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PARAMETER ESTIMATES FOR THE RELAXED DIMENSIONAL FACTORIZATION PRECONDITIONER AND APPLICATION TO HEMODYNAMICS∗
BibTeX
@MISC{Benzi_parameterestimates,
author = {Michele Benzi and Simone Deparis and Gwenol Gr and Alfio Quarteroni and Michele Benzi and Simone Deparis and Gwenol Grandperrin and Alfio},
title = {PARAMETER ESTIMATES FOR THE RELAXED DIMENSIONAL FACTORIZATION PRECONDITIONER AND APPLICATION TO HEMODYNAMICS∗},
year = {}
}
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Abstract
Abstract. We present new results on the Relaxed Dimensional Factorization (RDF) precondi-tioner for solving saddle point problems, first introduced in [5]. This method contains a parameter α> 0, to be chosen by the user. Previous works provided an estimate of α in the 2D case using Local Fourier Analysis. Novel algebraic estimation techniques for finding a suitable value of the RDF parameter in both the 2D and the 3D case with arbitrary geometries are proposed. These techniques are tested on a variety of discrete saddle point problems arising from the approximation of the Navier–Stokes equations using a Marker-and-Cell scheme and a finite element one. We also show results for a large-scale problem relevant for hemodynamics simulation that we solve in parallel using up to 8196 cores. Key words. scalable parallel preconditioners, finite element method, high performance com-puting, Navier–Stokes equations, hemodynamics applications, dimensional splitting preconditioner,
Keyphrases
parameter estimate navier stokes equation relaxed dimensional factorization discrete saddle point problem scalable parallel preconditioners finite element method local fourier analysis large-scale problem relevant hemodynamics application previous work suitable value high performance com-puting marker-and-cell scheme rdf parameter finite element saddle point problem present new result dimensional splitting preconditioner hemodynamics simulation key word novel algebraic estimation technique arbitrary geometry
