CMOS-Compatible Embedded Artificial Synaptic Device (eASD) for Neuromorphic Computing and AI Applications

The research showcases innovative embedded artificial synaptic devices (eASDs) implemented in a CMOS logic platform. These eASD devices demonstrate a large sensing window, exceptional endurance, and reliable data retention. Moreover, they can seamlessly integrate into neural network (NN) circuits, e...

Full description

Saved in:
Bibliographic Details
Published inIEEE transactions on electron devices Vol. 71; no. 2; pp. 1 - 7
Main Authors Huang, Yao-Hung, Yu, Hsin-Yuan, Chih, Yue-Der, Wang, Yih, King, Ya-Chin, Lin, Chrong Jung
Format Journal Article
LanguageEnglish
Published New York IEEE 01.02.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Artificial intelligence
Artificial neural networks
CMOS
computing-in-memory
embedded memory
high-k metal gate (HKMG)
Logic gates
Memristors
neural network (NN)
Neural networks
neuromorphic
Reliability
resistive random access memory (RRAM)
Switches
Synapses
Transistors
Online AccessGet full text

Cover

Abstract The research showcases innovative embedded artificial synaptic devices (eASDs) implemented in a CMOS logic platform. These eASD devices demonstrate a large sensing window, exceptional endurance, and reliable data retention. Moreover, they can seamlessly integrate into neural network (NN) circuits, effectively functioning as synapses with adjustable synaptic weights, making them highly valuable for artificial intelligence (AI) applications.
AbstractList The research showcases innovative embedded artificial synaptic devices (eASDs) implemented in a CMOS logic platform. These eASD devices demonstrate a large sensing window, exceptional endurance, and reliable data retention. Moreover, they can seamlessly integrate into neural network (NN) circuits, effectively functioning as synapses with adjustable synaptic weights, making them highly valuable for artificial intelligence (AI) applications.
Author King, Ya-Chin
Wang, Yih
Lin, Chrong Jung
Chih, Yue-Der
Yu, Hsin-Yuan
Huang, Yao-Hung
Author_xml – sequence: 1
  givenname: Yao-Hung
  orcidid: 0000-0002-4146-7403
  surname: Huang
  fullname: Huang, Yao-Hung
  organization: Institute of Electronics Engineering, Hsinchu, Taiwan
– sequence: 2
  givenname: Hsin-Yuan
  surname: Yu
  fullname: Yu, Hsin-Yuan
  organization: Institute of Electronics Engineering, Hsinchu, Taiwan
– sequence: 3
  givenname: Yue-Der
  surname: Chih
  fullname: Chih, Yue-Der
  organization: Design Technology Platform (DTP), Taiwan Semiconductor Manufacturing Company (TSMC), Hsinchu, Taiwan
– sequence: 4
  givenname: Yih
  surname: Wang
  fullname: Wang, Yih
  organization: Design Technology Platform (DTP), Taiwan Semiconductor Manufacturing Company (TSMC), Hsinchu, Taiwan
– sequence: 5
  givenname: Ya-Chin
  orcidid: 0000-0003-4065-0350
  surname: King
  fullname: King, Ya-Chin
  organization: Institute of Electronics Engineering, Hsinchu, Taiwan
– sequence: 6
  givenname: Chrong Jung
  surname: Lin
  fullname: Lin, Chrong Jung
  organization: Institute of Electronics Engineering, Hsinchu, Taiwan
BookMark eNpNkD1PwzAURS0EEm1hZ2CwxAJDir_i2GOUFqhU6NAyR4ntgKskDk6C1H-Pq3Zgenp6954nnSm4bF1rALjDaI4xks-75WJOEKFzShkXcXIBJjiOk0hyxi_BBCEsIkkFvQbTvt-HlTNGJsBm75ttlLmmKwZb1gYum9JobTRM_WArq2xRw-2hLbrBKrgwv1YZ-GjS7eIJVs7DDzN61zjffYfzETMOtv2CRRsAK5h2XW1VILu2vwFXVVH35vY8Z-DzZbnL3qL15nWVpetIEUmGKPyOVaywVExzTHVZsiouGeKUE60VFYoLplGiS54wrSTXshQcCc1KQ5Wu6Aw8nLiddz-j6Yd870bfhpc5kVggEnPBQwqdUsq7vvemyjtvm8Ifcozyo9A8CM2PQvOz0FC5P1WsMeZfnCYyZoL-Af5Bc40
CODEN IETDAI
