Mentors: Bryan Caron <bryan.caron@mcgill.ca>, Pierre Rioux, Natacha Beck, Serge Boroday, Darcy Quesnel
Skill level: Intermediate - Advanced
Required skills: Python; experience with version control systems (i.e. git) and team-based development methodologies; good understanding of the Linux operating system and development in a Linux environment
Time commitment: part time or full time (350 hours)
About: CBRAIN is a web-enabled distributed computing platform that facilitates collaborative research on large, distributed data by creating an easy-to-use interface for users (or groups of collaborating users) to access high-performance computing (HPC) and Cloud Computing resources. Through a series of web-based services, CBRAIN manages data access, transfer, caching and provenance, as well as data processing and reporting. While predominantly used to support researchers in neuroinformatics, CBRAIN is generic and modular, and can easily be extended with new data models and tools for a broad range of research disciplines. CBRAIN is an open source, flexible Ruby on Rails framework for accessing and processing large amounts of data across a distributed network of High Performance Computing (HPC) and Cloud Computing infrastructures. With over 1800 users from over 35 countries, CBRAIN is a key resource that lowers the technical barriers for scientists to conduct neuroinformatics research. More information about CBRAIN can be found at https://cbrain.ca and GitHub - aces/cbrain: CBRAIN is a flexible Ruby on Rails framework for accessing and processing of large data on high-performance computing infrastructures. · GitHub.
Aims: The objective of the project is to create a python-based command line interface (CLI), leveraging the CBRAIN APIs, which will enable more advanced users to perform all the typical operations of CBRAIN for data upload / download, file querying / selection, and processing task creation, execution and monitoring from a CLI that can be run on a remote resource without requiring the user to perform the same actions through the CBRAIN web interface. A CLI approach would provide users the ability to create more complex workflows while still leveraging CBRAIN’s core abilities to manage data movement and large-scale data processing.
Website: https://cbrain.ca and GitHub - aces/cbrain: CBRAIN is a flexible Ruby on Rails framework for accessing and processing of large data on high-performance computing infrastructures. · GitHub
Tech keywords: Keywords: Python, imaging, CBRAIN, distributed computing, cloud computing