Interactive High-Performance Computing with Jupyter

Course/Event Essentials

Event/Course Start
Event/Course End
Event/Course Format
Online
Live (synchronous)

Venue Information

Country: Germany
Venue Details: Click here

Training Content and Scope

Scientific Domain
Level of Instruction
Beginner
Sector of the Target Audience
Research and Academia
Industry
Public Sector
HPC Profile of Target Audience
Application Users
Application Developers
Data Scientists
Language of Instruction

Other Information

Organiser
Event/Course Description

Interactive exploration and analysis of large amounts of data from scientific simulations, in-situ visualization and application control are convincing scenarios for explorative sciences. Based on the open source software Jupyter or JupyterLab, a way has been available for some time now that combines interactive with reproducible computing while at the same time meeting the challenges of support for the wide range of different software workflows.

Even on supercomputers, the method enables the creation of documents that combine live code with narrative text, mathematical equations, visualizations, interactive controls, and other extensive output. However, a number of challenges must be mastered in order to make existing workflows ready for interactive high-performance computing. With so many possibilities, it's easy to lose sight of the big picture. This course provides a detailed introduction to interactive high-performance computing.

The following topics are covered:

  • Introduction to Jupyter
  • Parallel computing using Jupyter
  • Interactive & in-situ visualization
  • From ipywidgets to dashboards