Skip main navigation

Week 3 summary

Short summary of week three.
© CC-BY-NC-SA 4.0 by CSC - IT Center for Science Ltd.

We hope that you have enjoyed the third week of Python in High Performance Computing!

This week, we have discussed Cython, optimising static compiler for Python. By adding static type definitions into existing Python module (using Cython extension language) one can in best cases obtain over hundred-fold speed-ups. We also discussed how existing libraries (with C interface) or existing C and Fortran code can be interfaced with different Python tools.

By now, you should know how to transfer dynamic Python code into a more static compiled code with the help of Cython, as well as how to utilize C or Fortran code from Python.

Next week, we will explore the amazing wonderland of parallel computing and learn how to use multiple CPU cores with MPI for Python.

© CC-BY-NC-SA 4.0 by CSC - IT Center for Science Ltd.
This article is from the free online

Python in High Performance Computing

Created by
FutureLearn - Learning For Life

Our purpose is to transform access to education.

We offer a diverse selection of courses from leading universities and cultural institutions from around the world. These are delivered one step at a time, and are accessible on mobile, tablet and desktop, so you can fit learning around your life.

We believe learning should be an enjoyable, social experience, so our courses offer the opportunity to discuss what you’re learning with others as you go, helping you make fresh discoveries and form new ideas.
You can unlock new opportunities with unlimited access to hundreds of online short courses for a year by subscribing to our Unlimited package. Build your knowledge with top universities and organisations.

Learn more about how FutureLearn is transforming access to education