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Asynchronous Programming with C++
Asynchronous Programming with C++

Asynchronous Programming with C++: Build blazing-fast software with multithreading and asynchronous programming for ultimate efficiency

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Profile Icon Javier Reguera-Salgado Profile Icon Juan Antonio Rufes
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Coming Soon Coming Soon Publishing in Nov 2024
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Paperback Nov 2024 424 pages 1st Edition
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Arrow left icon
Profile Icon Javier Reguera-Salgado Profile Icon Juan Antonio Rufes
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Coming Soon Coming Soon Publishing in Nov 2024
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Paperback Nov 2024 424 pages 1st Edition
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Renews at $19.99p/m
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Asynchronous Programming with C++

Parallel Programming Paradigms

Before we dive into parallel programming using C++, throughout the first two chapters, we will focus on acquiring some foundational knowledge about the different approaches to building parallel software and how the software interacts with the machine hardware.

In this chapter, we will introduce parallel programming and the different paradigms and models that we can use when developing efficient, responsive, and scalable concurrent and asynchronous software.

There are many ways to group concepts and methods when classifying the different approaches we can take to develop parallel software. As we are focusing on software built with C++ in this book, we can divide the different parallel programming paradigms as follows: concurrency, asynchronous programming, parallel programming, reactive programming, dataflows, multithreading programming, and event-driven programming.

Depending on the problem at hand, a specific paradigm could be more suitable...

Technical requirements

No technical requirements apply for this chapter.

Throughout the book, we will develop different solutions using C++20 and, in some examples, C++23. Therefore, we will need to install GCC 14 and Clang 8.

All the code blocks shown in this book can be found in the following GitHub repository: https://github.com/PacktPublishing/Asynchronous-Programming-with-CPP.

Getting to know classifications, techniques, and models

Parallel computing occurs when tasks or computations are done simultaneously, with a task being a unit of execution or unit of work in a software application. As there are many ways to achieve parallelism, understanding the different approaches will be helpful to write efficient parallel algorithms. These approaches are described via paradigms and models.

But first, let us start by classifying the different parallel computing systems.

Systems classification and techniques

One of the earliest classifications of parallel computing systems was made by Michael J. Flynn in 1966. Flynn’s taxonomy defines the following classification based on the data streams and number of instructions a parallel computing architecture can handle:

  • Single-instruction-single-data (SISD) systems: Define a sequential program
  • Single-instruction-multiple-data (SIMD) systems: Where operations are done over a large dataset, for example...

Understanding various parallel programming paradigms

Now that we have explored some of the different models used for building parallel programs, it is time to move to a more abstract classification and learn about the fundamental styles or principles of how to code parallel programs by exploring the different parallel programming language paradigms.

Synchronous programming

A synchronous programming language is used to build programs where code is executed in a strict sequential order. While one instruction is being executed, the program remains blocked until the instruction finishes. In other words, there is no multitasking. This makes the code easier to understand and debug.

However, this behavior makes the program unresponsive to external events while it is blocked while running an instruction and difficult to scale.

This is the traditional paradigm used by most programming languages such as C, Python, or Java.

This paradigm is especially useful for reactive or embedded...

Exploring the metrics to assess parallelism

Metrics are measurements that can help us understand how a system is performing and to compare different improvement approaches.

Here are some metrics and formulas commonly used to evaluate parallelism in a system.

Degree of parallelism

Degree of parallelism (DOP) is a metric that indicates the number of operations being simultaneously executed by a computer. It is useful to describe the performance of parallel programs and multi-processor systems.

When computing the DOP, we can use the maximum number of operations that could be done simultaneously, measuring the ideal case scenario without bottlenecks or dependencies. Alternatively, we can use either the average number of operations or the number of simultaneous operations at a given point in time, reflecting the actual DOP achieved by a system. An approximation can be done by using profilers and performance analysis tools to measure the number of threads during a particular...

Summary

In this chapter, we learned about the different architectures and models we can use to build parallel systems. Then we explored the details of the variety of parallel programming paradigms available to develop parallel software and learned about their behavior and nuances. Finally, we defined some useful metrics to measure the performance of parallel programs.

