Book Image

Learning Julia

By : Anshul Joshi, Rahul Lakhanpal
Book Image

Learning Julia

By: Anshul Joshi, Rahul Lakhanpal

Overview of this book

Julia is a highly appropriate language for scientific computing, but it comes with all the required capabilities of a general-purpose language. It allows us to achieve C/Fortran-like performance while maintaining the concise syntax of a scripting language such as Python. It is perfect for building high-performance and concurrent applications. From the basics of its syntax to learning built-in object types, this book covers it all. This book shows you how to write effective functions, reduce code redundancies, and improve code reuse. It will be helpful for new programmers who are starting out with Julia to explore its wide and ever-growing package ecosystem and also for experienced developers/statisticians/data scientists who want to add Julia to their skill-set. The book presents the fundamentals of programming in Julia and in-depth informative examples, using a step-by-step approach. You will be taken through concepts and examples such as doing simple mathematical operations, creating loops, metaprogramming, functions, collections, multiple dispatch, and so on. By the end of the book, you will be able to apply your skills in Julia to create and explore applications of any domain.
Table of Contents (17 chapters)
Title Page
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
8
Data Visualization and Graphics

Parallel computing


Before we start exploring the parallel computing features provided by Julia, it's interesting to understand briefly what parallel computation means. Parallel computing is a type of computation in which many calculations, or the execution of processes, are carried out simultaneously. Here, a typical task is broken down into multiple similar subtasks that are processed independently, but whose results are combined together to give one final result.

Like every other modern-day programming language, Julia also allows for parallel computation of a different set of tasks. However, the way in which Julia performs parallel computing is different. It provides a multiprocessing environment, which is based on message passing (not to be confused with MPI), which allows programmers to run separate processes in separate memory domains at once. It is also important to note that Julia is, by design, distributed.

In accordance with the message passing implementation of Julia, communication...