FireWorks 0.1dev0

FireWorks workflow software

FireWorks allows you to define calculation workflows and execute them on remote computers, usually through a queueing system. Workflows are stored in a centralized database, and jobs are pulled from the database by registered computers.

Features

Unique features of FireWorks include:

• Dynamic workflows that react to results programmatically. A job can be automatically restarted, modified, or cancelled in case of error or other condition. Entire workflows can be changed automatically based on calculation results.
• Distribute calculations over multiple computing resources simultaneously.
• Automated duplicate workflow detection
• Plug-and-play on several large supercomputing clusters and queueing systems (future)
• Web-based monitoring of workflows (future)

Limitations

FireWorks is intended for applications where realtime performance of the workflow software is not a big issue. For example, if you require steps in a workflow to execute within a few seconds of one another, FireWorks might not be for you. In addition, FireWorks is a centralized workflow system.

Contributing

TODO: add description

Technical Issues

Installation

• Use pip-install
• run python setup.py nosetests

Setup on clusters / Tutorial (Future)

TODO: link to another page…

TODO: add proper docs

1. Create a subclass of QueueAdapter that handles queue issues - an example is PBSAdapterNersc
2. Create an appropriate JobParameters file for your cluster - an example is provided.
3. Try running rocket_launcher.py on your cluster with a test job config. See if it prints ‘howdy, you won’ or whatever.
4. Try changing the executable to be the Rocket. See if it grabs a job properly…