摘要
研究了增强型步长值预测器.通过对传统步长值预测器的改进,可对部分重复型非等步长数据序列作出正确预测,提升性能.文中讨论了增强型步长值预测器的诸设计因素,如信心系统机制和公共子数据存储等.模拟结果表明,增强型步长值预测器能够对绝大部分适于值预测的数据序列作出正确预测.
Stride data value predictor is widely used by researchers in value prediction study.Compared with the context-based hybrid data value predictors,stride data value predictors are simple.But when encountering nonstride repeated sequences,a stride value predictor does not perform as well as a context-based hybrid data value predictor.In this paper,a revised stride data value predictor is introduced.With a little augment,the new predictor can make correct predictions on some patterns that can only be done by the context-based hybrid data value predictors.Simulation results show that the new predictor works well with most value predictable instructions.Design decisions such as confidence mechanism and storing common sub-data values are analyzed.
出处
《华中科技大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2005年第z1期114-116,共3页
Journal of Huazhong University of Science and Technology(Natural Science Edition)
