16-20 November 2020
CET timezone

Python is increasingly used in high-performance computing projects. It can be used either as a high-level interface to existing HPC applications and libraries, as embedded interpreter, or directly.

This course combines lectures and hands-on sessions. We will show how Python can be used on parallel architectures and how to optimize critical parts of the kernel using various tools.

The following topics will be covered:

  • Interactive parallel programming with IPython
  • Profiling and optimization
  • High-performance NumPy
  • Just-in-time compilation with numba
  • Distributed-memory parallel programming with Python and MPI
  • Bindings to other programming languages and HPC libraries
  • Interfaces to GPUs

This course is aimed at scientists who wish to explore the productivity gains made possible by Python for HPC.

Prerequisites: Good working knowledge of Python and NumPy

Registration has ended. Applicants will be notified, whether they are accepted for participitation.

Instructors: Dr. Jan Meinke, Dr. Olav Zimmermann, JSC

For any questions concerning the course please send an e-mail to j.meinke@fz-juelich.de

There is an open survey.