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Energy is now a first-class design constraint along with performance in allcomputing settings. Energy predictive modelling based on performance monitoringcounts (PMCs) is the leading method used for prediction of energy consumptionduring an application execution. We use a model-theoretic approach to formulatethe assumed properties of existing models in a mathematical form. We extend theformalism by adding properties, heretofore unconsidered, that account for alimited form of energy conservation law. The extended formalism defines ourtheory of energy of computing. By applying the basic practical implications ofthe theory, we improve the prediction accuracy of state-of-the-art energymodels from 31% to 18%. We also demonstrate that use of state-of-the-artmeasurement tools for energy optimisation may lead to significant losses ofenergy (ranging from 56% to 65% for applications used in experiments) sincethey do not take into account the energy conservation properties.

Energy of Computing on Multicore CPUs: Predictive Models and Energy Conservation Law