Novel synaptic memory device for neuromorphic computing

Saptarshi Mandal, Ammaarah El-Amin, Kaitlyn Alexander, Bipin Rajendran, Rashmi Jha

Research output: Contribution to journalArticlepeer-review

70 Scopus citations

Abstract

This report discusses the electrical characteristics of two-terminal synaptic memory devices capable of demonstrating an analog change in conductance in response to the varying amplitude and pulse-width of the applied signal. The devices are based on Mn doped HfO2 material. The mechanism behind reconfiguration was studied and a unified model is presented to explain the underlying device physics. The model was then utilized to show the application of these devices in speech recognition. A comparison between a 20 nm × 20 nm sized synaptic memory device with that of a state-of-the-art VLSI SRAM synapse showed ∼ 10 × reduction in area and >106 times reduction in the power consumption per learning cycle.

Original languageEnglish (US)
Article number5333
JournalScientific reports
Volume4
DOIs
StatePublished - Jun 18 2014
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • General

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