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We present an algorithm that given a linear program with $n$ variables, $m$ constraints, and constraint matrix $A$, computes an $\epsilon$-approximate solution in $\tilde{O}(\sqrt{rank(A)}\log(1/\epsilon))$ iterations with high probability.…

Data Structures and Algorithms · Computer Science 2020-09-02 Yin Tat Lee , Aaron Sidford

We introduce a two-level direct solver for the Hierarchical Poincar\'e-Steklov (HPS) method for solving linear elliptic PDEs. HPS combines multidomain spectral collocation with a direct solver, enabling high-order discretizations for highly…

Numerical Analysis · Mathematics 2025-09-19 Joseph Kump , Anna Yesypenko , Per-Gunnar Martinsson

We present a fast algorithm for linear least squares problems governed by hierarchically block separable (HBS) matrices. Such matrices are generally dense but data-sparse and can describe many important operators including those derived…

Numerical Analysis · Mathematics 2014-06-17 Kenneth L. Ho , Leslie Greengard

We present a sparse linear system solver that is based on a multifrontal variant of Gaussian elimination, and exploits low-rank approximation of the resulting dense frontal matrices. We use hierarchically semiseparable (HSS) matrices, which…

Mathematical Software · Computer Science 2015-02-27 Pieter Ghysels , Xiaoye S. Li , Francois-Henry Rouet , Samuel Williams , Artem Napov

We study the design of polylogarithmic depth algorithms for approximately solving packing and covering semidefinite programs (or positive SDPs for short). This is a natural SDP generalization of the well-studied positive LP problem.…

Data Structures and Algorithms · Computer Science 2016-01-12 Zeyuan Allen-Zhu , Yin Tat Lee , Lorenzo Orecchia

Hierarchical low-rank approximation of dense matrices can reduce the complexity of their factorization from O(N^3) to O(N). However, the complex structure of such hierarchical matrices makes them difficult to parallelize. The block size and…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-02-05 Qianxiang Ma , Rio Yokota

We provide effective algorithms for solving block tridiagonal block Toeplitz systems with $m\times m$ quasiseparable blocks, as well as quadratic matrix equations with $m\times m$ quasiseparable coefficients, based on cyclic reduction and…

Numerical Analysis · Mathematics 2016-01-06 Dario A. Bini , Stefano Massei , Leonardo Robol

This paper presents a matrix-free multigrid method for solving the Stokes problem, discretized using $H^{\text{div}}$-conforming discontinuous Galerkin methods. We employ a Schur complement method combined with the fast diagonalization…

Numerical Analysis · Mathematics 2025-06-23 Cu Cui , Guido Kanschat

A fast multigrid solver is presented for high-order accurate Stokes problems discretised by local discontinuous Galerkin (LDG) methods. The multigrid algorithm consists of a simple V-cycle, using an element-wise block Gauss-Seidel smoother.…

Numerical Analysis · Mathematics 2020-11-25 Robert Saye

In this paper, we propose a fast distributed solver for linear equations given by symmetric diagonally dominant M-Matrices. Our approach is based on a distributed implementation of the parallel solver of Spielman and Peng by considering a…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-02-12 Rasul Tutunov , Haitham Bou Ammar , Ali Jadbabaie

We provide a flexible, open-source framework for hardware acceleration, namely massively-parallel execution on general-purpose graphics processing units (GPUs), applied to the hierarchical Poincar\'e--Steklov (HPS) family of algorithms for…

Numerical Analysis · Mathematics 2025-11-17 Owen Melia , Daniel Fortunato , Jeremy Hoskins , Rebecca Willett

Randomized sampling has recently been proven a highly efficient technique for computing approximate factorizations of matrices that have low numerical rank. This paper describes an extension of such techniques to a wider class of matrices…

Numerical Analysis · Mathematics 2015-03-25 Per-Gunnar Martinsson

In this paper, we investigate GPU based parallel triangular solvers systematically. The parallel triangular solvers are fundamental to incomplete LU factorization family preconditioners and algebraic multigrid solvers. We develop a new…

Mathematical Software · Computer Science 2016-06-03 Zhangxin Chen , Hui Liu , Bo Yang

We developed fast direct solver for 3D Helmholtz and Maxwell equations in layered medium. The algorithm is based on the ideas of cyclic reduction for separable matrices. For the grids with major uniform part (within the survey domain in the…

Numerical Analysis · Mathematics 2019-09-04 Vladimir Druskin , Mikhail Zaslavsky

In this work, we consider the solution of fluid-structure interaction problems using a monolithic approach for the coupling between fluid and solid subproblems. The coupling of both equations is realized by means of the arbitrary…

Numerical Analysis · Mathematics 2018-03-09 D. Jodlbauer , U. Langer , T. Wick

In this paper, we consider the matrices approximated in H2 format. The direct solution, as well as the preconditioning, of systems with such matrices is a challenging problem. We propose a non-extensive sparse factorization of the H2 matrix…

Numerical Analysis · Mathematics 2018-05-01 Daria Sushnikova , Ivan Oseledets

It is well known that multigrid methods are optimally efficient for solution of elliptic equations (O(N)), which means that effort is proportional to the number of points at which the solution is evaluated). Thus this is an ideal method to…

General Relativity and Quantum Cosmology · Physics 2007-05-23 Vishnu Natchu , Richard A. Matzner

Efficient solution of 3D elasticity problems is an important part of many industrial and scientific applications. Smoothed aggregation algebraic multigrid using rigid body modes for the tentative prolongation operator construction is an…

Mathematical Software · Computer Science 2022-02-21 Denis Demidov

In this paper, we study a hierarchical SSOR (HSSOR) method which could be used as a standalone method or as a smoother for a two-grid method. It is found that the method leads to faster convergence compared to more costly incomplete LU…

Numerical Analysis · Mathematics 2012-07-10 Pawan Kumar

We present the first parallel algorithm for solving systems of linear equations in symmetric, diagonally dominant (SDD) matrices that runs in polylogarithmic time and nearly-linear work. The heart of our algorithm is a construction of a…

Numerical Analysis · Computer Science 2013-11-14 Richard Peng , Daniel A. Spielman