Demonstration of transfer learning using 14 nm technology analog ReRAM array
Fabia Farlin Athena,
Omobayode Fagbohungbe,
Nanbo Gong
et al.
Abstract:Analog memory presents a promising solution in the face of the growing demand for energy-efficient artificial intelligence (AI) at the edge. In this study, we demonstrate efficient deep neural network transfer learning utilizing hardware and algorithm co-optimization in an analog resistive random-access memory (ReRAM) array. For the first time, we illustrate that in open-loop deep neural network (DNN) transfer learning for image classification tasks, convergence rates can be accelerated by approximately 3.5 ti… Show more
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