3D synaptic architecture with ultralow sub-10 fJ energy per spike for neuromorphic computation

I. Ting Wang, Yen Chuan Lin, Yu Fen Wang, Chung Wei Hsu, Tuo-Hung Hou

Research output: Contribution to journalConference articlepeer-review

32 Scopus citations

Abstract

A high-density 3D synaptic architecture based on self-rectifying Ta/TaOx/TiO2/Ti RRAM is proposed as an energy- and cost-efficient neuromorphic computation hardware. The device shows excellent analog synaptic features that can be accurately described by the physical and compact models. Ultra-low energy consumption comparable to that of a biological synapse (<10 fJ/spike) has been demonstrated for the first time.

Original languageEnglish
Article number7047127
Pages (from-to)28.5.1-28.5.4
Number of pages4
JournalTechnical Digest - International Electron Devices Meeting, IEDM
Volume2015-February
Issue numberFebruary
DOIs
StatePublished - 15 Dec 2015
Event2014 60th IEEE International Electron Devices Meeting, IEDM 2014 - San Francisco, United States
Duration: 15 Dec 201417 Dec 2014

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