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Conference papers
Emerging resistive memories for low power embedded applications and neuromorphic systems
Abstract : In this work, we will focus on the role that new nonvolatile resistive memory technologies can play in emerging fields of application, such as non-volatile logic circuits or neuromorphic circuits, to save energy and increase performance. Concerning the introduction of non-volatile functionalities at the logic level, we will demonstrate hybrid CMOS logic plus ReRAM (specifically CBRAM and OXRAM) circuits for ultra low power FPGA and fixed-logic IC design, as Non Volatile Flip-Flops. Concerning neuromorphic circuits, we will focus on the emulation of synaptic plasticity effects with resistive memory synapses. We will present large-scale energy efficient neuromorphic systems based on ReRAM as stochastic-binary synapses. Prototype applications such as complex visual- and auditory-pattern extraction will be also discussed using feedforward spiking neural networks.
Keywords :
Complex networks
Embedded systems
Energy efficiency
Feedforward neural networks
Field programmable gate arrays (FPGA)
Flip flop circuits
Low power electronics
Neural networks
Random access storage
Stochastic systems
artificial synapses
Embedded application
Neuromorphic circuits
Neuromorphic systems
Non-volatile flip-flops
ReRAM
Spiking neural networks
Synaptic plasticity
Logic circuits
https://hal-cea.archives-ouvertes.fr/cea-01817863
Contributor : Léna Le Roy Connect in order to contact the contributor
Submitted on : Monday, June 18, 2018 - 2:28:58 PM
Last modification on : Thursday, February 17, 2022 - 10:08:06 AM
Contributor : Léna Le Roy Connect in order to contact the contributor
Submitted on : Monday, June 18, 2018 - 2:28:58 PM
Last modification on : Thursday, February 17, 2022 - 10:08:06 AM