CitedBy_id crossref_primary_10_1016_j_chaos_2024_114860
Cites_doi 10.1109/IMW.2019.8739698
10.23919/VLSITechnologyandCir57934.2023.10185230
10.1109/TVLSI.2017.2776954
10.1109/TPAMI.2023.3282631
10.1109/ASPDAC.2017.7858419
10.1145/359576.359579
10.1109/VLSI-TSA54299.2022.9771034
10.1109/NANOARCH.2017.8053731
10.1186/s11671-020-03299-9
10.1109/IEDM.2013.6724693
10.1109/EDSSC.2017.8126414
10.1038/s41565-020-0655-z
10.1016/j.heliyon.2018.e00938
10.1109/MSSC.2019.2922889
10.1111/0885-9507.00219
10.1109/JEDS.2020.2987402
10.1109/MWSCAS.2017.8053199
10.1038/s41586-022-04992-8
10.3390/nano10081437
10.1109/MWSCAS48704.2020.9184484
10.1109/MWSCAS.1997.666107
10.3390/brainsci12070863
10.1109/VLSIT.2016.7573431
10.1109/MWSCAS.2015.7282128
10.1016/j.lindif.2023.102274
10.1515/ntrev-2018-0045
10.1109/JPROC.2012.2190369
10.1109/72.701181
10.1007/978-3-642-57760-4
ContentType Journal Article
Copyright Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2024
Copyright_xml – notice: Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2024
DBID 97E
RIA
RIE
AAYXX
CITATION
7SP
8FD
L7M
DOI 10.1109/TED.2023.3346857
DatabaseName IEEE All-Society Periodicals Package (ASPP) 2005-present
IEEE All-Society Periodicals Package (ASPP) 1998–Present
IEEE
CrossRef
Electronics & Communications Abstracts
Technology Research Database
Advanced Technologies Database with Aerospace
DatabaseTitle CrossRef
Technology Research Database
Advanced Technologies Database with Aerospace
Electronics & Communications Abstracts
DatabaseTitleList
Technology Research Database
Database_xml – sequence: 1
  dbid: RIE
  name: IEEE
  url: https://proxy.k.utb.cz/login?url=https://ieeexplore.ieee.org/
  sourceTypes: Publisher
DeliveryMethod fulltext_linktorsrc
Discipline Engineering
EISSN 1557-9646
EndPage 7
ExternalDocumentID 10_1109_TED_2023_3346857
10379548
Genre orig-research
GrantInformation_xml – fundername: Taiwan Semiconductor Manufacturing Company (TSMC)
  funderid: 10.13039/501100004368
– fundername: National Science and Technology Council (NSTC), Taiwan
GroupedDBID -~X
.DC
0R~
29I
4.4
5GY
6IK
97E
AAJGR
AASAJ
ABQJQ
ABVLG
ACGFO
ACGFS
ACIWK
ACNCT
AENEX
AKJIK
ALMA_UNASSIGNED_HOLDINGS
ASUFR
ATWAV
B-7
BEFXN
BFFAM
BGNUA
BKEBE
BPEOZ
CS3
DU5
EBS
F5P
HZ~
IFIPE
IPLJI
JAVBF
LAI
M43
MS~
O9-
OCL
P2P
RIA
RIE
RIG
RNS
TAE
TN5
3EH
5VS
AAYXX
ACKIV
AETIX
AI.
AIBXA
ALLEH
CITATION
EJD
H~9
IAAWW
IBMZZ
ICLAB
IDIHD
IFJZH
VH1
VJK
VOH
7SP
8FD
L7M
ID FETCH-LOGICAL-c292t-dde5c5c19c4d613dbb4f5b406362ddc38c684d07db674dc96d9b8608d4be3cdf3
IEDL.DBID RIE
ISSN 0018-9383
IngestDate Thu Oct 10 19:13:09 EDT 2024
Fri Aug 23 03:55:03 EDT 2024
Wed Jun 26 19:24:17 EDT 2024
IsPeerReviewed true
IsScholarly true
Issue 2
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c292t-dde5c5c19c4d613dbb4f5b406362ddc38c684d07db674dc96d9b8608d4be3cdf3
ORCID 0000-0003-4065-0350
0000-0002-4146-7403
PQID 2918025686
PQPubID 85466
PageCount 7
ParticipantIDs crossref_primary_10_1109_TED_2023_3346857
ieee_primary_10379548
proquest_journals_2918025686
PublicationCentury 2000
PublicationDate 2024-02-01
PublicationDateYYYYMMDD 2024-02-01
PublicationDate_xml – month: 02
  year: 2024
  text: 2024-02-01
  day: 01
PublicationDecade 2020
PublicationPlace New York
PublicationPlace_xml – name: New York
PublicationTitle IEEE transactions on electron devices
PublicationTitleAbbrev TED
PublicationYear 2024
Publisher IEEE
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher_xml – name: IEEE
– name: The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
References ref13
ref12
ref14
Pan (ref31)
ref30
ref33
ref10
ref32
ref2
ref1
Chen (ref18) 2021
ref16
ref19
