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The Minnesota Supercomputing Institute has implemented Jupyterhub and theJupyter notebook server as a general-purpose point-of-entry to interactive highperformance computing services. This mode of operation runs counter totraditional job-oriented HPC operations, but offers significant advantages forease-of-use, data exploration, prototyping, and workflow development. From theuser perspective, these features bring the computing cluster nearer to paritywith emerging cloud computing options. On the other hand, retreating fromfully-scheduled, job-based resource allocation poses challenges for resourceavailability and utilization efficiency, and can involve tools and technologiesoutside the typical core competencies of a supercomputing center's operationsstaff. MSI has attempted to mitigate these challenges by adopting Jupyter as acommon technology platform for interactive services, capable of providingcommand-line, graphical, and workflow-oriented access to HPC resources whilestill integrating with job scheduling systems and using existing computeresources. This paper will describe the mechanisms that MSI has put in place,advantages for research and instructional uses, and lessons learned.

Jupyter as Common Technology Platform for Interactive HPC Services