Andrew P. Davison (principal developer) and Daniel Wheeler (speaker)
Sumatra is a lightweight system for recording the history and provenance data for numerical simulations. It works particularly well for scientists that are in the intermediate stage between developing a code base and using that code base for active research. This is a common scenario and often results in a mode of development that mixes branching for both code development and production simulations. Using Sumatra avoids this unintended use of the versioning system by providing a lightweight design for recording the provenance data independently from the versioning system used for the code development. The lightweight design of Sumatra fits well with existing ad-hoc patterns of simulation management contrasting with more pervasive workflow tools, which can require a wholesale alteration of work patterns. Sumatra uses a straightforward Django-based data model enabling persistent data storage independently from the Sumatra installation. Sumatra provides a command line utility with a rudimentary web interface, but has the potential to become a full web-based simulation management solution. During the talk, the speaker will provide an introduction to Sumatra as well as demonstrate some typical usage patterns and discuss achievable future goals.
Daniel Wheeler's expertise lies in the development and deployment of software for applied scientific applications. He has a strong knowledge of numerical algorithms for solving partial differential equations as well as good skills in using and developing more general scientific computing tools. He has an extensive background (8 years) working with Python, Python/C interfaces and general numerical tool kits in high performance computing environments. He is one of the lead developers of the FiPy open-source PDE solver. He has over 40 refereed journal publications and an h-index of 19.
Andrew Davison is a senior research scientist in the Unité de Neurosciences, Information and Complexité of the Centre National de la Recherche Scientifique, where he leads the Neuroinformatics group. His research interests focus on biologically detailed modeling, simulating neuronal networks (particularly the mammalian visual system), and developing open-source tools to improve the reliability, reproducibility, and efficiency of biologically realistic simulation. He is the lead developer of Sumatra, and of the PyNN package for simulator-independent neuronal network modelling, and one of the lead developers of the Neo package for handling neurophysiology data in Python.