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Hands-On GPU Computing with Python

You're reading from   Hands-On GPU Computing with Python Explore the capabilities of GPUs for solving high performance computational problems

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Product type Paperback
Published in May 2019
Publisher Packt
ISBN-13 9781789341072
Length 452 pages
Edition 1st Edition
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Avimanyu Bandyopadhyay Avimanyu Bandyopadhyay
Author Profile Icon Avimanyu Bandyopadhyay
Avimanyu Bandyopadhyay
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Table of Contents (17) Chapters Close

Preface 1. Section 1: Computing with GPUs Introduction, Fundamental Concepts, and Hardware
2. Introducing GPU Computing FREE CHAPTER 3. Designing a GPU Computing Strategy 4. Setting Up a GPU Computing Platform with NVIDIA and AMD 5. Section 2: Hands-On Development with GPU Programming
6. Fundamentals of GPU Programming 7. Setting Up Your Environment for GPU Programming 8. Working with CUDA and PyCUDA 9. Working with ROCm and PyOpenCL 10. Working with Anaconda, CuPy, and Numba for GPUs 11. Section 3: Containerization and Machine Learning with GPU-Powered Python
12. Containerization on GPU-Enabled Platforms 13. Accelerated Machine Learning on GPUs 14. GPU Acceleration for Scientific Applications Using DeepChem 15. Other Books You May Enjoy Appendix A

Local containers

Containerization is a concept that takes the idea of virtualization many steps further. It is the process of providing readily deployable applications and their dependencies, preinstalled and preconfigured within individual containers at operating system level. These containers are all isolated user space instances:

By Natlibfi-arlehiko - Own work, CC BY-SA 4.0, https://commons.wikimedia.org/w/index.php?curid=69328769

With containerization, you no longer require even setting up a virtualized environment, as all of those measures are already taken care of. You can quickly get started with a production-ready interface. Hence we can conclude that containerization boosts productivity by a huge margin.

When we set up containers in a locally accessible system, it is referred to as local containerization. In this section, we are going to continue our discussion on local...

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