Low-Energy Acceleration of Binarized Convolutional Neural Networks Using a Spin Hall Effect Based Logic-in-Memory Architecture

IEEE Transactions on Emerging Topics in Computing(2021)

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摘要
Deep Learning (DL) offers the advantages of high accuracy performance at tasks such as image recognition, learning of complex intelligent behaviors, and large-scale information retrieval problems such as intelligent web search. To attain the benefits of DL, the high computational and energy-consumption demands imposed by the underlying processing, interconnect, and memory devices on which software...
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Convolution,Mathematical model,Writing,Computer architecture,Energy efficiency,Neural networks,Standards organizations
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