Hands-on: Numexpr

In this exercise we explore how to evaluate expressions efficiently with numexpr.

Source code for this exercise is located in numpy/numexpr/

Try different array expressions and investigate how much numexpr can speed them up. Try to vary also the number of threads used by numexpr. IPython and %timeit magic can be useful in testing.

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This article is from the free online course:

Python in High Performance Computing

Partnership for Advanced Computing in Europe (PRACE)