本blog中列举了我学习JVM的references，会不断的更新，为了避免版权问题，就不在blog上提供references的下载了，感兴趣的同学可自行下载或购买，:)
大多数的论文可从此下载：http://citeseer.ist.psu.edu/index.jsp
同时推荐@rednaxelafx 整理的jvm的参考资料：http://goo.gl/oXmRQ

References
  |— Towards a Renaissance VM
  |— Oracle JRockit The Definitive Guide
  |— JVM Magic
  |— JAVA虚拟机中文第二版
  |— Java Lang Spec 3.0
  |— Inside Out A Modern Virtual Machine Revealed
  |— Hotspot Overview
  |— Azul’s JVM experiences
  |— A Crash Course in Modern Hardware
  |— [ adaptive ]
        |— Understanding Adaptive Runtimes
        |— Adaptive Optimization of Java Real-time
        |— Adaptive Optimization in the Jalapeno JVM
  |— [ compiler ]
        |— The Java HotSpotTM Server Compiler
        |— Tailoring Graph-coloring Register Allocation For Runtime Compilation
        |— Linear Scan Register Allocation
        |— Design of the Java HotSpotTM Client Compiler for Java 6
  |— [ concurrent ]
        |— The.Art.of.Multiprocessor.Programming.Mar.2008
        |— The Concurrency Revolution The Hardware Story
        |— Multithreaded Programming Guide
        |— JVM Continuations
        |— java.util.concurrent Synchronizer Framework
        |— Java Concurrency Gotchas
        |— Groovy and Concurrency
        |— concurrent programming without locks
        |— Concurrency Grab Bag
        |— Alternative Concurrency Paradigms For the JVM
        |— Accelerating Java Workloads via GPUs
        |— A Scalable Lockfree Stack Algorithm
        |— A Concurrent Dynamic Analysis Framework
  |— [ io ]
        |— Asynchronous IO Tricks and Tips
  |— [ memory management ]
        |— Tuning Java Memory Manager
        |— The Ghost in the Virtual Machine A Reference to References
        |— The Garbage Collection Mythbusters
        |— SuperSizingJava
        |— Step by Step GC Tuning in the HotSpot Java Virtual Machine
        |— parallel gc ppt
        |— Oracle JDBC Memory Management
        |— NUMA-Aware-Java-Heaps-for-Server-Applications
        |— memorymanagement_whitepaper
        |— markcompact_gc ppt
        |— Leak Pruning
        |— GC Vs Explicit MM
        |— GC Tuning in the hotspot
        |— Garbage Collection and Memory Architecture
        |— Garbage Collection Algorithms For Automatic Dynamic Memory Management – Richard Jones
        |— [ Hotspot GC论文 ]
              |— Parallel Garbage Collection for Shared Memory Multiprocessors
              |— Garbage First Garbage Collector
              |— A Generational Mostly-concurrent Garbage Collector
        |— [ 其他JVM GC ]
              |— The pauseless gc
              |— Immix A Mark-Region Garbage Collector
              |— How to write a distributed gc
              |— GC Nirvana High Throughput And Low Latency Together
  |— [ monitoring and profiling ]
        |— Where Does All the Native Memory Go
        |— What’s Happening with My Application JVM Monitoring Tool
        |— Practical Lessons in Memory Analysis
        |— MonitoringGuide
        |— Microarchitectural Characterization of Production JVMs and JavaWorkloads
        |— Going Beyond Memory Leaks Debugging Java from Dumps, Using Memory Analyzer
        |— Diagnosing and Fixing Memory Leaks in Web Applications Tips from the Front Line
  |— [ osrelated ]
        |— poll-epoll_2
        |— poll-epoll_1
        |— memory systems
        |— Linux内核源代码情景分析
        |— linux_cpu_scheduler
        |— Linux 内核中断内幕
        |— Linux System and Performance Monitoring
        |— cpumemory
  |— [ performance ]
        |— Towards Performance Measurements for the Java Virtual Machine’s invokedynamic
        |— Thinking clearly about performance
        |— The Impact of Performance Asymmetry in Emerging Multicore Architectures
        |— the art of benchmarking
        |— Techniques for Obtaining High Performance in Java Programs
        |— Pipelining for Performance
        |— Performance myths and legends
        |— Performance Java Versus C
        |— How to Tune and Write Low-Latency Applications on the Java Virtual Machine
        |— How to Get the Most Performance from Sun JVM on Intel? Multi-Core Servers
        |— Comparing the Performance of Web Server Arch
        |— A Common API for Measuring Performance