July 25, 2019 - by CSCS

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 combined lectures and hands-on sessions. We showed how Python can be used on parallel architectures and how to optimize critical parts of the kernel using various tools.

The following topics were 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

Playlist with all the videos >>