Accelerating Massive Data Processing in Python with Heat (training course, hybrid)
Claudia Comito
(Course no. TBA in the training programme 2026 of Forschungszentrum Jülich)
Sie können an diesem Kurs entweder online oder vor Ort am JSC teilnehmen. Die Kurssprache ist Englisch.
Course Content:
This hands-on tutorial introduces the Heat library, which is designed to scale Python-based array computing and data science workflows to distributed and GPU-accelerated environments. Heat offers a familiar NumPy-like API while distributing memory-intensive operations using PyTorch and mpi4py.
Topics covered include:
- Heat Fundamentals: Get started with distributed arrays (DNDarrays), distributed I/O, data decomposition schemes, and array operations.
- Key Functionalities: Explore the multi-node linear algebra, statistics, signal processing, and machine learning capabilities.
- DIY Development: Learn how to use Heat's infrastructure to build your own multi-node, multi-GPU capable research applications.
Prerequisites:
Participants should have a laptop and experience with Python and its scientific ecosystem (e.g. NumPy, SciPy). A basic understanding of MPI is helpful but not required.
A personal institutional email address (university/research institution, government agency, organisation, or company) is required to register for JSC training courses. If you don't have an institutional email address, please get in touch with the contact person for this course.
Target Audience:
Researchers and Research Software Engineers (RSEs) working with large datasets that exceed the memory of a single machine.
HPC practitioners that support these scientists or that may be interested in supporting them in the future are also welcome.
Language:
The course will be held in English.
Duration:
1 half day
Dates:
9 November 2026, 10:00-15:00 each day
Venue:
Hybrid: You can participate either online or on-site at the Jülich Supercomputing Centre, Building 16.3, Room 211 (Training Room 2).
Number of Participants:
Maximum 20
Instructors:
Kai Krajsek, Thomas Saupe, Claudia Comito (JSC)
Juan Pedro Muriedas (KIT)
Registration:
The registration for the course will open in the first quarter of 2026.
