Saturating counter design for meta predictor in hybrid branch prediction
Young Jung Ahn, Dae Yon Hwang, Yong Suk Lee, Jin‐Young Choi, Gyungho Lee
Abstract
Young Jung Ahn, Dae Yon Hwang, Yong Suk Lee, Jin‐Young Choi, Gyungho Lee
Abstract
High-performance computer systems have made use of super-pipelining, dynamic scheduling and multiissue superscalar processor technologies. In these systems, branch prediction accuracy has a significant impact on the performance because the penalty for misprediction increases as pipelines deepen and the number of instructions issued per cycle increases. To have a better prediction accuracy, branch predictors utilized in high performance systems are a hybrid type. Hybrid branch prediction employs multiple branch predictors and selects one particular branch predictor per the program context of a given branch instruction instance for prediction. For choosing a particular branch predictor is a job of meta-predictor. This paper considers type and size of saturating counter design specifically for the meta predictor. State transitions different from a usual saturating counter may choose a particular predictor for prediction better and result a higher prediction accuracy.
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High-performance computer systems have made use of super-pipelining, dynamic scheduling and multiissue superscalar processor technologies. In these systems, branch prediction accuracy has a significant impact on the performance because the penalty for misprediction increases as pipelines deepen and the number of instructions issued per cycle increases. To have a better prediction accuracy, branch predictors utilized in high performance systems are a hybrid type. Hybrid branch prediction employs multiple branch predictors and selects one particular branch predictor per the program context of a given branch instruction instance for prediction. For choosing a particular branch predictor is a job of meta-predictor. This paper considers type and size of saturating counter design specifically for the meta predictor. State transitions different from a usual saturating counter may choose a particular predictor for prediction better and result a higher prediction accuracy.
Key concepts: Branch predictor, Computer science, Superscalar, Scheduling (production processes), Context (archaeology), Predictive modelling, Processor scheduling, Performance prediction