2010WSEAS Transactions on Computers archiveRequires access

A novel meta predictor design for hybrid branch prediction

Young Jung Ahn, Dae Yon Hwang, Yong Suk Lee, Jin‐Young Choi, Gyungho Lee

Open publisher page 0 citations

Abstract

Recent systems have been paved the way for being high-performance due to the super-pipelining, dynamic scheduling and superscalar processor technologies. The performance of the system is greatly affected by the accuracy of the branch prediction because the overhead of each misprediction has grown due to greater number of instructions per cycle and the deepened pipeline. Hybrid branch prediction is usually used to increase the prediction accuracy on such high-performance systems. Normally hybrid branch prediction uses several branch predictors. A meta-predictor selects which branch predictor should be used corresponding to the program context of the branch instruction instance for the branch prediction. In this paper, we discuss about the saturating counter within meta predictor. The design of the saturating counter which selects a predictor that has high-prediction ratio has brought out the high accuracy of the prediction for the branch predictor.

About this research paper

What this paper is about

Recent systems have been paved the way for being high-performance due to the super-pipelining, dynamic scheduling and superscalar processor technologies. The performance of the system is greatly affected by the accuracy of the branch prediction because the overhead of each misprediction has grown due to greater number of instructions per cycle and the deepened pipeline. Hybrid branch prediction is usually used to increase the prediction accuracy on such high-performance systems. Normally hybrid branch prediction uses several branch predictors. A meta-predictor selects which branch predictor should be used corresponding to the program context of the branch instruction instance for the branch prediction. In this paper, we discuss about the saturating counter within meta predictor. The design of the saturating counter which selects a predictor that has high-prediction ratio has brought out the high accuracy of the prediction for the branch predictor.

Why it matters

A significance statement is not available in the OpenAlex record.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

Recent systems have been paved the way for being high-performance due to the super-pipelining, dynamic scheduling and superscalar processor technologies. The performance of the system is greatly affected by the accuracy of the branch prediction because the overhead of each misprediction has grown due to greater number of instructions per cycle and the deepened pipeline. Hybrid branch prediction is usually used to increase the prediction accuracy on such high-performance systems. Normally hybrid branch prediction uses several branch predictors. A meta-predictor selects which branch predictor should be used corresponding to the program context of the branch instruction instance for the branch prediction. In this paper, we discuss about the saturating counter within meta predictor. The design of the saturating counter which selects a predictor that has high-prediction ratio has brought out the high accuracy of the prediction for the branch predictor.

Key concepts: Branch predictor, Superscalar, Computer science, Pipeline (software), Overhead (engineering), Performance prediction, Scheduling (production processes), Context (archaeology)

Related papers

Back to paper searchBrowse research topicsOriginal source
A novel meta predictor design for hybrid branch prediction — Research Paper | ScholarLens