Efficient nonlinear function approximation in analog resistive crossbars for recurrent neural networks
Abstract Analog In-memory Computing (IMC) has demonstrated energy-efficient and low latency implementation of convolution and fully-connected layers in deep neural networks (DNN) by using physics for computing in parallel resistive memory arrays. However, recurrent neural networks (RNN) that are wid...
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Main Authors: | Junyi Yang, Ruibin Mao, Mingrui Jiang, Yichuan Cheng, Pao-Sheng Vincent Sun, Shuai Dong, Giacomo Pedretti, Xia Sheng, Jim Ignowski, Haoliang Li, Can Li, Arindam Basu |
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Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2025-01-01
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Series: | Nature Communications |
Online Access: | https://doi.org/10.1038/s41467-025-56254-6 |
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