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In this work, we consider the reformulation of hierarchical ($\mathcal{H}$) matrix algorithms for many-core processors with a model implementation on graphics processing units (GPUs). $\mathcal{H}$ matrices approximate specific dense…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-09-04 Peter Zaspel

We propose a data-driven and machine-learning-based approach to compute non-Galerkin coarse-grid operators in algebraic multigrid (AMG) methods, addressing the well-known issue of increasing operator complexity. Guided by the AMG theory on…

Numerical Analysis · Mathematics 2023-07-18 Ru Huang , Kai Chang , Huan He , Ruipeng Li , Yuanzhe Xi

In this study, we present an $hp$-multigrid preconditioner for a divergence-conforming HDG scheme for the generalized Stokes and the Navier-Stokes equations using an augmented Lagrangian formulation. Our method relies on conforming…

Numerical Analysis · Mathematics 2023-03-14 Guosheng Fu , Wenzheng Kuang

Isogeometric Analysis (IgA) is a framework for setting up spline-based discretizations of partial differential equations, which has been introduced around a decade ago and has gained much attention since then. If large spline degrees are…

Numerical Analysis · Mathematics 2021-03-05 Christoph Hofer , Stefan Takacs

In this paper, a vertex-based auxiliary space multigrid(V-ASMG) method as a preconditioner of the PCG method is proposed for solving the large sparse linear equations derived from the linear elasticity equations. The main key of such V-ASMG…

Numerical Analysis · Mathematics 2025-05-15 Jiayin Li , Jinbiao Wu , Wenqian Zhang , Jiawen Liu

We propose a general algorithm for non-conforming adaptive mesh refinement (AMR) of unstructured meshes in high-order finite element codes. Our focus is on h-refinement with a fixed polynomial order. The algorithm handles triangular,…

Numerical Analysis · Computer Science 2019-05-13 Jakub Červený , Veselin Dobrev , Tzanio Kolev

In this paper we introduce a novel parallel pipeline for fast and accurate mapping of RNA sequences on servers equipped with multicore processors. Our software, named HPG-Aligner, leverages the speed of the Burrows-Wheeler Transform to map…

In this work we exploit agglomeration based $h$-multigrid preconditioners to speed-up the iterative solution of discontinuous Galerkin discretizations of the Stokes and Navier-Stokes equations. As a distinctive feature $h$-coarsened mesh…

Computational Physics · Physics 2017-09-13 Lorenzo Botti , Alessandro Colombo , Francesco Bassi

We present families of space-time finite element methods (STFEMs) for a coupled hyperbolic-parabolic system of poro- or thermoelasticity. Well-posedness of the discrete problems is proved. Higher order approximations inheriting most of the…

Numerical Analysis · Mathematics 2023-03-14 Mathias Anselmann , Markus Bause , Nils Margenberg , Pavel Shamko

We employ textbook multigrid efficiency (TME), as introduced by Achi Brandt, to construct an asymptotically optimal monolithic multigrid solver for the Stokes system. The geometric multigrid solver builds upon the concept of hierarchical…

Computational Engineering, Finance, and Science · Computer Science 2020-10-27 Nils Kohl , Ulrich Rüde

Multigrid algorithms are among the fastest iterative methods known today for solving large linear and some non-linear systems of equations. Greatly optimized for serial operation, they still have a great potential for parallelism not fully…

Numerical Analysis · Computer Science 2011-08-11 Julian Becerra-Sagredo , Carlos Malaga , Francisco Mandujano

This work introduces an adaptive mesh refinement technique for hierarchical hybrid grids with the goal to reach scalability and maintain excellent performance on massively parallel computer systems. On the block structured hierarchical…

Numerical Analysis · Mathematics 2025-08-11 Benjamin Mann , Ulrich Rüde

Alternating Direction Method of Multipliers (ADMM) has recently been proposed as a potential alternative optimizer to the Stochastic Gradient Descent(SGD) for deep learning problems. This is because ADMM can solve gradient vanishing and…

Optimization and Control · Mathematics 2021-06-24 Junxiang Wang , Zheng Chai , Yue Cheng , Liang Zhao

In recent years, mesh subdivision---the process of forging smooth free-form surfaces from coarse polygonal meshes---has become an indispensable production instrument. Although subdivision performance is crucial during simulation, animation…

Graphics · Computer Science 2019-01-17 Daniel Mlakar , Martin Winter , Hans-Peter Seidel , Markus Steinberger , Rhaleb Zayer

Large Language Models (LLMs) have achieved impressive performance across a wide range of applications. However, they often suffer from hallucinations in knowledge-intensive domains due to their reliance on static pretraining corpora. To…

Information Retrieval · Computer Science 2026-02-10 Lihui Liu , Jiayuan Ding , Subhabrata Mukherjee , Carl J. Yang

The Program Semantic Graph (PSG) introduced in prior work on Dimensional Type Systems and Deterministic Memory Management encodes compilation-relevant properties as binary edge relations between computation nodes. This representation is…

Programming Languages · Computer Science 2026-04-21 Houston Haynes

In this paper, we propose and evaluate the performance of a unified computational framework for preconditioning systems of linear equations resulting from the solution of coupled problems with monolithic schemes. The framework is composed…

Numerical Analysis · Mathematics 2016-08-24 Francesc Verdugo , Wolfgang A. Wall

In this paper, we propose a parallel solver for solving the quasi-static linear poroelasticity coupled with linear elasticity model in the Lagrange multiplier framework. Firstly, we reformulate the model into a coupling of the nearly…

Numerical Analysis · Mathematics 2025-09-09 Zhihao Ge , Chengxin Wang

Many subsurface engineering applications involve tight-coupling between fluid flow, solid deformation, fracturing, and similar processes. To better understand the complex interplay of different governing equations, and therefore design…

We present a space-time multigrid method based on tensor-product space-time finite element discretizations. The method is facilitated by the matrix-free capabilities of the {\ttfamily deal.II} library. It addresses both high-order…

Numerical Analysis · Mathematics 2024-08-12 Nils Margenberg , Peter Munch
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