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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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Author (1):
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Avimanyu Bandyopadhyay Avimanyu Bandyopadhyay
Author Profile Icon Avimanyu Bandyopadhyay
Avimanyu Bandyopadhyay
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Toc

Table of Contents (17) Chapters Close

Preface 1. Section 1: Computing with GPUs Introduction, Fundamental Concepts, and Hardware FREE CHAPTER
2. Introducing GPU Computing 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

Containerization on GPU-Enabled Platforms

In this new chapter, we will continue our exploration with GPUs while specifically focusing on user accessibility. You will learn about different environments to choose from when setting up a GPU-based programmable platform. These environments will be compared and discussed to help you decide on the most suitable one pertaining to usability and different situations or conditions. Following this, system-wide and virtual environments will be explained. Their advantages and disadvantages will also be explored.

Virtualenv, which is similar to Conda, will be discussed as an example of a closed environment separate from the base system. We will also look at a scenario where both system-wide and Virtualenv packages can co-exist and work together when accessed from a virtual environment.

Exploring further, containers such as Docker and Kubernetes...

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