JupyterHub on an on-premises cloud -- a special focus on GPU Accelerated Machine Learning and 3D Visualization
Blank-Burian M, Hölters J, Vogl R
Research article (book contribution) | Peer reviewedAbstract
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.
Details about the publication
Publisher: Bolis S, Desnos J-F, Merakos L, Vogl, R
Book title: Proceedings of the European University Information Systems Conference 2021
Page range: 69-76
Title of series: EPiC Series in Computing
Volume of series: 78
Status: Published
Release year: 2021
Language in which the publication is written: English
DOI: 10.29007/f8vp
Keywords: Cloud; data visualization; GPU virtualization; JupyterHub; Kubernetes; OpenStack
Authors from the University of Münster
| Blank-Burian, Markus | IT - Server & Storage |
| Hölters, Jürgen | IT - Systems |
| Vogl, Raimund | Center for Information Technology (CIT) |