Energy-constrained prefetching optimization in embedded applications

Abstract

In energy-constrained settings, most low-power compiler optimization techniques take the approach of minimizing the energy consumption while meeting no performance loss. However, it is possible that the available energy budget is not sufficient to meet the optimal performance objective. To limit energy consumption within a given energy budget, energy-constrained optimization approach is more significant. In this paper, we present an energy-constrained prefetching optimization approach through which memory or CPU stalls (caused by too early or too late prefetching) can be reduced so that energy budget is met. Optimal performance objective is achieved under a given energy budget. We evaluate the effectiveness of our energy-constrained prefetching optimization approach through simulations. © IFIP International Federation for Information Processing 2005.