aiidateam/aiida-core repository overview

AiiDA (www.aiida.net⁠) is a workflow manager for computational science with a strong focus on provenance, performance and extensibility.

⁠Features

• Workflows: Write complex, auto-documenting workflows in python, linked to arbitrary executables on local and remote computers. The event-based workflow engine supports tens of thousands of processes per hour with full checkpointing.
• Data provenance: Automatically track inputs, outputs & metadata of all calculations in a provenance graph for full reproducibility. Perform fast queries on graphs containing millions of nodes.
• HPC interface: Move your calculations to a different computer by changing one line of code. AiiDA is compatible with schedulers like SLURM⁠, PBS Pro⁠, torque⁠, SGE⁠ or LSF⁠ out of the box.
• Plugin interface: Extend AiiDA with plugins⁠ for new simulation codes (input generation & parsing), data types, schedulers, transport modes and more.
• Open Science: Export subsets of your provenance graph and share them with peers or make them available online for everyone on the Materials Cloud⁠.
• Open source: AiiDA is released under the MIT open source license⁠

⁠Installation

Please see AiiDA's documentation⁠.

⁠How to contribute

The AiiDA team appreciates help from a wide range of different backgrounds. Small improvements of the documentation or minor bug fixes are always welcome.

Please see the Contributor wiki⁠ on how to get started.

⁠Frequently Asked Questions

If you are experiencing problems with your AiiDA installation, please refer to the FAQ page of the documentation⁠.

⁠How to cite

If you use AiiDA in your research, please consider citing the following publications:

• AiiDA >= 1.0: S. P. Huber et al., AiiDA 1.0, a scalable computational infrastructure for automated reproducible workflows and data provenance, Scientific Data 7, 300 (2020); DOI: 10.1038/s41597-020-00638-4⁠
• AiiDA >= 1.0: M. Uhrin et al., Workflows in AiiDA: Engineering a high-throughput, event-based engine for robust and modular computational workflows, Computational Materials Science 187, 110086 (2021); DOI: 10.1016/j.commatsci.2020.110086⁠
• AiiDA < 1.0: Giovanni Pizzi, Andrea Cepellotti, Riccardo Sabatini, Nicola Marzari,and Boris Kozinsky, AiiDA: automated interactive infrastructure and database for computational science, Computational Materials Science 111, 218-230 (2016); DOI: 10.1016/j.commatsci.2015.09.013⁠

⁠License

AiiDA is distributed under the MIT open source license (see LICENSE.txt⁠). For a list of other open source components included in AiiDA, see open_source_licenses.txt⁠.

⁠Acknowledgements

AiiDA is a NumFOCUS Affiliated Project⁠ and supported by the MARVEL National Centre of Competence in Research⁠, the MaX European Centre of Excellence⁠ and by a number of other supporting projects, partners and institutions, whose complete list is available on the AiiDA website acknowledgements page⁠.