Book Image

Julia 1.0 Programming Cookbook

By : Bogumił Kamiński, Przemysław Szufel
Book Image

Julia 1.0 Programming Cookbook

By: Bogumił Kamiński, Przemysław Szufel

Overview of this book

Julia, with its dynamic nature and high-performance, provides comparatively minimal time for the development of computational models with easy-to-maintain computational code. This book will be your solution-based guide as it will take you through different programming aspects with Julia. Starting with the new features of Julia 1.0, each recipe addresses a specific problem, providing a solution and explaining how it works. You will work with the powerful Julia tools and data structures along with the most popular Julia packages. You will learn to create vectors, handle variables, and work with functions. You will be introduced to various recipes for numerical computing, distributed computing, and achieving high performance. You will see how to optimize data science programs with parallel computing and memory allocation. We will look into more advanced concepts such as metaprogramming and functional programming. Finally, you will learn how to tackle issues while working with databases and data processing, and will learn about on data science problems, data modeling, data analysis, data manipulation, parallel processing, and cloud computing with Julia. By the end of the book, you will have acquired the skills to work more effectively with your data
Table of Contents (18 chapters)
Title Page
Copyright and Credits
Dedication
About Packt
Contributors
Preface
Index

Sending parameters to remote Julia processes


In this recipe, we examine a distributed computation scenario running across many workers, where each worker process needs to communicate with other processes. Examples include running complex analytical jobs or large simulation/computational models.

In the recipe, we use a simplified example of how to run a distributed cellular automaton using Julia'sDistributedmodule and theParallelDataTransfer.jlpackage. Cellular automaton is a type of discrete model consisting of a number of cells with a finite set of possible states and a deterministic rule for transforming one state to another (see http://mathworld.wolfram.com/CellularAutomaton.html orhttps://en.wikipedia.org/wiki/Cellular_automaton). There are many possible rules for describing how subsequent states are calculated.

In this recipe, we will construct a one-dimensional binary cellular automaton, based on what is known as Rule 30 (see http://mathworld.wolfram.com/Rule30.html orhttps://en.wikipedia...