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Mastering C++ Multithreading
Mastering C++ Multithreading

Mastering C++ Multithreading: Write robust, concurrent, and parallel applications

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Mastering C++ Multithreading

Multithreading Implementation on the Processor and OS

The foundation of any multithreaded application is formed by the implementation of the required features by the hardware of the processor, as well as by the way these features are translated into an API for use by applications by the operating system. An understanding of this foundation is crucial for developing an intuitive understanding of how to best implement a multithreaded application.

This chapter looks at how hardware and operating systems have evolved over the years to arrive at the current implementations and APIs as they are in use today. It shows how the example code of the previous chapter ultimately translates into commands to the processor and related hardware.

Topics covered in this chapter include the following:

  • The evolution of processor hardware in order to support multithreading concepts
  • How operating systems...

Defining processes and threads

Essentially, to the operating system (OS), a process consists of one or more threads, each thread processing its own state and variables. One would regard this as a hierarchical configuration, with the OS as the foundation, providing support for the running of (user) processes. Each of these processes then consists of one or more threads. Communication between processes is handled by inter-process communication (IPC), which is provided by the operating system.

In a graphical view, this looks like the following:

Each process within the OS has its own state, with each thread in a process having its own state as well as the relative to the other threads within that same process. While IPC allows processes to communicate with each other, threads can communicate with other threads within the process in a variety of ways, which we'll explore in more...

The stack

As we saw in the preceding sections, the stack together with the CPU registers define a task. As mentioned earlier, this stack consists of stack frames, each of which defines the (local) variables, parameters, data, and instructions for that particular instance of task execution. Of note is that although the stack and stack frames are primarily a software concept, it is an essential feature of any modern OS, with hardware support in many CPU instruction sets. Graphically, it can be be visualized like the following:

The SP (ESP on x86) points to the top of the stack, with another pointer (Extended Base Pointer (EBP) for x86). Each frame contains a reference to the preceding frame (caller return address), as set by the OS.

When using a debugger with one's C++ application, this is basically what one sees when requesting the backtrack--the individual frames of the...

Defining multithreading

Over the past decades, a lot of different terms related to the way tasks are processed by a computer have been coined and come into common use. Many of these are also used interchangeably, correctly or not. An example of this is multithreading in comparison with multiprocessing.

Here, the latter means running one task per processor in a system with multiple physical processors, while the former means running multiple tasks on a singular processor simultaneously, thus giving the illusion that they are all being executed simultaneously:

Another interesting distinction between multiprocessing and multitasking is that the latter uses time-slices in order to run multiple threads on a single processor core. This is different from multithreading in the sense that in a multitasking system, no tasks will ever run in a concurrent fashion on the same CPU core, though...

Schedulers

A number of task-scheduling algorithms exist, each focusing on a different goal. Some may seek to maximize throughput, others minimize latency, while others may seek to maximize response time. Which scheduler is the optimal choice solely depends on the application the system is being used for.

For desktop systems, the scheduler is generally kept as general-purpose as possible, usually prioritizing foreground applications over background applications in order to give the user the best possible desktop experience.

For embedded systems, especially in real-time, industrial applications would instead seek to guarantee timing. This allows processes to be executed at exactly the right time, which is crucial in, for example, driving machinery, robotics, or chemical processes where a delay of even a few milliseconds could be costly or even fatal.

The scheduler type is also dependent...

Defining processes and threads


Essentially, to the operating system (OS), a process consists of one or more threads, each thread processing its own state and variables. One would regard this as a hierarchical configuration, with the OS as the foundation, providing support for the running of (user) processes. Each of these processes then consists of one or more threads. Communication between processes is handled by inter-process communication (IPC), which is provided by the operating system.

In a graphical view, this looks like the following:

Each process within the OS has its own state, with each thread in a process having its own state as well as the relative to the other threads within that same process. While IPC allows processes to communicate with each other, threads can communicate with other threads within the process in a variety of ways, which we'll explore in more depth in upcoming chapters. This generally involves some kind of shared memory between threads.

An application is loaded...

The stack


As we saw in the preceding sections, the stack together with the CPU registers define a task. As mentioned earlier, this stack consists of stack frames, each of which defines the (local) variables, parameters, data, and instructions for that particular instance of task execution. Of note is that although the stack and stack frames are primarily a software concept, it is an essential feature of any modern OS, with hardware support in many CPU instruction sets. Graphically, it can be be visualized like the following:

The SP (ESP on x86) points to the top of the stack, with another pointer (Extended Base Pointer (EBP) for x86). Each frame contains a reference to the preceding frame (caller return address), as set by the OS.

When using a debugger with one's C++ application, this is basically what one sees when requesting the backtrack--the individual frames of the stack showing the initial stack frame leading up until the current frame. Here, one can examine each individual frame's details...

Defining multithreading


Over the past decades, a lot of different terms related to the way tasks are processed by a computer have been coined and come into common use. Many of these are also used interchangeably, correctly or not. An example of this is multithreading in comparison with multiprocessing.

Here, the latter means running one task per processor in a system with multiple physical processors, while the former means running multiple tasks on a singular processor simultaneously, thus giving the illusion that they are all being executed simultaneously:

Another interesting distinction between multiprocessing and multitasking is that the latter uses time-slices in order to run multiple threads on a single processor core. This is different from multithreading in the sense that in a multitasking system, no tasks will ever run in a concurrent fashion on the same CPU core, though tasks can still be interrupted.

