Variance-aware weight quantization of multi-level resistive switching devices based on Pt/LaAlO3/SrTiO3 heterostructures

Lee, Sunwoo; Jeon, Jaeyoung; Eom, Kitae; Jeong, Chaehwa; Yang, Yongsoo; Park, Ji-Yong; Eom, Chang-Beom; Lee, Hyungwoo

doi:10.1038/s41598-022-13121-4

Title: Variance-aware weight quantization of multi-level resistive switching devices based on Pt/LaAlO3/SrTiO3 heterostructures

Journal Article · Tue May 31 00:00:00 EDT 2022 · Scientific Reports

DOI:https://doi.org/10.1038/s41598-022-13121-4· OSTI ID:1870550

Lee, Sunwoo; Jeon, Jaeyoung; Eom, Kitae; Jeong, Chaehwa; Yang, Yongsoo; Park, Ji-Yong; Eom, Chang-Beom; Lee, Hyungwoo

Abstract Resistive switching devices have been regarded as a promising candidate of multi-bit memristors for synaptic applications. The key functionality of the memristors is to realize multiple non-volatile conductance states with high precision. However, the variation of device conductance inevitably causes the state-overlap issue, limiting the number of available states. The insufficient number of states and the resultant inaccurate weight quantization are bottlenecks in developing practical memristors. Herein, we demonstrate a resistive switching device based on Pt/LaAlO ₃ /SrTiO ₃ (Pt/LAO/STO) heterostructures, which is suitable for multi-level memristive applications. By redistributing the surface oxygen vacancies, we precisely control the tunneling of two-dimensional electron gas (2DEG) through the ultrathin LAO barrier, achieving multiple and tunable conductance states (over 27) in a non-volatile way. To further improve the multi-level switching performance, we propose a variance-aware weight quantization (VAQ) method. Our simulation studies verify that the VAQ effectively reduces the state-overlap issue of the resistive switching device. We also find that the VAQ states can better represent the normal-like data distribution and, thus, significantly improve the computing accuracy of the device. Our results provide valuable insight into developing high-precision multi-bit memristors based on complex oxide heterostructures for neuromorphic applications.

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Research Organization:: Univ. of Wisconsin, Madison, WI (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Basic Energy Sciences (BES); National Research Foundation of Korea (NRF); Gordon and Betty Moore Foundation; Vannevar Bush Faculty Fellowship; US Department of the Navy, Office of Naval Research (ONR)

Grant/Contract Number:: FG02-06ER46327; 2021R1C1C1011219; 2021R1A4A1032085; GBMF9065; N00014-20-1-2844; 2019R1A2C1007913; 2020R1C1C100623911

OSTI ID:: 1870550

Alternate ID(s):: OSTI ID: 1904645

Journal Information:: Scientific Reports, Journal Name: Scientific Reports Vol. 12 Journal Issue: 1; ISSN 2045-2322

Publisher:: Nature Publishing GroupCopyright Statement

Country of Publication:: United Kingdom

Language:: English

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