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JVM Performance Engineering: Inside OpenJDK and the HotSpot Java Virtual Machine

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Description

  • Copyright 2024
  • Dimensions: 7" x 9-1/8"
  • Pages: 400
  • Edition: 1st
  • eBook (Watermarked)
  • ISBN-10: 0-13-465996-1
  • ISBN-13: 978-0-13-465996-1

Peek Under the Hood of the Complex but Fascinating Java Virtual Machine

Dive into the intricacies of JVM performance with JVM Performance Engineering, the essential guide for seasoned Java developers eager to demystify the JVM. Focusing on the OpenJDK HotSpot VM, this book provides insights into cutting-edge Java performance techniques and trends.

Distinguished Java Champion Monica Beckwith blends theoretical insights and practical tools--encompassing case studies, applications, use-case diagrams, and process flow charts--to demonstrate diagnostic techniques, performance methodologies, and optimizations.

This manual is a portal to excelling in Java performance engineering, offering Java developers, system architects, and software engineers the tools to foster career advancement and success with Java applications.

  • Examine the evolving Java type system, from lambda expressions to the advent of records and sealed classes, and explore how Project Valhalla aims to further optimize performance
  • Leverage the Unified JVM Logging Interface for enhanced diagnostics, monitoring, and performance testing, featuring the novel asynchronous logging mechanism
  • Grasp the intricate relationship between JVM and hardware, mastering end-to-end Java performance optimization techniques
  • Gain deep insights into JVM's garbage collection and memory management, examining the pivotal Garbage First and Z GCs--and how they are shaping the Java performance landscape
  • Explore efficient deployment strategies and techniques to accelerate JVM readiness, leveraging class data sharing, ahead-of-time compilation, and innovations like GraalVM and upcoming Project Leyden
  • Embark on an exploration of the synergy between the JVM and exotic hardware like GPUs and FPGAs and revel in the potential of Project Panama and TornadoVM in high-computational scenarios such as machine learning and data analytics
  • Look ahead to the future of Java concurrency with Virtual Threads, and investigate runtime optimizations of string handling and concurrency, propelling Java forward

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Sample Content

Table of Contents

Preface xv
Acknowledgments xxiii
About the Author xxvii

Chapter 1: The Performance Evolution of Java: The Language and the Virtual Machine 1
A New Ecosystem Is Born 2
A Few Pages from History 2
Understanding Java HotSpot VM and Its Compilation Strategies 3
HotSpot Garbage Collector: Memory Management Unit 13
The Evolution of the Java Programming Language and Its Ecosystem: A Closer Look 18
Embracing Evolution for Enhanced Performance 42

Chapter 2: Performance Implications of Java's Type System Evolution 43
Java's Primitive Types and Literals Prior to J2SE 5.0 44
Java's Reference Types Prior to J2SE 5.0 45
Java's Type System Evolution from J2SE 5.0 until Java SE 8 49
Java's Type System Evolution: Java 9 and Java 10 52
Java's Type System Evolution: Java 11 to Java 17 55
Beyond Java 17: Project Valhalla 58
Conclusion 68

Chapter 3: From Monolithic to Modular Java: A Retrospective and Ongoing Evolution 69
Introduction 69
Understanding the Java Platform Module System 70
From Monolithic to Modular: The Evolution of the JDK 78
Continuing the Evolution: Modular JDK in JDK 11 and Beyond 78
Implementing Modular Services with JDK 17 78
JAR Hell Versioning Problem and Jigsaw Layers 83
Open Services Gateway Initiative 91
Introduction to Jdeps, Jlink, Jdeprscan, and Jmod 93
Conclusion 96

Chapter 4: The Unified Java Virtual Machine Logging Interface 99
The Need for Unified Logging 99
Unification and Infrastructure 100
Tags in the Unified Logging System 101
Diving into Levels, Outputs, and Decorators 103
Practical Examples of Using the Unified Logging System 107
Optimizing and Managing the Unified Logging System 109
Asynchronous Logging and the Unified Logging System 110
Understanding the Enhancements in JDK 11 and JDK 17 113
Conclusion 113

Chapter 5: End-to-End Java Performance Optimization: Engineering Techniques and Micro-benchmarking with JMH 115
Introduction 115
Performance Engineering: A Central Pillar of Software Engineering 116
Metrics for Measuring Java Performance 118
The Role of Hardware in Performance 128
Performance Engineering Methodology: A Dynamic and Detailed Approach 145
The Importance of Performance Benchmarking 158
Conclusion 175

Chapter 6: Advanced Memory Management and Garbage Collection in OpenJDK 177
Introduction 177
Overview of Garbage Collection in Java 178
Thread-Local Allocation Buffers and Promotion-Local Allocation Buffers 179
Optimizing Memory Access with NUMA-Aware Garbage Collection 181
Exploring Garbage Collection Improvements 183
Future Trends in Garbage Collection 210
Practical Tips for Evaluating GC Performance 212
Evaluating GC Performance in Various Workloads 214
Live Data Set Pressure 216

Chapter 7: Runtime Performance Optimizations: A Focus on Strings, Locks, and Beyond 219
Introduction 219
String Optimizations 220
Enhanced Multithreading Performance: Java Thread Synchronization 236
Transitioning from the Thread-per-Task Model to More Scalable Models 259
Conclusion 270

Chapter 8: Accelerating Time to Steady State with OpenJDK HotSpot VM 273
Introduction 273
JVM Start-up and Warm-up Optimization Techniques 274
Decoding Time to Steady State in Java Applications 274
Managing State at Start-up and Ramp-up 278
GraalVM: Revolutionizing Java's Time to Steady State 290
Emerging Technologies: CRIU and Project CRaC for Checkpoint/Restore Functionality 292
Start-up and Ramp-up Optimization in Serverless and Other Environments 295
Boosting Warm-up Performance with OpenJDK HotSpot VM 300
Conclusion 306

Chapter 9: Harnessing Exotic Hardware: The Future of JVM Performance Engineering 307
Introduction to Exotic Hardware and the JVM 307
Exotic Hardware in the Cloud 309
The Role of Language Design and Toolchains 312
Case Studies 313
Envisioning the Future of JVM and Project Panama 333
Concluding Thoughts: The Future of JVM Performance Engineering 336

Index 337

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