Early design phase power/performance modeling through statistical simulation

Microprocessor design time and effort are getting impractical due to the huge number of simulations that need to be done to evaluate various processor configurations for various workloads. An early design stage methodology could be useful to efficiently cull huge design spaces to identify regions of interest to be further explored using more accurate simulations. In such an early design stage methodology, power consumption should be considered besides performance, since power consumption is becoming a key design issue for midrange and high-end microprocessor designs. In this paper, we propose to use statistical simulation as an early design stage methodology that considers both performance and power. We evaluate the applicability and the accuracy of this methodology and we show that statistical simulation is indeed capable of identifying a region of energy-efficient architectures. In addition, we demonstrate that this methodology can be used to explore workload design spaces in terms of power/performance by varying program characteristics that are hard to vary using real programs.