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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

Product type Paperback

Published in Jun 2019

Publisher Packt

ISBN-13 9781788298117

Length 218 pages

Edition 2nd Edition

Languages

Julia

Concepts

Distributed Computing

Author (1):

Avik Sengupta

View More author details

Table of Contents (13) Chapters

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

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Fast Numbers

As a numerical programming language, fast computations with numbers are central to everything we do in Julia. In the previous chapters, we discussed how the Julia compiler and runtime perform across a wide range of code. In this chapter, we will take a focused look at how the core numerical constructs are designed and implemented in Julia.

In this chapter, we will cover the following topics:

Numbers in Julia, their layout, and storage
Trading performance for accuracy
Subnormal numbers

The rest of the chapter is locked

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Authors (1)

Avik Sengupta

Avik Sengupta

Avik Sengupta is the Vice President of engineering at Julia Computing, contributor to open source Julia and maintainer of several Julia packages. Avik is the co-founder of two startups in the financial services and AI sectors and creator of large complex trading systems for the world's leading investment banks. Prior to Julia Computing, Avik was co-founder and CTO at AlgoCircle and at Itellix, director at Lab49 and head of algorithmic solutions at Decimal Point Analytics. Avik earned his MS in Computational Finance at Carnegie Mellon and MBA Finance at the Indian Institute of Management in Bangalore.

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