Info
Python is increasingly used in all kinds of scientific computing tasks and in AI / machine learning. This course provides a practical foundation in High Performance Computing with Python for users with basic Python knowledge. This course introduces techniques for accelerating Python applications in scientific and data-intensive environments. Participants learn to use libraries such as NumPy, and multiprocessing for parallel execution, and explore distributed computing with Python. Practical exercises focus on managing Python environments and optimizing performance. By the end, learners will be able to design and implement high-performance workflows on modern HPC systems.
The course is completely free and open to all members of Heinrich Heine University. It takes place in person over two days with about 120 minutes of lessons and 90 minutes of exercises each. To participate in the exercises, you need to bring your own laptop!
The course will be held in Reverse-hybrid format, i.e. the lessons will be streamed from the main site in Bonn to each satellite location, where local staff will be attending to answer your questions and help you during exercises.
Location: Zentrum für Informations- und Medientechnologie (ZIM), Heinrich Heine Universität Düsseldorf, Gebäude 25.41 Raum 00.67
Language: English
Dates: Mo., 15.06.2026 + Tu., 16.06.2026, 13:00-16:30 each day
The following topics will be covered:
Day 1:
1. Best practices: testing, formatting
2. pip, conda
3. Virtual environments, conda envs
4. pip, venv, conda on HPC clusters
5. Brief framework overview
Day 2:
6. Python performance
7. Understanding (NumPy) arrays
8. Array broadcasting
9. Advanced array indexing
There are a limited number of participant slots available. If you realize that you cannot make it to the course that you signed up for, please withdraw your registration to allow others the chance to participate.
If you have any questions regarding the course, please contact Pit Duwentäster (pit.duwentaester@hhu.de).