Python is being 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 session. We will show how Python can be used on parallel architectures and how performance critical parts of the kernel can be optimized using various tools.

Day 1: Using Python productively for parallel computing

Interactive parallel programming with IPython
High-performance NumPy and SciPy
Distributed-memory parallel programming with Python and MPI
Day 2: Python in concert with other programming languages and accelerators

Cython
f2py
PyCUDA
PyOpenCL
Numba
This course is aimed at scientists who wish to explore the productivity gains made possible by Python for HPC.

Prerequisites: Experience with Python and NumPy

Application
Registrations are only considered until 31 May 2016 due to available space, the maximal number of participants is limited. Applicants will be notified, whether they are accepted for participitation.

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

Contact
For any questions concerning the course please send an e-mail to [email protected]

https://events.prace-ri.eu/event/465/