Book Image

Julia Cookbook

By : Raj R Jalem, Rohit
Book Image

Julia Cookbook

By: Raj R Jalem, Rohit

Overview of this book

Want to handle everything that Julia can throw at you and get the most of it every day? This practical guide to programming with Julia for performing numerical computation will make you more productive and able work with data more efficiently. The book starts with the main features of Julia to help you quickly refresh your knowledge of functions, modules, and arrays. We’ll also show you how to utilize the Julia language to identify, retrieve, and transform data sets so you can perform data analysis and data manipulation. Later on, you’ll see how to optimize data science programs with parallel computing and memory allocation. You’ll get familiar with the concepts of package development and networking to solve numerical problems using the Julia platform. This book includes recipes on identifying and classifying data science problems, data modelling, data analysis, data manipulation, meta-programming, multidimensional arrays, and parallel computing. By the end of the book, you will acquire the skills to work more effectively with your data.
Table of Contents (7 chapters)

Basic concepts of parallel computing


Parallel computing is a way of dealing with data in a parallel way. This can be done by connecting multiple computers as a cluster and using their CPUs to carry out the computations.

This style of computation is used when handling large amounts of data and also while running complex algorithms over significantly large data. The computations are executed faster due to the availability of multiple CPUs running them in parallel as well as the direct availability of RAM to each of them.

Getting ready

Julia has in-built support for parallel computing and multiprocessing. So, these computations rarely require any external libraries for the task.

How to do it...

  1. Julia can be started on your local computer using multiple cores of your CPU. So, we will now have multiple workers for the process. This is how you can fire up Julia in multi-processing mode in your terminal. This creates two worker process in the machine, which means it uses two CPU cores for the purpose...