Trace-based just-in-time type specialization for dynamic languages

ABSTRACT

Dynamic languages such as JavaScript are more difficult to compile than statically typed ones. Since no concrete type information is available, traditional compilers need to emit generic code that can handle all possible type combinations at runtime. We present an alternative compilation technique for dynamically-typed languages that identifies frequently executed loop traces at run-time and then generates machine code on the fly that is specialized for the actual dynamic types occurring on each path through the loop. Our method provides cheap inter-procedural type specialization, and an elegant and efficient way of incrementally compiling lazily discovered alternative paths through nested loops. We have implemented a dynamic compiler for JavaScript based on our technique and we have measured speedups of 10x and more for certain benchmark programs.

References

1. LuaJIT roadmap 2008 -- http://lua-users.org/lists/lua-l/2008-02/msg00051.html.
2. Mozilla Firefox web browser and Thunderbird email client -- http://www.mozilla.com.
3. SPECJVM98 -- http://www.spec.org/jvm98/.
4. SpiderMonkey (JavaScript-C) Engine -- http://www.mozilla.org/js/spidermonkey/.
5. Surfin' Safari -- Blog Archive -- Announcing SquirrelFish Extreme -- http://webkit.org/blog/214/introducing-squirrelfish-extreme/.
6. A. Aho, R. Sethi, J. Ullman, and M. Lam. Compilers: Principles, techniques, and tools, 2006.
7. V. Bala, E. Duesterwald, and S. Banerjia. Dynamo: A transparent dynamic optimization system. In Proceedings of the ACM SIGPLAN Conference on Programming Language Design and Implementation, pages 1--12. ACM Press, 2000.
8. M. Berndl, B. Vitale, M. Zaleski, and A. Brown. Context Threading: a Flexible and Efficient Dispatch Technique for Virtual Machine Interpreters. In Code Generation and Optimization, 2005. CGO 2005. International Symposium on, pages 15--26, 2005.
9. C. Chambers and D. Ungar. Customization: Optimizing Compiler Technology for SELF, a Dynamically-Typed O bject-Oriented Programming Language. In Proceedings of the ACM SIGPLAN 1989 Conference on Programming Language Design and Implementation, pages 146--160. ACM New York, NY, USA, 1989.
10. A. Gal. Efficient Bytecode Verification and Compilation in a Virtual Machine Dissertation. PhD thesis, University Of California, Irvine, 2006.
11. A. Gal, C. W. Probst, and M. Franz. HotpathVM: An effective JIT compiler for resource-constrained devices. In Proceedings of the International Conference on Virtual Execution Environments, pages 144--153. ACM Press, 2006.
12. C. Garrett, J. Dean, D. Grove, and C. Chambers. Measurement and Application of Dynamic Receiver Class Distributions. 1994.
13. J. Ha, M. R. Haghighat, S. Cong, and K. S. McKinley. A concurrent trace-based just-in-time compiler for javascript. Dept.of Computer Sciences, The University of Texas at Austin, TR--09--06, 2009.
14. B. McCloskey. Personal communication.
15. I. Piumarta and F. Riccardi. Optimizing direct threaded code by selective inlining. In Proceedings of the ACM SIGPLAN 1998 conference on Programming language design and implementation, pages 291--300. ACM New York, NY, USA, 1998.
16. A. Rigo. Representation-Based Just-In-time Specialization and the Psyco Prototype for Python. In PEPM, 2004.
17. M. Salib. Starkiller: A Static Type Inferencer and Compiler for Python. Master's Thesis, 2004.
18. T. Suganuma, T. Yasue, and T. Nakatani. A Region-Based Compilation Technique for Dynamic Compilers. ACM Transactions on Programming Languages and Systems (TOPLAS), 28(1):134--174, 2006.
19. M. Zaleski, A. D. Brown, and K. Stoodley. YETI: A graduallY Extensible Trace Interpreter. In Proceedings of the International Conference on Virtual Execution Environments, pages 83--93. ACM Press, 2007.

Index Terms

• Software and its engineering

  • Software notations and tools

    • Compilers

      • Incremental compilers

      • Runtime environments

      • Source code generation