Bonn 2020 – scientific programme

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T: Fachverband Teilchenphysik

T 47: Neural networks and systematic uncertainties

T 47.1: Talk

Wednesday, April 1, 2020, 16:30–16:45, H-HS IV

VISPA: Platform as a Service (PaaS) for Scientific Data Analysis — Max Beer, Friederike Butt, Niclas Eich, Martin Erdmann, Peter Fackeldey, Benjamin Fischer, •Katharina Hafner, Dennis Noll, Yannik Rath, Erwin Rudi, Alexander Temme, and Maximilian Vieweg — Physikalisches Institut 3A, RWTH Aachen University

The VISPA project delivers a cloud platform that enables scientific data analysis with the convenience of using a web browser. Our goal is to explore how scientific work with data might look like in the future. Through the VISPA web platform, each user is provided with a working environment consisting of pre-installed tools and software. The working environment can be largely customized and expanded according to the users preferences. To enable a jump start into the infrastructure, a large collection of examples, including classical data analysis and deep learning, can be tried out directly. Computing resources like disk space, processors and GPUs are either assigned to individual users or groups of users, such as research teams. As the emerging JupyterLab is an ideal choice for a comprehensive, browser-based, and extensible work environment, it is currently being integrated into the VISPA frontend. Beside the new frontend, users can now have individual access rights to experimental data (public data, experiment data), use Jupyter Notebooks and state-of-the-art visualization tools for data analysis.