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The linear equations that arise in interior methods for constrained optimization are sparse symmetric indefinite and become extremely ill-conditioned as the interior method converges. These linear systems present a challenge for existing…

The direct method is one of the most important algorithms for solving linear systems of equations, with LU decomposition comprising a significant portion of its computation time. This study explores strategies to accelerate complex LU…

Numerical Analysis · Mathematics 2024-08-21 Tomonori Kouya

Recent strides in nonlinear model predictive control (NMPC) underscore a dependence on numerical advancements to efficiently and accurately solve large-scale problems. Given the substantial number of variables characterizing typical…

Robotics · Computer Science 2024-06-04 Wilson Jallet , Ewen Dantec , Etienne Arlaud , Justin Carpentier , Nicolas Mansard

We introduce a preconditioner based on a hierarchical low-rank compression scheme of Schur complements. The construction is inspired by standard nested dissection, and relies on the assumption that the Schur complements can be approximated,…

Numerical Analysis · Mathematics 2015-09-01 Paolo Gatto , Jan S. Hesthaven

We introduce a fast direct solver for variable-coefficient elliptic partial differential equations on surfaces based on the hierarchical Poincar\'e-Steklov method. The method takes as input an unstructured, high-order quadrilateral mesh of…

Numerical Analysis · Mathematics 2022-10-04 Daniel Fortunato

In a recent paper [{\em F. Bernal, J. Mor\'on-Vidal and J.A. Acebr\'on, Comp.$\&$ Math. App. 146:294-308 (2023)}] an hybrid supercomputing algorithm for elliptic equations has been put forward. The idea is that the interfacial nodal…

Numerical Analysis · Mathematics 2023-11-16 Jorge Morón-Vidal , Francisco Bernal , Atsushi Suzuki

We present a robust and scalable preconditioner for the solution of large-scale linear systems that arise from the discretization of elliptic PDEs amenable to rank compression. The preconditioner is based on hierarchical low-rank…

Numerical Analysis · Mathematics 2017-12-27 Gustavo Chávez , George Turkiyyah , Stefano Zampini , David Keyes

We consider the problem of efficiently solving large-scale linear least squares problems that have one or more linear constraints that must be satisfied exactly. Whilst some classical approaches are theoretically well founded, they can face…

Numerical Analysis · Mathematics 2021-12-24 Jennifer Scott , Miroslav Tuma

This article introduces HODLR2D, a new hierarchical low-rank representation for a class of dense matrices arising out of $N$ body problems in two dimensions. Using this new hierarchical framework, we propose a new fast matrix-vector product…

Numerical Analysis · Mathematics 2022-04-13 V A Kandappan , Vaishnavi Gujjula , Sivaram Ambikasaran

We propose efficient parallel algorithms and implementations on shared memory architectures of LU factorization over a finite field. Compared to the corresponding numerical routines, we have identified three main difficulties specific to…

Symbolic Computation · Computer Science 2014-02-17 Jean-Guillaume Dumas , Thierry Gautier , Clément Pernet , Ziad Sultan

We present a fast direct solution method for the advection-diffusion equation in one and two dimensions with non-periodic boundaries. Computational cost is reduced to $\mathcal O(N)$ by making a low-rank approximation of the Green's…

Computational Physics · Physics 2016-12-30 Jonathan R. Bull

An additive Runge-Kutta method is used for the time stepping, which integrates the linear stiff terms by an explicit singly diagonally implicit Runge-Kutta (ESDIRK) method and the nonlinear terms by an explicit Runge-Kutta (ERK) method. In…

Numerical Analysis · Mathematics 2024-05-08 Ke Chen , Daniel Appelö , Tracy Babb , Per-Gunnar Martinsson

Discretization of flow in fractured porous media commonly lead to large systems of linear equations that require dedicated solvers. In this work, we develop an efficient linear solver and its practical implementation for mixed-dimensional…

Numerical Analysis · Mathematics 2023-02-08 Xiaozhe Hu , Eirik Keilegavlen , Jan M. Nordbotten

In this paper, we propose and analyze the numerical algorithms for fast solution of periodic elliptic problems in random media in $\mathbb{R}^d$, $d=2,3$. We consider the stochastic realizations using checkerboard configuration of the…

Numerical Analysis · Mathematics 2020-07-16 Venera Khoromskaia , Boris N. Khoromskij

The dense matrix resulting from an integral equation (IE) based solution of Maxwell's equations can be compactly represented by an ${\cal H}^2$-matrix. Given a general dense ${\cal H}^2$-matrix, prevailing fast direct solutions involve…

Numerical Analysis · Mathematics 2018-01-22 Miaomiao Ma , Dan Jiao

We present an algorithm for the solution of a simultaneous space-time discretization of linear parabolic evolution equations with a symmetric differential operator in space. Building on earlier work, we recast this discretization into a…

Numerical Analysis · Mathematics 2021-09-07 Raymond van Venetië , Jan Westerdiep

This paper proposes a combination of a hybrid CPU--GPU and a pure GPU software implementation of a direct algorithm for solving shifted linear systems $(A - \sigma I)X = B$ with large number of complex shifts $\sigma$ and multiple…

Mathematical Software · Computer Science 2017-08-24 Nela Bosner , Zvonimir Bujanović , Zlatko Drmač

This paper introduces the hierarchical interpolative factorization for elliptic partial differential equations (HIF-DE) in two (2D) and three dimensions (3D). This factorization takes the form of an approximate generalized LU/LDL…

Numerical Analysis · Mathematics 2015-04-21 Kenneth L. Ho , Lexing Ying

A nested Schur complement solver is proposed for iterative solution of linear systems arising in exponential and implicit time integration of the Maxwell equations with perfectly matched layer (PML) nonreflecting boundary conditions. These…

Numerical Analysis · Mathematics 2019-02-01 Mike A. Botchev

Multigrid methods have been a popular approach for solving linear systems arising from the discretization of partial differential equations (PDEs) for several decades. They are particularly effective for accelerating convergence rates with…

Numerical Analysis · Mathematics 2025-12-10 Teoman Toprak , Florian Kummer