Book Image

Scientific Computing with Scala

By : Vytautas Jancauskas
Book Image

Scientific Computing with Scala

By: Vytautas Jancauskas

Overview of this book

Scala is a statically typed, Java Virtual Machine (JVM)-based language with strong support for functional programming. There exist libraries for Scala that cover a range of common scientific computing tasks – from linear algebra and numerical algorithms to convenient and safe parallelization to powerful plotting facilities. Learning to use these to perform common scientific tasks will allow you to write programs that are both fast and easy to write and maintain. We will start by discussing the advantages of using Scala over other scientific computing platforms. You will discover Scala packages that provide the functionality you have come to expect when writing scientific software. We will explore using Scala's Breeze library for linear algebra, optimization, and signal processing. We will then proceed to the Saddle library for data analysis. If you have experience in R or with Python's popular pandas library you will learn how to translate those skills to Saddle. If you are new to data analysis, you will learn basic concepts of Saddle as well. Well will explore the numerical computing environment called ScalaLab. It comes bundled with a lot of scientific software readily available. We will use it for interactive computing, data analysis, and visualization. In the following chapters, we will explore using Scala's powerful parallel collections for safe and convenient parallel programming. Topics such as the Akka concurrency framework will be covered. Finally, you will learn about multivariate data visualization and how to produce professional-looking plots in Scala easily. After reading the book, you should have more than enough information on how to start using Scala as your scientific computing platform
Table of Contents (16 chapters)
Scientific Computing with Scala
About the Author
About the Reviewer


In this chapter, we covered the different ways that are available if you want to perform parallel programming in Scala. The ways covered are: using JVM threading primitives, Scala's parallel collections, and the Akka framework.

The JVM threading primitives give a low-level access to the threading capabilities of JVM, but are prone to various problems inherent in most such threading API's. We saw how to write simple programs using the Thread class and how to avoid race conditions via the use of the synchronized statement.

We then explored Scala's parallel collections—parallelized versions of most collection classes. These work by executing various functional programming operations in parallel. Examples include, map, fold, and so on.

We saw how one can use this to very simply parallelize programs that use large collections and rely on functional programming operators. Finally, we scratched the surface of the massive Akka framework for actor-based concurrent programming. The framework...