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
About Packt

Profiling Julia code

The goal of code profiling ( 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...