Book Image

C++ High Performance - Second Edition

By : Björn Andrist, Viktor Sehr
5 (2)
Book Image

C++ High Performance - Second Edition

5 (2)
By: Björn Andrist, Viktor 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)
15
Other Books You May Enjoy
16
Index

Postponing sqrt computations

This section will show you how to use a proxy object in order to postpone, or even avoid, using the computationally heavy std::sqrt() function when comparing the length of two-dimensional vectors.

A simple two-dimensional vector class

Let's start with a simple two-dimensional vector class. It has x and y coordinates and a member function called length() that calculates the distance from the origin to the location (x, y). We will call the class Vec2D. Here follows the definition:

class Vec2D {
public:
  Vec2D(float x, float y) : x_{x}, y_{y} {}
  auto length() const {
    auto squared = x_*x_ + y_*y_;
    return std::sqrt(squared);
  }
private:
  float x_{};
  float y_{};
};

Here is an example of how clients can use Vec2D:

auto a = Vec2D{3, 4}; 
auto b = Vec2D{4, 4};
auto shortest = a.length() < b.length() ? a : b;
auto length = shortest.length();
std::cout << length; // Prints 5 

The example creates two vectors and...