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)

Analyzing memory allocation


The amount of memory used by a program is sometimes as important to track as the amount of time taken to run it. This is not only because memory is a limited resource that can be in short supply, but also because excessive allocation can easily lead to excessive execution time. The time taken to allocate and de-allocate memory and run the garbage collection can become quite significant when a program uses large amounts of memory.

The @time macro seen in the previous sections provides information about memory allocation for the expression or function being timed. In some cases however it may be difficult to predict where exactly in the code the memory allocation occurs. For these situations, Julia's track allocation functionality is just what is needed.

Using the memory allocation tracker

To get Julia to track memory allocation, start the julia process with the –track-allocation=user option as follows:

julia> track -allocation=user

This will start a normal Julia...