A survey on direct solvers for Galerkin methods

In this paper we describe the history, performance, and design concepts of direct solvers for algebraic systems resulting from Galerkin discretizations of partial differential equations. Popular direct solver implementations of Gaussian elimination (also known as LU factorization) are introduced and...

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Main Authors: Pardo, D., Paszynski, M., Collier, N., Alvarez, J., Dalcin, L., Calo, Victor
Format: Journal Article
Published: 2012
Online Access:http://hdl.handle.net/20.500.11937/62810
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author Pardo, D.
Paszynski, M.
Collier, N.
Alvarez, J.
Dalcin, L.
Calo, Victor
author_facet Pardo, D.
Paszynski, M.
Collier, N.
Alvarez, J.
Dalcin, L.
Calo, Victor
author_sort Pardo, D.
building Curtin Institutional Repository
collection Online Access
description In this paper we describe the history, performance, and design concepts of direct solvers for algebraic systems resulting from Galerkin discretizations of partial differential equations. Popular direct solver implementations of Gaussian elimination (also known as LU factorization) are introduced and briefly analyzed. We discuss three of the most relevant aspects influencing the performance of direct solvers on this kind of algebraic systems. First, the ordering of the degrees of freedom of the algebraic system has a significant impact on the solver performance, solution speed and memory requirements. The impact of unknowns ordering for elimination is exemplified and alternative ordering algorithms are described and compared. Second, the effect of round-off error on the simulation results is discussed. We detail this effect for uniform grids where the impact of round-off error on the solution is controlled by the condition number of the matrix in terms of the element size, but is independent of the polynomial order of approximation. Additionally, we discuss the link between unknown ordering and round-off error. Third, we describe the impact of the connectivity pattern (graph) of the basis functions on the performance of direct solvers. Variations in the connectivity structure of the resulting discrete system have severe impact on performance of the solver. That is, the resources needed to factorize the system strongly depend on its connectivity graph. Less connected graphs are cheaper to solve, that is, C0 finite element discretizations are cheaper to solve with direct solvers than Cp−1 discretizations.
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spelling curtin-20.500.11937-628102018-04-09T06:14:13Z A survey on direct solvers for Galerkin methods Pardo, D. Paszynski, M. Collier, N. Alvarez, J. Dalcin, L. Calo, Victor In this paper we describe the history, performance, and design concepts of direct solvers for algebraic systems resulting from Galerkin discretizations of partial differential equations. Popular direct solver implementations of Gaussian elimination (also known as LU factorization) are introduced and briefly analyzed. We discuss three of the most relevant aspects influencing the performance of direct solvers on this kind of algebraic systems. First, the ordering of the degrees of freedom of the algebraic system has a significant impact on the solver performance, solution speed and memory requirements. The impact of unknowns ordering for elimination is exemplified and alternative ordering algorithms are described and compared. Second, the effect of round-off error on the simulation results is discussed. We detail this effect for uniform grids where the impact of round-off error on the solution is controlled by the condition number of the matrix in terms of the element size, but is independent of the polynomial order of approximation. Additionally, we discuss the link between unknown ordering and round-off error. Third, we describe the impact of the connectivity pattern (graph) of the basis functions on the performance of direct solvers. Variations in the connectivity structure of the resulting discrete system have severe impact on performance of the solver. That is, the resources needed to factorize the system strongly depend on its connectivity graph. Less connected graphs are cheaper to solve, that is, C0 finite element discretizations are cheaper to solve with direct solvers than Cp−1 discretizations. 2012 Journal Article http://hdl.handle.net/20.500.11937/62810 10.1007/BF03322602 restricted
spellingShingle Pardo, D.
Paszynski, M.
Collier, N.
Alvarez, J.
Dalcin, L.
Calo, Victor
A survey on direct solvers for Galerkin methods
title A survey on direct solvers for Galerkin methods
title_full A survey on direct solvers for Galerkin methods
title_fullStr A survey on direct solvers for Galerkin methods
title_full_unstemmed A survey on direct solvers for Galerkin methods
title_short A survey on direct solvers for Galerkin methods
title_sort survey on direct solvers for galerkin methods
url http://hdl.handle.net/20.500.11937/62810