A Cost Estimation Based Speculative Path Prediction Method for Speculative Multithreading

Speculative multithreading(SpMT) technology is an effective mechanism for automatic parallelization of irregular programs.However,just generating speculative threads based on the control flow graph which only contains branch probability information,it is inevitable that there may be excessive constraints resulting from control and data dependence in practice.Therefore,it is very important to understand the trade-offs between different speculative paths.In this paper,by introducing the data dependence model and discussing the trade-offs between different speculative paths,we propose a novel cost estimation based speculative path prediction method which comprehensively takes account of control-and data-dependence.By this method,we attempt to seek a speculative path which has the minimum cost overhead.The experimental results show that there are interesting trade-offs between different speculative paths and we can indeed get better performance.On average,we achieve 2.43% performance improvement.