Book Image

Julia 1.0 High Performance - Second Edition

By : Avik Sengupta
Book Image

Julia 1.0 High Performance - Second Edition

By: Avik Sengupta

Overview of this book

Julia is a high-level, high-performance dynamic programming language for numerical computing. If you want to understand how to avoid bottlenecks and design your programs for the highest possible performance, then this book is for you. The book starts with how Julia uses type information to achieve its performance goals, and how to use multiple dispatches to help the compiler emit high-performance machine code. After that, you will learn how to analyze Julia programs and identify issues with time and memory consumption. We teach you how to use Julia's typing facilities accurately to write high-performance code and describe how the Julia compiler uses type information to create fast machine code. Moving ahead, you'll master design constraints and learn how to use the power of the GPU in your Julia code and compile Julia code directly to the GPU. Then, you'll learn how tasks and asynchronous IO help you create responsive programs and how to use shared memory multithreading in Julia. Toward the end, you will get a flavor of Julia's distributed computing capabilities and how to run Julia programs on a large distributed cluster. By the end of this book, you will have the ability to build large-scale, high-performance Julia applications, design systems with a focus on speed, and improve the performance of existing programs.
Table of Contents (19 chapters)
Title Page
Dedication
Foreword
Licences

Yeppp!

Many algorithms for scientific computing involve computing transcendental functions (log, sin, and cos) on arrays of floating point values. These are heavily used operations with strict correctness requirements, and thus, have been the target of many optimization efforts over the years. Faster versions of these functions can make a huge impact on the performance of many applications in the scientific computing domain.

In this area, the Yeppp! the software suite can be considered state of the art. Primarily written at Georgia Institute of Technology by Marat Dukhan, Yeppp! provides optimized implementations of modern processors of these functions, which are much faster compared to the implementations in system libraries.

Julia has a very easy-to-use binding to Yeppp! within a package. It can be installed using the built-in package management mechanism, Pkg.add(...