads
Geophysics
Grid refinement (mathematics)
Hexahedral finite elements
Octrees
Partial differential equations
Physics
Seismic waves
Wave propagation
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Summary:Adaptive mesh refinement and coarsening (AMR) is essential for the numerical solution of partial differential equations (PDEs) that exhibit behavior over a wide range of length and time scales. Because of the complex dynamic data structures and communication patterns and frequent data exchange and redistribution, scaling dynamic AMR to tens of thousands of processors has long been considered a challenge. We are developing ALPS, a library for dynamic mesh adaptation of PDEs that is designed to scale to hundreds of thousands of compute cores. Our approach uses parallel forest-of-octree-based hexahedral finite element meshes and dynamic load balancing based on space-filling curves. ALPS supports arbitrary-order accurate continuous and discontinuous finite element/spectral element discretizations on general geometries. We present scalability and performance results for two applications from geophysics: seismic wave propagation and mantle convection.
ISSN:1742-6596
1742-6588
1742-6596
DOI:10.1088/1742-6596/180/1/012009