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Adopt CodeMeta (#2237)
* added codemeta.json * suggested changes * Added orcid * Update maintainers and authors in pyproject.toml * SEO and unify keywords * Rearranged authors and maintainers * added publication and optional software * Add HiRSE_PS in acknowledgments section in README.md * Update acknowledgment links in README.md * Fix project name in acknowledgments section * use maintainer instead of contributor * Added funding Apparently this is still best practice even though the generator disagrees --------- Co-authored-by: Claudia Comito <39374113+ClaudiaComito@users.noreply.github.com> Co-authored-by: Thomas Saupe <39156931+brownbaerchen@users.noreply.github.com>
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‎README.md‎

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</details>
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### Acknowledgments
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This work was funded by the **Helmholtz Association Initiative and Networking Fund** (Project **ZT-I-0003**, "Helmholtz Analytics Framework"); the **Helmholtz AI** platform grant; the **European Space Agency (ESA)** (Programme [4000144045](https://activities.esa.int/index.php/4000144045)); the **Helmholtz Association Science Serve call 2025** (Project **DB002891**, [HeatHub](https://hifis.net/announcement/2026/01/08/scienceserve-awardees/)); the Google Summer of Code 2022 program.
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This work was funded by the **Helmholtz Association Initiative and Networking Fund** (Project **ZT-I-0003**, "Helmholtz Analytics Framework"); the **Helmholtz AI** platform grant; the **European Space Agency (ESA)** (Programme [4000144045](https://activities.esa.int/index.php/4000144045)); the **Helmholtz Association Innovation Fund** (Project [HiRSE](https://www.helmholtz-hirse.de/)); the **Helmholtz Association ScienceServe call 2025** (Project **DB002891**, [HeatHub](https://hifis.net/announcement/2026/01/08/scienceserve-awardees/)); the Google Summer of Code 2022 program.
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### License
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Heat is distributed under the **MIT license**. See the [LICENSE](https://github.com/helmholtz-analytics/heat/blob/main/LICENSE) file for details.

‎codemeta.json‎

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"description": "The Helmholtz Analytics Toolkit (Heat) is a powerful Python library for massively-parallel HPC. Its hardware-agnostic design, based on PyTorch and MPI, enables seamless scaling on Nvidia, AMD, and ARM architectures, excelling where task-parallel frameworks show limitations.",
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‎pyproject.toml‎

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{ name = "Daniel Coquelin", email = "daniel.coquelin@kit.edu"},
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{ name = "Kai Krajsek", email = "k.krajsek@fz-juelich.de"},
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{ name = "Claudia Comito", email = "c.comito@fz-juelich.de"},
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{ name = "Philipp Knechtges", email = "philipp.knechtges@dlr.de"},
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{ name = "Björn Hagemeier", email = "b.hagemeier@fz-juelich.de"},
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{ name = "Michael Tarnawa", email = "m.tarnawa@fz-juelich.de"},
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{ name = "Philipp Knechtges", email = "philipp.knechtges@dlr.de"},
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{ name = "Fabian Hoppe", email = "f.hoppe@dlr.de"},
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{ name = "Hakan Akdag", email = "hakan.akdag@dlr.de"},
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{ name = "Alexander Rüttgers", email = "alexander.ruettgers@dlr.de"},
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{ name = "Martin Siggel", email = "martin.siggel@dlr.de"},
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{ name = "Achim Basermann", email = "achim.basermann@dlr.de"},
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{ name = "Achim Streit", email = "achim.streit@kit.de"},
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{ name = "Claudia Comito", email = "c.comito@fz-juelich.de"},
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{ name = "Thomas Saupe", email = "t.baumann@fz-juelich.de"},
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{ name = "Michael Tarnawa", email = "m.tarnawa@fz-juelich.de"},
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{ name = "Fabian Hoppe", email = "f.hoppe@dlr.de"},
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{ name = "Juan Pedro Gutiérrez Hermosillo Muriedas", email = "juan.muriedas@kit.edu"},
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{ name = "Hakan Akdag", email = "hakan.akdag@dlr.de"},
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]
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license = "MIT"
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license-files = ["LICENSE"]
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keywords=["data", "analytics", "tensors", "distributed", "gpu"]
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keywords = [
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"python",
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"pytorch",
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"numpy",
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"mpi",
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"mpi4py",
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"distributed computing",
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"parallel computing",
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"high-performance computing",
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"hpc",
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"gpu",
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"multi-gpu",
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"tensors",
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"data analytics",
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"machine learning",
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"data science",
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"scientific computing",
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"array api"
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]
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classifiers=[
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"Development Status :: 5 - Production/Stable",
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"Programming Language :: Python :: 3.11",

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