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PARROT: Power Awareness Through Selective Dynamically Optimized Traces

  • Roni Rosner
  • Yoav Almog
  • Micha Moffie
  • Naftali Schwartz
  • Avi Mendelson
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3164)

Abstract

We present the PARROT concept aimed at both higher performance and power-awareness. The PARROT microarchitectural framework integrates trace caching, dynamic optimizations and pipeline decoupling. We employ a gradual and selective approach for applying complex mechanisms only for the most frequently used traces to maximize the performance gain at any given power constraint, thus attaining finer control of tradeoffs between performance and power awareness.

We show that the PARROT microarchitecture delivers performance increases comparable to those available through conventional doubling of execution resources (average 16% IPC improvement). This improvement comes through better utilization of all available resources with the combination of a trace cache and selective trace optimization. On the other hand, performance advantage of a trace cache alone is limited to wide-machine configurations. No less critical, however, is power awareness. The PARROT microarchitecture delivers the performance increase at a comparable energy level, whereas the conventional path to higher performance consumes an average 70% more energy. Meanwhile, for those designs which can tolerate a higher power budget, PARROT gracefully scales up to use additional execution resources in a uniformly efficient manner. In particular, a PARROT-style doubly-wide machine delivers an average 45% IPC improvement while actually improving the Cubic- MIPS-per-WATT power awareness metric by over 50%.

Keywords

Dynamic Optimization Instruction Cache Branch Predictor Atomic Trace Execution Core 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Roni Rosner
    • 1
  • Yoav Almog
    • 1
  • Micha Moffie
    • 1
  • Naftali Schwartz
    • 1
  • Avi Mendelson
    • 1
  1. 1.Microprocessor ResearchIntel LabsHaifaIsrael

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