Book Image

Python Parallel Programming Cookbook - Second Edition

By : Giancarlo Zaccone
Book Image

Python Parallel Programming Cookbook - Second Edition

By: Giancarlo Zaccone

Overview of this book

<p>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. </p><p> </p><p>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. </p><p> </p><p>By the end of this book, you will be confident in building concurrent and high-performing applications in Python.</p>
Table of Contents (16 chapters)
Title Page

Building applications with PyOpenCL

The first step in the construction of a program for PyOpenCL is the coding of the host application. This is performed on the CPU and has the task of managing the possible execution of the kernel on the GPU card (that is, the device).

A kernel is a basic unit of executable code, similar to a C function. It can be data-parallel or task-parallel. However, the cornerstone of PyOpenCL is the exploitation of parallelism.

A fundamental concept is a program, which is a collection of kernels and other functions, analogous to dynamic libraries. So, we can group instructions in a kernel and group different kernels into a program.

Programs can be called from applications. We have the execution queues that indicate the order in which the kernels are executed. However, in some cases, these can be launched without following the original order.

We can finally...