Book Image

Julia High Performance

By : Avik Sengupta
Book Image

Julia High Performance

By: Avik Sengupta

Overview of this book

Julia is a high performance, high-level dynamic language designed to address the requirements of high-level numerical and scientific computing. Julia brings solutions to the complexities faced by developers while developing elegant and high performing code. Julia High Performance will take you on a journey to understand the performance characteristics of your Julia programs, and enables you to utilize the promise of near C levels of performance in Julia. You will learn to analyze and measure the performance of Julia code, understand how to avoid bottlenecks, and design your program for the highest possible performance. In this book, you will also see how Julia uses type information to achieve its performance goals, and how to use multuple dispatch to help the compiler to emit high performance machine code. Numbers and their arrays are obviously the key structures in scientific computing – you will see how Julia’s design makes them fast. The last chapter will give you a taste of Julia’s distributed computing capabilities.
Table of Contents (14 chapters)

Chapter 6. Fast Arrays

It should not be a surprise to readers of this book that array operations are often the cornerstone of scientific and numeric programming. While arrays are a fundamental data structure in all programming, there are special considerations when they are used in numerical programming. One particular difference is that arrays are not just viewed as entities for data storage. Rather, they represent the fundamental mathematical structures of vectors and matrices.

In this chapter, we will discuss how to use arrays in Julia in the fastest possible way. When you profile your program, you will find that, in many cases, the majority of its execution time is spent in array operations. Therefore, the discussions in this chapter will likely turn out to be crucial in creating high-performance Julia code. The following are the topics we will cover:

  • Array internals and storage

  • Bounds checks

  • In-place operations

  • Subarrays

  • SIMD parallelization

  • Yeppp! for fast vector operations

  • Writing generic...