Alternative Implementations for Hybrid Branch Predictors
Po-Yung Chang, Eric Hao, Yale N. Patt
Abstract
Highly accurate branch prediction is an important requirement for
achieving high performance on deeply pipelined, superscalar processors.
To improve on the prediction accuracy of current single-scheme branch
predictors, hybrid (multiple-scheme) branch predictors have been
proposed~\cite{mcf93,cha:hao94}. These predictors combine multiple
single-scheme predictors into a single predictor. They use a selection
mechanism to decide for each branch, which single-scheme predictor to
use. The performance for a given implementation of a hybrid predictor
is dependent on the single-scheme predictors used and the selection
mechanism. To find the most effective implementations, this paper
examines several hybrid predictor implementations and compares their
prediction accuracies. In addition, it introduces a new selection
mechanism, the 2-level selector, which improves the performance of the
hybrid branch predictor.
Keywords
branch prediction, speculative execution, superscalar.
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