Python Parallel Programming Cookbook, 2nd Edition

Book Description

Implement effective programming techniques in Python to build scalable software that saves time and memory

Key Features

• Design distributed computing systems and massive computational tasks coherently
• Learn practical recipes with concise explanations that address development pain points encountered while coding parallel programs
• Understand how to host your parallelized applications on the cloud

Book Description

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.

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.

By the end of this book, you will be confident in building concurrent and high-performing applications in Python.

What you will learn

• Synchronize multiple threads and processes to manage parallel tasks
• Use message passing techniques to establish communication between processes to build parallel applications
• Program your own GPU cards to address complex problems
• Manage computing entities to execute distributed computational task
• Write efficient programs by adopting the event-driven programming model
• Explore cloud technology with Django and Google App Engine
• Apply parallel programming techniques that can lead to performance improvements

Who this book is for

The Python Parallel Programming Cookbook is 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.

Table of Contents

1. Getting Started with Parallel Computing and Python
2. Thread-based Parallelism
3. Process-based Parallelism
4. Message Passing
5. Asynchronous Programming
6. Distributed Python
7. Cloud Computing
8. Heterogeneous Computing
9. Python Debugging and Testing

中文：

书名：Python Parallel Programming Cookbook, 2nd Edition

在Python中实施有效的编程技术以构建可伸缩的软件，从而节省时间和内存

Key Features

• 一致地设计分布式计算系统和海量计算任务
• 学习实用食谱，通过简洁的解释来解决在编写并行程序时遇到的开发痛点
• 了解如何在云上托管您的并行应用程序

Book Description

如今，对于程序员来说，理解软件和硬件的并行本质之间的联系变得极其重要，以便他们的程序在计算机体系结构上高效运行。基于并行编程的应用程序速度快、健壮且易于扩展。

这个更新版本提供了在Python3.7中构建高效并发应用程序的尖端技术。这本书介绍了并行编程体系结构，并介绍了基于线程和基于进程的并行的基本配方。您将了解互斥、信号量、锁、利用线程的队列和多处理模块，所有这些都是构建并行应用程序的基本工具。MPI编程的诀窍将帮助您使用mpi4py的基本消息传递技术来同步进程。此外，您还将掌握异步编程，以及如何在PyCUDA和PyOpenCL框架中使用GPU的强大功能。最后，您将探索如何使用芹菜设计分布式计算系统，并使用PythonAnywhere、Docker和无服务器应用程序在云上构建Python应用程序。

到本书结束时，您将有信心用Python构建并发和高性能的应用程序。

What you will learn

• Synchronize multiple threads and processes to manage parallel tasks
• 使用消息传递技术在进程之间建立通信，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
• 使用Django和Google App Engine探索云技术
• 应用可提高性能的并行编程技术

这本书是为谁而写的

《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。

Table of Contents

1. 并行计算和Python入门
2. 基于线程的并行性
3. 基于进程的并行性
4. Message Passing
5. 异步编程
6. Distributed Python
7. Cloud Computing
8. 异构式计算
9. Python Debugging and Testing