Analytical modeling is applied to the automated design of application-specific superscalar processors. Using an analytical method bridges the gap between the size of the design space and the time required for detailed cycle-accurate simulations. The proposed design framework takes as inputs the design targets (upper bounds on execution time, area, and energy), design alternatives, and one or more application programs. The output is the set of out-of-order superscalar processors that are Pareto-optimal with respect to performance-energy-area. The core of the new design framework is made up of analytical performance and energy activity models, and an analytical model-based design optimization process. For a set of benchmark programs and a design space of 2000 designs, the design framework arrives at all performanceenergy-area Pareto-optimal design points within 16 minutes on a 2 GHz Pentium-4. In contrast, it is estimated that a naïve cycle-accurate simulation-based exhaustive search w...
Tejas Karkhanis, James E. Smith