Source: mpi4py-fft Section: python Priority: optional Maintainer: Debian Science Maintainers Uploaders: Drew Parsons Build-Depends: debhelper-compat (= 13), cython3, dh-python, libfftw3-dev, mpi-default-dev, python3-all-dev, python3-setuptools, python3-mpi4py, python3-numpy, python3-sphinx, Build-Depends-Indep: libjs-mathjax , python3-sphinx-rtd-theme , texinfo Standards-Version: 4.6.2 Homepage: https://github.com/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 Multi-Arch: foreign 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.