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

Implementing memory management with PyCUDA

PyCUDA programs should respect the rules dictated by the structure and the internal organization of SM that impose constraints on thread performances. In fact, the knowledge and the correct use of various types of memory that the GPU makes available are fundamental in order to achieve maximum efficiency. In those GPU cards, enabled for CUDA use, there are four types of memory, which are as follows:

  • Registers: Each thread is assigned a memory register which only the assigned thread can access, even if the threads belong to the same block.
  • Shared memory: Each block has its own shared memory between the threads that belong to it. Even this memory is extremely fast.
  • Constant memory: All threads in a grid have constant access to the memory, but can only be accessed in reading. The data present in it persists for the entire duration of...