Type
ArticleAuthors
Ketcheson, David I.
Ranocha, Hendrik

Parsani, Matteo

Waheed, Umair bin

Hadjimichael, Yiannis

KAUST Department
Applied Mathematics and Computational Science ProgramComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Extreme Computing Research Center
Date
2020-11-17Submitted Date
2020-07-13Permanent link to this record
http://hdl.handle.net/10754/666086
Metadata
Show full item recordAbstract
Ordinary differential equations (ODEs) are used to model a vast range of physical and other phenomena. They also arise in the discretization of partial differential equations. In most cases, solutions of differential equations must be approximated by numerical methods. The study of the properties of numerical methods for ODEs comprises an important and large body of knowledge. NodePy (available from https://github.com/ketch/nodepy, with documentation at https://nodepy.readthedocs.io/en/latest/) is a software package for designing and studying the properties of numerical ODE solvers. For the most important classes of methods, NodePy can automatically assess their stability, accuracy, and many other properties. NodePy has also been used as a catalog of coefficients for time integration methods in PDE solver codes.Citation
Ketcheson, D., Ranocha, H., Parsani, M., Waheed, U., & Hadjimichael, Y. (2020). NodePy: A package for the analysis of numerical ODE solvers. Journal of Open Source Software, 5(55), 2515. doi:10.21105/joss.02515Sponsors
Much of the initial NodePy development was performed by D. Ketcheson while he was supported by a DOE Computational Science Graduate Fellowship. Development has also been supported by funding from King Abdullah University of Science and Technology. Additional minor contributions to the code have been provided by Mikael Mortensen, Alex Fikl, Sidafa Conde, John Sellers, Kevin Siswandi, and Colin Macdonald.Publisher
The Open JournalJournal
Journal of Open Source SoftwareAdditional Links
https://joss.theoj.org/papers/10.21105/joss.02515ae974a485f413a2113503eed53cd6c53
10.21105/joss.02515
Scopus Count
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