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)

Bound checking


Like most dynamic languages, the Julia runtime performs bound checks on arrays by default. This means that the Julia compiler and runtime verify that the arrays are not indexed outside their limits and that all the indexes lie between the actual start and end of an array. Reading values of memory mistakenly beyond the end of an array is often the cause of many bugs and security issues in unmanaged software. Hence, bound checking is an important determinant of safety in your programs.

Removing the cost of bound checking

However, as with any extra operation, bound checking has costs too. There are extra operations for all array reads and writes. While this cost is reasonably small and is usually a good trade-off for safety, in some situations, where it can be guaranteed that the array bounds are never crossed, it may be worthwhile to remove these checks. This is possible in Julia using the @inbounds macro, as follows:

function prefix_bounds(a, b)
      for i = 2:size(a, 1)
   ...