A parallel solver for incompressible fluid flows

Yushan Wang*, Marc Baboulin, Jack Dongarra, Joël Falcou, Yann Fraigneau, Olivier Le Maitre

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

12 Scopus citations

Abstract

The Navier-Stokes equations describe a large class of fluid flows but are difficult to solve analytically because of their nonlinearity. We present in this paper a parallel solver for the 3-D Navier-Stokes equations of incompressible unsteady flows with constant coefficients, discretized by the finite difference method. We apply the prediction-projection method which transforms the Navier-Stokes equations into three Helmholtz equations and one Poisson equation. For each Helmholtz system, we apply the Alternating Direction Implicit (ADI) method resulting in three tridiagonal systems. The Poisson equation is solved using partial diagonalization which transforms the Laplacian operator into a tridiagonal one. We describe an implementation based on MPI where the computations are performed on each subdomain and information is exchanged on the interfaces, and where the tridiagonal system solutions are accelerated using vectorization techniques. We present performance results on a current multicore system.

Original languageEnglish (US)
Pages (from-to)439-448
Number of pages10
JournalProcedia Computer Science
Volume18
DOIs
StatePublished - Jan 1 2013
Event13th Annual International Conference on Computational Science, ICCS 2013 - Barcelona, Spain
Duration: Jun 5 2013Jun 7 2013

Keywords

  • ADI
  • Navier-stokes equations
  • Parallel computing
  • Partial diagonalization
  • Prediction-projection
  • SIMD

ASJC Scopus subject areas

  • Computer Science(all)

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