PyClaw: Accessible, Extensible, Scalable Tools for Wave Propagation Problems

Handle URI:
http://hdl.handle.net/10754/333595
Title:
PyClaw: Accessible, Extensible, Scalable Tools for Wave Propagation Problems
Authors:
Ketcheson, David I. ( 0000-0002-1212-126X ) ; Mandli, Kyle; Ahmadia, Aron ( 0000-0002-2573-2481 ) ; Alghamdi, Amal; de Luna, Manuel Quezada; Parsani, Matteo ( 0000-0001-7300-1280 ) ; Knepley, Matthew G.; Emmett, Matthew
Abstract:
Development of scientific software involves tradeoffs between ease of use, generality, and performance. We describe the design of a general hyperbolic PDE solver that can be operated with the convenience of MATLAB yet achieves efficiency near that of hand-coded Fortran and scales to the largest supercomputers. This is achieved by using Python for most of the code while employing automatically wrapped Fortran kernels for computationally intensive routines, and using Python bindings to interface with a parallel computing library and other numerical packages. The software described here is PyClaw, a Python-based structured grid solver for general systems of hyperbolic PDEs [K. T. Mandli et al., PyClaw Software, Version 1.0, http://numerics.kaust.edu.sa/pyclaw/ (2011)]. PyClaw provides a powerful and intuitive interface to the algorithms of the existing Fortran codes Clawpack and SharpClaw, simplifying code development and use while providing massive parallelism and scalable solvers via the PETSc library. The package is further augmented by use of PyWENO for generation of efficient high-order weighted essentially nonoscillatory reconstruction code. The simplicity, capability, and performance of this approach are demonstrated through application to example problems in shallow water flow, compressible flow, and elasticity.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division; Numerical Mathematics Group
Citation:
PyClaw: Accessible, Extensible, Scalable Tools for Wave Propagation Problems 2012, 34 (4):C210 SIAM Journal on Scientific Computing
Publisher:
Society for Industrial & Applied Mathematics (SIAM)
Journal:
SIAM Journal on Scientific Computing
Issue Date:
15-Aug-2012
DOI:
10.1137/110856976
Type:
Article
ISSN:
1064-8275; 1095-7197
Additional Links:
http://epubs.siam.org/doi/abs/10.1137/110856976; http://bitbucket.org/ahmadia/pyclaw-sisc-rr; http://numerics.kaust.edu.sa/papers/pyclaw-sisc/pyclaw-sisc.html; http://arxiv.org/abs/1111.6583
Appears in Collections:
Articles; Numerical Mathematics Group; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorKetcheson, David I.en
dc.contributor.authorMandli, Kyleen
dc.contributor.authorAhmadia, Aronen
dc.contributor.authorAlghamdi, Amalen
dc.contributor.authorde Luna, Manuel Quezadaen
dc.contributor.authorParsani, Matteoen
dc.contributor.authorKnepley, Matthew G.en
dc.contributor.authorEmmett, Matthewen
dc.date.accessioned2014-11-03T15:26:58Z-
dc.date.available2014-11-03T15:26:58Z-
dc.date.issued2012-08-15en
dc.identifier.citationPyClaw: Accessible, Extensible, Scalable Tools for Wave Propagation Problems 2012, 34 (4):C210 SIAM Journal on Scientific Computingen
dc.identifier.issn1064-8275en
dc.identifier.issn1095-7197en
dc.identifier.doi10.1137/110856976en
dc.identifier.urihttp://hdl.handle.net/10754/333595en
dc.description.abstractDevelopment of scientific software involves tradeoffs between ease of use, generality, and performance. We describe the design of a general hyperbolic PDE solver that can be operated with the convenience of MATLAB yet achieves efficiency near that of hand-coded Fortran and scales to the largest supercomputers. This is achieved by using Python for most of the code while employing automatically wrapped Fortran kernels for computationally intensive routines, and using Python bindings to interface with a parallel computing library and other numerical packages. The software described here is PyClaw, a Python-based structured grid solver for general systems of hyperbolic PDEs [K. T. Mandli et al., PyClaw Software, Version 1.0, http://numerics.kaust.edu.sa/pyclaw/ (2011)]. PyClaw provides a powerful and intuitive interface to the algorithms of the existing Fortran codes Clawpack and SharpClaw, simplifying code development and use while providing massive parallelism and scalable solvers via the PETSc library. The package is further augmented by use of PyWENO for generation of efficient high-order weighted essentially nonoscillatory reconstruction code. The simplicity, capability, and performance of this approach are demonstrated through application to example problems in shallow water flow, compressible flow, and elasticity.en
dc.language.isoenen
dc.publisherSociety for Industrial & Applied Mathematics (SIAM)en
dc.relation.urlhttp://epubs.siam.org/doi/abs/10.1137/110856976en
dc.relation.urlhttp://bitbucket.org/ahmadia/pyclaw-sisc-rren
dc.relation.urlhttp://numerics.kaust.edu.sa/papers/pyclaw-sisc/pyclaw-sisc.htmlen
dc.relation.urlhttp://arxiv.org/abs/1111.6583en
dc.rightsArchived with thanks to SIAM Journal on Scientific Computingen
dc.subjectscientific softwareen
dc.subjectwave propagationen
dc.subjectPythonen
dc.subjecthyperbolic PDEsen
dc.subjectClawpacken
dc.titlePyClaw: Accessible, Extensible, Scalable Tools for Wave Propagation Problemsen
dc.typeArticleen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.contributor.departmentNumerical Mathematics Groupen
dc.identifier.journalSIAM Journal on Scientific Computingen
dc.eprint.versionPublisher's Version/PDFen
dc.contributor.institutionUniversity of Texas at Austin, Austin, TX 78712-0027en
dc.contributor.institutionTexas A&M University, College Station, TX 77843en
dc.contributor.institutionUniversity of Chicago, Chicago, IL 60637en
dc.contributor.institutionUniversity of North Carolina at Chapel Hill, Chapel Hill, NC 27599en
dc.contributor.affiliationKing Abdullah University of Science and Technology (KAUST)en
kaust.authorKetcheson, David I.en
kaust.authorAhmadia, Aronen
kaust.authorAlghamdi, Amalen
kaust.authorParsani, Matteoen
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