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

Why do we need parallel computing?

The growth in computing power made available by modern computers has resulted in us facing computational problems of increasing complexity in relatively short time frames. Until the early 2000s, complexity was dealt with by increasing the number of transistors as well as the clock frequency of single-processor systems, which reached peaks of 3.5-4 GHz. However, the increase in the number of transistors causes the exponential increase of the power dissipated by the processors themselves. In essence, there is, therefore, a physical limitation that prevents further improvement in the performance of single-processor systems.

For this reason, in recent years, microprocessor manufacturers have focused their attention on multi-core systems. These are based on a core of several physical processors that share the same memory, thus bypassing the problem of dissipated power described earlier. In recent years, quad-core and octa-core systems have also become standard on normal desktop and laptop configurations.

On the other hand, such a significant change in hardware has also resulted in an evolution of software structure, which has always been designed to be executed sequentially on a single processor. To take advantage of the greater computational resources made available by increasing the number of processors, the existing software must be redesigned in a form appropriate to the parallel structure of the CPU, so as to obtain greater efficiency through the simultaneous execution of the single units of several parts of the same program.