16 citations · 44 across the 13 of their papers we have counts for
6 papers · 1 filter
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…
Ferroelectric MirrorBit-Integrated Field-Programmable Memory Array for TCAM, Storage, and In-Memory Computing Applications
Paritosh Meihar, Rowtu Srinu, Sandip Lashkare +6
In-memory computing on a reconfigurable architecture is the emerging field which performs an application-based resource allocation for computational efficiency and energy optimizat…
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…
Evolution of ferroelectricity with annealing temperature and thickness in sputter deposited undoped HfO on silicon
Md Hanif Ali, Adityanarayan Pandey, Rowtu Srinu +4
Ferroelectricity in sputtered undoped-HfO is attractive for composition control for low power and non-volatile memory and logic applications. Unlike doped HfO, evolution of…
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…
FeFET-based MirrorBit cell for High-density NVM storage
Paritosh Meihar, Rowtu Srinu, Vivek Saraswat +6
HfO2-based Ferroelectric field-effect transistor (FeFET) has become a center of attraction for non-volatile memory applications because of their low power, fast switching speed, hi…