18368

FluidFFT: common API (C++ and Python) for Fast Fourier Transform HPC libraries

Ashwin Vishnu Mohanan, Cyrille Bonamy, Pierre Augier
Linne Flow Centre, Department of Mechanics, KTH, 10044 Stockholm, Sweden
arXiv:1807.01775 [cs.MS], (3 Jul 2018)

@article{mohanan2018fluidfft,

   title={FluidFFT: common API (C++ and Python) for Fast Fourier Transform HPC libraries},

   author={Mohanan, Ashwin Vishnu and Bonamy, Cyrille and Augier, Pierre},

   year={2018},

   month={jul},

   archivePrefix={"arXiv"},

   primaryClass={cs.MS}

}

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 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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