Abstract: A performance measure (e.g., processor speed) for computing components such as servers is optimized by creating models of power consumption versus the performance measure for each server, adding the power models to derive an overall power model, and calculating an optimum set point for the performance measure which corresponds to a power limit on the servers using the overall power model. The set point is then used to set power budgets for the servers based on their power models, and the servers maintain power levels no greater than their respective power budgets. The server power models are preferably created in real time by monitoring power consumption and the performance measure to derive sets of data points for the servers, and performing regression on the sets of data points to yield power models for the servers. Multiple server power models may be created for different program applications.

Abstract: A performance measure (e.g., processor speed) for computing components such as servers is optimized by creating models of power consumption versus the performance measure for each server, adding the power models to derive an overall power model, and calculating an optimum set point for the performance measure which corresponds to a power limit on the servers using the overall power model. The set point is then used to set power budgets for the servers based on their power models, and the servers maintain power levels no greater than their respective power budgets. The server power models are preferably created in real time by monitoring power consumption and the performance measure to derive sets of data points for the servers, and performing regression on the sets of data points to yield power models for the servers. Multiple server power models may be created for different program applications.