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

Using the PyOpenCL module

Open Computing Language (OpenCL) is a framework used to develop programs that work across heterogeneous platforms, which can be made either by the CPU or GPU that are produced by different manufacturers. This platform was created by Apple, but has been developed and maintained by a non-profit consortium called the Khronos Group. This framework is the main alternative for the CUDA execution of software on a GPU, but has a point of view that is diametrically opposed. However, CUDA makes specialization its strong point (produced, developed, and compatible with NVIDIA), ensuring excellent performance at the expense of portability. OpenCL offers a solution compatible with nearly all devices on the market. Software written in OpenCL can run on processor products from all major industries, such as Intel, NVIDIA, IBM, and AMD. OpenCL includes a language to write kernels based on C99 (with some restrictions), allowing you to use the hardware available directly in the same...