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Data value prediction

Data value prediction . Bas van der Tol. Limits to ILP. Instruction Level Parallelism is limited by Control flow Data flow: true dependencies. Types of Speculative Execution. Sources of predicatable data. Data redundancy Error-checking Program constants Virtual function calls Glue code

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Data value prediction

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Presentation Transcript

  1. Data value prediction Bas van der Tol

  2. Limits to ILP Instruction Level Parallelism is limited by • Control flow • Data flow: true dependencies

  3. Types of Speculative Execution

  4. Sources of predicatable data • Data redundancy • Error-checking • Program constants • Virtual function calls • Glue code • Call-subgraph identities • Register spill code

  5. Register value locality

  6. Value Prediction Unit

  7. VPT Hit rate sensitivity to Size

  8. Example use of Value Prediction

  9. Penalties Penalties • Misprediction penalty • Structural hazards, both on correct and mispredictions

  10. Configurations used for experiments

  11. PowerPC 620 Speedup

  12. PowerPC 620+ Speedup

  13. Infinite Machine Model Speedup

  14. Data cache vs. Value Prediction

  15. Improving Prediction Accuracy • Last Value Prediction • Stride Prediction • Finite Context Method Predictors (fcm)

  16. Finite Context Models

  17. Prediction Success

  18. Conclusions • Data value prediction increases performance by 5% on PowerPC 620 • A performance gain of 23% is possible Future Developments • More parallel execution units • Better prediction models

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