O'Reilly logo

Python Parallel Programming Cookbook by Giancarlo Zaccone

Stay ahead with the world's most comprehensive technology and business learning platform.

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, tutorials, and more.

Start Free Trial

No credit card required

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

Introduction

The graphics processing unit (GPU) is an electronic circuit that specializes in processing data to render images from polygonal primitives. Although they were designed to carry out rendering images, ...

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, interactive tutorials, and more.

Start Free Trial

No credit card required