Adaptive numerical simulations with Trixi.jl: A case study of Julia for scientific computing
Mathematical Software
2022-01-19 v2 Numerical Analysis
Numerical Analysis
Computational Physics
Abstract
We present Trixi.jl, a Julia package for adaptive high-order 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 simulation-focused scientific computing, an area that is still dominated by traditional high-performance computing languages such as C, C++, and Fortran.
Keywords
Cite
@article{arxiv.2108.06476,
title = {Adaptive numerical simulations with Trixi.jl: A case study of Julia for scientific computing},
author = {Hendrik Ranocha and Michael Schlottke-Lakemper and Andrew R. Winters and Erik Faulhaber and Jesse Chan and Gregor J. Gassner},
journal= {arXiv preprint arXiv:2108.06476},
year = {2022}
}