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

Mutual exclusion implementations


Mutual exclusion is the principle which underlies thread-safe access of data within a multithreaded application. One can implement this both in hardware and software. The mutual exclusion (mutex) is the most elementary form of this functionality in most implementations.

Hardware

The simplest hardware-based implementation on a uniprocessor (single processor core), non-SMT system is to disable interrupts, and thus, prevent the task from being changed. More commonly, a so-called busy-wait principle is employed. This is the basic principle behind a mutex--due to how the processor fetches data, only one task can obtain and read/write an atomic value in the shared memory, meaning, a variable sized the same (or smaller) as the CPU's registers. This is further detailed in Chapter 8, Atomic Operations - Working with the Hardware.

When our code tries to lock a mutex, what this does is read the value of such an atomic section of memory, and try to set it to its locked...