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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

Testing an example from the DeepChem repository

Before testing the example, it is important that you have thoroughly studied the first section of this chapter and the concepts that follow. Without studying these concepts, it will be extremely difficult to understand the complete functionality of DeepChem.

How medicines reach their targets in our body

Some of you might already be aware that ibuprofen is a popular drug as a painkiller (for example, for a headache, backache, or other forms of pain). When you consume this medicine, it reaches your stomach and starts disintegrating in the acidic fluids present there within minutes! The dissolved ibuprofen travels into the small intestine and across its intestinal wall into a blood...

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