ForestClaw: Hybrid forest-of-octrees AMR for hyperbolic conservation laws

Carsten Burstedde, Donna Calhoun, Kyle Mandli, Andy R. Terrel

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

18 Scopus citations

Abstract

We present a new hybrid paradigm for parallel adaptive mesh refinement (AMR) that combines the scalability and lightweight architecture of tree-based AMR with the computational efficiency of patch-based solvers for hyperbolic conservation laws. The key idea is to interpret each leaf of the AMR hierarchy as one uniform compute patch in Rd with md degrees of freedom, where m is customarily between 8 and 32. Thus, computation on each patch can be optimized for speed, while we inherit the flexibility of adaptive meshes. In our work we choose to integrate with the p4est AMR library since it allows us to compose the mesh from multiple mapped octrees and enables the cubed sphere and other nontrivial multiblock geometries. We describe aspects of the parallel implementation and close with scalings for both MPI-only and OpenMP/MPI hybrid runs, where the largest MPI run executes on 16,384 CPU cores.

Original languageEnglish
Title of host publicationParallel Computing
Subtitle of host publicationAccelerating Computational Science and Engineering (CSE)
Pages253-262
Number of pages10
DOIs
StatePublished - 2014

Publication series

NameAdvances in Parallel Computing
Volume25
ISSN (Print)0927-5452

Keywords

  • HPC
  • adaptive mesh refinement
  • clawpack
  • hyperbolic conservation laws
  • manycore

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