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 optimize communication

An interesting feature that is provided by MPI concerns the virtual topologies. As already noted, all the communication functions (point-to-point or collective) refer to a group of processes. We have always used the MPI_COMM_WORLD group that includes all processes. It assigns a rank 0 to n-1 for each process that belongs to a communicator of the size n. However, MPI allows us to assign a virtual topology to a communicator. It defines a particular assignment of labels to the different processes. A mechanism of this type permits you to increase the execution performance. In fact, if you build a virtual topology, then every node will communicate only with its virtual neighbor, optimizing the performance.

For example, if the rank was randomly assigned, a message could be forced to pass to many other nodes before it reaches the destination. Beyond the question of performance, a virtual topology makes sure that the code is more clear and readable. MPI provides two...