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In this paper, we study the stability and convergence of a decoupled and linearized mixed finite element method (FEM) for incompressible miscible displacement in a porous media whose permeability and porosity are discontinuous across some…

Numerical Analysis · Mathematics 2014-06-18 Buyang Li , Hongxing Rui , Chaoxia Yang

Parallel finite element algorithms based on object-oriented concepts are presented. Moreover, the design and implementation of a data structure proposed are utilized in realizing a parallel geometric multigrid method. The ParFEMapper and…

Mathematical Software · Computer Science 2016-09-19 Sashikumaar Ganesan , Volker John , Gunar Matthies , Raviteja Meesala , Shamim Abdus , Ulrich Wilbrandt

This paper pushes further the intrinsic capabilities of the GFEM$^{gl}$ global-local approach introduced initially in [1]. We develop a distributed computing approach using MPI (Message Passing Interface) both for the global and local…

Numerical Analysis · Mathematics 2023-02-22 Alexis Salzman , Nicolas Moës

Processing large complex networks like social networks or web graphs has recently attracted considerable interest. In order to do this in parallel, we need to partition them into pieces of about equal size. Unfortunately, previous parallel…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-01-27 Henning Meyerhenke , Peter Sanders , Christian Schulz

Finite mixture models have been widely used for the modelling and analysis of data from heterogeneous populations. Maximum likelihood estimation of the parameters is typically carried out via the Expectation-Maximization (EM) algorithm. The…

Computation · Statistics 2016-06-08 Sharon X Lee , Kaleb L Lee , Geoffrey J McLachlan

The paper aims to establish a fully discrete finite element (FE) scheme and provide cost-effective solutions for one-dimensional time-space Caputo-Riesz fractional diffusion equations on a bounded domain $\Omega$. Firstly, we construct a…

Numerical Analysis · Mathematics 2017-07-27 Xiaoqiang Yue , Weiping Bu , Shi Shu , Menghuan Liu , Shuai Wang

In this work, we develop and analyze a higher-order finite element method for the multidimensional fragmentation equation. To the best of our knowledge, this is the first study to establish a rigorous, conforming finite element framework…

Numerical Analysis · Mathematics 2026-04-10 Arushi , Naresh Kumar

To prepare images for better segmentation, we need preprocessing applications, such as smoothing, to reduce noise. In this paper, we present an enhanced computation method for smoothing 2D object in binary case. Unlike existing approaches,…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-03-31 Ramzi Mahmoudi , Mohamed Akil

We present a shared-memory parallelization of flow-based refinement, which is considered the most powerful iterative improvement technique for hypergraph partitioning at the moment. Flow-based refinement works on bipartitions, so current…

Data Structures and Algorithms · Computer Science 2022-01-06 Lars Gottesbüren , Tobias Heuer , Peter Sanders

We focus on the study of multigrid methods with aggressive coarsening and polynomial smoothers for the solution of the linear systems corresponding to finite difference/element discretizations of the Laplace equation. Using local Fourier…

Numerical Analysis · Mathematics 2014-12-02 James Brannick , Xiaozhe Hu , Carmen Rodrigo , Ludmil Zikatanov

Particle-in-cell methods couple mesh-based methods for the solution of continuum mechanics problems, with the ability to advect and evolve particles. They have a long history and many applications in scientific computing. However, they have…

Numerical Analysis · Mathematics 2019-09-12 R. Gassmoeller , E. Heien , E. G. Puckett , W. Bangerth

We present a parallel computing strategy for a hybridizable discontinuous Galerkin (HDG) nested geometric multigrid (GMG) solver. Parallel GMG solvers require a combination of coarse-grain and fine-grain parallelism to improve time to…

Numerical Analysis · Mathematics 2019-07-18 M. S. Fabien , M. G. Knepley , R. T. Mills , B. M. Riviere

In this paper, we develop a new parallel auxiliary grid algebraic multigrid (AMG) method to leverage the power of graphic processing units (GPUs). In the construction of the hierarchical coarse grid, we use a simple and fixed coarsening…

Numerical Analysis · Mathematics 2012-12-07 Lu Wang , Xiaozhe Hu , Jonathan Cohen , Jinchao Xu

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

Standard gradient-based iteration algorithms for optimization, such as gradient descent and its various proximal-based extensions to nonsmooth problems, are known to converge slowly for ill-conditioned problems, sometimes requiring many…

Numerical Analysis · Mathematics 2026-03-24 G. H. M. Araújo , O. A. Krzysik , H. De Sterck

Mesh adaptivity is a useful tool for efficient solution to partial differential equations in very complex geometries. In the present paper we discuss the use of polygonal mesh refinement in order to tackle two common issues: first,…

Numerical Analysis · Mathematics 2021-12-21 Stefano Berrone , Alessandro D'Auria

A new field of numerical astrophysics is introduced which addresses the solution of large, multidimensional structural or slowly-evolving problems (rotating stars, interacting binaries, thick advective accretion disks, four dimensional…

Astrophysics · Physics 2009-10-30 David L. Meier

The present paper describes a parallel unstructured-mesh Plasma simulation code based on Finite Volume method. The code dynamically refines and coarses mesh for accurate resolution of the different features regarding the electron density.…

Computational Physics · Physics 2022-12-26 Imad Kissami , Souhail Maazioui , Fayssal Benkhaldoun

The geometric multigrid algorithm is an efficient numerical method for solving a variety of elliptic partial differential equations (PDEs). The method damps errors at progressively finer grid scales, resulting in faster convergence compared…

Numerical Analysis · Mathematics 2024-03-14 Francisco Holguin , GS Sidharth , Gavin Portwood

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
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