TY - GEN
T1 - A neuromorphic visual system using RRAM synaptic devices with Sub-pJ energy and tolerance to variability
T2 - 2012 IEEE International Electron Devices Meeting, IEDM 2012
AU - Yu, Shimeng
AU - Gao, Bin
AU - Fang, Zheng
AU - Yu, Hongyu
AU - Kang, Jinfeng
AU - Wong, H. S.Philip
PY - 2012
Y1 - 2012
N2 - We report the use of metal oxide resistive switching memory (RRAM) as synaptic devices for a neuromorphic visual system. At the device level, we experimentally characterized the gradual resistance modulation of RRAM by hundreds of identical pulses. As compared with phase change memory (PCM) reported recently in [1,2], >100×-1000× energy consumption reduction was achieved in RRAM as synaptic devices (<1 pJ per spike). Based on the experimental results, we developed a stochastic model to quantify the device switching dynamics. At the system level, we simulated the performance of image orientation selectivity on a neuromorphic visual system which consists of 1,024 CMOS neuron circuits and 16,348 RRAM synaptic devices. It was found that the system can tolerate the temporal and spatial variability which are commonly present in RRAM devices, suggesting the feasibility of large-scale hardware implementation of neuromorphic system using RRAM synaptic devices.
AB - We report the use of metal oxide resistive switching memory (RRAM) as synaptic devices for a neuromorphic visual system. At the device level, we experimentally characterized the gradual resistance modulation of RRAM by hundreds of identical pulses. As compared with phase change memory (PCM) reported recently in [1,2], >100×-1000× energy consumption reduction was achieved in RRAM as synaptic devices (<1 pJ per spike). Based on the experimental results, we developed a stochastic model to quantify the device switching dynamics. At the system level, we simulated the performance of image orientation selectivity on a neuromorphic visual system which consists of 1,024 CMOS neuron circuits and 16,348 RRAM synaptic devices. It was found that the system can tolerate the temporal and spatial variability which are commonly present in RRAM devices, suggesting the feasibility of large-scale hardware implementation of neuromorphic system using RRAM synaptic devices.
UR - http://www.scopus.com/inward/record.url?scp=84876153660&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84876153660&partnerID=8YFLogxK
U2 - 10.1109/IEDM.2012.6479018
DO - 10.1109/IEDM.2012.6479018
M3 - Conference contribution
AN - SCOPUS:84876153660
SN - 9781467348706
T3 - Technical Digest - International Electron Devices Meeting, IEDM
SP - 10.4.1-10.4.4
BT - 2012 IEEE International Electron Devices Meeting, IEDM 2012
Y2 - 10 December 2012 through 13 December 2012
ER -