12 citations · 13 across the 4 of their papers we have counts for
4 papers
Neural Network Training with Asymmetric Crosspoint Elements
Murat Onen, Tayfun Gokmen, Teodor K. Todorov +5
Analog crossbar arrays comprising programmable nonvolatile resistors are under intense investigation for acceleration of deep neural network training. However, the ubiquitous asymm…
SEMULATOR: Emulating the Dynamics of Crossbar Array-based Analog Neural System with Regression Neural Networks
Chaeun Lee, Seyoung Kim
As deep neural networks require tremendous amount of computation and memory, analog computing with emerging memory devices is a promising alternative to digital computing for edge…
Hardware and software co-optimization for the initialization failure of the ReRAM based cross-bar array
Youngseok Kim, Seyoung Kim, Chun-chen Yeh +2
Recent advances in deep neural network demand more than millions of parameters to handle and mandate the high-performance computing resources with improved efficiency. The cross-ba…
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…