Adaptive numerical simulations with Trixi.jl: A case study of Julia for scientific computing
Hendrik Ranocha, Michael Schlottke‐Lakemper, Andrew R. Winters, Erik Faulhaber, Jesse Chan, Gregor J. Gassner
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.
Topics & Concepts
FortranComputer scienceComputational scienceCode (set theory)Partial differential equationApplied mathematicsProgramming languageTheoretical computer scienceParallel computingMathematicsMathematical analysisSet (abstract data type)Meteorological Phenomena and SimulationsComputer Graphics and Visualization TechniquesComputational Fluid Dynamics and Aerodynamics