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JupyterHub on an on-premises cloud -- a special focus on GPU Accelerated Machine Learning and 3D Visualization

8 pagesPublished: October 12, 2021

Abstract

At the IT department of the University of Mu ̈nster (WWU IT) we build a private IaaS cloud based on OpenStack and Kubernetes (WWU Cloud). This cloud provides a generic platform for data storage and service hosting. WWU IT operates a JupyterHub on WWU Cloud for use in research and education. Researchers have access to virtual GPUs from their Jupyter sessions. These may be used to compile and natively run CUDA accelerated code, e.g. for machine learning. Using VirtualGL, we also provide an accelerated X server in Jupyter sessions. X11 applications are then accessible from the browser using noVNC.

Keyphrases: Cloud, data visualization, GPU virtualization, JupyterHub, Kubernetes, OpenStack

In: Spiros Bolis, Jean-François Desnos, Lazaros Merakos and Raimund Vogl (editors). Proceedings of the European University Information Systems Conference 2021, vol 78, pages 69--76

Links:
BibTeX entry
@inproceedings{EUNIS2021:JupyterHub_on_an_on_premises,
  author    = {Markus Blank-Burian and J\textbackslash{}"urgen H\textbackslash{}"olters and Raimund Vogl},
  title     = {JupyterHub on an on-premises cloud -- a special focus on GPU Accelerated Machine Learning and 3D Visualization},
  booktitle = {Proceedings of the European University Information Systems Conference 2021},
  editor    = {Spiros Bolis and Jean-Fran\textbackslash{}c\{c\}ois Desnos and Lazaros Merakos and Raimund Vogl},
  series    = {EPiC Series in Computing},
  volume    = {78},
  pages     = {69--76},
  year      = {2021},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2398-7340},
  url       = {https://easychair.org/publications/paper/V4Gn},
  doi       = {10.29007/f8vp}}
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