Book Image

IPython Interactive Computing and Visualization Cookbook - Second Edition

By : Cyrille Rossant
Book Image

IPython Interactive Computing and Visualization Cookbook - Second Edition

By: Cyrille Rossant

Overview of this book

Python is one of the leading open source platforms for data science and numerical computing. IPython and the associated Jupyter Notebook offer efficient interfaces to Python for data analysis and interactive visualization, and they constitute an ideal gateway to the platform. IPython Interactive Computing and Visualization Cookbook, Second Edition contains many ready-to-use, focused recipes for high-performance scientific computing and data analysis, from the latest IPython/Jupyter features to the most advanced tricks, to help you write better and faster code. You will apply these state-of-the-art methods to various real-world examples, illustrating topics in applied mathematics, scientific modeling, and machine learning. The first part of the book covers programming techniques: code quality and reproducibility, code optimization, high-performance computing through just-in-time compilation, parallel computing, and graphics card programming. The second part tackles data science, statistics, machine learning, signal and image processing, dynamical systems, and pure and applied mathematics.
Table of Contents (19 chapters)
IPython Interactive Computing and Visualization CookbookSecond Edition
Contributors
Preface
Index

Releasing the GIL to take advantage of multi-core processors with Cython and OpenMP


As we have seen in this chapter's introduction, CPython's GIL prevents pure Python code from taking advantage of multi-core processors. With Cython, we have a way to release the GIL temporarily in a portion of the code in order to enable multi-core computing. This is done with OpenMP, a multiprocessing API that is supported by most C compilers.

In this recipe, we will see how to parallelize the previous recipe's code on multiple cores.

Getting ready

To enable OpenMP in Cython, you just need to specify some options to the compiler. There is nothing special to install on your computer besides a good C compiler. See the instructions in this chapter's introduction for more details.

The code in this recipe has been written for GCC on Ubuntu. It can be adapted to other systems with minor changes to the %%cython options.

How to do it...

Our simple ray tracing engine implementation is embarrassingly parallel (see https...