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You're reading from  Java Deep Learning Cookbook

Product typeBook
Published inNov 2019
Reading LevelIntermediate
PublisherPackt
ISBN-139781788995207
Edition1st Edition
Languages
Java
Tools
Deeplearning4jTensorFlow
Concepts
Deep Learning
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Author (1)
Rahul Raj
Rahul Raj
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Rahul Raj

Rahul Raj has more than 7 years of IT industry experience in software development, business analysis, client communication, and consulting on medium-/large-scale projects in multiple domains. Currently, he works as a lead software engineer in a top software development firm. He has extensive experience in development activities comprising requirement analysis, design, coding, implementation, code review, testing, user training, and enhancements. He has written a number of articles about neural networks in Java and they are featured by DL4J/ official Java community channels. He is also a certified machine learning professional, certified by Vskills, the largest government certification body in India.
Read more about Rahul Raj

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Setting up heap spaces and garbage collection

Memory heap spaces and garbage collection are frequently discussed yet are often the most frequently ignored benchmarks. With DL4J/ND4J, you can configure two types of memory limit: on-heap memory and off-heap memory. Whenever an INDArray is collected by the JVM garbage collector, the off-heap memory will be de-allocated, assuming that it is not being used anywhere else. In this recipe, we will set up heap spaces and garbage collection for benchmarking.

How to do it...

  1. Add the required VM arguments to the Eclipse/IntelliJ IDE, as shown in the following example:
-Xms1G -Xmx6G -Dorg.bytedeco.javacpp.maxbytes=16G -Dorg.bytedeco.javacpp.maxphysicalbytes=20G

For example, in IntelliJ...

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Java Deep Learning Cookbook
Published in: Nov 2019Publisher: PacktISBN-13: 9781788995207
© 2019 Packt Publishing Limited All Rights Reserved

Author (1)

author image
Rahul Raj

Rahul Raj has more than 7 years of IT industry experience in software development, business analysis, client communication, and consulting on medium-/large-scale projects in multiple domains. Currently, he works as a lead software engineer in a top software development firm. He has extensive experience in development activities comprising requirement analysis, design, coding, implementation, code review, testing, user training, and enhancements. He has written a number of articles about neural networks in Java and they are featured by DL4J/ official Java community channels. He is also a certified machine learning professional, certified by Vskills, the largest government certification body in India.
Read more about Rahul Raj

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