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

Accelerating Code with the GPU

Accelerator cards for display graphics have a long and storied past. They've been available since the 70s. The late 90s, however, saw the introduction of programmable shaders that allowed the display to be generated by little programs that ran on specialized chips. It was quickly apparent, however, that the code used to draw triangles on screen, and transform and light them, could be generalized to many other fields. 

Originally designed for fast graphics calculations, they have found use in accelerating many kinds of numerical code. The defining characteristic of these processors has been their ability to run many threads—in the order of hundreds or thousandsin parallel, which then allows significant speedups in algorithms that can take advantage of this facility. Therefore, the general-purpose Graphics Processing...