Our case study work on how to preserve and reproduce a high energy physics (HEP) application with Parrot has been accepted by Journal of Physics: Conference Series (JPCS 2015).
The HEP application under investigation is called TauRoast, and authored by our physics collaborator, Matthias. TauRoast is a complex single-machine application having lots of implicit and explicit dependencies: CVS, github, PyYAML websites, personal websites, CVMFS, AFS, HDFS, NFS, and PanFS. The total size of these dependencies is about 166.8TB.
To make TauRoast reproducible, we propose one fine-grained dependency management toolkit based on Parrot to track the really used data and create a reduced package which gets rid of all the unused data. By doing so, the original execution environment with the size of 166.8TB is reduced into a package with the size of 21GB. The correctness of the preserved package is demonstrated in three different environments - the original machine, one virtual machine from the Notre Dame Cloud Platform and one virtual machine from the Amazon EC2 Platform.
Haiyan Meng, Matthias Wolf, Peter Ivie, Anna Woodard, Michael Hildreth and Douglas Thain, A Case Study in Preserving a High Energy Physics Application with Parrot, Journal of Physics: Conference Series, December, 2015. |