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Mastering C++ Multithreading

You're reading from   Mastering C++ Multithreading Write robust, concurrent, and parallel applications

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Product type Paperback
Published in Jul 2017
Publisher Packt
ISBN-13 9781787121706
Length 244 pages
Edition 1st Edition
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Author (1):
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Maya Posch Maya Posch
Author Profile Icon Maya Posch
Maya Posch
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Table of Contents (17) Chapters Close

Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
1. Revisiting Multithreading FREE CHAPTER 2. Multithreading Implementation on the Processor and OS 3. C++ Multithreading APIs 4. Thread Synchronization and Communication 5. Native C++ Threads and Primitives 6. Debugging Multithreaded Code 7. Best Practices 8. Atomic Operations - Working with the Hardware 9. Multithreading with Distributed Computing 10. Multithreading with GPGPU

Tracing the demo application


In the demonstration code of Chapter 1, Revisiting Multithreading, we looked at a simple c++11 application which used four threads to perform some processing. In this section, we will look at the same application, but from a hardware and OS perspective.

When we look at the start of the code in the main function, we see that we create a data structure containing a single (integer) value:

int main() {
    values.push_back(42);

After the OS creates a new task and associated stack structure, an instance of a vector data structure (customized for integer types) is allocated on the stack. The size of this was specified in the binary file's global data section (BSS for ELF).

When the application's execution is started using its entry function (main() by default), the data structure is modified to contain the new integer value.

Next, we create four threads, providing each with some initial data:

    thread tr1(threadFnc, 1);
    thread tr2(threadFnc, 2);
    thread tr3(threadFnc...
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