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Hugh J. Barnaby

dblp:69/3866 · DBLP profile ↗
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3ranked-venue papers
0as first author
1since 2021 · last 2022
0000-0002-8136-1849ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 2 · 1 since 2021Applied, interdisciplinary, general and emerging computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Memory systems · 44% Emerging computing paradigms · 44% Integrated circuit design · 13%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Emerging computing paradigms › neuromorphic computing
memristive devices
0.212015
Reconfigurable Memristive Device Technologies · Proc. IEEE 2015
Memory systems
non-volatile memory
0.212015
Reconfigurable Memristive Device Technologies · Proc. IEEE 2015
Integrated circuit design
3d integration
0.112015
Reconfigurable Memristive Device Technologies · Proc. IEEE 2015
YearPublicationVenuePosition
2022 Self-correcting Flip-flops for Triple Modular Redundant Logic in a 12-nm Technology
abstract
Area efficient self-correcting flip-flops for use with triple modular redundant (TMR) soft-error hardened logic are implemented in a 12-nm finFET process technology. The TMR flip-flop slave latches self-correct in the clock low phase using Muller C-elements in the latch feedback. These C-elements are driven by the two redundant stored values and not by the slave latch itself, saving area over a similar implementation using majority gate feedback. These flip-flops are implemented as large shift-register arrays on a test chip and have been experimentally tested for their soft-error mitigation in static and dynamic modes of operation using heavy ions and protons. We show how high clock skew can result in susceptibility to soft-errors in the dynamic mode, and explain the potential failure mechanism.
Lawrence T. Clark, Alen Duvnjak, Clifford Young-Sciortino, Matthew Cannon, John S. Brunhaver, Sapan Agarwal, Jereme Neuendank, Donald Wilson, Hugh J. Barnaby, Matthew J. Marinella
ISCAS9
2016 Demonstration of spike timing dependent plasticity in CBRAM devices with silicon neurons
abstract
Spike timing dependent plasticity (STDP) is an important neural process that enables biological neural networks to learn by strengthening or weakening synaptic connections between neurons. This work presents simulation results and post-silicon experimental data that demonstrate for the first time the possibility of tuning the on state resistance of a type of emerging resistive memory device known as conductive bridge random access memory (CBRAM) in accordance with the biological STDP rule for neuromorphic applications. STDP behavior is demonstrated for CBRAM devices integrated with CMOS spiking neuron circuitry through back end of line post-processing for different initial resistance values and spike durations.
Debayan Mahalanabis, M. Sivaraj, Hugh J. Barnaby, Michael N. Kozicki, Jennifer Blain Christen, Sarma B. K. Vrudhula
ISCAS5
2015 Reconfigurable Memristive Device Technologies
abstract
In this paper, we present a review of the state of the art in memristor technologies. Along with ionic conducting devices [i.e., conductive bridging random access memory (CBRAM)], we include phase change, and organic/organo-metallic technologies, and we review the most recent advances in oxide-based memristor technologies. We present progress on 3-D integration techniques, and we discuss the behavior of more mature memristive technologies in extreme environments.
Arthur H. Edwards, Hugh J. Barnaby, Kristy A. Campbell, Michael N. Kozicki, Wei Liu 0003, Matthew J. Marinella
Proc. IEEE2