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C++ High Performance

You're reading from   C++ High Performance Master the art of optimizing the functioning of your C++ code

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Product type Paperback
Published in Dec 2020
Publisher Packt
ISBN-13 9781839216541
Length 544 pages
Edition 2nd Edition
Languages
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Authors (2):
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Viktor Sehr Viktor Sehr
Author Profile Icon Viktor Sehr
Viktor Sehr
Björn Andrist Björn Andrist
Author Profile Icon Björn Andrist
Björn Andrist
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Toc

Table of Contents (17) Chapters Close

Preface 1. A Brief Introduction to C++ 2. Essential C++ Techniques FREE CHAPTER 3. Analyzing and Measuring Performance 4. Data Structures 5. Algorithms 6. Ranges and Views 7. Memory Management 8. Compile-Time Programming 9. Essential Utilities 10. Proxy Objects and Lazy Evaluation 11. Concurrency 12. Coroutines and Lazy Generators 13. Asynchronous Programming with Coroutines 14. Parallel Algorithms 15. Other Books You May Enjoy
16. Index

Parallel arrays

We will finish this chapter by talking about iterating over elements and exploring ways to improve performance when iterating over array-like data structures. I have already mentioned two important factors for performance when accessing data: spatial locality and temporal locality. When iterating over elements stored contiguously in memory, we will increase the probability that the data we need is already cached if we manage to keep our objects small, thanks to spatial locality. Obviously, this will have a great impact on performance.

Recall the cache-thrashing example, shown at the beginning of this chapter, where we iterated over a matrix. It demonstrated that we sometimes need to think about the way we access data, even if we have a fairly compact representation of the data.

Next, we will compare how long it takes to iterate over objects of different sizes. We will start by defining two structs, SmallObject and BigObject:

struct SmallObject { 
...
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