Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Save more on your purchases! discount-offer-chevron-icon
Savings automatically calculated. No voucher code required.
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Newsletter Hub
Free Learning
Arrow right icon
timer SALE ENDS IN
0 Days
:
00 Hours
:
00 Minutes
:
00 Seconds
Arrow up icon
GO TO TOP
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

Arrow left icon
Product type Paperback
Published in Aug 2025
Publisher Packt
ISBN-13 9781805124542
Length 270 pages
Edition 1st Edition
Languages
Tools
Arrow right icon
Author (1):
Arrow left icon
Paulo Motta Paulo Motta
Author Profile Icon Paulo Motta
Paulo Motta
Arrow right icon
View More author details
Toc

Table of Contents (17) Chapters Close

Preface 1. Understanding Where We Are Heading FREE CHAPTER
2. Introduction to Parallel Programming 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

Hello Again, but in Parallel

The objective of using GPUs is to exploit parallelism to accelerate the execution of our programs. For that, we must understand the parallel model that GPUs make available. In this chapter we’ll first learn about the SIMD execution model and discuss a simple program to test number primality in parallel, but using an approach which makes it almost like a CPU application. Then we will learn more about moving data to and from the GPU, since its memory is separated from the main system. The chapter closes with a section presenting a simple program that fully benefits from the use of GPUs.

Thus in this chapter we’re going to cover the following main topics:

  • SIMD execution model
  • Primality test with a not-so-parallel program
  • Moving memory
  • Vector addition in full parallel
lock icon The rest of the chapter is locked
Visually different images
CONTINUE READING
83
Tech Concepts
36
Programming languages
73
Tech Tools
Icon Unlimited access to the largest independent learning library in tech of over 8,000 expert-authored tech books and videos.
Icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Icon 50+ new titles added per month and exclusive early access to books as they are being written.
GPU Programming with C++ and CUDA
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Modal Close icon
Modal Close icon