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

Product type Paperback

Published in May 2019

Publisher Packt

ISBN-13 9781789341072

Length 452 pages

Edition 1st Edition

Languages

Python

Tools

CUDA

Concepts

Data Processing

Author (1):

Avimanyu Bandyopadhyay

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Table of Contents (17) Chapters

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

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Appendix A

How GPUs empower science and AI in current times

NVIDIA RAPIDS is a very recent example of using an open source system to carry out research related to science, AI, and other fields. There are numerous examples of research work in science that has been empowered by GPU acceleration. Let's understand its significance through some of these amazing research examples.

Bioinformatics workflow management

The following research paper is discussed in this section: Managing Complex Workflows in Bioinformatics: An Interactive Toolkit With GPU Acceleration, A Welivita, I Perera, D Meedeniya, A Wickramarachchi, V Mallawaarachchi (2018), IEEE Transactions on NanoBioscience, 17(3), 199-208, doi:10.1109/tnb.2018.2837122.

BioWorkflow...

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Hands-On GPU Computing with Python

Published in: May 2019

Publisher: Packt

ISBN-13: 9781789341072

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Authors (1)

Avimanyu Bandyopadhyay

Avimanyu Bandyopadhyay is currently pursuing a PhD degree in Bioinformatics based on applied GPU computing in Computational Biology at Heritage Institute of Technology, Kolkata, India. Since 2014, he developed a keen interest in GPU computing, and used CUDA for his master's thesis. He has experience as a systems administrator as well, particularly on the Linux platform. Avimanyu is also a scientific writer, technology communicator, and a passionate gamer. He has published technical writing on open source computing and has actively participated in NVIDIA's GPU computing conferences since 2016. A big-time Linux fan, he strongly believes in the significance of Linux and an open source approach in scientific research. Deep learning with GPUs is his new passion!

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