OSCAR: An Optimization Methodology Exploiting Spatial Correlation in Multicore Design Spaces
In this paper, the authors present OSCAR, an optimization methodology exploiting spatial correlation of multicore design spaces. This paper builds upon the observation that power consumption and performance metrics of spatially close design configurations (or points) are statistically correlated. The authors propose to exploit the correlation by using a Response Surface Model (RSM), i.e., a closed-form expression suitable for predicting the quality of nonsimulated design points. This model is useful during the Design Space Exploration (DSE) phase to quickly converge to the Pareto set of the multiobjective problem without executing lengthy simulations.