Python Parallel Programming Cookbook

Implement effective programming techniques in Python to build scalable software that saves time and memory
Key FeaturesDesign distributed computing systems and massive computational tasks coherentlyLearn practical recipes with concise explanations that address development pain points encountered while coding parallel programsUnderstand how to host your parallelized applications on the cloudBook DescriptionNowadays, 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.
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.
By the end of this book, you will be confident in building concurrent and high-performing applications in Python.
What you will learnSynchronize multiple threads and processes to manage parallel tasksUse message passing techniques to establish communication between processes to build parallel applicationsProgram your own GPU cards to address complex problemsManage computing entities to execute distributed computational taskWrite efficient programs by adopting the event-driven programming modelExplore cloud technology with Django and Google App EngineApply parallel programming techniques that can lead to performance improvementsWho this book is forThe Python Parallel Programming Cookbook is for software developers who are well-versed with Python and want to use parallel programming techniques to write powerful and efficient code. This book will help you master the basics and the advanced of parallel computing.
Giancarlo Zaccone has over fifteen years' experience of managing research projects in the scientific and industrial domains. He is a software and systems engineer at the European Space Agency (ESTEC), where he mainly deals with the cybersecurity of satellite navigation systems. Giancarlo holds a master's degree in physics and an advanced master's degree in scientific computing. Giancarlo has already authored the following titles, available from Packt: Python Parallel Programming Cookbook (First Edition), Getting Started with TensorFlow, Deep Learning with TensorFlow (First Edition), and Deep Learning with TensorFlow (Second Edition).