Improving the Accuracy of Energy Predictive Models for Multicore CPUs Using Additivity of Performance Monitoring Counters.

Energy predictive modelling using performance monitoring counters (PMCs) has emerged as the leading mainstream approach for modelling the energy consumption of an application. Modern computing platforms such as multicore CPUs provide a large set of PMCs. The programmers, however, can obtain only a small number of PMCs (typically 3–4) during an application run due to the limited number of hardware registers dedicated to storing them. Therefore, selection of a reliable subset of PMCs as predictor variables is crucial to the prediction accuracy of online energy models. State-of-the-art methods for selecting the PMCs are largely based on their correlation with energy consumption.