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Displaying 26 - 40 of 40

Streaming Batch Gradient Tracking for Neural Network Training

April 3, 2020
Author(s)
Siyuan Huang, Brian D. Hoskins, Matthew W. Daniels, Mark D. Stiles, Gina C. Adam
Faster and more energy efficient hardware accelerators are critical for machine learning on very large datasets. The energy cost of performing vector-matrix multiplication and repeatedly moving neural network models in and out of memory motivates a search

Nanoscale mapping of the double layer potential at the graphene-electrolyte interface

January 28, 2020
Author(s)
Evgheni Strelcov, Christopher M. Arble, Hongxuan Guo, Brian D. Hoskins, Alexander Yulaev, Ivan Vlassiouk, Nikolai B. Zhitenev, Alexander Tselev, Andrei A. Kolmakov
The structure and potential drop across the electrical double layer (EDL) govern the operation of multiple electrochemical devices, determine reaction potentials and condition ion transport through the cellular membranes in living organisms. Despite more

Streaming Batch Eigenupdates for Hardware Neural Networks

August 6, 2019
Author(s)
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

Spontaneous current constriction in threshold switching devices

April 9, 2019
Author(s)
Jonathan Goodwill, Georg Ramer, Dasheng Li, Brian Hoskins, Georges Pavlidis, Jabez J. McClelland, Andrea Centrone, James A. Bain, Marek Skowronski
Threshold switching devices exhibit extremely non-linear current-voltage characteristics, which are of increasing importance for a number of applications including solid-state memories and neuromorphic circuits. It has been proposed that such non-linear

Scalable method to find the shortest path in a graph with circuits of memristors

December 14, 2018
Author(s)
Alice Mizrahi, thomas Marsh, Brian D. Hoskins, Mark D. Stiles
Finding the shortest path in a graph has applications to a wide range of optimization problems. However, algorithmic methods scale with the size of the graph in terms of time and energy. We propose a method to solve the shortest path problem using circuits

In aqua electrochemistry probed by XPEEM: experimental setup, examples, and challenges

November 10, 2018
Author(s)
Slavomir Nemsak, Evgheni Strelcov, Hongxuan Guo, Brian Hoskins, Tomas Duchon, D Muller, Alexander Yulaev, Ivan Vlassiouk, Alexander Tselev, Andrei Kolmakov
Recent developments in environmental and liquid cells equipped with electron transparent graphene windows have enabled traditional surface science spectromicroscopy tools, such as XPS, PEEM, and SEM to be applied to study solid-liquid and liquid-gas

Research Update: Electron beam-based metrology after CMOS

July 19, 2018
Author(s)
James A. Liddle, Brian D. Hoskins, Andras Vladar, John S. Villarrubia
The strengths of and challenges facing electron-based metrology for post-CMOS technology are reviewed. Directed self-assembly, nanophotonics/plasmonics, and resistive switches and selectors, are examined as exemplars of important post-CMOS technologies

Stateful characterization of resistive switching TiO2 with electron beam induced currents

December 7, 2017
Author(s)
Brian D. Hoskins, Gina C. Adam, Evgheni Strelcov, Nikolai B. Zhitenev, Andrei A. Kolmakov, Dmitri B. Strukov, Jabez J. McClelland
Metal oxide resistive switches have become increasingly important as possible artificial synapses in next generation neuromorphic networks. Nevertheless, there is still no codified set of tools for studying fundamental properties of the devices. To this