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In this paper, we investigate the combination of multigrid methods and neural networks, starting from a Finite Element discretization of an elliptic PDE. Multigrid methods use interpolation operators to transfer information between…

Numerical Analysis · Mathematics 2021-09-14 Claudio Tomasi , Rolf Krause

We consider geometric multigrid methods for the solution of linear systems arising from isogeometric discretizations of elliptic partial differential equations. For classical finite elements, such methods are well known to be fast solvers…

Numerical Analysis · Mathematics 2017-05-16 Clemens Hofreither , Stefan Takacs , Walter Zulehner

We present a multigrid based eigensolver for computing low-modes of the Hermitian Wilson Dirac operator. For the non-Hermitian case multigrid methods have already replaced conventional Krylov subspace solvers in many lattice QCD…

High Energy Physics - Lattice · Physics 2015-09-24 Gunnar Bali , Sara Collins , Andreas Frommer , Karsten Kahl , Issaku Kanamori , Benjamin Müller , Matthias Rottmann , Jakob Simeth

The numerical simulation of structural mechanics applications via finite elements usually requires the solution of large-size and ill-conditioned linear systems, especially when accurate results are sought for derived variables interpolated…

Numerical Analysis · Mathematics 2019-06-26 Andrea Franceschini , Victor A. Paludetto Magri , Gianluca Mazzucco , Nicolò Spiezia , Carlo Janna

We present an iterative scheme, reminiscent of the Multigrid method, to solve large boundary value problems with Probabilistic Domain Decomposition (PDD). In it, increasingly accurate approximations to the solution are used as control…

Numerical Analysis · Mathematics 2017-01-06 Francisco Bernal , Juan A. Acebrón

A V-cycle multigrid method for the Hellan-Herrmann-Johnson (HHJ) discretization of the Kirchhoff plate bending problems is developed in this paper. It is shown that the contraction number of the V-cycle multigrid HHJ mixed method is bounded…

Numerical Analysis · Mathematics 2017-12-27 Long Chen , Jun Hu , Xuehai Huang

A multigrid method is proposed for solving nonlinear eigenvalue problems by the finite element method. With this new scheme, solving nonlinear eigenvalue problem is decomposed to a series of solutions of linear boundary value problems on…

Numerical Analysis · Mathematics 2015-01-09 Hehu Xie

We present a distributed framework of the Primal-Dual Hybrid Gradient (PDHG) algorithm for solving massive-scale linear programming (LP) problems. Although PDHG-based solvers demonstrate strong performance on single-node GPU architectures,…

Optimization and Control · Mathematics 2026-05-11 Hongpei Li , Yicheng Huang , Huikang Liu , Dongdong Ge , Yinyu Ye

In this paper, we present a geometric multigrid methodology for the solution of matrix systems associated with isogeometric compatible discretizations of the generalized Stokes and Oseen problems. The methodology provably yields a pointwise…

Numerical Analysis · Mathematics 2017-05-26 Christopher Coley , Joseph Benzaken , John A. Evans

In this paper, a full (nested) multigrid scheme is proposed to solve eigenvalue problems. The idea here is to use the multilevel correction method to transform the solution of eigenvalue problem to a series of solutions of the corresponding…

Numerical Analysis · Mathematics 2015-06-23 Hehu Xie

We present W-cycle multigrid algorithms for the solution of the linear system of equations arising from a wide class of $hp$-version discontinuous Galerkin discretizations of elliptic problems. Starting from a classical framework in…

Numerical Analysis · Mathematics 2013-12-02 P. F. Antonietti , M. Sarti , M. Verani

We present a monolithic $hp$ space-time multigrid method for tensor-product space-time finite element discretizations of the Stokes equations. Geometric and polynomial coarsening of the space-time mesh is performed, and the entire algorithm…

Numerical Analysis · Mathematics 2025-12-11 Nils Margenberg , Markus Bause , Peter Munch

Partial Differential Equations (PDEs) describe several problems relevant to many fields of applied sciences, and their discrete counterparts typically involve the solution of sparse linear systems. In this context, we focus on the analysis…

Numerical Analysis · Mathematics 2022-01-17 Antonella Galizia , Simone Cammarasana , Andrea Clematis , Giuseppe Patane'

In this paper, we study FPGA based pipelined and superscalar design of two variants of conjugate gradient methods for solving Laplacian equation on a discrete grid; the first version corresponds to the original conjugate gradient algorithm,…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-03-13 Sahithi Rampalli , Natasha Sehgal , Ishita Bindlish , Tanya Tyagi , Pawan Kumar

The support vector machine is a flexible optimization-based technique widely used for classification problems. In practice, its training part becomes computationally expensive on large-scale data sets because of such reasons as the…

Machine Learning · Statistics 2016-11-28 Ehsan Sadrfaridpour , Sandeep Jeereddy , Ken Kennedy , Andre Luckow , Talayeh Razzaghi , Ilya Safro

Important computational physics problems are often large-scale in nature, and it is highly desirable to have robust and high performing computational frameworks that can quickly address these problems. However, it is no trivial task to…

Mathematical Software · Computer Science 2017-09-18 J. Chang , K. B. Nakshatrala , M. G. Knepley , L. Johnsson

We present a multigrid algorithm for self consistent solution of the Kohn-Sham equations in real space. The entire problem is discretized on a real space mesh with a high order finite difference representation. The resulting self consistent…

Materials Science · Physics 2009-10-31 Jian Wang , Thomas L. Beck

In this paper, we further develop a family of parallel time integrators known as Revisionist Integral Deferred Correction methods (RIDC) to allow for the semi-implicit solution of time dependent PDEs. Additionally, we show that our…

Distributed, Parallel, and Cluster Computing · Computer Science 2012-09-20 Benjamin Ong , Andrew Melfi , Andrew Christlieb

An efficient linear solver plays an important role while solving partial differential equations (PDEs) and partial integro-differential equations (PIDEs) type mathematical models. In most cases, the efficiency depends on the stability and…

Numerical Analysis · Mathematics 2013-04-15 Samir Kumar Bhowmik

This paper presents a numerical study on multigrid algorithms of $V$-cycle type for problems posed in the Hilbert space $H(\mathbf{curl})$ in three dimensions. The multigrid methods are designed for discrete problems originated from the…

Numerical Analysis · Mathematics 2022-09-07 Duk-Soon Oh