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High-level energy macromodeling of embedded software

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4 Author(s)
Tat Kee Tan ; Dept. of Electr. Eng., Princeton Univ., NJ, USA ; A. Raghunathan ; G. Lakshminarayana ; N. K. Jha

Presents an efficient and accurate high level software energy estimation methodology using the concept of characterization-based macromodeling. In characterization-based macromodeling, a function or subroutine is characterized using an accurate lower level energy model of the target processor to construct a macromodel that relates the energy consumed in the function under consideration to various parameters that can be easily observed or calculated from a high-level programming language description. The constructed macromodels eliminate the need for significantly slower instruction-level interpretation or hardware simulation that is required in conventional approaches to software energy estimation. Two different approaches to macromodeling for embedded software offer distinct efficiency-accuracy characteristics: 1) complexity-based macromodeling, where the variables that determine the algorithmic complexity of the function under consideration are used as macromodeling parameters and 2) profiling-based macromodeling, where internal profiling statistics for the functions are used as the parameters in the energy macromodels

Published in:

IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems  (Volume:21 ,  Issue: 9 )