High-level software energy macro-modeling

T. K. Tan, A. Raghunathan, G. Lakshminarayana, N. K. Jha

Research output: Contribution to journalConference articlepeer-review

64 Scopus citations

Abstract

This paper presents an efficient and accurate high-level software energy estimation methodology using the concept of characterization-based macro-modeling. In characterization-based macro-modeling, a function or sub-routine is characterized using an accurate lower-level energy model of the target processor, to construct a macro-model 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 macro-models eliminate the need for significantly slower instruction-level interpretation or hardware simulation that is required in conventional approaches to software energy estimation. We present two different approaches to macro-modeling for embedded software that offer distinct efficiency-accuracy characteristics: (i) complexity-based macro-modeling, where the variables that determine the algorithmic complexity of the function under consideration are used as macro-modeling parameters, and (ii) profiling-based macro-modeling, where internal profiling statistics for the functions are used as parameters in the energy macro-models. We have experimentally validated our software energy macro-modeling techniques on a wide range of embedded software routines and two different target processor architectures. Our experiments demonstrate that high-level macro-models constructed using the proposed techniques are able to estimate the energy consumption to within 95% accuracy on the average, while commanding speedups of one to five orders-of-magnitude over current instruction-level and architectural energy estimation techniques.

Original languageEnglish (US)
Pages (from-to)605-610
Number of pages6
JournalProceedings - Design Automation Conference
DOIs
StatePublished - Jan 1 2001
Event38th Design Automation Conference - Las Vegas, NV, United States
Duration: Jun 18 2001Jun 22 2001

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture
  • Control and Systems Engineering

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