Python Parallel Programming Cookbook

by Giancarlo Zaccone

Overview

Master efficient parallel programming to build powerful applications using Python

Key Features

Design and implement efficient parallel software

Master new programming techniques to address and solve complex programming problems

Explore the world of parallel programming with this book, which is a go-to resource for different kinds of parallel computing tasks in Python, using examples and topics covered in great depth

Book Description

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.

What you will learn

Synchronize multiple threads and processes to manage parallel tasks

Implement message passing communication between processes to build parallel applications

Program your own GPU cards to address complex problems

Manage computing entities to execute distributed computational tasks

Write efficient programs by adopting the event-driven programming model

Explore the cloud technology with DJango and Google App Engine

Apply parallel programming techniques that can lead to performance improvements

Who this book is for

Python Parallel Programming Cookbook is intended for software developers who are well versed with Python and want to use parallel programming techniques to write powerful and efficient code. This book will help you master the basics and the advanced of parallel computing.

Product Details

ISBN-13:	9781785289583
Publisher:	Packt Publishing
Publication date:	08/29/2015
Pages:	286
Product dimensions:	7.50(w) x 9.25(h) x 0.60(d)

About the Author

Giancarlo Zaccone has more than 10 years of experience in managing research projects, both in scientific and industrial domains. He worked as a researcher at the National Research Council (CNR), where he was involved in a few parallel numerical computing and scientific visualization projects. He currently works as a software engineer at a consulting company, developing and maintaining software systems for space and defense applications. Giancarlo holds a master's degree in physics from the University of Naples Federico II and has completed a second-level postgraduate master's program in scientific computing from the Sapienza University of Rome. You can know more about him at https://it.linkedin.com/in/giancarlozaccone.

Table of Contents

1. Getting Started with Parallel Computing and Python
2. Introduction
3. The parallel computing memory architecture
4. Memory organization
5. Parallel programming models
6. How to design a parallel program
7. How to evaluate the performance of a parallel program
8. Introducing Python
9. Python in a parallel world
10. Introducing processes and threads
11. Start working with processes in Python
12. Start working with threads in Python
13. Thread-based Parallelism
14. Process-based Parallelism
15. Asynchronous Programming
16. Distributed Python
17. GPU Programming with Python