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In this paper, we propose and evaluate the performance of a unified computational framework for preconditioning systems of linear equations resulting from the solution of coupled problems with monolithic schemes. The framework is composed…

Numerical Analysis · Mathematics 2016-08-24 Francesc Verdugo , Wolfgang A. Wall

Despite hundreds of papers on preconditioned linear systems of equations, there remains a significant lack of comprehensive performance benchmarks comparing various preconditioners for solving symmetric positive definite (SPD) systems. In…

Numerical Analysis · Mathematics 2025-05-28 Marc A. Tunnell , David F. Gleich

Many subsurface engineering applications involve tight-coupling between fluid flow, solid deformation, fracturing, and similar processes. To better understand the complex interplay of different governing equations, and therefore design…

In this paper, we further investigate and refine the subspace-constrained preconditioning technique to enhance the theoretical and numerical convergence properties of randomized iterative methods for solving linear systems. In particular,…

Numerical Analysis · Mathematics 2026-05-29 Yonghan Sun , Hou-Duo Qi , Deren Han , Jiaxin Xie

We present a modified version of the PRESB preconditioner for two-by-two block system of linear equations with the coefficient matrix $$\textbf{A}=\left(\begin{array}{cc} F & -G^* G & F \end{array}\right),$$ where $F\in\mathbb{C}^{n\times…

Numerical Analysis · Mathematics 2024-05-15 Owe Axelsson , Dovod Khojasteh Slakuyeh

The computation time for reservoir simulation is dominated by the linear solver. The sets of linear equations which arise in reservoir simulation have two distinctive features: the problems are usually highly anisotropic, with a dominant…

Numerical Analysis · Mathematics 2014-02-10 Haran Jackson , Michele Taroni , David Ponting

For some typical and widely used non-convex half-quadratic regularization models and the Ambrosio-Tortorelli approximate Mumford-Shah model, based on the Kurdyka-\L ojasiewicz analysis and the recent nonconvex proximal algorithms, we…

Optimization and Control · Mathematics 2021-07-30 Shengxiang Deng , Ismail Ben Ayed , Hongpeng Sun

Most efficient linear solvers use composable algorithmic components, with the most common model being the combination of a Krylov accelerator and one or more preconditioners. A similar set of concepts may be used for nonlinear algebraic…

Numerical Analysis · Mathematics 2016-07-15 Peter R. Brune , Matthew G. Knepley , Barry F. Smith , Xuemin Tu

In this paper we introduce an algebraic recursive multilevel incomplete factorization preconditioner, based on a distributed Schur complement formulation, for solving general linear systems. The novelty of the proposed method is to combine…

Numerical Analysis · Mathematics 2015-09-23 Yiming Bu , Bruno Carpentieri , Zhaoli Shen , Tingzhu Huang

To precondition a large and sparse linear system, two direct methods for approximate factoring of the inverse are devised. The algorithms are fully parallelizable and appear to be more robust than the iterative methods suggested for the…

Numerical Analysis · Mathematics 2012-08-20 Mikko Byckling , Marko Huhtanen

We consider the use of multipreconditioning to solve linear systems when more than one preconditioner is available but the optimal choice is not known. In particular, we consider a selective multipreconditioned GMRES algorithm where we…

Numerical Analysis · Mathematics 2021-07-08 Niall Bootland , Andrew Wathen

This paper investigates a type of fast and flexible preconditioners to solve multilinear system $\mathcal{A}\textbf{x}^{m-1}=\textbf{b}$ with $\mathcal{M}$-tensor $\mathcal{A}$ and obtains some important convergent theorems about…

Numerical Analysis · Mathematics 2021-10-08 Eisa Khosravi Dehdezi , Saeed Karimi

An implementation of GMRES with multiple preconditioners (MPGMRES) is proposed for solving shifted linear systems with shift-and-invert preconditioners. With this type of preconditioner, the Krylov subspace can be built without requiring…

Numerical Analysis · Mathematics 2016-03-31 Tania Bakhos , Peter Kitanidis , Scott Ladenheim , Arvind K. Saibaba , Daniel Szyld

A new domain decomposition preconditioner is introduced for efficiently solving linear systems Ax = b with a symmetric positive definite matrix A. The particularity of the new preconditioner is that it is not necessary to have access to the…

Numerical Analysis · Mathematics 2021-06-23 Nicole Spillane

The compositional model is often used to describe multicomponent multiphase porous media flows in the petroleum industry. The fully implicit method with strong stability and weak constraints on time-step sizes is commonly used in the…

Numerical Analysis · Mathematics 2024-09-18 Li Zhao , Chen-Song Zhang , Chun-Sheng Feng , Shi Shu

We propose an alternative implementation of preconditioning techniques for the solution of non-linear problems. Within the framework of Newton-Krylov methods, preconditioning techniques are needed to improve the performance of the solvers.…

Computational Physics · Physics 2008-04-02 G. Lapenta , S. Ju

We present a preconditioner based on spectral projection that is combined with a deflated Krylov subspace method for solving ill conditioned linear systems of equations. Our results show that the proposed algorithm requires many fewer…

Numerical Analysis · Mathematics 2016-09-23 Man-Chung Yeung , Craig C. Douglas , Long Lee

Coupled multiphysics problems often give rise to interface conditions naturally formulated in fractional Sobolev spaces. Here, both positive- and negative fractionality are common. When designing efficient solvers for discretizations of…

Numerical Analysis · Mathematics 2018-06-04 Trygve Bærland , Miroslav Kuchta , Kent-Andre Mardal

A class of preconditioners is introduced to enhance geometry optimisation and transition state search of molecular systems. We start from the Hessian of molecular mechanical terms, decompose it and retain only its positive definite part to…

Chemical Physics · Physics 2018-04-06 Letif Mones , Gabor Csanyi , Christoph Ortner

In this paper, we address the efficient numerical solution of linear and quadratic programming problems, often of large scale. With this aim, we devise an infeasible interior point method, blended with the proximal method of multipliers,…

Numerical Analysis · Mathematics 2021-01-18 Luca Bergamaschi , Jacek Gondzio , Ángeles Martínez , John W. Pearson , Spyridon Pougkakiotis
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