HMCPA: Heuristic Method Utilizing Critical Path Analysis for Design Space Exploration of Superscalar Microprocessors

Microprocessor design space exploration at-tempts to determine the optimal parameter conguration to satisfy target requirements within limited time. Current mainstream superscalar microprocessors typically use out-of-order execution and fully utilize instruction level parallelism. However, the increasing complexity of superscalar microprocessor design leads to ever big design space, which poses a challenge to the determination of the optimal design point. To address this problem, this paper proposes a heuristic method utilizing critical path analysis (HMCPA) to perform design space exploration of superscalar microprocessors. Profiling a program running on a simulator enables the program dependence graph to be built by using the detailed information generated during the simulation. The critical path of the dependence graph can then be obtained and further analyzed to determine the performance bottleneck under current design conguration. Based on the information of the performance bottleneck, design space exploration can fnally be conducted efficiently. Experimental results show that compared with the traversal and simulated annealing methods, HMCPA can effectively reduce the number of design points that need to be explored, as well as determine the optimal conguration quickly.