FluidSim: Modular, Object-Oriented Python Package for High-Performance CFD Simulations

Ashwin Vishnu Mohanan,Cyrille Bonamy,Pierre Augier,Miguel Calpe Linares

doi:10.5334/jors.239

Abstract

The Python package fluidsim is introduced in this article as an extensible framework for Computational Fluid Mechanics (CFD) solvers. It is developed as a part of FluidDyn project (Augier et al., 2018), an effort to promote open-source and open-science collaboration within fluid mechanics community and intended for both educational as well as research purposes. Solvers in fluidsim are scalable, High-Performance Computing (HPC) codes which are powered under the hood by the rich, scientific Python ecosystem and the Application Programming Interfaces (API) provided by fluiddyn and fluidfft packages (Mohanan et al., 2018). The present article describes the design aspects of fluidsim, viz. use of Python as the main language; focus on the ease of use, reuse and maintenance of the code without compromising performance. The implementation details including optimization methods, modular organization of features and object-oriented approach of using classes to implement solvers are also briefly explained. Currently, fluidsim includes solvers for a variety of physical problems using different numerical methods (including finite-difference methods). However, this metapaper shall dwell only on the implementation and performance of its pseudo-spectral solvers, in particular the two- and three-dimensional Navier-Stokes solvers. We investigate the performance and scalability of fluidsim in a state of the art HPC cluster. Three similar pseudo-spectral CFD codes based on Python (Dedalus, SpectralDNS) and Fortran (NS3D) are presented and qualitatively and quantitatively compared to fluidsim. The source code is hosted at Bitbucket as a Mercurial repository bitbucket.org/fluiddyn/fluidsim and the documentation generated using Sphinx can be read online at fluidsim.readthedocs.io.

Highlights

The Python package fluidsim is introduced in this article as an extensible framework for Computational Fluid Mechanics (CFD) solvers
It is developed as a part of FluidDyn project [2], an effort to promote opensource and open-science collaboration within fluid mechanics community and intended for both educational as well as research purposes
Solvers in fluidsim are scalable, High-Performance Computing (HPC) codes which are powered under the hood by the rich, scientific Python ecosystem and the Application Programming Interfaces (API) provided by fluiddyn and fluidfft packages [11]

Summary

SOFTWARE METAPAPER

FluidSim: Modular, Object-Oriented Python Package for High-Performance CFD Simulations. Advanced users, who may extend fluidsim by developing customized solvers for new problems by taking advantage of built-in operators and time-stepping classes. A simple 2D Navier-Stokes simulation can be launched using the following Python script: from fluidsim.solvers.ns2d.solver import Simul params = Simul.create_default_params() # Modify parameters as needed sim = Simul(params) sim.time_stepping.start(). Note that while the 3D Navier-Stokes solver relies on some generic base classes, such as Operators PseudoSpectral3D and TimeSteppingPseudo Spectral, shared with other solvers for other purposes there are solver-specific classes The latter is often inherited from the base classes in fluidsim.base or classes available in other solvers — this made possible by the use of an object-oriented approach. The time in pure Python remains for all cases largely negligible compared to the time spent in compiled extensions

Operating System

Findings

Software location Archive