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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 (11) Chapters Close

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

Being careless - data races


A data race, also known as a race condition, occurs when two or more threads attempt to write to the same shared memory simultaneously. As a result, the state of the shared memory during and at the end of the sequence of instructions executed by each thread is by definition, non-deterministic.

As we saw in Chapter 6, Debugging Multithreaded Code, data races are reported quite often by tools used to debug multi-threaded applications. For example:

==6984== Possible data race during write of size 1 at 0x5CD9260 by thread #1
 ==6984== Locks held: none
 ==6984==    at 0x40362C: Worker::stop() (worker.h:37)
 ==6984==    by 0x403184: Dispatcher::stop() (dispatcher.cpp:50)
 ==6984==    by 0x409163: main (main.cpp:70)
 ==6984== 
 ==6984== This conflicts with a previous read of size 1 by thread #2
 ==6984== Locks held: none
 ==6984==    at 0x401E0E: Worker::run() (worker.cpp:51)
 ==6984==    by 0x408FA4: void std::_Mem_fn_base<void (Worker::*)(), true>::operator()&lt...
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