145 citations · 981 across the 31 of their papers we have counts for
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Algorithm for Training Neural Networks on Resistive Device Arrays
Tayfun Gokmen, Wilfried Haensch
Hardware architectures composed of resistive cross-point device arrays can provide significant power and speed benefits for deep neural network training workloads using stochastic…
Zero-shifting Technique for Deep Neural Network Training on Resistive Cross-point Arrays
Hyungjun Kim, Malte Rasch, Tayfun Gokmen +5
A resistive memory device-based computing architecture is one of the promising platforms for energy-efficient Deep Neural Network (DNN) training accelerators. The key technical cha…
Design and Characterization of Superconducting Nanowire-Based Processors for Acceleration of Deep Neural Network Training
Murat Onen, Brenden A. Butters, Emily Toomey +2
Training of deep neural networks (DNNs) is a computationally intensive task and requires massive volumes of data transfer. Performing these operations with the conventional von Neu…
Training large-scale ANNs on simulated resistive crossbar arrays
Malte J. Rasch, Tayfun Gokmen, Wilfried Haensch
Accelerating training of artificial neural networks (ANN) with analog resistive crossbar arrays is a promising idea. While the concept has been verified on very small ANNs and toy…