Statistical approach in a system level methodology to deal with process variation

Abstract

The impact of process variation in state of the art technology makes traditional (worst case) designs unnecessarily pessimistic, which translates to suboptimal designs in terms of both energy consumption and performance. In this context, developing variation aware design methodologies becomes a must. These techniques should provide better performance-energy balances while the percentage of faulty products keeps controlled. Furthermore, it would be advisable to consider adaptations of the system during lifetime, in order to provide robustness against ageing. In this paper we propose a design approach which tackles process variation on the memory system by using multimode memories. At design time we perform a heuristic exploration using probabilistic models of these memories, which generates a set of system configurations that minimize energy consumption for a given set of timing constraints. The percentage of systems that will satisfy these deadlines, even under process variation, is taken as a design parameter. Additionally, if system monitors are available, a setup stage optimizes the initial set of configurations for the actual memory parameters. Our simulations show that this methodology provides significant energy savings while still meeting timing constraints.