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Julia High Performance

You're reading from   Julia High Performance Optimizations, distributed computing, multithreading, and GPU programming with Julia 1.0 and beyond

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Product type Paperback
Published in Jun 2019
Publisher Packt
ISBN-13 9781788298117
Length 218 pages
Edition 2nd Edition
Languages
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Author (1):
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Avik Sengupta Avik Sengupta
Author Profile Icon Avik Sengupta
Avik Sengupta
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Table of Contents (13) Chapters Close

Preface 1. Julia is Fast FREE CHAPTER 2. Analyzing Performance 3. Types, Type Inference, and Stability 4. Making Fast Function Calls 5. Fast Numbers 6. Using Arrays 7. Accelerating Code with the GPU 8. Concurrent Programming with Tasks 9. Threads 10. Distributed Computing with Julia 11. Licences
12. Other Books You May Enjoy

Threads

In the last chapter, we saw how tasks provide a simple way to run multiple streams of compute, even on a single CPU core, when there is I/O involved. However, as the modern CPU has grown to include multiple cores that all operate simultaneously, we need to be able to execute Julia code on them in parallel. The way to do that is typically described as threads or threading, and, in this chapter, we will talk about the facilities Julia provides to run programs on multiple CPU cores simultaneously.

We will begin by noting that Julia's threading features are marked experimental. They are still useful, as you will see in this chapter. However, there is a large internal refactoring that is currently underway. It is expected that these will land in Julia versions 1.3 onward. These changes will make these features more robust, and high-performance, and remove some of their...

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