PyAlbany: A Python interface to the C++ multiphysics solver Albany
Albany is a parallel C++ finite element library for solving forward and inverse problems involving partial differential equations (PDEs). In this paper we introduce PyAlbany, a newly developed Python interface to the Albany library. PyAlbany can be used to effectively drive Albany enabling fast and...
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| Published in: | Journal of computational and applied mathematics Vol. 425; no. C; p. 115037 |
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| Main Authors: | , , |
| Format: | Journal Article |
| Language: | English |
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Belgium
Elsevier B.V
01.06.2023
Elsevier |
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| ISSN: | 0377-0427, 1879-1778 |
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| Abstract | Albany is a parallel C++ finite element library for solving forward and inverse problems involving partial differential equations (PDEs). In this paper we introduce PyAlbany, a newly developed Python interface to the Albany library. PyAlbany can be used to effectively drive Albany enabling fast and easy analysis and post-processing of applications based on PDEs that are pre-implemented in Albany. PyAlbany relies on the library PyBind11 to bind Python with C++ Albany code. Here we detail the implementation of PyAlbany and showcase its capabilities through a number of examples targeting a heat-diffusion problem. In particular we consider (1) the generation of samples for a Monte Carlo application, (2) a scalability study, (3) a study of parameters on the performance of a linear solver, and (4) a tool for performing eigenvalue decompositions of matrix-free operators for a Bayesian inference application. |
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| AbstractList | Albany is a parallel C++ finite element library for solving forward and inverse problems involving partial differential equations (PDEs). In this paper we introduce PyAlbany, a newly developed Python interface to the Albany library. PyAlbany can be used to effectively drive Albany enabling fast and easy analysis and post-processing of applications based on PDEs that are pre-implemented in Albany. PyAlbany relies on the library PyBind11 to bind Python with C++ Albany code. Here we detail the implementation of PyAlbany and showcase its capabilities through a number of examples targeting a heat-diffusion problem. In particular we consider (1) the generation of samples for a Monte Carlo application, (2) a scalability study, (3) a study of parameters on the performance of a linear solver, and (4) a tool for performing eigenvalue decompositions of matrix-free operators for a Bayesian inference application. |
| ArticleNumber | 115037 |
| Author | Hartland, Tucker Perego, Mauro Liegeois, Kim |
| Author_xml | – sequence: 1 givenname: Kim orcidid: 0000-0002-1182-4078 surname: Liegeois fullname: Liegeois, Kim email: knliege@sandia.gov organization: Center for Computing Research, Sandia National Laboratories, United States of America – sequence: 2 givenname: Mauro surname: Perego fullname: Perego, Mauro organization: Center for Computing Research, Sandia National Laboratories, United States of America – sequence: 3 givenname: Tucker surname: Hartland fullname: Hartland, Tucker organization: University of California, Merced, United States of America |
| BackLink | https://www.osti.gov/biblio/1909486$$D View this record in Osti.gov |
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| Copyright | 2023 Elsevier B.V. |
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| Keywords | Python front-end Python interface Nonintrusive parameter computations Albany |
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