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    This was brought to you by:

    block this user Andreas Ermedahl Trusted member

    Assistant Professor

    Mälardalen University

    An Accurate Instruction-Level Energy Consumption Model for Embedded RISC Processors

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    Energy consumption of software is becoming an increasingly important issue in designing mobile embedded systems where batteries are used as the main power source. As a consequence, recently, a number of promising techniques have been proposed to optimize software for reduced energy consumption. Such low-power software techniques require an energy consumption model that can be used to estimate or predict the energy consumed by software. We propose a technique to derive an accurate energy consumption model at the instruction level, combining an empirical method and a statistical analysis technique. The result of the proposed approach is given by a model equation that characterizes energy behavior of software based on the properties of the instructions. Experimental results show that the model equation can accurately estimate the energy consumption of random instruction sequences, with an average error of 2.5 %. Keywords Low-power systems, instruction-level energy model, regression analysis 1.

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    Title : An Accurate Instruction-Level Energy Consumption Model for Embedded RISC Processors
    Abstract : Energy consumption of software is becoming an increasingly important issue in designing mobile embedded systems where batteries are used as the main power source. As a consequence, recently, a number of promising techniques have been proposed to optimize software for reduced energy consumption. Such low-power software techniques require an energy consumption model that can be used to estimate or predict the energy consumed by software. We propose a technique to derive an accurate energy consumption model at the instruction level, combining an empirical method and a statistical analysis technique. The result of the proposed approach is given by a model equation that characterizes energy behavior of software based on the properties of the instructions. Experimental results show that the model equation can accurately estimate the energy consumption of random instruction sequences, with an average error of 2.5 %. Keywords Low-power systems, instruction-level energy model, regression analysis 1.
    Subject : unspecified
    Area : Computer Science
    Language : English
    Affiliations : 
    Url : http://www.docs.uu.se/~ebbe/publications/energy_consumption_mode
    Doi : 10.1.1.20.8840

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