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  • Book Overview & Buying Julia High Performance
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Julia High Performance

Julia High Performance

By : Avik Sengupta
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Julia High Performance

Julia High Performance

4 (4)
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 (9 chapters)
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Shared arrays


Distributed arrays are a fully generic solution that scales across many networked hosts in order to work on data that cannot fit in the memory of a single machine. However, in many circumstances, although the data does fit in the memory, we want multiple Julia processes to improve throughput by fully utilizing all the cores in a machine. In this situation, shared arrays are useful to get different Julia processes operating on the same data.

Shared arrays, as the name suggests, are arrays that are shared across multiple Julia processes on the same machine.

Constructing SharedArray requires specifying its type, its dimensions, and the list of process IDs that will have access to the array, as follows:

S=SharedArray( Float64, (100, 100, 5), pids=[2,3,4,5]);

Once a shared array is created, it is accessible in full to all the specified workers (on the same machine). Unlike a distributed array, the data is not partitioned, and hence there is no need for any data transfer between nodes...

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Julia High Performance
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