Nov 4 – 8, 2019
Adelaide Convention Centre
Australia/Adelaide timezone

Knowledge sharing on deep learning in physics research using VISPA

Nov 7, 2019, 3:30 PM
1h
Hall F (Adelaide Convention Centre)

Hall F

Adelaide Convention Centre

Poster Track 5 – Software Development Posters

Speaker

Manfred Peter Fackeldey (Rheinisch Westfaelische Tech. Hoch. (DE))

Description

The VISPA (VISual Physics Analysis) project provides a streamlined work environment for physics analyses and hands-on teaching experiences with a focus on deep learning.
VISPA has already been successfully used in HEP analyses and teaching and is now being further developed into an interactive deep learning platform.
One specific example is to meet knowledge sharing needs in deep learning by combining paper, code and data at a central place.
Additionally the possibility to run it directly from the web browser is a key feature of this development.
Any SSH reachable resource can be accessed via the VISPA web interface.
This enables a flexible and experiment agnostic computing experience.
The user interface is based on JupyterLab and is extended with analysis specific tools, such as a parametric file browser and TensorBoard.
Our VISPA instance is backed by extensive GPU resources and a rich software environment.
We present the current status of the VISPA project and its upcoming new features.

Consider for promotion No

Primary authors

Mr Alexander Temme (RWTH Aachen University) Benjamin Fischer (RWTH Aachen University (DE)) Dennis Noll (RWTH Aachen University (DE)) Mrs Katharina Hafner (RWTH Aachen University) Manfred Peter Fackeldey (Rheinisch Westfaelische Tech. Hoch. (DE)) Marcel Rieger (CERN) Martin Erdmann (Rheinisch Westfaelische Tech. Hoch. (DE)) Martin Urban (RWTH Aachen University) Mr Max Beer (RWTH Aachen University) Mr Max Vieweg (RWTH Aachen University) Mr Niclas Eich (RWTH Aachen University) Yannik Alexander Rath (RWTH Aachen University (DE))

Presentation materials