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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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Toc

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

Creating Julia clusters

In Chapter 9, Threads, we covered how to use the experimental threading functionality to utilize multiple processors within a single processor. Some embedded libraries used in Julia, such as OpenBLAS, use their own threading facilities to scale across multiple CPUs. Julia's asynchronous IO libraries can also offload network or file IO to a separate operating system thread. Notwithstanding these exceptions, most Julia code continues to be limited to a single core.

Julia, however, contains an easy-to-use multiprocessor mechanism. You can start multiple Julia processes, either on a single host, or across a network, and control, communicate, and execute programs across the entire cluster.

Starting a cluster

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