%0 Journal Article
%T Performance Evaluation of Different Data Value Prediction Schemes
%A Yong Xiao
%A Xing-Ming Zhou
%A <br>Yong
%A Xiao
%A and
%A Xing-Ming
%A Zhou
%J 计算机科学技术学报
%D 2005
%I 
%X Data value prediction has been widely accepted as an effective mechanism to break data hazards for high performance processor design. Several works have reported promising performance potential. However, there is hardly enough information that is presented in a clear way about performance comparison of these prediction mechanisms. This paper investigates the performance impact of four previously proposed value predictors, namely last value predictor, stride value predictor, two-level value predictor and hybrid (stride two-level) predictor. The impact of misprediction penalty, which has been frequently ignored, is discussed in detail. Several other implementation issues, including instruction window size, issue width and branch predictor are also addressed and simulated. Simulation results indicate that data value predictors act differently under different configurations. In some cases, simpler schemes may be more beneficial than complicated ones. In some particular cases, value prediction may have negative impact on performance.
%K data value predictors
%K performance impact
%K simulation<br>性能评估
%K 数据值预报
%K 运行冲撞
%K 数学模拟
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=F57FEF5FAEE544283F43708D560ABF1B&aid=C701B630AFCE711989E345D251599096&yid=2DD7160C83D0ACED&vid=A04140E723CB732E&iid=94C357A881DFC066&sid=D9D6C3CD78BED2C5&eid=F8AEC975DBDD7F2F&journal_id=1000-9000&journal_name=计算机科学技术学报&referenced_num=0&reference_num=17