Efficient microprocessor design space exploration through statistical simulation

To cope with the widening design gap, the ever increasing impact of technology, reflected in increased interconnect delay and power consumption, and the time-consuming simulations needed to define the architecture of a microprocessor computer engineers need techniques to explore the design space efficiently in an early design stage. These techniques should be able to identify a region of interest with desirable characteristics in terms of performance, power consumption and cycle time. In addition, they should be fast since the design space is huge and the design time is limited. In this paper we demonstrate that statistical simulation is an early design stage technique capable of making viable microprocessor design decisions efficiently in early stages of the design flow while considering performance, power consumption and cycle time