Book Image

Python Parallel Programming Cookbook - Second Edition

By : Giancarlo Zaccone
Book Image

Python Parallel Programming Cookbook - Second Edition

By: Giancarlo Zaccone

Overview of this book

<p>Nowadays, it has become extremely important for programmers to understand the link between the software and the parallel nature of their hardware so that their programs run efficiently on computer architectures. Applications based on parallel programming are fast, robust, and easily scalable. </p><p> </p><p>This updated edition features cutting-edge techniques for building effective concurrent applications in Python 3.7. The book introduces parallel programming architectures and covers the fundamental recipes for thread-based and process-based parallelism. You'll learn about mutex, semaphores, locks, queues exploiting the threading, and multiprocessing modules, all of which are basic tools to build parallel applications. Recipes on MPI programming will help you to synchronize processes using the fundamental message passing techniques with mpi4py. Furthermore, you'll get to grips with asynchronous programming and how to use the power of the GPU with PyCUDA and PyOpenCL frameworks. Finally, you'll explore how to design distributed computing systems with Celery and architect Python apps on the cloud using PythonAnywhere, Docker, and serverless applications. </p><p> </p><p>By the end of this book, you will be confident in building concurrent and high-performing applications in Python.</p>
Table of Contents (16 chapters)
Title Page

Thread-Based Parallelism

Currently, the most widely used programming paradigm for the management of concurrency in software applications is based on multithreading. Generally, an application is made by a single process that is divided into multiple independent threads, which represent activities of different types that run in parallel and compete with each other.

Nowadays, modern applications that use multithreading have been adopted on a massive scale. In fact, all current processors are multicore, just so they can perform parallel operations and exploit the computer's computational resources.

Hence, multithreaded programming is definitely a good way to achieve concurrent applications. However, multithreaded programming often hides some non-trivial difficulties, which must be managed appropriately to avoid errors such as deadlocks&...