TY - GEN
T1 - Modeling a Floating-Gate Memristive Device for Computer Aided Design of Neuromorphic Computing
AU - Danial, L.
AU - Gupta, V.
AU - Pikhay, E.
AU - Roizin, Y.
AU - Kvatinsky, S.
N1 - Publisher Copyright:
© 2020 EDAA.
PY - 2020/3
Y1 - 2020/3
N2 - Memristive technology is still not mature enough for the very large-scale integration necessary to obtain practical value from neuromorphic computing. While nonvolatile floating-gate synapse transistors have been implemented in very large-scale integrated neuromorphic systems, their large footprint still constrains an upper bound on the overall performance. A two-terminal floating-gate memristive device can combine the technological maturity of the floating-gate transistor and the conceptual novelty of the memristor using a standard CMOS process. In this paper, we present a top-down computer aided design framework of the floating-gate memristive device and show its potential in neuromorphic computing. Our framework includes a Verilog-A model, small-signal schematics, a stochastic model, Monte-Carlo simulations, layout, DRC, LVS, and RC extraction.
AB - Memristive technology is still not mature enough for the very large-scale integration necessary to obtain practical value from neuromorphic computing. While nonvolatile floating-gate synapse transistors have been implemented in very large-scale integrated neuromorphic systems, their large footprint still constrains an upper bound on the overall performance. A two-terminal floating-gate memristive device can combine the technological maturity of the floating-gate transistor and the conceptual novelty of the memristor using a standard CMOS process. In this paper, we present a top-down computer aided design framework of the floating-gate memristive device and show its potential in neuromorphic computing. Our framework includes a Verilog-A model, small-signal schematics, a stochastic model, Monte-Carlo simulations, layout, DRC, LVS, and RC extraction.
KW - CAD
KW - Floating-gate
KW - VLSI
KW - artificial neural networks
KW - device modeling
KW - flash memory
KW - memristors
KW - neuromorphic computing
UR - http://www.scopus.com/inward/record.url?scp=85087382380&partnerID=8YFLogxK
U2 - 10.23919/DATE48585.2020.9116354
DO - 10.23919/DATE48585.2020.9116354
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AN - SCOPUS:85087382380
T3 - Proceedings of the 2020 Design, Automation and Test in Europe Conference and Exhibition, DATE 2020
SP - 472
EP - 477
BT - Proceedings of the 2020 Design, Automation and Test in Europe Conference and Exhibition, DATE 2020
A2 - Di Natale, Giorgio
A2 - Bolchini, Cristiana
A2 - Vatajelu, Elena-Ioana
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 Design, Automation and Test in Europe Conference and Exhibition, DATE 2020
Y2 - 9 March 2020 through 13 March 2020
ER -