203 citations · 1.3k across the 57 of their papers we have counts for
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Encoding Neural and Synaptic Functionalities in Electron Spin: A Pathway to Efficient Neuromorphic Computing
Abhronil Sengupta, Kaushik Roy
Present day computers expend orders of magnitude more computational resources to perform various cognitive and perception related tasks that humans routinely perform everyday. This…
An All-Memristor Deep Spiking Neural Computing System: A Step Towards Realizing the Low Power,Stochastic Brain
Parami Wijesinghe, Aayush Ankit, Abhronil Sengupta +1
Deep 'Analog Artificial Neural Networks' (ANNs) perform complex classification problems with remarkably high accuracy. However, they rely on humongous amount of power to perform th…
Stochastic Spiking Neural Networks Enabled by Magnetic Tunnel Junctions: From Nontelegraphic to Telegraphic Switching Regimes
Chamika M. Liyanagedera, Abhronil Sengupta, Akhilesh Jaiswal +1
Stochastic spiking neural networks based on nanoelectronic spin devices can be a possible pathway to achieving "brainlike" compact and energy-effcient cognitive intelligence. The c…
TraNNsformer: Neural network transformation for memristive crossbar based neuromorphic system design
Aayush Ankit, Abhronil Sengupta, Kaushik Roy
Implementation of Neuromorphic Systems using post Complementary Metal-Oxide-Semiconductor (CMOS) technology based Memristive Crossbar Array (MCA) has emerged as a promising solutio…
Stochastic Spin-Orbit Torque Devices as Elements for Bayesian Inference
Yong Shim, Shuhan Chen, Abhronil Sengupta +1
Probabilistic inference from real-time input data is becoming increasingly popular and may be one of the potential pathways at enabling cognitive intelligence. As a matter of fact,…
RESPARC: A Reconfigurable and Energy-Efficient Architecture with Memristive Crossbars for Deep Spiking Neural Networks
Aayush Ankit, Abhronil Sengupta, Priyadarshini Panda +1
Neuromorphic computing using post-CMOS technologies is gaining immense popularity due to its promising abilities to address the memory and power bottlenecks in von-Neumann computin…