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2002 | OriginalPaper | Buchkapitel

A Comprehensive Analysis of Indirect Branch Prediction

verfasst von : Oliverio J. Santana, Ayose Falcón, Enrique Fernández, Pedro Medina, Alex Ramírez, Mateo Valero

Erschienen in: High Performance Computing

Verlag: Springer Berlin Heidelberg

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Indirect branch prediction is a performance limiting factor for current computer systems, preventing superscalar processors from exploiting the available ILP. Indirect branches are responsible for 55.7% of mispredictions in our benchmark set, although they only stand for 15.5% of dynamic branches. Moreover, a 10.8% average IPC speedup is achievable by perfectly predicting all indirect branches.The Multi-Stage Cascaded Predictor (MSCP) is a mechanism proposed for improving indirect branch prediction. In this paper, we show that a MSCP can replace a BTB and accurately predict the target address of both indirect and non-indirect branches. We do a detailed analysis of MSCP behavior and evaluate it in a realistic setup, showing that a 5.7% average IPC speedup is achievable.

Metadaten
Titel
A Comprehensive Analysis of Indirect Branch Prediction
verfasst von
Oliverio J. Santana
Ayose Falcón
Enrique Fernández
Pedro Medina
Alex Ramírez
Mateo Valero
Copyright-Jahr
2002
Verlag
Springer Berlin Heidelberg
DOI
https://doi.org/10.1007/3-540-47847-7_13

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