Massively parallel solver for the high-order Galerkin Least-Squares method
Author(s)
Yano, Masayuki, Ph. D. Massachusetts Institute of Technology
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Other Contributors
Massachusetts Institute of Technology. Computation for Design and Optimization Program.
Advisor
David L. Darmofal.
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A high-order Galerkin Least-Squares (GLS) finite element discretization is combined with massively parallel implicit solvers. The stabilization parameter of the GLS discretization is modified to improve the resolution characteristics and the condition number for the high-order interpolation. The Balancing Domain Decomposition by Constraints (BDDC) algorithm is applied to the linear systems arising from the two-dimensional, high-order discretization of the Poisson equation, the advection-diffusion equation, and the Euler equation. The Robin-Robin interface condition is extended to the Euler equation using the entropy-symmetrized variables. The BDDC method maintains scalability for the high-order discretization for the diffusion-dominated flows. The Robin-Robin interface condition improves the performance of the method significantly for the advection-diffusion equation and the Euler equation. The BDDC method based on the inexact local solvers with incomplete factorization maintains the scalability of the exact counterpart with a proper reordering.
Description
Thesis (S.M.)--Massachusetts Institute of Technology, Computation for Design and Optimization Program, 2009. This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. Cataloged from student submitted PDF version of thesis. Includes bibliographical references (p. 85-91).
Date issued
2009Department
Massachusetts Institute of Technology. Computation for Design and Optimization ProgramPublisher
Massachusetts Institute of Technology
Keywords
Computation for Design and Optimization Program.