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

The Julia profiler

The Julia runtime includes a built-in profiler, which can be used to measure how long each line of code takes to run, relative to a certain code base. It can therefore be used to identify bottlenecks in code, which can, in turn, be used to prioritize optimization efforts.

This built-in system implements what is known as a sampling profiler. As its name suggests, it samples the program call stack at certain points in time. When the profiler is run, it stops and inspects the running system every few milliseconds (by default, 1 millisecond on UNIX, and 10 milliseconds on Windows). At every point, the profiler identifies the list of function calls (and the line of code they originate), from the start of the program to the current point, and updates a counter for every line it sees on the call stack. The idea is that the lines of code that are executed most are...