Reducing branch misprediction penalty via selective branch recovery

摘要: Branch misprediction penalty consists of two components: the time wasted on misspeculative execution until mispredicted branch is resolved and to restart pipeline with useful instructions once resolved. Current processor trends, large instruction windows deep pipelines, amplify both components penalty. We propose a novel method, called selective recovery (SBR), reduce SBR exploits frequently occurring type control independence - exact convergence where path converges exactly at beginning correct path. In such cases, selectively reuses results computed during obviates need fetch or rename convergent again. Thus, addresses To increase likelihood mispredictions that can be handled SBR, we also present an effective means for inducing paths. With significantly improve performance (between 3%-22%, average 8%) wide range benchmarks over our baseline does not exploit SBR.