Energy analysis for an executable program on a single computer based on BP neural network

Abstract

Power management of application programs is a hot research in the area of green computing and high-productivity computing. Because of the complexity of application programs, heterogeneity of processors and uncertainty of the running environment, it is difficult to propose an accurate method to predict energy consumption for application program directly. So, we present a power analysis paradigm for application program based on artificial neural network. First, we build a power analysis model based on back propagation neural network (BPNN). The three factors of software, hardware and environment are taken as the inputs of BPNN, and energy consumption and finish time as the outputs of BPNN. Next, we choose lot of classic application programs from different fields as training samples. After learning and training, an expected BPNN is obtained which can be used to predict energy consumption for other new programs. Repeated experiments show that this power analysis paradigm is rational and feasible.