Efficient Design Space Exploration for Customized Processors

Customized processors offer the system developer rapidly designed logic specifically constructed to meet the performance and area demands of a given application. Recently, there have been several major projects that automate the process of transforming an optimal processor specification into an efficient layout for manufacturing. Missing from these efforts, however, is an automated approach to constructing the optimal specifications in the first place. In this paper we introduce an efficient, fully automated methodology for guiding the design and optimization of a custom processor. Our approach is to decompose the overall problem of choosing an optimal architecture into a set of sub-problems that are, to first order, independent. For each sub-problem, we create a model that relates performance to area. From this, we build a constraint system that can be solved using linear-integer programming techniques, and arrive at an optimal parameter selection for all architectural components. Using our approach, it takes only a few minutes to explore the entire architecture design space of a custom processor. We show that the expected performance using our model correlates strongly to detailed pipeline simulations, and present results showing design tradeoffs for several different benchmarks.Pre-2018 CSE ID: CS2001-068