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Selective branch prediction reversal by correlating with data values and control flow

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4 Author(s)
Aragon, J.L. ; Dept. Ingenieria y Tecnologia de Computadores, Murcia Univ., Spain ; Gonzalez, J. ; Garcia, J.M. ; Gonzalez, A.

Branch prediction is one of the main hurdles in the roadmap towards deeper pipelines and higher clock frequencies. This work presents a new approach to enhancing current branch predictors: Selective Branch Prediction Reversal. The rationale behind this proposal is the fact that many branch mispredictions can be avoided if branch prediction is selectively reversed. We present a Branch Prediction Reversal Unit (BPRU) that selectively reverses branch predictions by correlating with the predicted values of the branch inputs, in addition to recent control flow. As a case study, we have included the BPRU in an already proposed branch predictor, the Branch Predictor through Value Prediction (BPVP). The effect is a reduction by half in its original misprediction rate. We have also measured the improvement when the BPRU engine is used in a hybrid scheme composed of a BPVP and a gshare predictor. Results using immediate updates show average reductions in misprediction rate ranging from 7% to 14%. Performance evaluation of the proposed BPRU in a 20-stage superscalar processor shows an IPC improvement of up to 9%

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Computer Design, 2001. ICCD 2001. Proceedings. 2001 International Conference on

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