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

Process-Based Parallelism

In the previous chapter, we learned how to use threads to implement concurrent applications. This chapter will examine the process-based approach that we introduced in Chapter 1, Getting Started with Parallel Computing and PythonIn particular, the focus of the chapter is on the Python multiprocessing module.

The Python multiprocessing module, which is a part of the standard library of the language, implements the shared memory programming paradigm, that is, the programming of a system that consists of one or more processors that have access to a shared memory.

In this chapter, we will cover the following recipes:

  • Understanding Python's multiprocessing module
  • Spawning a process
  • Naming a process
  • Running processes in the background
  • Killing a process
  • Defining a process in a subclass
  • Using a queue to exchange objects
  • Using pipes...