Abstract

This paper introduces a power optimization paradigm for sequential components based on the concept of computational kernel, a highly simplified logic block whose behavior mimics the steady-state behavior of the original specification. We present a flexible framework that supports a number of algorithmic options for carrying out kernel extraction. We first describe an exact symbolic procedure that is applicable to components for which only a functional specification (i.e., the state transition graph) is available. Due to its computational complexity, this procedure is mainly of theoretical interest and it is not usable for large circuits. We then propose two approximate algorithms that can be adopted in practical situations. The first one is simulation-based and it is suitable to cases where input data streams representing typical operation of the component are available. The second approach performs kernel extraction by iteratively refining a structural representation of the component obtained through synthesis. The impact of the power optimization paradigm based on kernel extraction is demonstrated by the results of extensive experimentation carried out on a number of benchmarks of different characteristics and nature.

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