Enabling Interactive Supercomputing at JSC Lessons Learned

Jens Henrik Göbbert*, Tim Kreuzer, Alice Grosch, Andreas Lintermann, Morris Riedel

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

Research and analysis of large amounts of data from scientific simulations, in-situ visualization, and application control are convincing scenarios for interactive supercomputing. The open-source software Jupyter (or JupyterLab) is a tool that has already been used successfully in many scientific disciplines. With its open and flexible web-based design, Jupyter is ideal for combining a wide variety of workflows and programming methods in a single interface. The multi-user capability of Jupyter via JuypterHub excels it for scientific applications at supercomputing centers. It combines the workspace that is local to the user and the corresponding workspace on the HPC systems. In order to meet the requirements for more interactivity in supercomputing and to open up new possibilities in HPC, a simple and direct web access for starting and connecting to login or compute nodes with Jupyter or JupyterLab at Jülich Supercomputing Centre (JSC) is presented. To corroborate the flexibility of the new method, the motivation, applications, details and challenges of enabling interactive supercomputing, as well as goals and prospective future work will be discussed.

Original languageEnglish
Title of host publicationHigh Performance Computing - ISC High Performance 2018 International Workshops, Revised Selected Papers
EditorsRio Yokota, John Shalf, Michèle Weiland, Sadaf Alam
PublisherSpringer Verlag
Pages669-677
Number of pages9
ISBN (Print)9783030024642
DOIs
Publication statusPublished - 2018
EventInternational Conference on High Performance Computing, ISC High Performance 2018 - Frankfurt, Germany
Duration: 28 Jun 201828 Jun 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11203 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceInternational Conference on High Performance Computing, ISC High Performance 2018
Country/TerritoryGermany
CityFrankfurt
Period28/06/1828/06/18

Bibliographical note

Funding Information:
Acknowledgement. This work is supported by the Rhinodiagnost project funded by the Zentrale Innovationsprogramm Mittelstand (ZIM) of the Federal Ministry of Economical Affairs and Energy (BMWi) and the InHPC-DE project as part of the SiVeGCS project to promote closer technical integration of the three GCS HPC centers in Stuttgart (HLRS), Jülich (JSC) and Munich (LRZ).

Publisher Copyright:
© 2018, Springer Nature Switzerland AG.

Other keywords

  • High Performance Computing
  • Interactive supercomputing
  • Jupyter

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