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# pfd-parallel - Massively Parallel Partial Fraction Decomposition
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Note: The information below, and more details, can be found in our wiki
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<p align="center">
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<a href="https://github.com/singular-gpispace/pfd-parallel/wiki">Documentation of the pfd-parallel project</a>
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</p>
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This package provide a massively parallel framework for partial fraction decomposition of
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rational functions based on the [Singular/GPI-Space framework](https://www.mathematik.uni-kl.de/~boehm/singulargpispace/).
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The project is supported by [Project B5](https://www.computeralgebra.de/sfb/projects/singular-a-new-level-of-abstraction-and-performance/) of [SFB-TRR 195](https://www.computeralgebra.de/sfb/) and [SymbTools](https://rptu.de/forschung/forschungsinitiative-rlp/symbtools) of [Forschungsinitiative RLP](https://mwg.rlp.de/de/themen/wissenschaft/forschung-transfer-und-innovation/forschung-und-innovation/forschungsinitiative-des-landes-rlp/).
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Our implementation is based on a combination of the following two algorithms:
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1) the enhanced Leinartas' algorithm described in the paper
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Janko Boehm, Marcel Wittmann, Zihao Wu, Yingxuan Xu, and Yang Zhang:
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IBP reduction coefficients made simple, JHEP 12 (2020) 054,
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which has been implemened in [Singular](https://www.singular.uni-kl.de) in the library
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[pfd.lib](https://github.com/Singular/Singular/blob/spielwiese/Singular/LIB/pfd.lib).
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2) the MultivariateApart algorithm as described in
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Matthias Heller, Andreas von Manteuffel, Comput.Phys.Commun. 271 (2022) 108174
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Although applicable in general, the primary aim of our package is the partial fraction
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decomposition of integration-by-parts coefficients in high energy physics.
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Our package relies on code developed in the repository
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[framework](https://github.com/singular-gpispace/framework)
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implemented primarily by Lukas Ristau.
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Since most useful in applications in high energy physics, the main function of our framework applies the partial fraction decoposition
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function to a specified subset of entries of a two-dimensional array of rational functions.
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To use the framework, it is required to install Singular, GPI-Space,
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some of their dependencies and the project code itself. In the following we provide two different
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ways of installation. The preferable way is the use the supercomputing package manager Spack, which will take

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