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You're reading from  Java for Data Science

Product typeBook
Published inJan 2017
Reading LevelIntermediate
PublisherPackt
ISBN-139781785280115
Edition1st Edition
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Authors (2):
Richard M. Reese
Richard M. Reese
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Richard M. Reese

Richard Reese has worked in the industry and academics for the past 29 years. For 10 years he provided software development support at Lockheed and at one point developed a C based network application. He was a contract instructor providing software training to industry for 5 years. Richard is currently an Associate Professor at Tarleton State University in Stephenville Texas. Richard is the author of various books and video courses some of which are as follows: Natural Language Processing with Java. Java for Data Science Getting Started with Natural Language Processing in Java
Read more about Richard M. Reese

Jennifer L. Reese
Jennifer L. Reese
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Jennifer L. Reese

Jennifer L. Reese studied computer science at Tarleton State University. She also earned her M.Ed. from Tarleton in December 2016. She currently teaches computer science to high-school students. Her interests include the integration of computer science concepts with other academic disciplines, increasing diversity in computer science courses, and the application of data science to the field of education. She has co-authored two books: Java for Data Science and Java 7 New Features Cookbook. She previously worked as a software engineer. In her free time she enjoys reading, cooking, and traveling—especially to any destination with a beach. She is a musician and appreciates a variety of musical genres.
Read more about Jennifer L. Reese

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Using Aparapi


Aparapi (https://github.com/aparapi/aparapi) is a Java library that supports concurrent operations. The API supports code running on GPUs or CPUs. GPU operations are executed using OpenCL, while CPU operations use Java threads. The user can specify which computing resource to use. However, if GPU support is not available, Aparapi will revert to Java threads.

The API will convert Java byte codes to OpenCL at runtime. This makes the API largely independent from the graphics card used. The API was initially developed by AMD but has been released as open source. This is reflected in the basic package name, com.amd.aparari. Aparapi offers a higher level of abstraction than provided by OpenCL.

Aparapi code is located in a class derived from the Kernel class. Its execute method will start the operations. This will result in an internal call to a run method, which needs to be overridden. It is within the run method that concurrent code is placed. The run method is executed multiple times...

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Java for Data Science
Published in: Jan 2017Publisher: PacktISBN-13: 9781785280115

Authors (2)

author image
Richard M. Reese

Richard Reese has worked in the industry and academics for the past 29 years. For 10 years he provided software development support at Lockheed and at one point developed a C based network application. He was a contract instructor providing software training to industry for 5 years. Richard is currently an Associate Professor at Tarleton State University in Stephenville Texas. Richard is the author of various books and video courses some of which are as follows: Natural Language Processing with Java. Java for Data Science Getting Started with Natural Language Processing in Java
Read more about Richard M. Reese

author image
Jennifer L. Reese

Jennifer L. Reese studied computer science at Tarleton State University. She also earned her M.Ed. from Tarleton in December 2016. She currently teaches computer science to high-school students. Her interests include the integration of computer science concepts with other academic disciplines, increasing diversity in computer science courses, and the application of data science to the field of education. She has co-authored two books: Java for Data Science and Java 7 New Features Cookbook. She previously worked as a software engineer. In her free time she enjoys reading, cooking, and traveling—especially to any destination with a beach. She is a musician and appreciates a variety of musical genres.
Read more about Jennifer L. Reese