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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

What this book covers

Chapter 1, A Brief Introduction to C++, introduces some important properties of C++, such as zero-cost abstractions, value semantics, const correctness, explicit ownership, and error handling. It also discusses the drawbacks of C++.

Chapter 2, Essential C++ Techniques, outlines automatic type deduction using auto, lambda functions, move semantics, and error handling.

Chapter 3, Analyzing and Measuring Performance, will teach you how to analyze algorithmic complexity using big O notation. The chapter also discusses how to profile your code to find hotspots and how to set up performance tests using Google Benchmark.

Chapter 4, Data Structures, takes you through the importance of structuring data so that it can be accessed quickly. Containers from the standard library, such as std::vector, std::list, std::unordered_map, and std::priority_queue, are introduced. Finally, this chapter demonstrates how to use parallel arrays.

Chapter 5, Algorithms, introduces the most important algorithms from the standard library. You will also learn how to use iterators and ranges, and how to implement your own generic algorithms.

Chapter 6, Ranges and Views, will teach you how to compose algorithms using the Ranges library introduced in C++20. You will learn why views from the Ranges library are useful and some benefits of lazy evaluation.

Chapter 7, Memory Management, focuses on safe and efficient memory management. This includes memory ownership, RAII, smart pointers, stack memory, dynamic memory, and custom memory allocators.

Chapter 8, Compile-Time Programming, explains metaprogramming techniques using constexpr, consteval, and type traits. You will also learn how to use C++20 concepts and the new Concepts library. Finally, it provides practical examples of metaprogramming use cases, such as reflection.

Chapter 9, Essential Utilities, will guide you through the Utilities library and how to benefit from types such as std::optional, std::any, and std::variant using compile-time programming techniques.

Chapter 10, Proxy Objects and Lazy Evaluation, explores how proxy objects can be used to perform under-the-hood optimizations while preserving clean syntax. Additionally, some creative uses of operator-overloading are demonstrated.

Chapter 11, Concurrency, covers the fundamentals of concurrent programming, including parallel execution, shared memory, data races, and deadlocks. It also includes an introduction to the C++ Thread support library, the Atomic library, and the C++ memory model.

Chapter 12, Coroutines and Lazy Generators, contains a general introduction to the coroutine abstraction. You will learn how ordinary functions and coroutines are executed on the CPU using the stack and the heap. C++20 stackless coroutines are introduced and you will discover how to solve problems using generators.

Chapter 13, Asynchronous Programming with Coroutines, introduces concurrent programming using stackless coroutines from C++20 and touches on the subject of asynchronous network programming using Boost.Asio.

Chapter 14, Parallel Algorithms, starts by showing the complexity of writing parallel algorithms and how to measure their performance. It then demonstrates how to utilize standard library algorithms in a parallel context using execution policies.

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