Python Parallel Programming Cookbook

Book Description

Master efficient parallel programming to build powerful applications using Python

About This Book

• 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

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.

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

In Detail

Parallel programming techniques are required for a developer to get the best use of all the computational resources available today and to build efficient software systems. From multi-core to GPU systems up to the distributed architectures, the high computation of programs throughout requires the use of programming tools and software libraries. Because of this, it is becoming increasingly important to know what the parallel programming techniques are. Python is commonly used as even non-experts can easily deal with its concepts.

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 also understand the StarCluster framework, Pycsp, Scoop, and Disco modules in Python. Further on, you will learn GPU programming with Python using the PyCUDA module along with evaluating performance limitations. Next you will get acquainted with the cloud computing concepts in Python, using Google App Engine (GAE), and building your first application with GAE. Lastly, you will learn about grid computing concepts in Python and using PyGlobus toolkit, GFTP and GASS COPY to transfer files, and service monitoring in PyGlobus.

Style and approach

A step-by-step guide to parallel programming using Python, with recipes accompanied by one or more programming examples. It is a practically oriented book and has all the necessary underlying parallel computing concepts.

Table of Contents

Chapter 1: Getting Started with Parallel Computing and Python
Chapter 2: Thread-based Parallelism
Chapter 3: Process-based Parallelism
Chapter 4: Asynchronous Programming
Chapter 5: Distributed Python
Chapter 6: GPU Programming with Python

中文：

书名：Python Parallel Programming Cookbook

掌握高效的并行编程以使用Python构建功能强大的应用程序

About This Book

• 高效并行软件的设计与实现
• 掌握新的编程技术，解决复杂的编程问题
• 通过这本书探索并行编程的世界，这本书是关于不同类型的并行计算任务的Python语言的首选资源，使用深入讨论的示例和主题

Who This Book Is For

《Python并行编程指南》面向精通Python并希望使用并行编程技术编写功能强大且高效的代码的软件开发人员。本书将帮助您掌握并行计算的基础知识和高级知识。

What You Will Learn

• Synchronize multiple threads and processes to manage parallel tasks
• 实现进程之间的消息传递通信，以构建并行应用程序
• 对您自己的GPU卡进行编程以解决复杂问题
• 管理计算实体以执行分布式计算任务
• 采用事件驱动编程模型编写高效程序
• Explore the cloud technology with DJango and Google App Engine
• 应用可提高性能的并行编程技术

In Detail

开发人员需要使用并行编程技术来最大限度地利用当今可用的所有计算资源，并构建高效的软件系统。从多核到GPU系统再到分布式体系结构，程序的高计算量始终需要使用编程工具和软件库。正因为如此，了解什么是并行编程技术变得越来越重要。由于即使是非专家也可以很容易地处理它的概念，所以通常使用Python。

这本书将教您使用Python中的示例进行并行编程技术，并将帮助您探索编写允许同时发生多个进程的代码的多种方法。它从向您介绍并行计算的世界开始，接着介绍了Python的基础知识。然后，通过同步线程并使用锁、互斥、信号量队列、GIL和线程池，使用Python线程模块探索基于线程的并行性模型。

接下来，您将学习基于进程的并行，其中您将使用消息传递同步进程，并了解MPI Python模块的性能。然后，您将继续学习使用Python asyncio模块以及处理异常的异步并行编程模型。继续学习，您将发现使用Python进行分布式计算，并学习如何安装代理、使用Celery Python模块和创建Worker。

您还将了解使用Python语言编写的StarCluster框架、Pycsp、Scoop和Disco模块。在进一步的学习中，您将使用PyCUDA模块学习使用Python进行GPU编程，并评估性能限制。接下来，您将使用Google App Engine(GAE)熟悉Python中的云计算概念，并使用GAE构建您的第一个应用程序。最后，您将学习使用Python语言中的网格计算概念，以及使用PyGlobus工具包、Gftp和Gass Copy传输文件，以及在PyGlobus中进行服务监控。

Style and approach

使用Python进行并行编程的分步指南，并附有一个或多个编程示例。它是一本面向实践的书，拥有所有必要的基本并行计算概念。

Table of Contents

第1章：并行计算和Python入门
Chapter 2: Thread-based Parallelism
第3章：基于进程的并行性
Chapter 4: Asynchronous Programming
Chapter 5: Distributed Python
第6章：使用Python进行GPU编程