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

Sharing data


In the example given in this chapter, we saw how to share information between threads in addition to synchronizing threads--this in the form of the requests we passed from the main thread into the dispatcher from which each request gets passed on to a different thread.

The essential idea behind the sharing of data between threads is that the data to be shared exists somewhere in a way which is accessible to two threads or more. After this, we have to ensure that only one thread can modify the data, and that the data does not get modified while it's being read. Generally, we would use mutexes or similar to ensure this.

Using r/w-locks

Read-write locks are a possible optimization here, because they allow multiple threads to read simultaneously from a single data source. If one has an application in which multiple worker threads read the same information repeatedly, it would be more efficient to use read-write locks than basic mutexes, because the attempts to read the data will not...