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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

MPI versus threads


One might think that it would be easiest to use MPI to allocate one instance of the MPI application to a single CPU core on each cluster node, and this would be true. It would, however, not be the fastest solution.

Although for communication between processes across a network MPI is likely the best choice in this context, within a single system (single or multi-CPU system) using multithreading makes a lot of sense.

The main reason for this is simply that communication between threads is significantly faster than inter-process communication, especially when using a generalized communication layer such as MPI.

One could write an application that uses MPI to communicate across the cluster's network, whereby one allocates one instance of the application to each MPI node. The application itself would detect the number of CPU cores on that system, and create one thread for each core. Hybrid MPI, as it's often called, is therefore commonly used, for the advantages it provides:

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