Welcome to AiiDA’s documentation!#
An open-source Python infrastructure to help researchers with automating, managing, persisting, sharing and reproducing the complex workflows associated with modern computational science and all associated data (see features).
aiida-core version: 2.4.0.post0
AiiDA installation, configuration and troubleshooting.
First time users: Get your feet wet with AiiDA basics!
Learn how to use AiiDA to power your own work.
Background information on AiiDA’s underlying concepts.
Comprehensive documentation of AiiDA components: command-line interface, Python interface, and RESTful API.
Notes on AiiDA’s design and architecture aimed at core developers.
How to cite#
If you use AiiDA for your research, please cite the following work:
Sebastiaan. P. Huber, Spyros Zoupanos, Martin Uhrin, Leopold Talirz, Leonid Kahle, Rico Häuselmann, Dominik Gresch, Tiziano Müller, Aliaksandr V. Yakutovich, Casper W. Andersen, Francisco F. Ramirez, Carl S. Adorf, Fernando Gargiulo, Snehal Kumbhar, Elsa Passaro, Conrad Johnston, Andrius Merkys, Andrea Cepellotti, Nicolas Mounet, Nicola Marzari, Boris Kozinsky, and Giovanni Pizzi, 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
Martin Uhrin, Sebastiaan. P. Huber, Jusong Yu, Nicola Marzari, and Giovanni Pizzi, 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
If the ADES concepts are referenced, please also cite:
Martin Uhrin, Sebastiaan. P. Huber, Jusong Yu, Nicola Marzari, and Giovanni Pizzi, 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 <https://doi.org/10.1016/j.commatsci.2020.110086>
AiiDA is 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.
AiiDA is a NumFOCUS Affiliated Project. Visit numfocus.org for more information.