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Search Publications by

Advait Madhavan (Assoc)

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Displaying 1 - 12 of 12

Implementation of a Binary Neural Network on a Passive Array of Magnetic Tunnel Junctions

July 18, 2022
Jonathan Goodwill, Nitin Prasad, Brian Hoskins, Matthew Daniels, Advait Madhavan, Lei Wan, Tiffany Santos, Michael Tran, Jordan Katine, Patrick Braganca, Mark Stiles, Jabez J. McClelland
The increasing scale of neural networks and their growing application space have produced a demand for more energy and memory efficient artificial-intelligence-specific hardware. Avenues to mitigate the main issue, the von Neumann bottleneck, include in

Mutual control of stochastic switching for two electrically coupled superparamagnetic tunnel junctions

August 19, 2021
Philippe Talatchian, Matthew Daniels, Advait Madhavan, Matthew Pufall, Emilie Jue, William Rippard, Jabez J. McClelland, Mark Stiles
Superparamagnetic tunnel junctions (SMTJs) are promising sources for the randomness required by some compact and energy-efficient computing schemes. Coupling them gives rise to collective behavior that could be useful for cognitive computing. We use a

Impact ionization-induced bistability in CMOS transistors at cryogenic temperatures for capacitorless memory applications

July 29, 2021
Alexander Zaslavsky, Curt A. Richter, Pragya Shrestha, Brian Hoskins, Son Le, Advait Madhavan, Jabez J. McClelland
Cryogenic operation of complementary metal oxide semiconductor (CMOS) silicon transistors is crucial for quantum information science, but it brings deviations from standard transistor operation. Here we report on sharp current jumps and stable hysteretic

A System for Validating Resistive Neural Network Prototypes

July 27, 2021
Brian Hoskins, Mitchell Fream, Matthew Daniels, Jonathan Goodwill, Advait Madhavan, Jabez J. McClelland, Osama Yousuf, Gina C. Adam, Wen Ma, Muqing Liu, Rasmus Madsen, Martin Lueker-Boden
Building prototypes of heterogeneous hardware systems based on emerging electronic, magnetic, and photonic devices is an increasingly important area of research. On the face of it, the novel implementation of these systems, especially for online learning

Temporal Memory with Magnetic Racetracks

December 1, 2020
Hamed Vakili, Mohammed N. Sakib, Samiran Ganguly, Mircea Stan, Matthew Daniels, Advait Madhavan, Mark D. Stiles, Avik W. Ghosh
Race logic is a relative timing code that represents information in a wavefront of digital edges on a set of wires in order to accelerate dynamic programming and machine learning algorithms. Skyrmions, bubbles, and domain walls are mobile magnetic

Storing and retrieving wavefronts with resistive temporal memory

October 10, 2020
Advait Madhavan, Mark D. Stiles
We extend the reach of temporal computing schemes by developing a memory for multi-channel temporal patterns or "wavefronts." This temporal memory re-purposes conventional one-transistor-one-resistor (1T1R) memristor crossbars for use in an arrival-time

Energy-efficient stochastic computing with superparamagnetic tunnel junctions

March 5, 2020
Matthew W. Daniels, Advait Madhavan, Philippe Talatchian, Alice Mizrahi, Mark D. Stiles
Stochastic computing has been limited by the inaccuracies introduced by correlations between the pseudorandom bitstreams used in the calculation. We hybridize a stochastic version of magnetic tunnel junctions with basic CMOS logic gates to create a

Streaming Batch Eigenupdates for Hardware Neural Networks

August 6, 2019
Brian D. Hoskins, Matthew W. Daniels, Siyuan Huang, Advait Madhavan, Gina C. Adam, Nikolai B. Zhitenev, Jabez J. McClelland, Mark D. Stiles
Neuromorphic networks based on nanodevices, such as metal oxide memristors, phase change memories, and flash memory cells, have generated considerable interest for their increased energy efficiency and density in comparison to graphics processing units

A Truth-Matrix View into Unary Computing

June 22, 2019
Advait Madhavan, Georgios Tzimpragos, Mark D. Stiles, Timothy Sherwood
Our community has been exploring Time-of-arrival based codes as a candidate for very low energy information processing. A ``space-time'' algebra has been recently proposed that captures the essential features of such a paradigm. In order to gain some