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Java Concurrency and Parallelism

Java Concurrency and Parallelism

By : Jay Wang
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Java Concurrency and Parallelism

Java Concurrency and Parallelism

5 (1)
By: Jay Wang

Overview of this book

If you’re a software developer, architect, or systems engineer, exploring Java’s concurrency utilities and synchronization in the cloud, this book is an essential resource. Tech visionary Jay Wang, with over three decades of experience transforming industry giants, brings unparalleled expertise to guide you through Java’s concurrency and parallel processing in cloud computing. This comprehensive book starts by establishing the foundational concepts of concurrency and parallelism, vital for cloud-native development, and gives you a complete overview, highlighting challenges and best practices. Wang expertly demonstrates Java’s role in big data, machine learning, microservices, and serverless computing, shedding light on how Java’s tools are effectively utilized in these domains. Complete with practical examples and insights, this book bridges theory with real-world applications, ensuring a holistic understanding of Java in cloud-based scenarios. You’ll navigate advanced topics, such as synchronizing Java’s concurrency with cloud auto-scaling and GPU computing, and be equipped with the skills and foresight to tackle upcoming trends in cloud technology. This book serves as your roadmap to innovation and excellence in Java cloud applications, giving you in-depth knowledge and hands-on practice for mastering Java in the cloud era.
Table of Contents (20 chapters)
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Part 1: Foundations of Java Concurrency and Parallelism in Cloud Computing
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Part 2: Java's Concurrency in Specialized Domains
12
Part 3: Mastering Concurrency in the Cloud – The Final Frontier

Java’s tools for parallel processing in ML workflows

Parallel processing has become a cornerstone for ML workflows, enabling the handling of complex computations and large datasets with increased efficiency. Java, with its robust ecosystem, offers a variety of libraries and frameworks designed to support and enhance ML development through parallel processing. This section explores the pivotal role of these tools, with a focus on DL4J for neural networks and Java’s concurrency utilities for data processing.

DL4J – pioneering neural networks in Java

DL4J is a powerful open source library for building and training neural networks in Java. It provides a high-level API for defining and configuring neural network architectures, making it easier for Java developers to incorporate deep learning into their applications.

One of the key advantages of DL4J is its ability to leverage Java’s concurrency features for efficient training of neural networks. DL4J...

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