Biophysical Society Thematic Meeting - November 16-20, 2015

Biophysics in the Understanding, Diagnosis, and Treatment of Infectious Diseases Poster Abstracts

5-POS Board 5 JMS: Creating and Running Complex Computational Pipelines on High Performance Computer Clusters David Brown , David Penkler, Thommas Musyoka, Özlem Tastan Bishop. Rhodes University, Grahamstown, South Africa. Modern computing has enabled research that was previously considered unfeasible. Parallel algorithms have been developed to run over powerful multicore machines. For even more computing power, these machines can be aggregated together into large high performance computing (HPC) clusters. On these clusters, jobs can be spread out across a large number of nodes instead of being executed on a single machine. This can substantially decrease the time required to execute resource intensive modeling and simulation jobs – a common requirement in the field of biophysics. It is also useful when a large number of much smaller jobs need to be executed. Unfortunately, running jobs on a cluster involves a steep learning curve. Jobs must be submitted via software systems known as resource managers. These systems are usually run via the command line and require expertise that most researchers do not have. To solve this problem, we have developed JMS (Job Management System), a web-based front-end to an HPC cluster. JMS allows users to run, manage and monitor jobs via a user-friendly web interface. It also lets users create new tools that can be pipelined together with existing tools to create complex computational workflows. These workflows can be saved, versioned and reused as needed. All tools, workflows and jobs can be shared with other users to create a highly collaborative work environment. In addition, tools and workflows can be made public via external interfaces. Although applicable to any field, JMS is currently being tailored toward structural bioinformatics with the introduction of tools and workflows for homology modelling, docking studies, and molecular dynamics. JMS has been open-sourced and is freely available at https://github.com/RUBi-ZA/JMS.

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