A parallel direct solver for the self-adaptive hp Finite Element Method

Maciej R. Paszyński, David Pardo, Carlos Torres-Verdín, Leszek F. Demkowicz, Victor M. Calo

Research output: Contribution to journalArticlepeer-review

38 Scopus citations

Abstract

In this paper we present a new parallel multi-frontal direct solver, dedicated for the hp Finite Element Method (hp-FEM). The self-adaptive hp-FEM generates in a fully automatic mode, a sequence of hp-meshes delivering exponential convergence of the error with respect to the number of degrees of freedom (d.o.f.) as well as the CPU time, by performing a sequence of hp refinements starting from an arbitrary initial mesh. The solver constructs an initial elimination tree for an arbitrary initial mesh, and expands the elimination tree each time the mesh is refined. This allows us to keep track of the order of elimination for the solver. The solver also minimizes the memory usage, by de-allocating partial LU factorizations computed during the elimination stage of the solver, and recomputes them for the backward substitution stage, by utilizing only about 10% of the computational time necessary for the original computations. The solver has been tested on 3D Direct Current (DC) borehole resistivity measurement simulations problems. We measure the execution time and memory usage of the solver over a large regular mesh with 1.5 million degrees of freedom as well as on the highly non-regular mesh, generated by the self-adaptive h p-FEM, with finite elements of various sizes and polynomial orders of approximation varying from p = 1 to p = 9. From the presented experiments it follows that the parallel solver scales well up to the maximum number of utilized processors. The limit for the solver scalability is the maximum sequential part of the algorithm: the computations of the partial LU factorizations over the longest path, coming from the root of the elimination tree down to the deepest leaf. © 2009 Elsevier Inc. All rights reserved.
Original languageEnglish (US)
Pages (from-to)270-281
Number of pages12
JournalJournal of Parallel and Distributed Computing
Volume70
Issue number3
DOIs
StatePublished - Mar 2010

ASJC Scopus subject areas

  • Artificial Intelligence
  • Hardware and Architecture
  • Theoretical Computer Science
  • Software
  • Computer Networks and Communications

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