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

What is a thread?

A thread is an independent execution flow that can be executed in parallel and concurrently with other threads in the system.

Multiple threads can share data and resources, taking advantage of the so-called space of shared information. The specific implementation of threads and processes depends on the OS on which you plan to run the application, but, in general, it can be stated that a thread is contained inside a process and that different threads in the same process conditions share some resources. In contrast to this, different processes do not share their own resources with other processes.

A thread is composed of three elements: program counters, registers, and stack. Shared resources with other threads of the same process essentially include data and OS resources. Moreover, threads have their own state of execution, namely, thread state, and can be synchronized...