Python for HPC - Part I

Course/Event Essentials

Event/Course Start
Event/Course End
Event/Course Format
Mixed
Live (synchronous)

Venue Information

Country: Belgium
Venue Details: Click here

Training Content and Scope

Scientific Domain
Technical Domain
Level of Instruction
Intermediate
Advanced
Sector of the Target Audience
Research and Academia
Industry
Public Sector
HPC Profile of Target Audience
Application Users
Application Developers
Data Scientists
Language of Instruction

Other Information

Supporting Project(s)
EuroCC2/CASTIEL2
Event/Course Description

Python is making inroads into the HPC landscape. However, writing Python code for efficient scientific computing is not entirely trivial. In this course a  variety of techniques and libraries will be discussed that are useful in this context. Subjects covered include profiling of code to discover opportunities  for optimization, using Cython, a Python extension that translate critical code sections into efficient C, wrapping C/C++/Fortran libraries in Python,  multithreaded/multiprocess Python, distributed programming use mpi4py, and pySpark for data science.

Target audience
This info session is primarily targeted at VSC-users, although other interested parties are welcome as well.

Prior knowledge required: 
Participants have programming experience in Python and preferably also in C/C++ or Fortran.

Result/Objectives
Participants can make an informed choice on various techniques to improve the performance of Python code, and know how to call C/C++ or Fortran functions from Python.