Book Image

Python Parallel Programming Cookbook

By : Giancarlo Zaccone
Book Image

Python Parallel Programming Cookbook

By: Giancarlo 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 (13 chapters)
Python Parallel Programming Cookbook
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

Collective communication using broadcast


During the development of a parallel code, we often find ourselves in the situation where we have to share between multiple processes the value of a certain variable at runtime or certain operations on variables that each process provides (presumably with different values).

To resolve this type of situations, the communication trees are used (for example the process 0 sends data to the processes 1 and 2, which respectively will take care of sending them to the processes 3, 4, 5, and 6, and so on).

Instead, MPI libraries provide functions ideal for the exchange of information or the use of multiple processes that are clearly optimized for the machine in which they are performed.

Broadcasting data from process 0 to processes 1, 2, 3, and 4

A communication method that involves all the processes belonging to a communicator is called a collective communication. Consequently, a collective communication generally involves more than two processes. However, instead...