LLNL/parelag

Name: parelag

Owner: Lawrence Livermore National Laboratory

Description: Parallel element agglomeration algebraic multigrid upscaling and solvers.

Created: 2017-07-10 18:17:58.0

Updated: 2018-02-07 21:41:28.0

Pushed: 2018-02-21 22:43:36.0

Homepage: null

Size: 783

Language: C++

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README

Element-Agglomeration Algebraic Multigrid and Upscaling Library

version 2.0

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https://github.com/llnl/parelag

ParElag is a parallel distributed memory C++ library for numerical upscaling of finite element discretizations.

For building instructions, see the file INSTALL. Copyright information and licensing restrictions can be found in the file COPYRIGHT.

ParElag implements upscaling and algebraic multigrid techniques for the efficient solution of the algebraic linear system arising from mixed finite element discretization of saddle point problems. In particular, it constructs upscaled discretization for wide classes of partial differential equations and unstructured meshes in an element-based algebraic multigrid framework. This approach has the potential to be more accurate than classical upscaling techniques based on piecewise polynomial approximation. In fact, the coarse spaces and respective coarse models computed by ParElag not only posses the same stability and approximation properties of the original finite element discretization but also are operator dependent.

ParElag uses the MFEM library (http://mfem.org) for the finite element discretization and supports several solvers from the HYPRE library. Visualization in ParElag is based on GLvis (http://glvis.org).

For examples of using ParElag, see the examples/ directory.

This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. LLNL-CODE-745557.


This work is supported by the National Institutes of Health's National Center for Advancing Translational Sciences, Grant Number U24TR002306. This work is solely the responsibility of the creators and does not necessarily represent the official views of the National Institutes of Health.