The concept of a process and a shared memory space between the threads contained...

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Key benefits

  • Delve into the fundamentals of multithreading and concurrency and find out how to implement them
  • Explore atomic operations to optimize code performance
  • Apply concurrency to both distributed computing and GPGPU processing

Description

Multithreaded applications execute multiple threads in a single processor environment, allowing developers achieve concurrency. This book will teach you the finer points of multithreading and concurrency concepts and how to apply them efficiently in C++. Divided into three modules, we start with a brief introduction to the fundamentals of multithreading and concurrency concepts. We then take an in-depth look at how these concepts work at the hardware-level as well as how both operating systems and frameworks use these low-level functions. In the next module, you will learn about the native multithreading and concurrency support available in C++ since the 2011 revision, synchronization and communication between threads, debugging concurrent C++ applications, and the best programming practices in C++. In the final module, you will learn about atomic operations before moving on to apply concurrency to distributed and GPGPU-based processing. The comprehensive coverage of essential multithreading concepts means you will be able to efficiently apply multithreading concepts while coding in C++.

Who is this book for?

This book is for intermediate C++ developers who wish to extend their knowledge of multithreading and concurrent processing. You should have basic experience with multithreading and be comfortable using C++ development toolchains on the command line.

What you will learn

  • Deep dive into the details of the how various operating systems currently implement multithreading
  • Choose the best multithreading APIs when designing a new application
  • Explore the use of mutexes, spin-locks, and other synchronization concepts and see how to safely pass data between threads
  • Understand the level of API support provided by various C++ toolchains
  • Resolve common issues in multithreaded code and recognize common pitfalls using tools such as Memcheck, CacheGrind, DRD, Helgrind, and more
  • Discover the nature of atomic operations and understand how they can be useful in optimizing code
  • Implement a multithreaded application in a distributed computing environment
  • Design a C++-based GPGPU application that employs multithreading
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Length: 244 pages
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Language : English
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Table of Contents

10 Chapters
Revisiting Multithreading Chevron down icon Chevron up icon
Multithreading Implementation on the Processor and OS Chevron down icon Chevron up icon
C++ Multithreading APIs Chevron down icon Chevron up icon
Thread Synchronization and Communication Chevron down icon Chevron up icon
Native C++ Threads and Primitives Chevron down icon Chevron up icon
Debugging Multithreaded Code Chevron down icon Chevron up icon
Best Practices Chevron down icon Chevron up icon
Atomic Operations - Working with the Hardware Chevron down icon Chevron up icon
Multithreading with Distributed Computing Chevron down icon Chevron up icon
Multithreading with GPGPU Chevron down icon Chevron up icon

Customer reviews

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Rating distribution
Full star icon Full star icon Full star icon Half star icon Empty star icon 3.1
(12 Ratings)
5 star 33.3%
4 star 16.7%
3 star 8.3%
2 star 8.3%
1 star 33.3%
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Debasish Aug 14, 2019
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Good
Amazon Verified review Amazon
T. Farrier May 12, 2018
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Clear and comprehensive treatment.
Amazon Verified review Amazon
Ignacio A. Ruiz Reyes Oct 16, 2017
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I've been working with multithreaded C programming for 5years now and bought this book to get an idea how it works on C++ and i'm very pleased with my investing decision, since this book allowed me not only reinforce my knowledge on traditional multithreading, also get some very interesting background on history and libraries available, but also "quantum" leap to the power of standardized C++ features!!! explanations are precise, examples are simple yet functional, so you can get the idea just reading the code; if you don't trust or want to see it in action, you can compile and run the examples yourself!Extra mention for chapters 6, 9 and 10, since not many books talk about multithreading in the context of debugging, distributed computing or GPU programming, and mastering this concepts will definitely give you an edge or get you ready for stuff like AI or HPC.
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Lou mauget Nov 21, 2017
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This is an excellent treatment of a thorny area of coding: processing that shares state, proceeding at odd intervals, or simultaneously. Programmers and architects are accustomed to designing for asynchronous data from a mouse click, a keyboard submission, or a response to a network or DBMS request. Now, picture implementing low-level code to handle a barrage of asynchronous or concurrent activity. All, while keeping the processor utilized and not stomping on anybody's state. At that point it becomes harder for a hapless human to reason about, let alone to implement. Certainly, there are higher-level languages and frameworks for taming some situations, but perhaps we're tasked with creating a part of such a framework! Maybe we're designing or writing such code "down to the metal", trying to implement a problem most-efficiently. C++ has flexibly kept pace with hardware evolution, but with flexibility comes choices that could present new complexity.This book shows the reader how to exploit late-breaking C++ multithreading and concurrent-programming capabilities, It begins with an overview of the hardware it exploits. It progresses through a comprehensive set of subjects that include synchronization, debugging, and best practices. A bonus is a chapter on multithreading with a GPGPU.This book serves both as a tutorial and as a reference for use later. Note that it does not address C++17, because the book slightly predates C++17. Disclosure: I was a technical reviewer of the manuscript.
Amazon Verified review Amazon
bk Jan 31, 2018
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
Good book for multithreading
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