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mpi4py-fft package

mpi4py-fft 2.0.3-3build1 source package in Ubuntu

Changelog

mpi4py-fft (2.0.3-3build1) focal; urgency=medium

  * No-change rebuild to build with python3.8.

 -- Matthias Klose <email address hidden>  Fri, 18 Oct 2019 18:52:25 +0000

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Uploaded by:
Matthias Klose
Uploaded to:
Focal
Original maintainer:
Debian Science Team
Architectures:
any all
Section:
misc
Urgency:
Medium Urgency

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mpi4py-fft_2.0.3.orig.tar.bz2 151.2 KiB 9d6d1bb9b9fd7ba3dcdba8350ffc8992879c12fcea8a16dfb4fc4a0c0f1c5397
mpi4py-fft_2.0.3-3build1.debian.tar.xz 3.9 KiB a506d4e867bc7c5e4fc38eb9cc9f6eb09bdcd33b110c84a372a873bc16369e91
mpi4py-fft_2.0.3-3build1.dsc 2.2 KiB 19eff9ddf377b04e3a72bca10eadd69044366cf7464ce16ba137c2d98c9b6a26

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Binary packages built by this source

python3-mpi4py-fft: a Python package for computing Fast Fourier Transforms (FFTs) with MPI

 mpi4py-fft is a Python package for computing Fast Fourier Transforms
 (FFTs). Large arrays are distributed and communications are handled
 under the hood by MPI for Python (mpi4py). To distribute large arrays
 we are using a new and completely generic algorithm that allows for
 any index set of a multidimensional array to be distributed. We can
 distribute just one index (a slab decomposition), two index sets
 (pencil decomposition) or even more for higher-dimensional arrays.
 .
 In mpi4py-fft there is also included a Python interface to the FFTW
 library. This interface can be used without MPI, much like pyfftw,
 and even for real-to-real transforms, like discrete cosine or sine
 transforms.
 .
 The package provides a Python interface to FFTW, but with MPI
 parallelisation. This enables strong scaling tested to 16000 cores,
 or weak scaling tested to 2000 cores. The algorithm is documented at
 https://arxiv.org/abs/1804.09536
 .
 This package installs the library for Python 3.

python3-mpi4py-fft-dbgsym: debug symbols for python3-mpi4py-fft
python3-mpi4py-fft-doc: a Python package for computing Fast Fourier Transforms (FFTs) with MPI (docs)

 mpi4py-fft is a Python package for computing Fast Fourier Transforms
 (FFTs). Large arrays are distributed and communications are handled
 under the hood by MPI for Python (mpi4py). To distribute large arrays
 we are using a new and completely generic algorithm that allows for
 any index set of a multidimensional array to be distributed. We can
 distribute just one index (a slab decomposition), two index sets
 (pencil decomposition) or even more for higher-dimensional arrays.
 .
 In mpi4py-fft there is also included a Python interface to the FFTW
 library. This interface can be used without MPI, much like pyfftw,
 and even for real-to-real transforms, like discrete cosine or sine
 transforms.
 .
 The package provides a Python interface to FFTW, but with MPI
 parallelisation. This enables strong scaling tested to 16000 cores,
 or weak scaling tested to 2000 cores. The algorithm is documented at
 https://arxiv.org/abs/1804.09536
 .
 This is the common documentation package.