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Python Parallel Programming Cookbook

You're reading from   Python Parallel Programming Cookbook Master efficient parallel programming to build powerful applications using Python

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Product type Paperback
Published in Aug 2015
Publisher
ISBN-13 9781785289583
Length 286 pages
Edition 1st Edition
Languages
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Author (1):
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Giancarlo Zaccone Giancarlo Zaccone
Author Profile Icon Giancarlo Zaccone
Giancarlo Zaccone
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Toc

Table of Contents (8) Chapters Close

Preface 1. Getting Started with Parallel Computing and Python 2. Thread-based Parallelism FREE CHAPTER 3. Process-based Parallelism 4. Asynchronous Programming 5. Distributed Python 6. GPU Programming with Python Index

Chapter 6. GPU Programming with Python

In this chapter, we will cover the following recipes:

  • Using the PyCUDA module
  • How to build a PyCUDA application
  • Understanding the PyCUDA Memory Model with matrix manipulation
  • Kernel invocations with GPUArray
  • Evaluating element-wise expressions with PyCUDA
  • The MapReduce operation with PyCUDA
  • GPU programming with NumbaPro
  • Using GPU-accelerated libraries with NumbaPro
  • Using the PyOpenCL module
  • How to build a PyOpenCL application
  • Evaluating element-wise expressions with PyOpenCL
  • Testing your GPU application with PyOpenCL
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