The Minnesota Supercomputing Institute has implemented JupyterHub and the Jupyter Notebook server as a general-purpose point of entry to interactive high-performance computing services. This mode of operation runs counter to traditional job-oriented HPC operations but offers significant advantages for ease of use, data exploration, prototyping, and workflow development. From the user perspective, these features bring the computing cluster nearer to parity with emerging cloud computing options. On the other hand, retreating from fully scheduled, job-based resource allocation poses challenges for resource availability and utilization efficiency and can involve tools and technologies outside the typical core competencies of a supercomputing center’s operations staff. MSI has attempted to mitigate these challenges by adopting Jupyter as a one-stop shop for interactive services, capable of providing command-line, graphical, and workflow-oriented access to HPC resources while still integrating with job scheduling systems and using existing compute resources. Join in to explore the mechanisms that MSI has put in place, the advantages for research and instructional uses, and lessons learned.
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