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In this paper, we consider a classical form of optimal algebraic multigrid (AMG) interpolation that directly minimizes the two-grid convergence rate and compare it with the so-called ideal form that minimizes a certain weak approximation…

Numerical Analysis · Mathematics 2017-03-31 James Brannick , Fei Cao , Karsten Kahl , Rob Falgout , Xiaozhe Hu

We design and implement a parallel algebraic multigrid method for isotropic graph Laplacian problems on multicore Graphical Processing Units (GPUs). The proposed AMG method is based on the aggregation framework. The setup phase of the…

Numerical Analysis · Mathematics 2013-02-12 James Brannick , Yao Chen , Xiaozhe Hu , Ludmil Zikatanov

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

We develop a robust matrix-free, communication avoiding parallel, high-degree polynomial preconditioner for the Conjugate Gradient method for large and sparse symmetric positive definite linear systems. We discuss the selection of a scaling…

Numerical Analysis · Mathematics 2022-08-03 L. Bergamaschi , M. Ferronato , G. Isotton , C. Janna , A. Martinez

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

The transition to a sustainable, low-carbon energy future requires transformative advancements in energy and environmental technologies. Carbon capture and sequestration, underground hydrogen storage, and nuclear waste geological disposal…

Efficient numerical solvers for sparse linear systems are crucial in science and engineering. One of the fastest methods for solving large-scale sparse linear systems is algebraic multigrid (AMG). The main challenge in the construction of…

Machine Learning · Computer Science 2020-09-25 Ilay Luz , Meirav Galun , Haggai Maron , Ronen Basri , Irad Yavneh

Solving systems of linear equations is a problem occuring frequently in water engineering applications. Usually the size of the problem is too large to be solved via direct factorization. One can resort to iterative approaches, in…

Machine Learning · Computer Science 2019-06-18 Johannes Sappl , Laurent Seiler , Matthias Harders , Wolfgang Rauch

Detailed understanding of the coupling between fluid flow and solid deformation in porous media is crucial for the development biomedical devices and novel energy technologies relating to a wide range of geological and biological processes.…

Fluid Dynamics · Physics 2021-09-22 Francisco J. Carrillo

We consider the coupled system of equations that describe flow in fractured porous media. To describe such types of problems, multicontinuum and multiscale approaches are used. Because in multicontinuum models, the permeability of each…

Numerical Analysis · Mathematics 2023-05-31 Maria Vasilyeva

Large linear systems are ubiquitous in modern computational science and engineering. The main recipe for solving them is the use of Krylov subspace iterative methods with well-designed preconditioners. Recently, GNNs have been shown to be a…

Machine Learning · Computer Science 2025-02-04 Vladislav Trifonov , Alexander Rudikov , Oleg Iliev , Yuri M. Laevsky , Ivan Oseledets , Ekaterina Muravleva

Recent advances in the field of machine learning open a new era in high performance computing. Applications of machine learning algorithms for the development of accurate and cost-efficient surrogates of complex problems have already…

Numerical Analysis · Mathematics 2022-08-26 Stefanos Nikolopoulos , Ioannis Kalogeris , Vissarion Papadopoulos , George Stavroulakis

Algebraic or geometric multigrid methods are commonly used in numerical solvers as they are a multi-resolution method able to handle problems with multiple scales. In this work, we propose a modification to the commonly-used U-Net neural…

Fluid Dynamics · Physics 2021-05-11 Quang Tuyen Le , Chin Chun Ooi

We provide a new algebraic technique to solve the sequential flow problem in polynomial space. The task is to maximise the flow through a graph where edge capacities can be changed over time by choosing a sequence of capacity labelings from…

Optimization and Control · Mathematics 2026-02-09 Hugo Gimbert , Corto Mascle , Patrick Totzke

The mechanical behaviour of a poroelastic medium permeated by multiple interacting fluid networks can be described by a system of time-dependent partial differential equations known as the multiple-network poroelasticity (MPET) equations or…

Numerical Analysis · Mathematics 2020-10-20 Eleonora Piersanti , Jeonghun J. Lee , Travis Thompson , Kent-Andre Mardal , Marie E. Rognes

For a prescribed porosity, the coupled magma/mantle flow equations can be formulated as a two-field system of equations with velocity and pressure as unknowns. Previous work has shown that while optimal preconditioners for the two-field…

Numerical Analysis · Mathematics 2016-07-08 Sander Rhebergen , Garth N. Wells , Andrew J. Wathen , Richard F. Katz

In this note, the existing porousMultiphaseFoam toolbox, developed initially for any two-phase flow in porous media is extended to the specific case of the Richards' equation which neglect the pressure gradient of the non-wetting phase.…

Computational Engineering, Finance, and Science · Computer Science 2015-10-07 Pierre Horgue , Jacques Franc , Romain Guibert , Gérald Debenest

The numerical simulation of multiphase flows presents several challenges, namely the transport of different phases within de domain and the inclusion of capillary effects. Here, these are approached by enforcing a discrete…

Fluid Dynamics · Physics 2021-10-11 Nicol'as Valle , F. Xavier Trias , Jes'us Castro

The implementation of efficient multigrid preconditioners for elliptic partial differential equations (PDEs) is a challenge due to the complexity of the resulting algorithms and corresponding computer code. For sophisticated finite element…

Mathematical Software · Computer Science 2016-10-07 Lawrence Mitchell , Eike Hermann Müller

In this paper, we combine discrete empirical interpolation techniques, global mode decomposition methods, and local multiscale methods, such as the Generalized Multiscale Finite Element Method (GMsFEM), to reduce the computational…

Numerical Analysis · Mathematics 2023-07-19 Manal Alotaibi , Victor M. Calo , Yalchin Efendiev , Juan Galvis , Mehdi Ghommem