aiidateam/aiida-core

The official repository for the AiiDA code

What it solves

AiiDA is designed to solve the challenges of reproducibility and scalability in computational science. It provides a framework for managing complex simulation workflows, ensuring that every step of the calculation—including inputs, outputs, and metadata—is automatically tracked for full provenance.

How it works

AiiDA uses an event-based workflow engine that allows users to write workflows in Python. These workflows can link to executables on either local or remote computers, and the engine supports high-throughput processing (tens of thousands of processes per hour) with full checkpointing. It maintains a provenance graph of all calculations, which can be queried for data retrieval and reproducibility.

Who it’s for

It is built for computational scientists and researchers who need to run high-throughput simulations across different HPC (High-Performance Computing) environments and maintain a strict record of the provenance of their results.

Highlights

  • Automatic Provenance Tracking: Automatically records all inputs, outputs, and metadata in a graph for full reproducibility.
  • HPC Integration: Out-of-the-box compatibility with major schedulers like SLURM, PBS Pro, Torque, SGE, and LSF.
  • Extensible Plugin System: Allows users to add support for new simulation codes, data types, and transport modes.
  • High-Performance Engine: An event-based engine capable of handling tens of thousands of processes per hour.
  • Open Science Support: Enables exporting provenance graphs to share results via the Materials Cloud.

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