Abstract
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 common technology platform 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. This paper will describe the mechanisms that MSI has put in place, advantages for research and instructional uses, and lessons learned.
Original language | English (US) |
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Number of pages | 6 |
DOIs | |
State | Published - Jul 26 2018 |
Event | 2018 Practice and Experience in Advanced Research Computing Conference: Seamless Creativity, PEARC 2018 - Pittsburgh, United States Duration: Jul 22 2017 → Jul 26 2017 |
Other
Other | 2018 Practice and Experience in Advanced Research Computing Conference: Seamless Creativity, PEARC 2018 |
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Country/Territory | United States |
City | Pittsburgh |
Period | 7/22/17 → 7/26/17 |
Bibliographical note
6 pages, 2 figures, in PEARC '18: Proceedings of Practice and Experience in Advanced Research Computing, July 22--26, 2018, Pittsburgh, PA, USAKeywords
- cs.DC
- cs.CY