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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

Introduction to Parallel Programming

Welcome to the world of graphics processing unit (GPU) programming!

Before we talk about programming GPUs, we must understand what parallel programming is and how it can benefit our applications. As with everything in life, it has its challenges. In this chapter, we’ll explore both the benefits and drawbacks of parallel programming, laying the groundwork for our deep dive into GPU programming. So in this first chapter, we’ll be discussing a variety of topics without developing any code. In doing so, we’ll establish the foundations on which to build throughout our journey.

Apart from being useful, the information provided in this chapter is fundamental to understanding what happens inside a GPU, as we’ll discuss shortly. By the end of the chapter, you’ll understand why parallelism is important and when it makes sense to use it in your applications.

In this chapter, we’re going to cover the following...

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