5 citations · 5 across the 4 of their papers we have counts for
4 papers
Design Space and Variability Analysis of SOI MOSFET for Ultra-Low Power Band-to-Band Tunneling Neurons
Jay Sonawane, Shubham Patil, Abhishek Kadam +4
Large spiking neural networks (SNNs) require ultra-low power and low variability hardware for neuromorphic computing applications. Recently, a band-to-band tunneling-based (BTBT) i…
Process Voltage Temperature Variability Estimation of Tunneling Current for Band-to-Band-Tunneling based Neuron
Shubham Patil, Anand Sharma, Gaurav R +5
Compact and energy-efficient Synapse and Neurons are essential to realize the full potential of neuromorphic computing. In addition, a low variability is indeed needed for neurons…
Schottky Barrier MOSFET Enabled Ultra-Low Power Real-Time Neuron for Neuromorphic Computing
Shubham Patil, Jayatika Sakhuja, Ajay Kumar Singh +5
Energy-efficient real-time synapses and neurons are essential to enable large-scale neuromorphic computing. In this paper, we propose and demonstrate the Schottky-Barrier MOSFET-ba…
An Accurate Process Induced Variability Aware Compact Model-based Circuit Performance Estimation for Design-Technology Co-optimization
Shubham Patil, Amita Rawat, Udayan Ganguly
In sub-10nm FinFETs, Line-edge-roughness (LER) and metal-gate granularity (MGG) are the two most dominant sources of variability and are mostly modeled semi-empirically. In this wo…