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Data Structures and Algorithms with the C++ STL

You're reading from   Data Structures and Algorithms with the C++ STL A guide for modern C++ practitioners

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Product type Paperback
Published in Feb 2024
Publisher Packt
ISBN-13 9781835468555
Length 458 pages
Edition 1st Edition
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John Farrier John Farrier
Author Profile Icon John Farrier
John Farrier
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Table of Contents (30) Chapters Close

Preface 1. Part 1: Mastering std::vector FREE CHAPTER
2. Chapter 1: The Basics of std::vector 3. Chapter 2: Mastering Iterators with std::vector 4. Chapter 3: Mastering Memory and Allocators with std::vector 5. Chapter 4: Mastering Algorithms with std::vector 6. Chapter 5: Making a Case for std::vector 7. Part 2: Understanding STL Data Structures
8. Chapter 6: Advanced Sequence Container Usage 9. Chapter 7: Advanced Ordered Associative Container Usage 10. Chapter 8: Advanced Unordered Associative Container Usage 11. Chapter 9: Advanced Container Adaptor Usage 12. Chapter 10: Advanced Container View Usage 13. Part 3: Mastering STL Algorithms
14. Chapter 11: Fundamental Algorithms and Searching 15. Chapter 12: Manipulation and Transformation 16. Chapter 13: Numeric and Range -Based Operations 17. Chapter 14: Permutations, Partitions, and Heaps 18. Chapter 15: STL with Ranges 19. Part 4: Creating STL-Compatible Types and Algorithms
20. Chapter 16: Creating STL-Types Containers 21. Chapter 17: Creating STL -Compatible Algorithms 22. Chapter 18: Type Traits and Policies 23. Part 5: STL Data Structures and Algorithms: Under the Hood
24. Chapter 19: Exception Safety 25. Chapter 20: Thread Safety and Concurrency with the STL 26. Chapter 21: STL Interaction with Concepts and Coroutines 27. Chapter 22: Parallel Algorithms with the STL 28. Index 29. Other Books You May Enjoy

Advanced numeric operations

In order to take our journey with the numeric operations of the C++ STL a step further, let’s look at the advanced numerical procedures that elevate data handling and make parallelism and concurrency allies in the pursuit of performance.

Remember our discussion about generating sequences and computing summaries? Well, imagine supercharging these operations to process enormous volumes of data efficiently by harnessing the power of multiple processors. This is precisely where advanced numeric operations shine. Parallel algorithms, introduced in C++17, provide the means to achieve this, ensuring our computations are both swift and efficient, even in concurrent environments.

When dealing with vast datasets, sequential processing often doesn’t cut it. Take the example of summing up a large vector of numbers. Doing it in a straight line gets the job done but might not be the quickest. However, the operation can be sped up significantly by splitting...

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