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We propose a new approach to learning the subgrid-scale model when simulating partial differential equations (PDEs) solved by the method of lines and their representation in chaotic ordinary differential equations, based on neural ordinary…

Numerical Analysis · Mathematics 2023-04-14 Shinhoo Kang , Emil M. Constantinescu

The Riesz maps of the $L^2$ de Rham complex frequently arise as subproblems in the construction of fast preconditioners for more complicated problems. In this work we present multigrid solvers for high-order finite element discretizations…

Numerical Analysis · Mathematics 2023-12-08 Pablo D. Brubeck , Patrick E. Farrell

We propose a generalized multiscale finite element method (GMsFEM) based on clustering algorithm to study the elliptic PDEs with random coefficients in the multi-query setting. Our method consists of offline and online stages. In the…

Numerical Analysis · Mathematics 2018-08-01 Eric T. Chung , Yalchin Efendiev , Wing Tat Leung , Zhiwen Zhang

This paper presents the use of element-based algebraic multigrid (AMGe) hierarchies, implemented in the ParELAG (Parallel Element Agglomeration Algebraic Multigrid Upscaling and Solvers) library, to produce multilevel preconditioners and…

Numerical Analysis · Mathematics 2023-07-04 Delyan Z. Kalchev , Panayot S. Vassilevski , Umberto Villa

Linear solvers for large and sparse systems are a key element of scientific applications, and their efficient implementation is necessary to harness the computational power of current computers. Algebraic MultiGrid (AMG) preconditioners are…

Numerical Analysis · Mathematics 2022-04-25 Pasqua D'Ambra , Fabio Durastante , Salvatore Filippone

The multiscale complexity of modern problems in computational science and engineering can prohibit the use of traditional numerical methods in multi-dimensional simulations. Therefore, novel algorithms are required in these situations to…

Numerical Analysis · Mathematics 2021-06-15 Cale Harnish , Luke Dalessandro , Karel Matous , Daniel Livescu

Earth system models are developed with a tight coupling to target hardware, often containing specialized code predicated on processor characteristics. This coupling stems from using imperative languages that hard-code computation schedules…

As the need for computational power and efficiency rises, parallel systems become increasingly popular among various scientific fields. While multiple core-based architectures have been the center of attention for many years, the rapid…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-06-11 E. I. Ioannidis , N. Cheimarios , A. N. Spyropoulos , A. G. Boudouvis

Multiphase flows are an important class of fluid flow and their study facilitates the development of diverse applications in industrial, natural, and biomedical systems. We consider a model that uses a continuum description of both phases…

Fluid Dynamics · Physics 2025-08-04 Bindi M. Nagda , Aaron Barrett , Boyce E. Griffith , Aaron L. Fogelson , Jian Du

The goal of this paper is to design optimal multilevel solvers for the finite element approximation of second order linear elliptic problems with piecewise constant coefficients on bisection grids. Local multigrid and BPX preconditioners…

Numerical Analysis · Mathematics 2012-02-13 Long Chen , Michael Holst , Jinchao Xu , Yunrong Zhu

We consider a linear iterative solver for large scale linearly constrained quadratic minimization problems that arise, for example, in optimization with PDEs. By a primal-dual projection (PDP) iteration, which can be interpreted and…

Optimization and Control · Mathematics 2020-12-07 Anton Schiela , Matthias Stöcklein , Martin Weiser

Solving high-dimensional partial differential equations (PDEs) efficiently requires handling multi-scale features across varying resolutions. To address this challenge, we present the Multiwavelet-based Multigrid Neural Operator (M2NO), a…

Machine Learning · Computer Science 2025-12-15 Zhihao Li , Zhilu Lai , Xiaobo Zhang , Wei Wang

We combine concepts from multilevel solvers for partial differential equations (PDEs) with neural network based deep learning and propose a new methodology for the efficient numerical solution of high-dimensional parametric PDEs. An…

Machine Learning · Computer Science 2023-04-05 Cosmas Heiß , Ingo Gühring , Martin Eigel

Multiphysics problems such as multicomponent diffusion, phase transformations in multiphase systems and alloy solidification involve numerical solution of a coupled system of nonlinear partial differential equations (PDEs). Numerical…

Materials Science · Physics 2022-11-24 Vir Karan , A. Maruthi Indresh , Saswata Bhattacharyya

The versatile Arbitrary-DERivative (ADER) scheme is cast in a multilevel framework (ML-ADER) for fast solution of system of linear hyperbolic partial differential equations. The solution is cycled through spatial operators of varying…

Computational Physics · Physics 2017-04-05 S. M. Joshi , A. Chatterjee

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

Support for lower precision computation is becoming more common in accelerator hardware due to lower power usage, reduced data movement and increased computational performance. However, computational science and engineering (CSE) problems…

Numerical Analysis · Mathematics 2021-05-18 Jennifer A. Loe , Christian A. Glusa , Ichitaro Yamazaki , Erik G. Boman , Sivasankaran Rajamanickam

Matrix-free finite element implementations of massively parallel geometric multigrid save memory and are often significantly faster than implementations using classical sparse matrix techniques. They are especially well suited for…

Numerical Analysis · Mathematics 2016-08-24 Simon Bauer , Marcus Mohr , Ulrich Rüde , Jens Weismüller , Markus Wittmann , Barbara Wohlmuth

In this paper, we present a multiscale method for simulations of the multicontinua unsaturated flow problems in heterogeneous fractured porous media. The mathematical model is described by the system of Richards equations for each continuum…

Numerical Analysis · Mathematics 2019-08-02 Denis Spiridonov , Maria Vasilyeva , Eric T. Chung

The key innovation in this paper is an open-source, high-performance iterative solver for high contrast, strongly anisotropic elliptic partial differential equations implemented within dune-pdelab. The iterative solver exploits a robust,…

Numerical Analysis · Mathematics 2020-02-19 Richard Butler , Tim Dodwell , Anne Reinarz , Anhad Sandhu , Robert Scheichl , Linus Seelinger