168 citations · 221 across the 3 of their papers we have counts for
3 papers
Analog CMOS-based Resistive Processing Unit for Deep Neural Network Training
Seyoung Kim, Tayfun Gokmen, Hyung-Min Lee +1
Recently we have shown that an architecture based on resistive processing unit (RPU) devices has potential to achieve significant acceleration in deep neural network (DNN) training…
Training Deep Convolutional Neural Networks with Resistive Cross-Point Devices
Tayfun Gokmen, O. Murat Onen, Wilfried Haensch
In a previous work we have detailed the requirements to obtain a maximal performance benefit by implementing fully connected deep neural networks (DNN) in form of arrays of resisti…
On the possibility of obtaining MOSFET-like performance and sub-60 mV/decade swing in 1D broken-gap tunnel transistors
Siyuranga O. Koswatta, Steven J. Koester, Wilfried Haensch
Tunneling field-effect transistors (TFETs) have gained a great deal of recent interest due to their potential to reduce power dissipation in integrated circuits. One major challeng…