Book Image

Python Parallel Programming Cookbook

By : Zaccone
Book Image

Python Parallel Programming Cookbook

By: Zaccone

Overview of this book

This book will teach you parallel programming techniques using examples in Python and will help you explore the many ways in which you can write code that allows more than one process to happen at once. Starting with introducing you to the world of parallel computing, it moves on to cover the fundamentals in Python. This is followed by exploring the thread-based parallelism model using the Python threading module by synchronizing threads and using locks, mutex, semaphores queues, GIL, and the thread pool. Next you will be taught about process-based parallelism where you will synchronize processes using message passing along with learning about the performance of MPI Python Modules. You will then go on to learn the asynchronous parallel programming model using the Python asyncio module along with handling exceptions. Moving on, you will discover distributed computing with Python, and learn how to install a broker, use Celery Python Module, and create a worker. You will understand anche Pycsp, the Scoop framework, and disk modules in Python. Further on, you will learnGPU programming withPython using the PyCUDA module along with evaluating performance limitations.
Table of Contents (8 chapters)
7
Index

Introduction

Currently, the most widely used programming paradigm for the management of concurrence 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 parallel and compete with each other.

Although such a style of programming can lead to disadvantages of use and problems that need to be solved, modern applications with the mechanism of multithreading are still used quite widely.

Practically, all the existing operating systems support multithreading, and in almost all programming languages, there are mechanisms that you can use to implement concurrent applications through the use of threads.

Therefore, multithreaded programming is definitely a good choice to achieve concurrent applications. However, it is not the only choice available—there are several other alternatives, some of which, inter alia, perform better on the definition...