Book Image

Learning Concurrency in Python

By : Elliot Forbes
Book Image

Learning Concurrency in Python

By: Elliot Forbes

Overview of this book

Python is a very high level, general purpose language that is utilized heavily in fields such as data science and research, as well as being one of the top choices for general purpose programming for programmers around the world. It features a wide number of powerful, high and low-level libraries and frameworks that complement its delightful syntax and enable Python programmers to create. This book introduces some of the most popular libraries and frameworks and goes in-depth into how you can leverage these libraries for your own high-concurrent, highly-performant Python programs. We'll cover the fundamental concepts of concurrency needed to be able to write your own concurrent and parallel software systems in Python. The book will guide you down the path to mastering Python concurrency, giving you all the necessary hardware and theoretical knowledge. We'll cover concepts such as debugging and exception handling as well as some of the most popular libraries and frameworks that allow you to create event-driven and reactive systems. By the end of the book, you'll have learned the techniques to write incredibly efficient concurrent systems that follow best practices.
Table of Contents (20 chapters)
Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
Index

Chapter 11. Using the GPU

In this penultimate chapter, you'll learn about the various ways we can leverage the power of the GPU in order to greatly improve the performance of our Python programs. We'll take a general look at what GPUs are and what sort of advantages they can give us should we leverage them in certain scenarios within our Python programs.

We'll then look at the various Python wrappers that will enable us to use these GPUs for our more general purpose based programs without having to dive too deeply into the finer details.

Libraries such as PyCUDA are incredible in the sense that they enable programmers to create these high-performance applications without having to learn far more complex and low-level languages such as C and C++.

In this chapter, we'll explore a number of different libraries that are quite widely used in the GPU programming ecosystem. We'll cover the basics of how to get up and running with these libraries before showing how these concepts can be translated...