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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

Summary

In this chapter, we discussed how Julia uses a machine representation of numbers to achieve a C-like performance for its arithmetic computations. We noted how to work within these design constraints, and considered the edge cases that are introduced.

Working with single numbers, however, is the easy part. Most numerical computations, as we noted throughout this chapter, consist of working on large sets of numbers. In the next chapter, we will take a look at how to work with arrays in a performant manner.

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