Automated Interactive Infrastructure and Database for Computational Science

If you use AiiDA please cite:
AiiDA 1.x
Main paper: S.P. Huber et al., Scientific Data 7, 300 (2020)
AiiDA engine: M. Uhrin et al., Comp. Mat. Sci. 187 (2021)

AiiDA 0.x
First paper, ADES model: G. Pizzi et al. Comp. Mat. Sci. 111, 218-230 (2016) (open access version)

What is AiiDA?

AiiDA is 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.


AiiDA is built to support and streamline the four core pillars of the ADES model: Automation, Data, Environment, and Sharing. Key features include:

  • Workflows: AiiDA allows to build and execute complex, auto-documenting workflows linked to multiple codes on local and remote computers.
  • High-throughput: AiiDA’s event-based workflow engine supports tens of thousands of processes per hour with full check-pointing.
  • Data provenance: AiiDA automatically tracks and records inputs, outputs and metadata of all calculations and workflows in extensive provenance graphs that preserve the full lineage of all data.
  • Advanced queries: AiiDA’s query language enables fast graph queries on millions of nodes.
  • Plugin interface: AiiDA can support via plugins any computational code and data analytics tool, data type, scheduler, connection mode, etc. (see public plugin repository)
  • HPC interface: AiiDA can seamlessly deal with heterogeneous and remote computing resources; it works with many schedulers out of the box (SLURM, PBS Pro, torque, SGE or LSF).
  • Open science: AiiDA allows to export both full databases and selected subsets, to be shared with collaborators or made available and browsable online on the Archive and Explore sections of Materials Cloud.
  • Open source: AiiDA is released under the MIT open-source license.

Most recent news

AiiDA on the cover of the Comp. Mat. Sci. journal

Starting this January, AiiDA graphs will be on the cover image of Computational Materials Science...
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New AiiDA tutorial in Lausanne, May 2017

The second edition of the MARVEL/Psi-k/MaX "Tutorial on high-throughput computations: general methods and applications using...
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AiiDA moves from BitBucket to GitHub

The AiiDA code has moved as of today from BitBucket, that has hosted the source...
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Report of the AiiDA coding week (Dec 2016)

We have posted a new article in the "Blog posts" section with the summary, report, photos and...
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Postdoc opening – integration of AiiDA with the nanoporous genome library

An open postdoc position is available at EPFL (Sion and Lausanne, Switzerland) in the MARVEL...
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Upcoming AiiDA tutorial, ICTP Trieste, January 2017

Next winter we will have a new tutorial for AiiDA users, within the "Advanced Workshop...
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