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Julia 1.0 Programming Cookbook

You're reading from Julia 1.0 Programming Cookbook Over 100 numerical and distributed computing recipes for your daily data science work?ow

Product type Paperback

Published in Nov 2018

Publisher Packt

ISBN-13 9781788998369

Length 460 pages

Edition 1st Edition

Languages

Julia

Tools

Boost

Concepts

Data Science

Authors (2):

Przemysław Szufel

Bogumił Kamiński

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Table of Contents (12) Chapters

Preface

1. Installing and Setting Up Julia

2. Data Structures and Algorithms FREE CHAPTER

3. Data Engineering in Julia

4. Numerical Computing with Julia

5. Variables, Types, and Functions

6. Metaprogramming and Advanced Typing

7. Handling Analytical Data

8. Julia Workflow

9. Data Science

10. Distributed Computing

11. Other Books You May Enjoy

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Profiling Julia code

The goal of code profiling (https://en.wikibooks.org/wiki/Introduction_to_Software_Engineering/Testing/Profiling)https://en.wikibooks.org/wiki/Introduction_to_Software_Engineering/Testing/Profilingis to identify bottlenecks (critical parts)of the code that have a considerable effect on its performance. Once the most time-consuming code sections have been identified, additional code optimization can be considered. From the standpoint of computation time, it makes sense to only optimize those code fragments that take a significant time to run. Julia offers a simple, yet useful, built-in sampling profiler.

Getting ready

The sampling profiler is built into Julia. However, in order to visualize profiling results, theProfileView.jlpackage is recommended, whichcan be installed with the Julia package manager. In the Julia command line, press the] key and run the following command:

(v1.0) pkg> add ProfileView

We will also show how to perform profiling using Juno'sJuno.@profile...

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Authors (2)

Kamiński

Kamiński

Bogumi Kamiski (GitHub username: bkamins) is an associate professor and head of the Decision Support and Analysis Unit at the SGH Warsaw School of Economics, as well as adjunct professor at the data science laboratory, Ryerson University, Toronto. He is coeditor of the Central European Journal of Economic Modeling and Econometrics, and of the Multiple Criteria Decision Making journal. His scientific interests center on operational research and computational social science. He has authored over 50 research articles on simulation, optimization, and prediction methods. He also has 15+ years' experience in the deployment of large-scale advanced analytics solutions for industry and public administration.

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Szufel

Szufel

Przemysaw Szufel (GitHub username: pszufe) is an assistant professor in the Decision Support and Analysis Unit at the SGH Warsaw School of Economics. His current research focuses on distributed systems and methods for the execution of large-scale simulations for numerical experiments and optimization. He is working on asynchronous algorithms for the parallel execution of large-scale computations in the cloud and distributed computational environments. He has authored, and co-authored, several open source tools for high-performance and numerical simulation.

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