The effect of speculatively updating branch history on branch prediction accuracy, revisited
Eric Hao, Po-Yung Chang, Yale N. Patt
Abstract
Open-access reader
Eric Hao, Po-Yung Chang, Yale N. Patt
Abstract
Open-access reader
Recent research has suggested that the branch history register need not contain the outcomes of the most recent branches in order for the Two-Level Adaptive Branch Predictor to work well. From this result, it is tempting to conclude that the branch history register need not be speculatively updated. This paper revisits this work and explains when the most recent branch outcomes can be omitted without significantly affecting performance. It also explains why this result does not imply that speculative update is not important. This paper shows that because the number of unresolved branches present in the machine varies during program execution, branch predictors without speculative update perform significantly worse than branch predictors with speculative update.
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Recent research has suggested that the branch history register need not contain the outcomes of the most recent branches in order for the Two-Level Adaptive Branch Predictor to work well. From this result, it is tempting to conclude that the branch history register need not be speculatively updated. This paper revisits this work and explains when the most recent branch outcomes can be omitted without significantly affecting performance. It also explains why this result does not imply that speculative update is not important. This paper shows that because the number of unresolved branches present in the machine varies during program execution, branch predictors without speculative update perform significantly worse than branch predictors with speculative update.
Key concepts: Branch predictor, Speculative execution, Computer science, Out-of-order execution, Speculative multithreading, Work (physics), Register (sociolinguistics), Parallel computing