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Statistical simulation is a technique for fast performance evaluation of superscalar processors. First, intrinsic statistical information is collected from a single detailed simulation of a program. This information is then used to generate a synthetic instruction trace that is fed to a simple processor model, along with cache and branch prediction statistics. Because of the probabilistic nature of the simulation, it quickly converges to a performance rate. The simplicity and simulation speed make it useful for fast design space exploration; as such, it is a good complement to conventional detailed simulation.
Nussbaum et al. (Sat,) studied this question.