Modeling UpLink power control with outage probabilities
Kenneth L. Clarkson, K. Georg Hampel, et al.
VTC Spring 2007
Analog In-Memory Computing using Resistive Processing Unit (RPU) has been proposed for Neural Network (NN) training. However, hardware demonstration has been limited to using some digital emulation to assist the analog chip function. Using capacitor as analog weight, we report the first analog Neural Network training chip, where ALL Multiple and Accumulate (MAC) function are performed in analog cross-point arrays, and all weights are updated in parallel. The chip measure full MNIST training accuracy of 92.7% with run time faster than digital system in real time.
Kenneth L. Clarkson, K. Georg Hampel, et al.
VTC Spring 2007
Ehud Altman, Kenneth R. Brown, et al.
PRX Quantum
R.B. Morris, Y. Tsuji, et al.
International Journal for Numerical Methods in Engineering
Imran Nasim, Michael E. Henderson
Mathematics