Operand-value-based modeling of dynamic energy consumption of soft processors in FPGA

Abstract

This paper presents a novel method for estimating the dynamic energy consumption of soft processors in FPGA, using an operand-value-based model at the instruction level. Our energy model contains three components: the instruction base energy, the maximum variation in the instruction energy due to input data, and the impact of one’s density of the operand values during software execution. Using multiple benchmarks, we demonstrate that our model has only 4.7% average error and 12% worst case error compared to the reference post-place-and-route simulations, and is more than twice as accurate as existing instruction-level models.