Dual Dynamic Inference: Enabling More Efficient, Adaptive and Controllable Deep Inference

10 Jul 2019Yue WangJianghao ShenTing-Kuei HuPengfei XuTan NguyenRichard BaraniukZhangyang WangYingyan Lin

State-of-the-art convolutional neural networks (CNNs) yield record-breaking predictive performance, yet at the cost of high-energy-consumption inference, that prohibits their widely deployments in resource-constrained Internet of Things (IoT) applications. We propose a dual dynamic inference (DDI) framework that highlights the following aspects: 1) we integrate both input-dependent and resource-dependent dynamic inference mechanisms under a unified framework in order to fit the varying IoT resource requirements in practice... (read more)

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