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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 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

Calculating numerical integrals

To start with: what is an integral? Well, an integral is a concept in calculus that represents the area under a curve on a graph, between two points. Imagine you are tracking the path of a car moving along a road, and at fixed intervals you measure the car’s speed. Now, if you plot that and calculate the area under the curve representing its speed over time, considering that distance = speed × time, you get the total distance the car traveled! In simple terms, an integral sums up tiny slices of area to find a total, making it a powerful way to measure quantities that accumulate over a range.

Why are integrals useful?

Integrals are everywhere in science, engineering, and beyond. They help us measure quantities that change continuously—like distance, energy, or growth—by calculating the total quantity over time or space. For example, engineers use integrals to determine forces on structures, economists use them...

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