TY - GEN
T1 - Compact oscillation neuron exploiting metal-insulator-transition for neuromorphic computing
AU - Chen, Pai Yu
AU - Seo, Jae-sun
AU - Cao, Yu
AU - Yu, Shimeng
N1 - Publisher Copyright:
© 2016 ACM.
PY - 2016/11/7
Y1 - 2016/11/7
N2 - The phenomenon of metal-insulator-transition (MIT) in strongly correlated oxides, such as NbO2, have shown the oscillation behavior in recent experiments. In this work, the MIT based two-terminal device is proposed as a compact oscillation neuron for the parallel read operation from the resistive synaptic array. The weighted sum is represented by the frequency of the oscillation neuron. Compared to the complex CMOS integrate-and-fire neuron with tens of transistors, the oscillation neuron achieves significant area reduction, thereby alleviating the column pitch matching problem of the peripheral circuitry in resistive memories. Firstly, the impact of MIT device characteristics on the weighted sum accuracy is investigated when the oscillation neuron is connected to a single resistive synaptic device. Secondly, the array-level performance is explored when the oscillation neurons are connected to the resistive synaptic array. To address the interference of oscillation between columns in simple cross-point arrays, a 2-transistor-1-resistor (2T1R) array architecture is proposed at negligible increase in array area. Finally, the circuit-level benchmark of the proposed oscillation neuron with the CMOS neuron is performed. At single neuron node level, oscillation neuron shows >12.5X reduction of area. At 128×128 array level, oscillation neuron shows a reduction of ∼4% total area, >30% latency, ∼5X energy and ∼40X leakage power, demonstrating its advantage of being integrated into the resistive synaptic array for neuro-inspired computing.
AB - The phenomenon of metal-insulator-transition (MIT) in strongly correlated oxides, such as NbO2, have shown the oscillation behavior in recent experiments. In this work, the MIT based two-terminal device is proposed as a compact oscillation neuron for the parallel read operation from the resistive synaptic array. The weighted sum is represented by the frequency of the oscillation neuron. Compared to the complex CMOS integrate-and-fire neuron with tens of transistors, the oscillation neuron achieves significant area reduction, thereby alleviating the column pitch matching problem of the peripheral circuitry in resistive memories. Firstly, the impact of MIT device characteristics on the weighted sum accuracy is investigated when the oscillation neuron is connected to a single resistive synaptic device. Secondly, the array-level performance is explored when the oscillation neurons are connected to the resistive synaptic array. To address the interference of oscillation between columns in simple cross-point arrays, a 2-transistor-1-resistor (2T1R) array architecture is proposed at negligible increase in array area. Finally, the circuit-level benchmark of the proposed oscillation neuron with the CMOS neuron is performed. At single neuron node level, oscillation neuron shows >12.5X reduction of area. At 128×128 array level, oscillation neuron shows a reduction of ∼4% total area, >30% latency, ∼5X energy and ∼40X leakage power, demonstrating its advantage of being integrated into the resistive synaptic array for neuro-inspired computing.
KW - metal-insulator-transition
KW - neuromorphic computing
KW - neuron
KW - oscillation
KW - resistive memory
KW - synaptic array
UR - http://www.scopus.com/inward/record.url?scp=85001022713&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85001022713&partnerID=8YFLogxK
U2 - 10.1145/2966986.2967015
DO - 10.1145/2966986.2967015
M3 - Conference contribution
AN - SCOPUS:85001022713
T3 - IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD
BT - 2016 IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 35th IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2016
Y2 - 7 November 2016 through 10 November 2016
ER -