PetIGA: A framework for highperformance isogeometric analysis
Abstract
We present PetIGA, a code framework to approximate the solution of partial differential equations using isogeometric analysis. PetIGA can be used to assemble matrices and vectors which come from a Galerkin weak form, discretized with NonUniform Rational Bspline basis functions. We base our framework on PETSc, a highperformance library for the scalable solution of partial differential equations, which simplifies the development of largescale scientific codes, provides a rich environment for prototyping, and separates parallelism from algorithm choice. We describe the implementation of PetIGA, and exemplify its use by solving a model nonlinear problem. To illustrate the robustness and flexibility of PetIGA, we solve some challenging nonlinear partial differential equations that include problems in both solid and fluid mechanics. Lastly, we show strong scaling results on up to 4096 cores, which confirm the suitability of PetIGA for large scale simulations.
 Authors:

 King Abdullah Univ. of Science and Technology (KAUST), Thuwal (Saudi Arabia); Centro de Investigacion de Metodos Computacionales (CIMEC), Santa Fe (Argentina); Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET), Santa Fe (Argentina)
 Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
 King Abdullah Univ. of Science and Technology (KAUST), Thuwal (Saudi Arabia)
 Publication Date:
 Research Org.:
 Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
 Sponsoring Org.:
 USDOE
 OSTI Identifier:
 1327764
 Grant/Contract Number:
 AC0500OR22725
 Resource Type:
 Accepted Manuscript
 Journal Name:
 Computer Methods in Applied Mechanics and Engineering
 Additional Journal Information:
 Journal Volume: 308; Journal Issue: C; Journal ID: ISSN 00457825
 Publisher:
 Elsevier
 Country of Publication:
 United States
 Language:
 English
 Subject:
 97 MATHEMATICS AND COMPUTING; isogeometric analysis; highperformance computing; finite element method; opensource software
Citation Formats
Dalcin, Lisandro, Collier, Nathaniel, Vignal, Philippe, Cortes, Adriano M. A., and Calo, Victor M. PetIGA: A framework for highperformance isogeometric analysis. United States: N. p., 2016.
Web. doi:10.1016/j.cma.2016.05.011.
Dalcin, Lisandro, Collier, Nathaniel, Vignal, Philippe, Cortes, Adriano M. A., & Calo, Victor M. PetIGA: A framework for highperformance isogeometric analysis. United States. doi:10.1016/j.cma.2016.05.011.
Dalcin, Lisandro, Collier, Nathaniel, Vignal, Philippe, Cortes, Adriano M. A., and Calo, Victor M. Wed .
"PetIGA: A framework for highperformance isogeometric analysis". United States. doi:10.1016/j.cma.2016.05.011. https://www.osti.gov/servlets/purl/1327764.
@article{osti_1327764,
title = {PetIGA: A framework for highperformance isogeometric analysis},
author = {Dalcin, Lisandro and Collier, Nathaniel and Vignal, Philippe and Cortes, Adriano M. A. and Calo, Victor M.},
abstractNote = {We present PetIGA, a code framework to approximate the solution of partial differential equations using isogeometric analysis. PetIGA can be used to assemble matrices and vectors which come from a Galerkin weak form, discretized with NonUniform Rational Bspline basis functions. We base our framework on PETSc, a highperformance library for the scalable solution of partial differential equations, which simplifies the development of largescale scientific codes, provides a rich environment for prototyping, and separates parallelism from algorithm choice. We describe the implementation of PetIGA, and exemplify its use by solving a model nonlinear problem. To illustrate the robustness and flexibility of PetIGA, we solve some challenging nonlinear partial differential equations that include problems in both solid and fluid mechanics. Lastly, we show strong scaling results on up to 4096 cores, which confirm the suitability of PetIGA for large scale simulations.},
doi = {10.1016/j.cma.2016.05.011},
journal = {Computer Methods in Applied Mechanics and Engineering},
number = C,
volume = 308,
place = {United States},
year = {2016},
month = {5}
}
Web of Science