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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

Comparing GPU programmable platforms on NVIDIA and AMD

So far, we have explored the scope of computing on NVIDIA and AMD GPUs through two separate chapters. Now, let's specifically look into the comparisons between their respective APIs:

NVIDIA CUDA

AMD ROCm

The API is called Compute Unified Device Architecture

The API is called Radeon Open Compute platform

Proprietary

Open source

Released in 2007

Released in 2016

Wider support

Still under adoption and very actively catching up

Significant number of programmable libraries

Fewer libraries than CUDA but active ongoing development

Cannot be used with non-NVIDIA devices

Cross-platform independence due to open standards

CUDA-C language being used

HIP for cross-platform; HC for AMD GPUs

.cu extension used for files

.cpp extension used for files

Non-portable

CUDA code...

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