Page History

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We changed the high-level intermediate representation of the client compiler to use static single assignment (SSA) form, which simplifies global optimizations. Additionally, we implemented a global register allocator that uses the linear scan algorithm. This work is part of the production version since Java 6.

• Thomas Kotzmann, Christian Wimmer, Hanspeter Mössenböck, Thomas Rodriguez, Kenneth Russell, David Cox: Design of the Java HotSpot™ Client Compiler for Java 6. In ACM Transactions on Architecture and Code Optimization, volume 5, issue 1, article 7. ACM Press, 2008. doi:10.1145/1369396.1370017
  Explains the structure of the client compiler, its intermediate representations, and the optimization algorithms. It describes the client compiler of the Java HotSpot™ VM of Java 6. Java 7 and OpenJDK contain no significant changes, so all information up-to-date.

• Christian Wimmerr: Linear Scan Register Allocation for the Java HotSpot™ Client Compiler. Master's thesis, Institute for System Software, Johannes Kepler University Linz, 2004.
  Extended description of the client compiler, with a focus on the register allocator. Read Chapter 4 for if you are interested in the details of the compiler and the intermediate representations. The term "research compiler" in this thesis refers to the product version of Java 6 (which was not released at the time of writing).

• Christian Wimmer, Hanspeter Mössenböck: Optimized Interval Splitting in a Linear Scan Register Allocator. In Proceedings of the ACM/USENIX International Conference on Virtual Execution Environments, pages 132-141. ACM Press, 2005. doi:10.1145/1064979.1064998
  Description of the register allocation algorithm of the current client compiler.

• Hanspeter Mössenböck, Michael Pfeiffer: Linear Scan Register Allocation in the Context of SSA Form and Register Constraints. In Proceedings of the International Conference on Compiler Construction, LNCS 2304, pages 229-246. Springer-Verlag, 2002.
  Describes an early version of the work, so it does not reflect the current product version.

• Hanspeter Mössenböck: Adding Static Single Assignment Form and a Graph Coloring Register Allocator to the Java HotSpot™ Client Compiler. Technical Report 15, Institute for Practical Computer Science, Johannes Kepler University Linz, 2000.
  Describes an early version of the work, so it does not reflect the current product version. The graph coloring register allocator was later replaced by the linear scan register allocator.

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• Thomas Würthinger: Visualization of Program Dependence Graphs. Master's thesis, Institute for System Software, Johannes Kepler University Linz, 2007.
  This thesis describes the architecture and implementation of the tool and also contains a user guide. It does not describe the final version, but is still up-to-date.

• Thomas Würthinger, Christian Wimmer, Hanspeter Mössenböck: Visualization of Program Dependence Graphs. In Proceedings of the International Conference on Compiler Construction, LNCS 4959, pages 193-196. Springer-Verlag, 2008. doi:10.1007/978-3-540-78791-4_13
  A short tool demonstration paper that briefly sketches the purpose and structure of the application.

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We added a fast algorithm for array bounds check elimination to the client compiler that optimizes frequently used patterns of array accesses and uses the deoptimization facilities of the Java HotSpot™ VM. This is a research project, but the algorithm could be part of a future product version.

• Thomas Würthinger, Christian Wimmer, Hanspeter Mössenböck: Array Bounds Check Elimination for the Java HotSpot™ Client Compiler. In Proceedings of the International Conference on Principles and Practice of Programming in Java, pages 125-133. ACM Press, 2007. doi:10.1145/1294325.1294343
  Conference paper that describes the optimization process, with a focus on the usage of deoptimization to avoid code duplication.

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We implemented an optimization that fuses the string object with its character array that holds the actual content. New bytecodes access the characters and allocate the strings. Nevertheless, the optimization is implemented completely inside the VM. The necessary bytecode rewriting is performed by the class loader. Optimized string objects are significantly smaller than the old string and its character array. This eliminates field loads, reduces the memory pressure, and the time necessary for garbage collection. It is a research project, but could show up in a future product version because it has a high impact on the performance.

• Christian Häubl, Christian Wimmer, Hanspeter Mössenböck: Optimized Strings for the Java HotSpot™ Virtual Machine. In Proceedings of the International Conference on Principles and Practice of Programming in Java, pages 105-114. ACM Press, 2008. doi:10.1145/1411732.1411747

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• Thomas Kotzmann: Escape Analysis in the Context of Dynamic Compilation and Deoptimization. PhD thesis, Institute for System Software, Johannes Kepler University Linz, 2005.
  Describes the details of all algorithms and contains an extensive evaluation as well as a survey of related work.

• Thomas Kotzmann, Hanspeter Mössenböck: Run-Time Support for Optimizations Based on Escape Analysis. In Proceedings of the International Symposium on Code Generation and Optimization, pages 49-60. IEEE Computer Society, 2007. doi:10.1109/CGO.2007.34
  Conference paper that describes the support necessary in the runtime system, the garbage collector, and the deoptimization framework.

• Thomas Kotzmann, Hanspeter Mössenböck: Escape Analysis in the Context of Dynamic Compilation and Deoptimization. In Proceedings of the ACM/USENIX International Conference on Virtual Execution Environments, pages 111-120. ACM Press, 2005. doi:10.1145/1064979.1064996
  Conference paper that describes the core algorithm for escape analysis that is integrated into the client compiler.

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We designed a feedback-directed optimization system for object inlining and array inlining that utilizes the just-in-time compiler and the garbage collector. Object inlining reduces the costs of field accesses by combining referenced objects with their referencing object. The order of objects on the heap is changed by the garbage collector so that they are placed next to each other. Then their offset is fixed, i.e. the objects are colocated. This allows field loads to be replaced by address arithmetic using the just-in-time compiler. Array inlining expands the concepts of object inlining to arrays, which are frequently used for the implementation of dynamic data structures. There are currently no plans to integrate this work into the product version.

• Christian Wimmer, Hanspeter Mössenböck: Feedback-Directed Object Inlining and Array Inlining. Technical Report, Institute for System Software, Johannes Kepler University Linz, 2008.
  Summary report that covers all parts of the optimization, but does not describe the algorithmic details. Read this if you want to get familiar with the topic.

• Christian Wimmer: Automatic Object Inlining in a Java Virtual Machine. PhD thesis, Institute for System Software, Johannes Kepler University Linz, 2008.
  Describes the details of all algorithms and contains an extensive evaluation as well as a survey of related work. Read this if you are interested in the implementation details.

• Christian Wimmer, Hanspeter Mössenböck: Automatic Array Inlining in Java Virtual Machines. In Proceedings of the International Symposium on Code Generation and Optimization, pages 14-23. ACM Press, 2008. doi:10.1145/1356058.1356061
  Conference paper that covers only the array inlining part of the optimization system.

• Christian Wimmer, Hanspeter Mössenböck: Automatic Feedback-Directed Object Inlining in the Java HotSpot™ Virtual Machine. In Proceedings of the ACM/USENIX International Conference on Virtual Execution Environments, pages 12-21. ACM Press, 2007. doi:10.1145/1254810.1254813
  Conference paper that covers only the object inlining part of the optimization system.

• Christian Wimmer, Hanspeter Mössenböck: Automatic Object Colocation Based on Read Barriers. In Proceedings of the Joint Modular Languages Conference, LNCS 4228, pages 326-345. Springer-Verlag, 2006. doi:10.1007/11860990_20
  Conference paper that covers only the object colocation part. It describes an early version of the work, so it does not fully reflect the final version.