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

Summary


In this chapter, we looked in some detail at the MPI standard, along with a number of its implementations, specifically Open MPI, and we looked at how to set up a cluster. We also saw how to use OpenMP to easily add multithreading to existing codes.

At this point, the reader should be capable of setting up a basic Beowulf or similar cluster, configuring it for MPI, and running basic MPI applications on it. How to communicate between MPI processes and how to define custom data types should be known. In addition, the reader will be aware of the potential pitfalls when programming for MPI.

In the next chapter, we will take all our knowledge of the preceding chapters and see how we can combine it in the final chapter, as we look at general-purpose computing on videocards (GPGPU).