When I first learned about Julia in early 2012, it was clear to me that this is a language that I've wanted for many years. The use of multiple dispatch made it very easy to express mathematical concepts, while the speed of the language made it feasible to express them in the Julia. I came for the elegance and stayed for the performance. On the other hand, some users come to Julia for the performance and stay for the elegance. Either way, in order to fully appreciate the power and beauty of the language, it needs to live up to its promise of high performance.
I hope this book will help Julia programmers at all levels to learn the design techniques and paradigms that produce fast Julia code. One of the nice things about Julia is that its performance characteristics are simple and easy to reason out. I hope this book will provide you with a framework to think about and analyze the performance of your own code.
Chapter 1, Julia is Fast, discuses some of the design underpinning the language and its focus on high performance.
Chapter 2, Analyzing Julia Performance, provides the tools and techniques you can use to measure and analyze the performance of your own programs.
Chapter 3, Types in Julia, describes the type system and discusses why writing type-stable code is crucial to high performance.
Chapter 4, Functions and Macros – Structuring Julia Code for High Performance, discusses techniques to use dispatch and code generation to structure high-performance programs.
Chapter 5, Fast Numbers, discusses the basic numeric types and why they are fast.
Chapter 6, Fast Arrays, describes ways to use multidimensional arrays in the fastest possible way.
Chapter 7, Beyond the Single Processor, provides an introduction to Julia's distributed computing facilities.
If you are reading this book, we assume you have installed Julia and written a few simple Julia programs and that you are familiar with Julia REPL. The basic Julia installation, available from http://julialang.org/downloads, is the only prerequisite for this book. We will demonstrate most of the techniques in the book using REPL, and we encourage your to follow along. Paste the commands on to REPL and inspect the output yourself.
This book is for beginner- and intermediate-level Julia developers who are interested in high-performance technical computing. We expect you to have a basic understanding of Julia's syntax and have written a few small Julia programs prior to reading this book.
In this book, you will find a number of text styles that distinguish between different kinds of information. Here are some examples of these styles and an explanation of their meaning.
Code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles are shown as follows: "abstract types are defined using the abstract keyword."
A block of code is set as follows:
function bar(a, b)
x::Int64 = 0
y = a+b+x
return y
endAny command-line input or output is written as follows:
julia> @benchmark serial_add()
================ Benchmark Results ========================
Time per evaluation: 6.95 ms [6.59 ms, 7.31 ms]
Proportion of time in GC: 0.00% [0.00%, 0.00%]
Memory allocated: 0.00 bytes
Number of allocations: 0 allocations
Number of samples: 100
Number of evaluations: 100
Time spent benchmarking: 0.86 s New terms and important words are shown in bold.
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