Book Image

Mastering C++ Multithreading

By : Maya Posch
Book Image

Mastering C++ Multithreading

By: Maya Posch

Overview of this book

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++.
Table of Contents (17 chapters)
Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
8
Atomic Operations - Working with the Hardware

The scheduler


A good example of multithreading with a significant amount of synchronization and communication between threads is the scheduling of tasks. Here, the goal is to accept incoming tasks and assign them to work threads as quickly as possible.

In this scenario, a number of different approaches are possible. Often one has worker threads running in an active loop, constantly polling a central queue for new tasks. Disadvantages of this approach include wasting of processor cycles on the said polling, and the congestion which forms at the synchronization mechanism used, generally a mutex. Furthermore, this active polling approach scales very poorly when the number of worker threads increase.

Ideally, each worker thread would wait idly until it is needed again. To accomplish this, we have to approach the problem from the other side: not from the perspective of the worker threads, but from that of the queue. Much like the scheduler of an operating system, it is the scheduler which is aware...