Parallel Concurrent And Distributed Programming In Java
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Java Concurrency and Parallelism
Unlock Java's full potential for cloud computing through expert insights from real-world case studies and stay ahead with the latest trends in agile and robust Java application development Key Features Master concurrency and parallelism to overcome cloud computing challenges in Java Build scalable solutions with Big Data, ML, microservices, and serverless architectures Explore cloud scaling, GPU utilization, and future tech innovations in Java applications Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionIf 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. What you will learn Understand Java concurrency in cloud app development Get to grips with the core concepts of serverless computing in Java Boost cloud scaling and performance using Java skills Implement Java GPU acceleration for advanced computing tasks Gain insights into Java's role in the evolving cloud and AI technology Access hands-on exercises for real-world Java applications Explore diverse Java case studies in tech and fintech Implement Java in AI-driven cloud and data workflows Analyze Java's application in IoT and real-time analytics Who this book is for This book is for Java developers, software engineers, and cloud architects with intermediate Java knowledge. It's ideal for professionals transitioning to cloud-native development or seeking to enhance their concurrent programming skills. DevOps engineers and tech leads involved in cloud migration will also find valuable insights. Basic Java proficiency, familiarity with cloud concepts, and some experience with distributed systems is expected.
Parallel and Concurrent Programming in Haskell
Author: Simon Marlow
language: en
Publisher: "O'Reilly Media, Inc."
Release Date: 2013-07-12
If you have a working knowledge of Haskell, this hands-on book shows you how to use the language’s many APIs and frameworks for writing both parallel and concurrent programs. You’ll learn how parallelism exploits multicore processors to speed up computation-heavy programs, and how concurrency enables you to write programs with threads for multiple interactions. Author Simon Marlow walks you through the process with lots of code examples that you can run, experiment with, and extend. Divided into separate sections on Parallel and Concurrent Haskell, this book also includes exercises to help you become familiar with the concepts presented: Express parallelism in Haskell with the Eval monad and Evaluation Strategies Parallelize ordinary Haskell code with the Par monad Build parallel array-based computations, using the Repa library Use the Accelerate library to run computations directly on the GPU Work with basic interfaces for writing concurrent code Build trees of threads for larger and more complex programs Learn how to build high-speed concurrent network servers Write distributed programs that run on multiple machines in a network