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Dynamo 100107092845-phpapp02
- Dynamo is a dynamic optimization system developed at HP Labs in 1996 that performs dynamic binary translation and optimization at runtime. - It works transparently by initially interpreting the instruction stream until hot instruction sequences, or traces, are identified. Then it generates optimized versions of the traces and stores them in a software code cache called the fragment cache. - Key aspects of how Dynamo works include trace selection and formation, trace optimization, fragment linking and management, handling signals and exceptions, and mechanisms for "bailing out" of optimized code back to interpretation if optimizations cannot be applied.
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Dynamo 100107092845-phpapp02
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- 2. • Dynamo • • • more challenging situation • -O Dynamo -O4 • HP PA-8000, HPUX10.20 OS 2010 1 8
- 3. • ’00 • • • Shrink-wrapped software (as a collection of DLLs) • (Java JIT/ ) • • CISC→RISC→VLIW 2010 1 8
- 4. Dynamo • 1996 HP Lab. • dynamic optimization system ( ) • Software • transparent • (preparatory) • programmer assistance • legachy • /JIT 2010 1 8
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- 6. • JIT(Self, Smaltalk-80, Java) • selective dynamic compilation • user annotation • language extensions • non-native system emulation • offline binary translation • superscalar microprocessor • trace cache 2010 1 8
- 7. Cited by 189 #. Cites 40 30 20 10 0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 1 8
- 8. 2009 • Efe Yardimci et al., Mostly static program partitioning of binary executables • Ryan W. Moore et al., Addressing the challenges of DBT for the ARM architecture • Borys J. Bradel et al., A study of potential parallelism among traces in Java programs • Tobias Werth et al., Dynamic code footprint optimization for the IBM Cell Broadband Engine • Seung Woo Son et al., A compiler-directed data prefetching scheme for chip multiprocessors • Kim Hazelwood et al., Scalable support for multithreaded applications on dynamic binary instrumentation systems • Mason Chang et al., Tracing for web 3.0: trace compilation for the next generation web applications • Andreas Gal et al., Trace-based just-in-time type specialization for dynamic languages • Florian Brandner, Precise simulation of interrupts using a rollback mechanism • Jason Mars et al., Scenario Based Optimization: A Framework for Statically Enabling Online Optimizations • Jianjun Li et al., An Evaluation of Misaligned Data Access Handling Mechanisms in Dynamic Binary Translation Systems • Naveen Kumar et al., Transparent Debugging of Dynamically Optimized Code • Alessandro Pellegrini et al., Di-DyMeLoR: Logging only Dirty Chunks for Efficient Management of Dynamic Memory Based Optimistic Simulation Objects • Daniel Williams et al., Using program metadata to support SDT in object-oriented applications • Carl Friedrich Bolz et al., Tracing the meta-level: PyPy's tracing JIT compiler 2010 1 8
- 9. • Overview of how Dynamo works • Dynamo’s startup mechanism • • • • • 2010 1 8
- 10. Overview Dynamo only interprets the inst. stream until a “hot” inst. seq. is identified. Dynamo generates an optimized ver. of the trace(fragment) into a software code cache(fragment cache). 2010 1 8
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- 12. Fragment Formation • Trace Selection • not accuracy, but predictability • the amount of counter updates and counter storage • interpretation • Trace Optimization • fall-through direction remains on the trace • Fragment code generation • emitting the fragment body • emitting the fragment exit stubs 2010 1 8
- 13. Trace Selection • interpretation > statistical PC sampling • MRET to pick hot traces 2010 1 8
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- 16. Fragment Cache Management • Cold Traces • Dynamo fragment creation rate sharp • fragment Free Object GC 2010 1 8
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- 18. Signal Handling • fragment Signal • signal / • fragment • Prototype • Conservative/Aggressive 2010 1 8
- 19. Speedup ratio 150kB fragment cache startup overhead the lack of stable working set 2010 1 8
- 20. Bailing-out bail-out 0 2010 1 8
- 21. 2010 1 8