Composite matrix construction for structured grid adaptive mesh refinement
Structured-grid adaptive mesh refinement (SAMR) is an approach to mesh generation that supports structured access to data and adaptive mesh refinement for discretized partial differential equations (PDEs). Solution algorithms often require that an inverse of an operator be applied, a system of algeb...
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ftcdlib:oai:escholarship.org:ark:/13030/qt88x5c6bp 2024-02-04T10:01:17+01:00 Composite matrix construction for structured grid adaptive mesh refinement Adams, Mark F Cornford, Stephen L Martin, Daniel F McCorquodale, Peter 2019-11-01 application/pdf https://escholarship.org/uc/item/88x5c6bp unknown eScholarship, University of California qt88x5c6bp https://escholarship.org/uc/item/88x5c6bp public Information and Computing Sciences Applied Computing Algebraic multigrid Preconditioning PETSc Adaptive mesh refinement Mathematical Sciences Physical Sciences Nuclear & Particles Physics article 2019 ftcdlib 2024-01-08T19:06:07Z Structured-grid adaptive mesh refinement (SAMR) is an approach to mesh generation that supports structured access to data and adaptive mesh refinement for discretized partial differential equations (PDEs). Solution algorithms often require that an inverse of an operator be applied, a system of algebraic equations must be solved, and this process is often the primary computational cost in an application. SAMR is well suited to geometric multigrid solvers, which can be effective, but often do not adapt well to complex geometry including material coefficients. Algebraic multigrid (AMG) is more robust in the face of complex geometry, in both boundary conditions and internal material interfaces. AMG requires a stored matrix linearization of the operator. We discuss an approach, and an implementation in the Chombo block-structured AMR framework, for constructing composite grid matrices from a SAMR hierarchy of grids for use in linear solvers in the PETSc numerical library. We consider a case study with the Chombo-based BISICLES ice sheet modeling application. Article in Journal/Newspaper Ice Sheet University of California: eScholarship |
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Open Polar |
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University of California: eScholarship |
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unknown |
topic |
Information and Computing Sciences Applied Computing Algebraic multigrid Preconditioning PETSc Adaptive mesh refinement Mathematical Sciences Physical Sciences Nuclear & Particles Physics |
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Information and Computing Sciences Applied Computing Algebraic multigrid Preconditioning PETSc Adaptive mesh refinement Mathematical Sciences Physical Sciences Nuclear & Particles Physics Adams, Mark F Cornford, Stephen L Martin, Daniel F McCorquodale, Peter Composite matrix construction for structured grid adaptive mesh refinement |
topic_facet |
Information and Computing Sciences Applied Computing Algebraic multigrid Preconditioning PETSc Adaptive mesh refinement Mathematical Sciences Physical Sciences Nuclear & Particles Physics |
description |
Structured-grid adaptive mesh refinement (SAMR) is an approach to mesh generation that supports structured access to data and adaptive mesh refinement for discretized partial differential equations (PDEs). Solution algorithms often require that an inverse of an operator be applied, a system of algebraic equations must be solved, and this process is often the primary computational cost in an application. SAMR is well suited to geometric multigrid solvers, which can be effective, but often do not adapt well to complex geometry including material coefficients. Algebraic multigrid (AMG) is more robust in the face of complex geometry, in both boundary conditions and internal material interfaces. AMG requires a stored matrix linearization of the operator. We discuss an approach, and an implementation in the Chombo block-structured AMR framework, for constructing composite grid matrices from a SAMR hierarchy of grids for use in linear solvers in the PETSc numerical library. We consider a case study with the Chombo-based BISICLES ice sheet modeling application. |
format |
Article in Journal/Newspaper |
author |
Adams, Mark F Cornford, Stephen L Martin, Daniel F McCorquodale, Peter |
author_facet |
Adams, Mark F Cornford, Stephen L Martin, Daniel F McCorquodale, Peter |
author_sort |
Adams, Mark F |
title |
Composite matrix construction for structured grid adaptive mesh refinement |
title_short |
Composite matrix construction for structured grid adaptive mesh refinement |
title_full |
Composite matrix construction for structured grid adaptive mesh refinement |
title_fullStr |
Composite matrix construction for structured grid adaptive mesh refinement |
title_full_unstemmed |
Composite matrix construction for structured grid adaptive mesh refinement |
title_sort |
composite matrix construction for structured grid adaptive mesh refinement |
publisher |
eScholarship, University of California |
publishDate |
2019 |
url |
https://escholarship.org/uc/item/88x5c6bp |
genre |
Ice Sheet |
genre_facet |
Ice Sheet |
op_relation |
qt88x5c6bp https://escholarship.org/uc/item/88x5c6bp |
op_rights |
public |
_version_ |
1789967039683624960 |