The agree predictor
Eric Sprangle, Robert S. Chappell, Mitch Alsup, Yale N. Patt
Abstract
Eric Sprangle, Robert S. Chappell, Mitch Alsup, Yale N. Patt
Abstract
Deeply pipelined, superscalar processors require accurate branch prediction to achieve high performance. Two-level branch predictors have been shown to achieve high prediction accuracy. It has also been shown that branch interference is a major contributor to the number of branches mispredicted by two-level predictors.This paper presents a new method to reduce the interference problem called agree prediction, which reduces the chance that two branches aliasing the same PHT entry will interfere negatively. We evaluate the performance of this scheme using full traces (both user and supervisor) of the SPECint95 benchmarks. The result is a reduction in the misprediction rate of gcc ranging from 8.62% with a 64K-entry PHT up to 33.3% with a 1K-entry PHT.
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Deeply pipelined, superscalar processors require accurate branch prediction to achieve high performance. Two-level branch predictors have been shown to achieve high prediction accuracy. It has also been shown that branch interference is a major contributor to the number of branches mispredicted by two-level predictors.This paper presents a new method to reduce the interference problem called agree prediction, which reduces the chance that two branches aliasing the same PHT entry will interfere negatively. We evaluate the performance of this scheme using full traces (both user and supervisor) of the SPECint95 benchmarks. The result is a reduction in the misprediction rate of gcc ranging from 8.62% with a 64K-entry PHT up to 33.3% with a 1K-entry PHT.
Key concepts: Computer science, Supervisor, Branch predictor, Interference (communication), Ranging, Parallel computing, Algorithm, Computer network