On the impact of OxRAM-based synapses variability on convolutional neural networks performance

In this work, both temporal (cycle-to-cycle) and spatial (device-to-device) variability of hafnium oxide based OxRAM cells are investigated at array level. The impact of the resistance variability on OxRAM-based convolutional neural network is then evaluated. Two different types of neurons, analog a...

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Bibliographic Details
Main Authors: Garbin, D., Vianello, E., Bichler, O., Azzaz, M., Rafhay, Q., Candelier, P., Gamrat, C., Ghibaudo, G., DeSalvo, B., Perniola, L.
Format: Conference Proceeding
Language:English
Subjects:
Convolutional Neural Network
Decision support systems
Driver circuits
Nanoscale devices
Neurons
OxRAM
resistive memory
synapse
variability
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Summary:In this work, both temporal (cycle-to-cycle) and spatial (device-to-device) variability of hafnium oxide based OxRAM cells are investigated at array level. The impact of the resistance variability on OxRAM-based convolutional neural network is then evaluated. Two different types of neurons, analog and digital, are considered. Results show that the studied architecture is strongly immune to both temporal and spatial variability.
ISSN:2327-8218
2327-8226
DOI:10.1109/NANOARCH.2015.7180611