journal article·2020-09

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

Jin Joo Ryu, Kanghyeok Jeon, Guhyun Kim, Min Kyu Yang, Chunjoong Kim, Doo Seok Jeong, Gun Hwan Kim

Advanced Electronic Materials· Volume 6· Issue 9
Publisher page

Abstract

Abstract 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.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Advanced Memory and Neural Computing · Ferroelectric and Negative Capacitance Devices · Semiconductor materials and devices

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Division of Advanced Materials Korea Research Institute of Chemical Technology (KRICT) 141 Gajeong‐Ro, Yuseong‐Gu Daejeon 34114 Republic of Korea

Department of Materials Science and Engineering Chungnam National University Daejeon 34134 Republic of Korea

Division of Materials Science and Engineering Hanyang University Wansimni‐ro 222, Seongdong‐gu Seoul 04763 Republic of Korea

Intelligent Electronic Device Lab Sahmyook University 815 Hwarang‐ro, Nowon‐Gu Seoul 01795 Republic of Korea

Funding

Korea Research Institute of Chemical Technology · Ministry of Trade, Industry and Energy

References (33)

Show source-provided references
1. Krizhevsky A. · Adv. Neural Inf. Process. Syst. · 2012 · 25 · 1097
2. Taigman Y. · IEEE Conf. Comput. Vision Pattern Recogn. · 2014 · 27 · 1701
3. T.Mikolov K.Chen G.Corrado J.Dean Efficient estimation of word representation in vector space ICLR workshop arXiv:1302.37812013.
4. Collobert R. · J. Mach. Learn. Res. · 2011 · 12 · 2493
5. 10.1038/nature1423610.1038/nature14236 ↗
6. 10.1038/nature1696110.1038/nature16961 ↗
7. 10.1038/nature2427010.1038/nature24270 ↗
8. 10.1038/nature1453910.1038/nature14539 ↗
9. Hennessy J. L. · 2011
10. Gao M. · 2015 · 113
11. T.vincon A.Koch I.Petrov Moving processing to data: On the influence of processing in memory on data management arXiv:1905.047672019.
12. Devaux F. · 2019 · 1
13. Okumura S. · 2019 · C24810.23919/VLSIC.2019.8778187 ↗
14. 10.3389/fnins.2019.0138310.3389/fnins.2019.01383 ↗
15. 10.1109/TMSCS.2017.272116010.1109/TMSCS.2017.2721160 ↗
16. Imani M. · 2019 · 802
17. 10.1002/adma.20170472910.1002/adma.201704729 ↗
18. 10.1038/s41578-019-0159-310.1038/s41578-019-0159-3 ↗
19. 10.1109/JPROC.2012.219036910.1109/JPROC.2012.2190369 ↗
20. 10.1080/23746149.2016.125958510.1080/23746149.2016.1259585 ↗
21. 10.1002/admt.20190003710.1002/admt.201900037 ↗
22. Carver A. M. · Proc. IEEE · 1990 · 78 · 10
23. 10.1109/LED.2017.271916110.1109/LED.2017.2719161 ↗
24. 10.1109/TED.2016.261564810.1109/TED.2016.2615648 ↗
25. 10.1021/acsami.8b2003510.1021/acsami.8b20035 ↗
26. 10.1016/j.cplett.2004.01.08010.1016/j.cplett.2004.01.080 ↗
27. 10.1016/S0040-6090(98)00975-410.1016/S0040-6090(98)00975-4 ↗
28. 10.1016/0257-8972(95)02594-410.1016/0257-8972(95)02594-4 ↗
29. 10.1109/JPROC.2017.268483010.1109/JPROC.2017.2684830 ↗
30. 10.1063/1.335541510.1063/1.3355415 ↗
31. 10.1063/1.504043010.1063/1.5040430 ↗
32. 10.1088/1361-6528/ab348010.1088/1361-6528/ab3480 ↗
33. 10.1016/j.mser.2014.06.00210.1016/j.mser.2014.06.002 ↗