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A flexible and fast PyTorch toolkit for simulating training and inference on analog crossbar arrays


Apr 05, 2021
Malte J. Rasch, Diego Moreda, Tayfun Gokmen, Manuel Le Gallo, Fabio Carta, Cindy Goldberg, Kaoutar El Maghraoui, Abu Sebastian, Vijay Narayanan

* Submitted to AICAS2021 

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Algorithm for Training Neural Networks on Resistive Device Arrays


Sep 17, 2019
Tayfun Gokmen, Wilfried Haensch

* 26 pages, 7 fiures 

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Zero-shifting Technique for Deep Neural Network Training on Resistive Cross-point Arrays


Aug 02, 2019
Hyungjun Kim, Malte Rasch, Tayfun Gokmen, Takashi Ando, Hiroyuki Miyazoe, Jae-Joon Kim, John Rozen, Seyoung Kim


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Training large-scale ANNs on simulated resistive crossbar arrays


Jun 06, 2019
Malte J. Rasch, Tayfun Gokmen, Wilfried Haensch


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Efficient ConvNets for Analog Arrays


Jul 03, 2018
Malte J. Rasch, Tayfun Gokmen, Mattia Rigotti, Wilfried Haensch


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Training LSTM Networks with Resistive Cross-Point Devices


Jun 01, 2018
Tayfun Gokmen, Malte Rasch, Wilfried Haensch

* 17 pages, 5 figures 

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Analog CMOS-based Resistive Processing Unit for Deep Neural Network Training


Jun 20, 2017
Seyoung Kim, Tayfun Gokmen, Hyung-Min Lee, Wilfried E. Haensch


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Training Deep Convolutional Neural Networks with Resistive Cross-Point Devices


May 22, 2017
Tayfun Gokmen, O. Murat Onen, Wilfried Haensch

* 22 pages, 6 figures, 2 tables 

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Acceleration of Deep Neural Network Training with Resistive Cross-Point Devices


Mar 23, 2016
Tayfun Gokmen, Yurii Vlasov

* Front. Neurosci 10, 333 (2016) 
* 19 pages, 5 figures, 2 tables 

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