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docs/source/conf.py

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# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom
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# ones.
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extensions = [
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'sphinx.ext.graphviz',
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]
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# Add any paths that contain templates here, relative to this directory.
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# Add any paths that contain custom static files (such as style sheets) here,
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# relative to this directory. They are copied after the builtin static files,
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# so a file named "default.css" will overwrite the builtin "default.css".
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html_static_path = ['_static']
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html_static_path = ['_static']

docs/source/index.rst

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pages/api.rst
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pages/benchmarks.rst
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pages/publications.rst
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pages/contributing.rst

docs/source/pages/contributing.rst

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=============
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Contributing
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=============
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Overview of the contribution process
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====================================
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The graph below illustrates the general process for contributing code
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changes to 2decomp&fft:
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.. graphviz::
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digraph G {
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review[shape="diamond", label="Changes approved"]
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commit[label="commit changes locally"]
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PR[label="Open/update Pull Request"];
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Idea -> "Open new issue" -> commit -> PR
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PR -> review
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review -> merge [label="yes"]
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review -> commit [label=" no"]
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"Pick existing issue" -> commit
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{
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rank=sink;
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review; merge
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}
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}
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Contributions are accepeted in the form of pull requests targeting the
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`main` branch on the 2decomp&fft GitHub repository. See `(GitHub docs)
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Creating a pull request
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<https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/proposing-changes-to-your-work-with-pull-requests/creating-a-pull-request>`_.
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By default your GitHub account will not be able to push changes to the
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2decomp&fft repo, and you will have to open the pull request from a fork. See
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`(GitHub docs) Creating a pull request from a fork
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<https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/proposing-changes-to-your-work-with-pull-requests/creating-a-pull-request-from-a-fork>`_.
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Note that the whole process is **driven by issues**. If you found a
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bug not currently referenced by an existing issue, or have an idea on
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how to improve a part of 2decomp&fft, please open a new item on the issue
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tracker before opening a pull request.
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docs/source/pages/fft.rst

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=========================
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Fast Fourier Transforms
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=========================
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The Discrete Fourier Transform (DFT) plays an important role in many scientific and technical applications, including time-series and waveform analysis, solutions to linear partial
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differential equations, convolution, digital signal processing, and image filtering. Many algorithms have been proposed to compute DFTs with a good efficiency and the most famous clas of efficient algorithms is generally referred to as fast Fourier transform (FFT) algorithms.
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The 2Decomp&FFT is providing an API to perform FFTs at scale using a 2D Domain Decomposition on CPUs and on GPUs. There are hundreds of FFT software packages available but only few of them suitable for multi-GPUs.
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readme.md

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test

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