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
About the Author
About the Reviewers

How to synchronize processes

Multiple processes can work together to perform a given task. Usually, they share data. It is important that the access to shared data by various processes does not produce inconsistent data. Processes that cooperate by sharing data must therefore act in an orderly manner in order to access that data. Synchronization primitives are quite similar to those encountered for the library and threading.

They are as follows:

  • Lock: This object can be in one of the states: locked and unlocked. A lock object has two methods, acquire() and release(), to manage the access to a shared resource.

  • Event: This realizes simple communication between processes, one process signals an event and the other processes wait for it. An Event object has two methods, set() and clear(), to manage its own internal flag.

  • Condition: This object is used to synchronize parts of a workflow, in sequential or parallel processes. It has two basic methods, wait() is used to wait for a condition and notify_all...