Book Image

Modern C++ Programming Cookbook - Second Edition

By : Marius Bancila
5 (1)
Book Image

Modern C++ Programming Cookbook - Second Edition

5 (1)
By: Marius Bancila

Overview of this book

C++ has come a long way to be one of the most widely used general-purpose languages that is fast, efficient, and high-performance at its core. The updated second edition of Modern C++ Programming Cookbook addresses the latest features of C++20, such as modules, concepts, coroutines, and the many additions to the standard library, including ranges and text formatting. The book is organized in the form of practical recipes covering a wide range of problems faced by modern developers. The book also delves into the details of all the core concepts in modern C++ programming, such as functions and classes, iterators and algorithms, streams and the file system, threading and concurrency, smart pointers and move semantics, and many others. It goes into the performance aspects of programming in depth, teaching developers how to write fast and lean code with the help of best practices. Furthermore, the book explores useful patterns and delves into the implementation of many idioms, including pimpl, named parameter, and attorney-client, teaching techniques such as avoiding repetition with the factory pattern. There is also a chapter dedicated to unit testing, where you are introduced to three of the most widely used libraries for C++: Boost.Test, Google Test, and Catch2. By the end of the book, you will be able to effectively leverage the features and techniques of C++11/14/17/20 programming to enhance the performance, scalability, and efficiency of your applications.
Table of Contents (16 chapters)
Other Books You May Enjoy

Implementing parallel map and fold with threads

In Chapter 3, Exploring Functions, we discussed two higher-order functions: map, which applies a function to the elements of a range by either transforming the range or producing a new range, and fold, which combines the elements of a range into a single value. The various implementations we did were sequential. However, in the context of concurrency, threads, and asynchronous tasks, we can leverage the hardware and run parallel versions of these functions to speed up their execution for large ranges, or when the transformation and aggregation are time-consuming. In this recipe, we will see a possible solution for implementing map and fold using threads.

Getting ready

You need to be familiar with the concepts of the map and fold functions. It is recommended that you read the Implementing higher-order functions map and fold recipe from Chapter 3, Exploring Functions. In this recipe, we will use the various thread functionalities...