Highly Linear and Symmetric Weight Modification in HfO2‐Based Memristive Devices for High‐Precision Weight Entries

In this study, highly reliable and accurate weight‐modification behaviors are realized using a W/Al2O3 (3 nm)/HfO2 (7 nm)/TiN memristive device. The accuracy of the simulated inference of the MNIST dataset when considering the weight‐modification behavior is ≈95%. It is determined the optimal progra...

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Bibliographic Details
Published in:Advanced electronic materials Vol. 6; no. 9
Main Authors: Ryu, Jin Joo, Jeon, Kanghyeok, Kim, Guhyun, Yang, Min Kyu, Kim, Chunjoong, Jeong, Doo Seok, Kim, Gun Hwan
Format: Journal Article
Language:English
Published: 01-09-2020
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Summary:In this study, highly reliable and accurate weight‐modification behaviors are realized using a W/Al2O3 (3 nm)/HfO2 (7 nm)/TiN memristive device. The accuracy of the simulated inference of the MNIST dataset when considering the weight‐modification behavior is ≈95%. It is determined the optimal programming voltage pulsing conditions considering i) a high linearity in the weight‐modification, ii) symmetry between potentiation and depression, and iii) an alleviation of the voltage‐driving circuit overhead for the related part of weight‐modification process. Particular emphasis is placed on the last concern, and thus, the fixed shape of each programming pulse for both potentiation and depression are utilized. The optimal pulse design is 500 µs for the pulse rising, plateau, and falling times and a 2 V amplitude at the absolute scale. Additionally, the nonparametric method to evaluate the linearity and symmetry as opposed to the application of several parametric methods are proposed. The nonparametric method is based on an evaluation of actual data rather than models, and thus considers the actual variability in the conductance change, which is otherwise often ignored in the parameter optimization process. Highly linear and symmetric weight‐modification is realized in a HfO2‐based simple resistive switching device for in‐memory processing application. The obtained device shows an inference accuracy of 95% using hand‐written numbers in simulation. A nonparametric method for evaluating weight‐modification behavior is proposed, which demonstrates that this device exhibits highly optimum characteristic compared to previous reports.
ISSN:2199-160X
2199-160X
DOI:10.1002/aelm.202000434