【摘要】 随着高性能超标量处理器的流水线深度和发射度的增加,为挖掘宽发射、深度流水线处理器的潜在性能,设计一个杰出的转移预测器已变得越来越重要。常规的两级转移预测器是根据局部转移历史信息或全局转移历史信息来预测转移的结果,文章给出了一种新的转移预测方案,称为LGshare,它同时使用全局和局部转移历史信息来改进超标量微处理器的转移预测准确度。当模式历史表(PHT)的大小固定时,与常规的两级预测器相比,LGshare能获得更高的转移预测准确度。更多还原

【Abstract】 As the pipeline depth and issue rate of high-performance superscalar processors increase, the importance of an excellent branch predictor becomes more crucial to delivering the potential performance of a wide-issue, deep pipeline processor. Conventional two-level branch predictors predict the outcome of a branch either based on the local branch history information or based on the global branch history information. This paper proposes a new branch prediction scheme, called LGshare, which employs both the global and local branch history information simultaneously to improve the branch prediction accuracy for superscalar processors. It is shown that LGshare can achieve higher branch prediction accuracy than conventional two-level predictors when the size of the pattern history table is fixed.更多还原