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Multigrid is a powerful solver for large-scale linear systems arising from discretized partial differential equations. The convergence theory of multigrid methods for symmetric positive definite problems has been well developed over the…

Numerical Analysis · Mathematics 2022-04-19 Xuefeng Xu

The creation of a volumetric mesh representing the interior of an input polygonal mesh is a common requirement in graphics and computational mechanics applications. Most mesh creation techniques assume that the input surface is not…

Simulation of multiphase poromechanics involves solving a multi-physics problem in which multiphase flow and transport are tightly coupled with the porous medium deformation. To capture this dynamic interplay, fully implicit methods, also…

Numerical Analysis · Mathematics 2021-01-08 Quan M. Bui , Daniel Osei-Kuffuor , Nicola Castelletto , Joshua A. White

Hypergraphs, which use hyperedges to capture groupwise interactions among different entities, have gained increasing attention recently for their versatility in effectively modeling real-world networks. In this paper, we study the problem…

Data Structures and Algorithms · Computer Science 2025-04-04 Haozhe Yin , Kai Wang , Wenjie Zhang , Ying Zhang , Ruijia Wu , Xuemin Lin

Hypergraphs, increasingly utilised to model complex and diverse relationships in modern networks, have gained significant attention for representing intricate higher-order interactions. Among various challenges, cohesive subgraph discovery…

Social and Information Networks · Computer Science 2025-07-14 Dahee Kim , Hyewon Kim , Song Kim , Minseok Kim , Junghoon Kim , Yeon-Chang Lee , Sungsu Lim

This paper describes a massively parallel algebraic multigrid method based on non-smoothed aggregation. It is especially suited for solving heterogeneous elliptic problems as it uses a greedy heuristic algorithm for the aggregation that…

Numerical Analysis · Mathematics 2013-10-01 Markus Blatt , Olaf Ippisch , Peter Bastian

Numerical solvers of Partial Differential Equations (PDEs) are of fundamental significance to science and engineering. To date, the historical reliance on legacy techniques has circumscribed possible integration of big data knowledge and…

Numerical Analysis · Mathematics 2024-08-12 Xi Han , Fei Hou , Hong Qin

Lattice metamaterials enable lightweight, multifunctional structures, yet homogenization-based evaluation of their effective properties remains computationally expensive. Neural surrogates offer speed but often lack the accuracy and…

Graphics · Computer Science 2026-04-30 Yu Xing , Yang Liu , Tianyang Xue , Lin Lu

In recent years, topology optimization has been developed sufficiently and many researchers have concentrated on enhancing to computationally numerical algorithms for computational effectiveness of this method. Along with the development of…

Numerical Analysis · Mathematics 2023-01-19 Nam G. Luu , Thanh T. Banh

Hierarchical code coupling strategies make it possible to combine the results of individual numerical solvers into a self-consistent symplectic solution. We explore the possibility of allowing such a coupling strategy to be non-intrusive.…

Instrumentation and Methods for Astrophysics · Physics 2020-04-22 Simon Portegies Zwart , Inti Pelupessy , Carmen Martinez-Barbosa , Arjen van Elteren , Steve McMillan

The challenge to fully exploit the potential of existing and upcoming scientific instruments like large single-dish radio telescopes is to process the collected massive data effectively and efficiently. As a "quasi 2D stencil computation"…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-07-12 Hao Wang , Ce Yu , Jian Xiao , Shanjiang Tang , Min Long , Ming Zhu

Algebraic multigrid (AMG) is often an effective solver for symmetric positive definite (SPD) linear systems resulting from the discretization of general elliptic PDEs, or the spatial discretization of parabolic PDEs. However, convergence…

Numerical Analysis · Mathematics 2019-09-10 Thomas A. Manteuffel , Steffen Munzenmaier , John Ruge , Ben S. Southworth

Multigrid methods are asymptotically optimal algorithms ideal for large-scale simulations. But, they require making numerous algorithmic choices that significantly influence their efficiency. Unlike recent approaches that learn optimal…

Computational Engineering, Finance, and Science · Computer Science 2024-12-12 Dinesh Parthasarathy , Tommaso Bevilacqua , Martin Lanser , Axel Klawonn , Harald Köstler

The computational complexity of naive, sampling-based uncertainty quantification for 3D partial differential equations is extremely high. Multilevel approaches, such as multilevel Monte Carlo (MLMC), can reduce the complexity significantly,…

Computational Engineering, Finance, and Science · Computer Science 2016-07-13 Björn Gmeiner , Daniel Drzisga , Ulrich Ruede , Robert Scheichl , Barbara Wohlmuth

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

We consider an efficient computational framework for speeding up several machine learning algorithms with almost no loss of accuracy. The proposed framework relies on projections via structured matrices that we call Structured Spinners,…

Multi-Party Computation in the Head (MPCitH) algorithms are appealing candidates in the additional US NIST standardization rounds for Post-Quantum Cryptography (PQC) with respect to key sizes and mathematical hardness assumptions. However,…

Cryptography and Security · Computer Science 2024-11-20 Maximilian Schöffel , Hiandra Tomasi , Norbert Wehn

Despite the rapidly evolving field of computational electromagnetics, few open-source tools have managed to tackle the problem of automatic mesh generation for properly discretizing the problem of interest into a finite set of elements…

Signal Processing · Electrical Eng. & Systems 2022-09-22 Apostolos Spanakis-Misirlis

We develop a robust solver for a mixed finite element convex splitting scheme for the Cahn-Hilliard equation. The key ingredient of the solver is a preconditioned minimal residual algorithm (with a multigrid preconditioner) whose…

Numerical Analysis · Mathematics 2017-09-14 Susanne C. Brenner , Amanda E. Diegel , Li-Yeng Sung

A few grid-computing tools are available for public use. However, such systems are usually quite complex and require several man-months to set up. In case the user wishes to set-up an ad-hoc grid in a small span of time, such tools cannot…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-10-07 Gaurav Menghani , Anil Harwani , Yash Londhe , Kalpesh Kagresha
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