Atomate - reproducible computational materials science workflows in Python
Posted on Sat 05 August 2017 in science
If you've done any computational work on a high-performance computing system, odds are you are very familiar with shell scripting and running code in at least 3 different languages that was passed down through the years. You know the theory of how it all works, but can never find the time to weed through, organize and update someone else's FORTRAN code (that was out of date when it was written in 2002) to use the latest techniques. Atomate aims to solve these problems by leveraging the community developed materials science tools and analyses in pymatgen and the workflow management/database creation of FireWorks to document and allow for easy execution of community standardized and easily customizable workflows managed and written using Python.
Link to the paper: Mathew, K. et al. Atomate: A high-level interface to generate, execute, and analyze computational materials science workflows. Comput. Mater. Sci. 139, 140–152 (2017).