A cost estimation based speculative path determination method for speculative thread partitioning

As an effective mechanism for parallelizing irregular programs which are hard by conventional approaches, speculative multithreading (SpMT) technology has been proposed and being rapidly developed. While speculative parallelization can potentially deliver significant speedup for programs, the accuracy of the control- and data- speculation would limit these speedups in practice. In fact, different thread partitioning results by different speculative paths would lead to different overheads; and these overheads would seriously affect the parallel performance. Therefore, it is very important to understand the trade-offs between different speculative paths. The largest problem is that these existing prediction and speculation methods do not integrate the data dependence into the control speculation in order to obtain the maximum benefit. In this paper, by discussing the trade-offs between different speculative paths, we propose a novel cost estimation based speculative path determination 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 5.37% performance improvement.