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GPU Programming with C++ and CUDA

You're reading from   GPU Programming with C++ and CUDA Uncover effective techniques for writing efficient GPU-parallel C++ applications

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Product type Paperback
Published in Aug 2025
Publisher Packt
ISBN-13 9781805124542
Length 270 pages
Edition 1st Edition
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Author (1):
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Paulo Motta Paulo Motta
Author Profile Icon Paulo Motta
Paulo Motta
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Table of Contents (17) Chapters Close

Preface 1. Understanding Where We Are Heading
2. Introduction to Parallel Programming FREE CHAPTER 3. Setting Up Your Development Environment 4. Hello CUDA 5. Hello Again, but in Parallel 6. Bring It On!
7. A Closer Look into the World of GPUs 8. Parallel Algorithms with CUDA 9. Performance Strategies 10. Moving Forward
11. Overlaying Multiple Operations 12. Exposing Your Code to Python 13. Exploring Existing GPU Models 14. Unlock Your Book’s Exclusive Benefits 15. Other Books You May Enjoy
16. Index

An overview of GPU architecture

After all that cooking, it's time for a change. Let's talk about GPUs.First, let me say that I’ve decided to explain GPUs first before comparing them with CPUs. I’m doing this on the assumption that you're already somewhat familiar with the (basic) architecture of a modern CPU.GPUs were originally thought to accelerate the output of processing graphics, since modern computer usage takes place almost exclusively in graphical environments. This differs from computing in the past, where the character-based interfaces that were used weren't graphically demanding. However, a shift occurred when it was noticed that a processing unit that was capable of dealing with the computations necessary for computer graphics could also be used for anything that could be expressed in terms of matrix computations, which is what linear algebra is all about.In the next chapter, we're going to focus specifically on NVIDIA GPUs...

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GPU Programming with C++ and CUDA
Published in: Aug 2025
Publisher: Packt
ISBN-13: 9781805124542
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