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Python High Performance, Second Edition

You're reading from   Python High Performance, Second Edition Build high-performing, concurrent, and distributed applications

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Product type Paperback
Published in May 2017
Publisher Packt
ISBN-13 9781787282896
Length 270 pages
Edition 2nd Edition
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Author (1):
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Dr. Gabriele Lanaro Dr. Gabriele Lanaro
Author Profile Icon Dr. Gabriele Lanaro
Dr. Gabriele Lanaro
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Table of Contents (10) Chapters Close

Preface Benchmarking and Profiling FREE CHAPTER Pure Python Optimizations Fast Array Operations with NumPy and Pandas C Performance with Cython Exploring Compilers Implementing Concurrency Parallel Processing Distributed Processing Designing for High Performance

Parallel Cython with OpenMP

Cython provides a convenient interface to perform shared-memory parallel processing through OpenMP. This lets you write extremely efficient parallel code directly in Cython without having to create a C wrapper.

OpenMP is a specification and an API designed to write multithreaded, parallel programs. The OpenMP specification includes a series of C preprocessor directives to manage threads and provides communication patterns, load balancing, and other synchronization features. Several C/C++ and Fortran compilers (including GCC) implement the OpenMP API.

We can introduce the Cython parallel features with a small example. Cython provides a simple API based on OpenMP in the cython.parallel module. The simplest way to achieve parallelism is through prange, which is a construct that automatically distributes loop operations in multiple threads.

First of all, we can write the serial version of...

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