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C++ High Performance

C++ High Performance

By : Björn Andrist, Sehr
4.4 (24)
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C++ High Performance

C++ High Performance

4.4 (24)
By: Björn Andrist, Sehr

Overview of this book

C++ High Performance, Second Edition guides you through optimizing the performance of your C++ apps. This allows them to run faster and consume fewer resources on the device they're running on without compromising the readability of your codebase. The book begins by introducing the C++ language and some of its modern concepts in brief. Once you are familiar with the fundamentals, you will be ready to measure, identify, and eradicate bottlenecks in your C++ codebase. By following this process, you will gradually improve your style of writing code. The book then explores data structure optimization, memory management, and how it can be used efficiently concerning CPU caches. After laying the foundation, the book trains you to leverage algorithms, ranges, and containers from the standard library to achieve faster execution, write readable code, and use customized iterators. It provides hands-on examples of C++ metaprogramming, coroutines, reflection to reduce boilerplate code, proxy objects to perform optimizations under the hood, concurrent programming, and lock-free data structures. The book concludes with an overview of parallel algorithms. By the end of this book, you will have the ability to use every tool as needed to boost the efficiency of your C++ projects.
Table of Contents (17 chapters)
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15
Other Books You May Enjoy
16
Index

Asymptotic complexity and big O notation

There is usually more than one way to solve a problem, and if efficiency is a concern, you should first focus on high-level optimizations by choosing the right algorithms and data structures. A useful way of evaluating and comparing algorithms is by analyzing their asymptotic computational complexity—that is, analyzing how the running time or memory consumption grows when the size of the input increases. In addition, the C++ standard library specifies the asymptotic complexity for all containers and algorithms, which means that a basic understanding of this topic is a must if you are using this library. If you already have a good understanding of algorithm complexity and the big O notation, you can safely skip this section.

Let's start off with an example. Suppose we want to write an algorithm that returns true if it finds a specific key in an array, or false otherwise. In order to find out how our algorithm behaves when passed...

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