TY - GEN
T1 - Design Considerations of Selector Device in Cross-Point RRAM Array for Neuromorphic Computing
AU - Woo, Jiyong
AU - Peng, Xiaochen
AU - Yu, Shimeng
N1 - Funding Information:
ACKNOWLEDGMENT This work is in part supported by NSF-CCF-1552687, NSF-CCF-1740225, and grants from Samsung.
Publisher Copyright:
© 2018 IEEE.
PY - 2018/4/26
Y1 - 2018/4/26
N2 - We investigate the impact of selector device in cross-point resistive switching memory (RRAM) array on weighted sum operation in the neural network. The requirement of selector devices in a neuromorphic system may be different than that in a conventional memory system. In this work, we developed Verilog-A device models to accurately describe current-voltage (I-V) characteristics of one-selector and one-RRAM (1S-1R) devices obtained experimentally, and then performed the array-level SPICE simulations for weighted sum operation. The weighted sum accuracy is benchmarked as a function of selector non-linearity, array size, and wire resistance. Our results reveal that linearity of the I-V curve in the 1S-1R device with respect to input vector plays an important role in precisely reading-out the weighted sum. Finally, we discuss the desired characteristics of the selector device to be used for the inference stage of the neuromorphic systems.
AB - We investigate the impact of selector device in cross-point resistive switching memory (RRAM) array on weighted sum operation in the neural network. The requirement of selector devices in a neuromorphic system may be different than that in a conventional memory system. In this work, we developed Verilog-A device models to accurately describe current-voltage (I-V) characteristics of one-selector and one-RRAM (1S-1R) devices obtained experimentally, and then performed the array-level SPICE simulations for weighted sum operation. The weighted sum accuracy is benchmarked as a function of selector non-linearity, array size, and wire resistance. Our results reveal that linearity of the I-V curve in the 1S-1R device with respect to input vector plays an important role in precisely reading-out the weighted sum. Finally, we discuss the desired characteristics of the selector device to be used for the inference stage of the neuromorphic systems.
KW - RRAM
KW - neuromorphic computing
KW - resistive switching
KW - selector
KW - weighted sum
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U2 - 10.1109/ISCAS.2018.8351735
DO - 10.1109/ISCAS.2018.8351735
M3 - Conference contribution
AN - SCOPUS:85041995025
T3 - Proceedings - IEEE International Symposium on Circuits and Systems
BT - 2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018
Y2 - 27 May 2018 through 30 May 2018
ER -