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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

Product type Paperback

Published in Aug 2025

Publisher Packt

ISBN-13 9781805124542

Length 270 pages

Edition 1st Edition

Languages

Tools

Concepts

Application Development

Author (1):

Paulo Motta

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Table of Contents (17) Chapters

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

How to unlock these benefits in three easy steps

15. Other Books You May Enjoy

16. Index

Summary

In this chapter we have worked our way through a variety of optimization strategies, as well as the use of the graphical profiler that is available in the CUDA toolkit. This is an essential tool to help attack the hot spots in our kernels so that we use our time as effectively and efficiently as possible.

In the next chapter we will learn another strategy to accelerate our code: overlaying memory transfers with kernel execution.

The rest of the chapter is locked

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Authors (1)

Paulo Motta

Paulo Motta

Paulo Motta completed the PhD in Computer Science with an emphasis in parallel systems at PUC-Rio in 2011. Currently, Paulo Motta is a Senior Research Software Development Engineer at Microsoft and a postdoctoral researcher on quantum walks simulations with Hiperwalk at the National Scientific Computing Laboratory in Brazil. Paulo is a senior member of IEEE Computer Society with over 25 years' experience in software development and 9 years experience as a university professor.

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