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Java Concurrency and Parallelism

You're reading from   Java Concurrency and Parallelism Master advanced Java techniques for cloud-based applications through concurrency and parallelism

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Product type Paperback
Published in Aug 2024
Publisher Packt
ISBN-13 9781805129264
Length 496 pages
Edition 1st Edition
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Author (1):
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Jay Wang Jay Wang
Author Profile Icon Jay Wang
Jay Wang
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Table of Contents (20) Chapters Close

Preface 1. Part 1: Foundations of Java Concurrency and Parallelism in Cloud Computing FREE CHAPTER
2. Chapter 1: Concurrency, Parallelism, and the Cloud: Navigating the Cloud-Native Landscape 3. Chapter 2: Introduction to Java’s Concurrency Foundations: Threads, Processes, and Beyond 4. Chapter 3: Mastering Parallelism in Java 5. Chapter 4: Java Concurrency Utilities and Testing in the Cloud Era 6. Chapter 5: Mastering Concurrency Patterns in Cloud Computing 7. Part 2: Java's Concurrency in Specialized Domains
8. Chapter 6: Java and Big Data – a Collaborative Odyssey 9. Chapter 7: Concurrency in Java for Machine Learning 10. Chapter 8: Microservices in the Cloud and Java’s Concurrency 11. Chapter 9: Serverless Computing and Java’s Concurrent Capabilities 12. Part 3: Mastering Concurrency in the Cloud – The Final Frontier
13. Chapter 10: Synchronizing Java’s Concurrency with Cloud Auto-Scaling Dynamics 14. Chapter 11: Advanced Java Concurrency Practices in Cloud Computing 15. Chapter 12: The Horizon Ahead 16. Index 17. Other Books You May Enjoy Appendix A: Setting up a Cloud-Native Java Environment 1. Appendix B: Resources and Further Reading

GPU acceleration in Java – leveraging CUDA, OpenCL, and native libraries

To harness the immense computational power of GPUs within Java applications, developers have several options at their disposal. This section explores how Java developers can leverage CUDA, OpenCL, and native libraries to accelerate computations and tap into the parallel processing capabilities of GPUs. We’ll delve into the strengths and weaknesses of each approach, guiding you toward the most suitable solution for your specific use case.

Fundamentals of GPU computing

GPUs have evolved from their original purpose of rendering graphics to becoming powerful tools for general-purpose computation. This shift, known as general-purpose computing on graphics processing units (GPGPU), leverages the parallel processing capabilities of GPUs to perform computations more efficiently than traditional CPUs in certain tasks.

Unlike CPUs, which have a few cores optimized for sequential processing, GPUs have...

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