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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
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

Summary

In this chapter, we learned about different GPU manufacturers and computing on NVIDIA and AMD GPU platforms. We also compared these two leading GPU manufactures and explored their scope and applicability options through a CUDA versus ROCm comparison. We looked through different GPUs and saw which one to choose according to a specific requirement. Finally, we revisited configuration options from Chapter 2, Designing a GPU Computing Strategy, and saw how we can modify them toward a liquid-cooled setup. Considering the RTX 2080 Ti and the Radeon VII, we understood their applicability by modifying two of our previously listed configurations in the High-end budget section in Chapter 2, Designing a GPU Computing Strategy.

Now that you have come to the end of this chapter, you should now be able to distinguish between NVIDIA and AMD GPUs based on your set of computational requirements...

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