John Niroula

Multiscale Co-Design Analysis of Energy, Latency, Area, and Accuracy of a ReRAM Analog Neural Training Accelerator

Neural networks are an increasingly attractive algorithm for natural language processing and pattern recognition. Deep networks with >50M parameters are made possible by modern GPU clusters...

Using Floating Gate Memory to Train Ideal Accuracy Neural Networks

Floating gate SONOS (Silicon-Oxygen-Nitrogen-Oxygen-Silicon) transistors can be used to train neural networks to ideal accuracies that match those of floating point digital weights on the MNIST...

Towards DTCO in High Temperature GaN-on-Si Technology: Arithmetic Logic Unit at 300 °C and CAD Framework up to 500 °C

Impact of Linearity and Write Noise of Analog Resistive Memory Devices in a Neural Algorithm Accelerator

First Demonstration of GaN Vertical Power FinFETs on Engineered Substrate

First Demonstration of GaN RF HEMTs on Engineered Substrate

Materials and Technology Issues for the Next Generation of Power Electronic Devices

Record High Temperature Performance in Scaled AlGaN/GaN-on-Si HEMTs up to 500°C