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p4est : Scalable Algorithms for Parallel Adaptive Mesh Refinement on Forests of Octrees
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p4est : Scalable Algorithms for Parallel Adaptive Mesh Refinement on Forests of Octrees
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p4est : Scalable Algorithms for Parallel Adaptive Mesh Refinement on Forests of Octrees
p4est : Scalable Algorithms for Parallel Adaptive Mesh Refinement on Forests of Octrees
Journal Article

p4est : Scalable Algorithms for Parallel Adaptive Mesh Refinement on Forests of Octrees

2011
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Overview
(ProQuest: ... denotes formulae/symbols omitted.)The authors present scalable algorithms for parallel adaptive mesh refinement and coarsening (AMR), partitioning, and 2:1 balancing on computational domains composed of multiple connected two-dimensional quadtrees or three-dimensional octrees, referred to as a forest of octrees. By distributing the union of octants from all octrees in parallel, they combine the high scalability proven previously for adaptive single-octree algorithms with the geometric flexibility that can be achieved by arbitrarily connected hexahedral macromeshes, in which each macroelement is the root of an adapted octree. A key concept of their approach is an encoding scheme of the interoctree connectivity that permits arbitrary relative orientations between octrees. They demonstrate the parallel scalability of p4est on its own and in combination with two geophysics codes. Using p4est they generate and adapt multioctree meshes with up to 5.13 x ... octants on as many as 220,320 CPU cores and execute the 2:1 balance algorithm in less than 10 seconds per million octants per process.