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

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

doi:10.5334/jors.239

Cited by 11 publications

(11 citation statements)

References 11 publications

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“…Among the existing flexible spectral solvers for marching in time PDEs in Cartesian geometries, alternatives to Coral include Dedalus (Burns et al, 2020), spectralDNS (Mortensen, 2018), FluidDyn (Augier et al, 2019), and FluidSim (Mohanan et al, 2019). For more complex geometries, options include nek5000 (Fisher, n.d.), Nektar++ (Moxey et al, 2020), Freefem++ (Hecht, 2012), and Fenics (Alnaes et al, 2015).…”

Section: State Of the Fieldmentioning

confidence: 99%

Coral: a parallel spectral solver for fluid dynamics and partial differential equations

Miquel¹

2021

JOSS

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Coral is a fast, flexible, and efficient time-stepper for solving a large class of partial differential equations, at the core of which are the Navier-Stokes equations that govern fluid motions. Written in Fortran and employing the MPI standard for parallelization, the scalability of Coral allows the code to leverage the resources of high-performance computing infrastructures (up to hundreds of thousands of core, see Li & Laizet ( 2010)), while running efficiently on laptops and workstations. Equations are entered by the user in the form of a plain text file following a simple and legible syntax. No coding proficiency in Fortran is required. This flexibility makes Coral suitable for both students and researchers with no coding experience.

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Section: State Of the Fieldmentioning

confidence: 99%

Coral: a parallel spectral solver for fluid dynamics and partial differential equations

Miquel¹

2021

JOSS

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“…5 It first generates the Cython source code as a pair of .pyx and .pxd files containing a class wrapping its C++ counterpart. 6 The Cython files are produced from template files (specialized for the 2D and 3D cases) using the template library mako. Thereafter, Cython [2] generates C++ code with necessary Python bindings, which are then built in the form of extensions or dynamic libraries importable in Python code.…”

Section: Code Organizationmentioning

confidence: 99%

“…html 5. Detailed steps for installation are provided in the documentation 6. Uses an approach similar to guidelines "Using C++ inCython" in the Cython documentation 7.…”

mentioning

confidence: 99%

FluidFFT: Common API (C++ and Python) for Fast Fourier Transform HPC Libraries

Mohanan¹,

Bonamy²,

Augier

2019

JORS

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The Python package fluidfft provides a common Python API for performing Fast Fourier Transforms (FFT) in sequential, in parallel and on GPU with different FFT libraries (FFTW, P3DFFT, PFFT, cuFFT). fluidfft is a comprehensive FFT framework which allows Python users to easily and efficiently perform FFT and the associated tasks, such as computing linear operators and energy spectra. We describe the architecture of the package composed of C++ and Cython FFT classes, Python "operator" classes and Pythran functions. The package supplies utilities to easily test itself and benchmark the different FFT solutions for a particular case and on a particular machine. We present a performance scaling analysis on three different computing clusters and a microbenchmark showing that fluidfft is an interesting solution to write efficient Python applications using FFT.

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“…The code of this package is presented in further detail in its documentation (https://fluiddyn.readthedocs.io/) and some prominent features are presented in the following subsection. A detailed presentation on the above packages can be found in their respective documentations on the web and for fluidfft and fluidsim in the two companion papers [4,5]. The code base was designed to follow Python 2.7 syntax during its genesis.…”

Section: Implementation and Architecture Organization Of The Code In mentioning

confidence: 99%

“…We use FluidDyn (with capital letters) to name the project and fluiddyn for the base package 4. https://matrix.to/#/#fluiddyn-users:matrix.org 5. https://www.freelists.org/list/fluiddyn.…”

mentioning

confidence: 99%

FluidDyn: A Python Open-Source Framework for Research and Teaching in Fluid Dynamics by Simulations, Experiments and Data Processing

Augier¹,

Mohanan²,

Bonamy

2019

JORS

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FluidDyn is a project to foster open-science and open-source in the fluid dynamics community. It is thought of as a research project to channel open-source dynamics, methods and tools to do science. We propose a set of Python packages forming a framework to study fluid dynamics with different methods, in particular laboratory experiments (package fluidlab), simulations (packages fluidfft, fluidsim and fluidfoam) and data processing (package fluidimage). In the present article, we give an overview of the specialized packages of the project and then focus on the base package called fluiddyn, which contains common code used in the specialized packages. Packages fluidfft and fluidsim are described with greater detail in two companion papers [4, 5]. With the project FluidDyn, we demonstrate that specialized scientific code can be written with methods and good practices of the open-source community. The Mercurial repositories are available in Bitbucket (https://bitbucket.org/fluiddyn/). All codes are documented using Sphinx and Read the Docs, and tested with continuous integration run on Bitbucket Pipelines and Travis. To improve the reuse potential, the codes are as modular as possible, leveraging the simple object-oriented programming model of Python. All codes are also written to be highly efficient, using C++, Cython and Pythran to speedup the performance of critical functions.

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

Cited by 11 publications

References 11 publications

Coral: a parallel spectral solver for fluid dynamics and partial differential equations

Coral: a parallel spectral solver for fluid dynamics and partial differential equations

FluidFFT: Common API (C++ and Python) for Fast Fourier Transform HPC Libraries

FluidDyn: A Python Open-Source Framework for Research and Teaching in Fluid Dynamics by Simulations, Experiments and Data Processing

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