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International Conference on High Performance Computing

ISC High Performance 2018: High Performance Computing pp 669–677Cite as

Enabling Interactive Supercomputing at JSC Lessons Learned

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11203))

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.

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Notes

  1. 1.

    https://jupyter.org.

  2. 2.

    https://ipython.org.

  3. 3.

    https://jupyterlab.readthedocs.io.

  4. 4.

    https://jupyterhub.readthedocs.io.

  5. 5.

    https://jupyter-jsc.fz-juelich.de.

  6. 6.

    https://www.unity-idm.eu.

  7. 7.

    https://www.unicore.eu/.

  8. 8.

    https://www.rhinodiagnost.eu/.

  9. 9.

    https://keras.io.

  10. 10.

    https://www.tensorflow.org.

  11. 11.

    https://www.paraview.org.

  12. 12.

    https://wci.llnl.gov/simulation/computer-codes/visit.

References

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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).

Author information

Authors and Affiliations

  1. Jülich Supercomputing Centre, Forschungszentrum Jülich GmbH, Jülich, Germany

    Jens Henrik Göbbert, Tim Kreuzer, Alice Grosch & Morris Riedel

  2. Institute of Aerodynamics and Chair of Fluid Mechanics, RWTH Aachen University, Aachen, Germany

    Andreas Lintermann

  3. Jülich Aachen Research Alliance (JARA) - High Performance Computing, RWTH Aachen University, Aachen, Germany

    Andreas Lintermann

Authors
  1. Jens Henrik Göbbert
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  2. Tim Kreuzer
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  3. Alice Grosch
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  4. Andreas Lintermann
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  5. Morris Riedel
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Corresponding author

Correspondence to Jens Henrik Göbbert .

Editor information

Editors and Affiliations

  1. Tokyo Institute of Technology, Tokyo, Japan

    Rio Yokota

  2. University of Edinburgh, Edinburgh, UK

    Michèle Weiland

  3. Lawrence Berkeley National Laboratory, Berkeley, CA, USA

    John Shalf

  4. Swiss National Supercomputing Centre, Lugano, Switzerland

    Sadaf Alam

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Göbbert, J.H., Kreuzer, T., Grosch, A., Lintermann, A., Riedel, M. (2018). Enabling Interactive Supercomputing at JSC Lessons Learned. In: Yokota, R., Weiland, M., Shalf, J., Alam, S. (eds) High Performance Computing. ISC High Performance 2018. Lecture Notes in Computer Science(), vol 11203. Springer, Cham. https://doi.org/10.1007/978-3-030-02465-9_48

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  • DOI: https://doi.org/10.1007/978-3-030-02465-9_48

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-02464-2

  • Online ISBN: 978-3-030-02465-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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