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This content is taken from the Partnership for Advanced Computing in Europe (PRACE)'s online course, Python in High Performance Computing. Join the course to learn more.

Week 1 summary

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

This week, we have discussed various performance challenges in Python programs and have set up the programming environment for the course. We have also introduced various ways of investigating the performance of Python programs. We hope that you remember the number one rule in performance optimization:

Measure before you optimize!

By now, you should know how to use the cProfile profiling tool which is included in the Python standard library.

Next week, we will look into how to use fixed size, uniformly typed NumPy arrays to get more performance in Python.

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This article is from the free online course:

Python in High Performance Computing

Partnership for Advanced Computing in Europe (PRACE)