Abstract:Designing energy-efficient hardware continues to be challenging due to arithmetic complexities. The problem is further exacerbated in systems powered by energy harvesters as variable power levels can limit their computation capabilities. In this work, we propose a run-time configurable adaptive approximation method for multiplication that is capable of managing the energy and performance tradeoffsideally suited in these systems. Central to our approach is a Significance-Driven Logic Compression (SDLC) multipli… Show more
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