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Title: Parallel partitioning strategies for the adaptive solution of conservation laws

Conference ·
OSTI ID:198200
; ;  [1]
  1. Rensselaer Polytechnic Institute, Troy, NY (United States); and others

We describe and examine the performance of adaptive methods for Solving hyperbolic systems of conservation laws on massively parallel computers. The differential system is approximated by a discontinuous Galerkin finite element method with a hierarchical Legendre piecewise polynomial basis for the spatial discretization. Fluxes at element boundaries are computed by solving an approximate Riemann problem; a projection limiter is applied to keep the average solution monotone; time discretization is performed by Runge-Kutta integration; and a p-refinement-based error estimate is used as an enrichment indicator. Adaptive order (p-) and mesh (h-) refinement algorithms are presented and demonstrated. Using an element-based dynamic load balancing algorithm called tiling and adaptive p-refinement, parallel efficiencies of over 60% are achieved on a 1024-processor nCUBE/2 hypercube. We also demonstrate a fast, tree-based parallel partitioning strategy for three-dimensional octree-structured meshes. This method produces partition quality comparable to recursive spectral bisection at a greatly reduced cost.

Research Organization:
Sandia National Laboratories (SNL), Albuquerque, NM, and Livermore, CA (United States)
DOE Contract Number:
AC04-76DP00789
OSTI ID:
198200
Report Number(s):
CONF-9307220-Vol.75; CNN: Contract DAAL03-91-G-0215; Contract DAAL03-89-C-0038; TRN: 96:001696-0012
Resource Relation:
Conference: Modeling, mesh generation and adaptive numerical methods for partial differential equations program, Minneapolis, MN (United States), 6-23 Jul 1993; Other Information: PBD: 1995; Related Information: Is Part Of Modeling, mesh generation, and adaptive numerical methods for partial differential equations; Babuska, I. [ed.] [Univ. of Maryland, College Park, MD (United States). Inst. for Physical Science and Technology]; Henshaw, W.D. [ed.] [Los Alamos National Lab., NM (United States)]; Oliger, J.E. [ed.] [Research Inst. for Advanced Computer Science, Moffet Field, CA (United States)]; Flaherty, J.E. [ed.] [Rensselaer Polytechnic Inst., Troy, NY (United States)]; Hopcroft, J.E. [ed.] [Cornell Univ., Ithaca, NY (United States). Coll. of Engineering]; Tezduyar, T. [ed.] [Army High Performance Computing Research Center, Minneapolis, MN (United States)]; PB: 501 p.
Country of Publication:
United States
Language:
English