Book Image

Python Parallel Programming Cookbook

By : Zaccone
Book Image

Python Parallel Programming Cookbook

By: 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 (8 chapters)
7
Index

What you need for this book

All the examples of this book can be tested in a Windows 7 32-bit machine. Also, a Linux environment will be useful.

The Python versions needed to run the examples are:

  • Python 3.3 (for the first five chapters)
  • Python 2.7 (only for Chapter 6, GPU Programming with Python)

The following modules (all of which are freely downloadable) are required:

  • mpich-3.1.4
  • pip 6.1.1
  • mpi4py1.3.1
  • asyncio 3.4.3
  • Celery 3.1.18
  • Numpy 1.9.2
  • Flower 0.8.32 (optional)
  • SCOOP 0.7.2
  • Pyro 4.4.36
  • PyCSP 0.9.0
  • DISCO 0.5.2
  • RPyC 3.3.0
  • PyCUDA 2015.1.2
  • CUDA Toolkit 4.2.9 (at least)
  • NVIDIA GPU SDK 4.2.9 (at least)
  • NVIDIA GPU driver
  • Microsoft Visual Studio 2008 C++ Express Edition (at least)
  • Anaconda Python Distribution
  • NumbaPro compiler
  • PyOpenCL 2015.1
  • Win32 OpenCL Driver 15.1 (at least)