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1998
IEEE

Dynamic History-length Fitting: A Third Level of Adaptivity for Branch Prediction

9 years 4 months ago
Dynamic History-length Fitting: A Third Level of Adaptivity for Branch Prediction
Accurate branch prediction is essential for obtaining high performance in pipelined superscalar processors that execute instructions speculatively. Some of the best current predictors combine a part of the branch address with a fixed amount of global history of branch outcomes in order to make a prediction. These predictors cannot perform uniformly well across all workloads because the best amount of history to be used depends on the code, the input data and the frequency of context switches. Consequently, all predictors that use a fixed history length are therefore unable to perform up to their maximum potential. We introduce a method --called DHLF-- that dynamically determines the optimum history length during execution, adapting to the specific requirements of any code, input data and system workload. Our proposal adds an extra level of adaptivity to two-level adaptive branch predictors. The DHLF method can be applied to any one of the predictors that combine global branch history ...
Toni Juan, Sanji Sanjeevan, Juan J. Navarro
Added 05 Aug 2010
Updated 05 Aug 2010
Type Conference
Year 1998
Where ISCA
Authors Toni Juan, Sanji Sanjeevan, Juan J. Navarro
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