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  • Book Overview & Buying Mastering Concurrency Programming with Java 9, Second Edition
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Mastering Concurrency Programming with Java 9, Second Edition

Mastering Concurrency Programming with Java 9, Second Edition

By : Javier Fernández González
3.8 (4)
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Mastering Concurrency Programming with Java 9, Second Edition

Mastering Concurrency Programming with Java 9, Second Edition

3.8 (4)
By: Javier Fernández González

Overview of this book

Concurrency programming allows several large tasks to be divided into smaller sub-tasks, which are further processed as individual tasks that run in parallel. Java 9 includes a comprehensive API with lots of ready-to-use components for easily implementing powerful concurrency applications, but with high flexibility so you can adapt these components to your needs. The book starts with a full description of the design principles of concurrent applications and explains how to parallelize a sequential algorithm. You will then be introduced to Threads and Runnables, which are an integral part of Java 9's concurrency API. You will see how to use all the components of the Java concurrency API, from the basics to the most advanced techniques, and will implement them in powerful real-world concurrency applications. The book ends with a detailed description of the tools and techniques you can use to test a concurrent Java application, along with a brief insight into other concurrency mechanisms in JVM.
Table of Contents (21 chapters)
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Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Dedication
Preface

First example: matrix multiplication


Matrix multiplication is one of the basic operations that you can do with matrices and a classic problem used in concurrent and parallel programming courses. If you have a matrix A with m rows and n columns and another matrix B with n columns and p columns, you can multiply both matrices and obtain a matrix C with m rows and p columns. You can check https://en.wikipedia.org/wiki/Matrix_multiplication to find a detailed description about this operation.

In this section, we will implement a serial version of an algorithm to multiply two matrices and three different concurrent versions. Then, we will compare the four solutions to see when concurrency gives us a better performance.

Common classes

To implement this example we have used a class named MatrixGenerator. We use it to generate random matrices to multiply. This class has a method named generate() that receives the number of rows and columns you want in your matrix as parameters and generates a matrix...

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