Explore Products

Best Sellers

New Releases

Books

Videos

Audiobooks

Learning Hub

Free Learning

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

View More author details

Table of Contents (12) Chapters

Preface

1. Installing and Setting Up Julia FREE CHAPTER

2. Data Structures and Algorithms

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

Leave a review - let other readers know what you think

Multithreading in Julia

In this recipe, we use Julia's multithreading mechanism to speed up computations of statistics over a large DataFrame.

Getting ready

For this recipe, you need to use the DataFrames.jl and BenchmarkTools.jl packages, which can be installed with the Julia package manager. If you need to add them then in the Julia command line, press the ] key and run these commands:

(v1.0) pkg> add DataFrames
(v1.0) pkg> add BenchmarkTools

This will install the DataFrames.jl and BenchmarkTools.jl packages and all their dependencies.

In this recipe, we use Julia's threading mechanism. The number of threads is controlled via the JULIA_NUM_THREADS system variable, which needs to be assigned before starting...

The rest of the chapter is locked

A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.

Unlock this book and the full library FREE for 7 days

Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of

Start free trial

Renews at $19.99/month. Cancel anytime

Authors (2)

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.

See other products by Kamiński

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.

See other products by Szufel