Automated energy/performance macromodeling of embedded software
Proceedings of the 41st annual Design Automation Conference
Energy macromodeling of embedded operating systems
ACM Transactions on Embedded Computing Systems (TECS)
Hybrid simulation for embedded software energy estimation
Proceedings of the 42nd annual Design Automation Conference
Balancing power consumption in multiprocessor systems
Proceedings of the 1st ACM SIGOPS/EuroSys European Conference on Computer Systems 2006
An energy-aware framework for dynamic software management in mobile computing systems
ACM Transactions on Embedded Computing Systems (TECS)
SOFSEM'11 Proceedings of the 37th international conference on Current trends in theory and practice of computer science
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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