Better Branch Prediction Through Prophet/Critic Hybrids

Falcón, Ayose; Stark, Jared; Ramírez, Alex; Lai, Konrad; Valero, Mateo

doi:10.1109/mm.2005.5

Cited by 3 publications

(1 citation statement)

References 21 publications

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“…The filter part is exemplified by Sentry Table Filter [1], yet conceptually other filter methods, such as PPD [17] or NBD [25] can also be applied. The hedging part (Hedge State Machine) can adopt Complementary Branch Prediction (CBP) [18] [19] or other methods, such as the Prophet/Critic Hybrid Branch Prediction [15] [16]. In this paper, the hedging part is embodied by CBP.…”

Section: A Hedging Filter Hfmentioning

confidence: 99%

Cost-effective branch prediction by combining hedging and filtering

Maa

Yen

Kuo

et al. 2010

2010 International Computer Symposium (ICS2010)

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With the ever increasing needs of power aware architecture and circuit design in recent years, how to reduce the power consumption of processors without sacrificing performance has become an important issue. In this paper, we propose a new method for low power branch predictionHedging Filter, which combines filtering scheme reducing dynamic power consumption with hedging prediction mechanism lowering static power dissipation. We analyze and empirically study this proposed scheme embodied in the Sentry Table-Complementary Branch Prediction combo with respect to critical path delay, performance, hardware overhead and power consumption. Hedging Filter not only preserves critical path delay and prediction accuracy, but also contributes to the savings of dynamic and static power. From our evaluation, presuming equivalent or superior performance with respect to traditional counterparts, the proposed method reduces branch prediction hardware cost by up to 71% and power saving by up to 79% respectively.

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