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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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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

The social impact of GPUs

Big data is everywhere and so datasets are also everywhere, meaning that GPUs and AI can be applied to any other computational field. Since we have already discussed how GPUs can contribute in science and AI, let's read about some more examples in other fields that reveal more about how GPUs can contribute to our society.

We are going to discuss some diverse fields here, but, of course, there are no limits!

Archaeological restoration/reconstruction

The following research paper is discussed in this section: Automated GPU-Based Surface Morphology Reconstruction of Volume Data for Archaeology, D Jungblut, S Karl, H Mara, S Krömker, G Wittum (2012), Contributions in Mathematical and Computational...

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