Adaptive numerical simulations with Trixi.jl: A case study of Julia for scientific computing
Abstract
We present Trixi.jl, a Julia package for adaptive highorder numerical simulations of hyperbolic partial differential equations. Utilizing Julia's strengths, Trixi.jl is extensible, easy to use, and fast. We describe the main design choices that enable these features and compare Trixi.jl with a mature open source Fortran code that uses the same numerical methods. We conclude with an assessment of Julia for simulationfocused scientific computing, an area that is still dominated by traditional highperformance computing languages such as C, C++, and Fortran.
 Publication:

arXiv eprints
 Pub Date:
 August 2021
 DOI:
 10.48550/arXiv.2108.06476
 arXiv:
 arXiv:2108.06476
 Bibcode:
 2021arXiv210806476R
 Keywords:

 Computer Science  Mathematical Software;
 Mathematics  Numerical Analysis;
 Physics  Computational Physics
 EPrint:
 Proceedings of the JuliaCon Conferences, 2022