Hyunkwang Lee

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The continued success of Deep Neural Networks (DNNs) in classification tasks has sparked a trend of accelerating their execution with specialized hardware. While published designs easily give an order of magnitude improvement over general-purpose hardware, few look beyond an initial implementation. This paper presents Minerva, a highly automated co-design(More)
We demonstrate a battery-powered multi-chip system optimized for insect-scale flapping wing robots that meets the tight weight limit and real-time performance demands of autonomous flight. Measured results show open-loop wing flapping driven by a power electronics unit and energy efficiency improvements via hardware acceleration. Introduction Recent(More)
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