"In recent years, energy consumption of multi-cores has been
a critical research agenda as chip multiprocessors (CMPs) have emerged
as the leading architectural choice of computing systems. Unlike the uni-processor environment, the energy consumption of an application running on a CMP depends not only on the characteristics of the application
but also the behaviour of its co-runners (applications running on other
cores). In this paper, we model the energy-performance trade-off using
machine learning. We use the model to sacrifice a certain user-specified
percentage of the maximum achievable performance of an application to
save energy. "