In the next chapter, we will explore the relationship between hardware and software, as well as how software maps and interacts with the underlying hardware. We will also learn what threads, processes, and services are, how threads are scheduled, and how they communicate with each other. Furthermore, we will cover inter-process communication and much more.

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Key benefits

  • Learn how to use modern C++ features, including futures, promises, async, and coroutines to build asynchronous solutions
  • Develop cross-platform network and low-level I/O projects with Boost.Asio
  • Master optimization techniques by understanding how software adapts to machine hardware
  • Purchase of the print or Kindle book includes a free PDF eBook

Description

As hardware advancements continue to accelerate, bringing greater memory capacity and more CPU cores, software must evolve to adapt to efficiently use all available resources and reduce idle CPU cycles. In this book, two seasoned software engineers with about five decades of combined experience will teach you how to implement concurrent and asynchronous solutions in C++. You’ll gain a comprehensive understanding of parallel programming paradigms—covering concurrent, asynchronous, parallel, multithreading, reactive, and event-driven programming, as well as dataflows—and see how threads, processes, and services are related. Moving into the heart of concurrency, the authors will guide you in creating and managing threads and exploring C++’s thread-safety mechanisms, including mutual exclusion, atomic operations, semaphores, condition variables, latches, and barriers. With this solid foundation, you’ll focus on pure asynchronous programming, discovering futures, promises, the async function, and coroutines. The book takes you step by step through using Boost.Asio and Boost.Cobalt to develop network and low-level I/O solutions, proven performance and optimization techniques, and testing and debugging asynchronous software. By the end of this C++ book, you’ll be able to implement high-performance software using modern asynchronous C++ techniques.

Who is this book for?

This book is for developers who have some experience using C++, regardless of their professional field. If you want to improve your C++ skills and learn how to develop high-performance software using the latest modern C++ features, this book is for you.

What you will learn

  • Explore the different parallel paradigms and know when to apply them
  • Acquire deep knowledge of thread management and safety mechanisms
  • Understand asynchronous programming in C++, including coroutines
  • Leverage network asynchronous programming by using Boost.Asio and Boost.Cobalt
  • Add proven performance and optimization techniques to your toolbox
  • Find out how to test and debug asynchronous software

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Table of Contents

20 Chapters
Part 1:Foundations of Parallel Programming and Process Management Chevron down icon Chevron up icon
Chapter 1: Parallel Programming Paradigms Chevron down icon Chevron up icon
Chapter 2: Processes, Threads, and Services Chevron down icon Chevron up icon
Part 2: Advanced Thread Management and Synchronization Techniques Chevron down icon Chevron up icon
Chapter 3: How to Create and Manage Threads in C++ Chevron down icon Chevron up icon
Chapter 4: Thread Synchronization with Locks Chevron down icon Chevron up icon
Chapter 5: Atomic Operations Chevron down icon Chevron up icon
Part 3: Asynchronous Programming with Promises, Futures, and Coroutines Chevron down icon Chevron up icon
Chapter 6: Promises and Futures Chevron down icon Chevron up icon
Chapter 7: The Async Function Chevron down icon Chevron up icon
Chapter 8: Asynchronous Programming Using Coroutines Chevron down icon Chevron up icon
Part 4: Advanced Asynchronous Programming with Boost Libraries Chevron down icon Chevron up icon
Chapter 9: Asynchronous Programming Using Boost.Asio Chevron down icon Chevron up icon
Chapter 10: Coroutines with Boost.Cobalt Chevron down icon Chevron up icon
Part 5: Debugging, Testing, and Performance Optimization in Asynchronous Programming Chevron down icon Chevron up icon
Chapter 11: Logging and Debugging Asynchronous Software Chevron down icon Chevron up icon
Chapter 12: Sanitizing and Testing Asynchronous Software Chevron down icon Chevron up icon
Chapter 13: Improving Asynchronous Software Performance Chevron down icon Chevron up icon
Index Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon
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