A statistically rigorous approach for improving simulation methodology

TLDR: This paper demonstrates the application of a rigorous statistical technique to the setup and analysis phases of the simulation process by applying a Plackett and Burman design to identify key processor parameters and classify benchmarks based on how they affect the processor.

Abstract: Due to cost, time, and flexibility constraints, simulators are often used to explore the design space when developing new processor architectures, as well as when evaluating the performance of new processor enhancements. However, despite this dependence on simulators, statistically rigorous simulation methodologies are not typically used in computer architecture research. A formal methodology can provide a sound basis for drawing conclusions gathered from simulation results by adding statistical rigor, and consequently, can increase confidence in the simulation results. This paper demonstrates the application of a rigorous statistical technique to the setup and analysis phases of the simulation process. Specifically, we apply a Plackett and Burman design to: (1) identify key processor parameters; (2) classify benchmarks based on how they affect the processor; and (3) analyze the effect of processor performance enhancements. Our technique expands on previous work by applying a statistical method to improve the simulation methodology instead of applying a statistical model to estimate the performance of the processor.