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Hands-On GPU Computing with Python

You're reading from  Hands-On GPU Computing with Python

Product type Book
Published in May 2019
Publisher Packt
ISBN-13 9781789341072
Pages 452 pages
Edition 1st Edition
Languages
Author (1):
Avimanyu Bandyopadhyay Avimanyu Bandyopadhyay
Profile icon Avimanyu Bandyopadhyay

Table of Contents (17) Chapters

Preface Section 1: Computing with GPUs Introduction, Fundamental Concepts, and Hardware
Introducing GPU Computing Designing a GPU Computing Strategy Setting Up a GPU Computing Platform with NVIDIA and AMD Section 2: Hands-On Development with GPU Programming
Fundamentals of GPU Programming Setting Up Your Environment for GPU Programming Working with CUDA and PyCUDA Working with ROCm and PyOpenCL Working with Anaconda, CuPy, and Numba for GPUs Section 3: Containerization and Machine Learning with GPU-Powered Python
Containerization on GPU-Enabled Platforms Accelerated Machine Learning on GPUs GPU Acceleration for Scientific Applications Using DeepChem Other Books You May Enjoy Appendix A

Summary

In this chapter, we learned about the basic concepts behind GPU computing, the history behind its evolution, and its scope of use in diverse fields. We also learned about the simplicity of Python syntax and why this simplicity can be of great significance when harnessing GPUs for computational work. In the final section, we looked at the uses of GPU applications beyond just science and AI, and we looked at various fields, such as archaeology, weather, music, sports, art, security, agriculture, and economics.

If you are a gamer and/or a computing enthusiast, from now on, you will be able to better understand the computational aspect of GPUs and Python code. The various fields of applications that were discussed in the later sections of this chapter will now allow you to have a general idea about the limitless areas in which you can create your own GPU applications. GPU...

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