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Source: mpi4py-fft
Section: python
Priority: optional
Maintainer: Debian Science Maintainers <debian-science-maintainers@lists.alioth.debian.org>
Uploaders: Drew Parsons <dparsons@debian.org>
Build-Depends: debhelper-compat (= 12),
cython3,
dh-python,
libfftw3-dev,
mpi-default-dev,
python3-all-dev,
python3-setuptools,
python3-mpi4py,
python3-numpy,
python3-sphinx,
python3-sphinx-rtd-theme,
texinfo
Standards-Version: 4.4.0
Homepage: https://bitbucket.org/mpi4py/mpi4py-fft
Vcs-Browser: https://salsa.debian.org/science-team/mpi4py-fft
Vcs-Git: https://salsa.debian.org/science-team/mpi4py-fft.git
Package: python3-mpi4py-fft
Architecture: any
Depends: ${python3:Depends}, ${shlibs:Depends}, ${misc:Depends}
Suggests: python-mpi4py-fft-doc
Description: 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.
Package: python3-mpi4py-fft-doc
Architecture: all
Section: doc
Depends: libjs-mathjax, ${sphinxdoc:Depends}, ${misc:Depends}
Description: 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.
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