Müller (ref11) 1995
ref24
ref23
ref26
ref25
ref20
ref22
ref21
ref28
ref27
Duta (ref15) 2021
ref29
ref8
ref7
Brants (ref17)
ref9
ref4
ref3
ref6
ref5
References_xml – ident: ref21
  doi: 10.1109/IMW.2019.8739698
– ident: ref27
  doi: 10.23919/VLSITechnologyandCir57934.2023.10185230
– ident: ref6
  doi: 10.1109/TVLSI.2017.2776954
– year: 2021
  ident: ref15
  article-title: Pyramidal Convolution: Rethinking convolutional neural networks for visual recognition
  publication-title: arXiv:2006.11538
  contributor:
    fullname: Duta
– ident: ref16
  doi: 10.1109/TPAMI.2023.3282631
– ident: ref33
  doi: 10.1109/ASPDAC.2017.7858419
– ident: ref4
  doi: 10.1145/359576.359579
– ident: ref30
  doi: 10.1109/VLSI-TSA54299.2022.9771034
– ident: ref32
  doi: 10.1109/NANOARCH.2017.8053731
– ident: ref2
  doi: 10.1186/s11671-020-03299-9
– ident: ref25
  doi: 10.1109/IEDM.2013.6724693
– ident: ref24
  doi: 10.1109/EDSSC.2017.8126414
– ident: ref8
  doi: 10.1038/s41565-020-0655-z
– ident: ref12
  doi: 10.1016/j.heliyon.2018.e00938
– ident: ref7
  doi: 10.1109/MSSC.2019.2922889
– ident: ref10
  doi: 10.1111/0885-9507.00219
– ident: ref5
  doi: 10.1109/JEDS.2020.2987402
– ident: ref22
  doi: 10.1109/MWSCAS.2017.8053199
– ident: ref9
  doi: 10.1038/s41586-022-04992-8
– ident: ref3
  doi: 10.3390/nano10081437
– ident: ref28
  doi: 10.1109/MWSCAS48704.2020.9184484
– start-page: 10.5.1
  volume-title: IEDM Tech. Dig.
  ident: ref31
  article-title: 1Kbit FinFET dielectric (FIND) RRAM in pure 16 nm FinFET CMOS logic process
  contributor:
    fullname: Pan
– ident: ref20
  doi: 10.1109/MWSCAS.1997.666107
– ident: ref13
  doi: 10.3390/brainsci12070863
– ident: ref26
  doi: 10.1109/VLSIT.2016.7573431
– ident: ref23
  doi: 10.1109/MWSCAS.2015.7282128
– ident: ref19
  doi: 10.1016/j.lindif.2023.102274
– year: 2021
  ident: ref18
  article-title: Evaluating large language models trained on code
  publication-title: arXiv:2107.03374
  contributor:
    fullname: Chen
– ident: ref29
  doi: 10.1515/ntrev-2018-0045
– ident: ref1
  doi: 10.1109/JPROC.2012.2190369
– start-page: 858
  volume-title: Proc. Joint Conf. Empirical Methods Natural Lang. Process. Comput. Natural Lang. Learn. (EMNLP-CoNLL)
  ident: ref17
  article-title: Large language models in machine translation
  contributor:
    fullname: Brants
– ident: ref14
  doi: 10.1109/72.701181
– volume-title: Neural Networks: An Introduction
  year: 1995
  ident: ref11
  doi: 10.1007/978-3-642-57760-4
  contributor:
    fullname: Müller
SSID ssj0016442
Score 2.4788356
Snippet The research showcases innovative embedded artificial synaptic devices (eASDs) implemented in a CMOS logic platform. These eASD devices demonstrate a large...
SourceID proquest
crossref
ieee
SourceType Aggregation Database
Publisher
StartPage 1
SubjectTerms Artificial intelligence
Artificial neural networks
CMOS
computing-in-memory
embedded memory
high-k metal gate (HKMG)
Logic gates
Memristors
neural network (NN)
Neural networks
neuromorphic
Reliability
resistive random access memory (RRAM)
Switches
Synapses
Transistors
Title CMOS-Compatible Embedded Artificial Synaptic Device (eASD) for Neuromorphic Computing and AI Applications
URI https://ieeexplore.ieee.org/document/10379548
https://www.proquest.com/docview/2918025686
Volume 71
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV07T8MwELYoEwy8EeUlDwx0SEgax7HHqg8VJGAoSGxRfHakCpoiSAf49ZztFFUgJDZLiR3LZ993zt19R8hFKUoAXUBQQgwBInQZSGA6iE0KrNAMjWCbjXx7x8eP7OYpfWqS1V0ujDHGBZ-Z0DadL1_PYWF_lV3ZnDZLUNYirUxKn6z17TJAYPfU4DGeYLx3LX2SkbxCHRDaMuFhkjAuLBKtYJArqvJLEzt4GW2Tu-XEfFTJc7ioVQifPzgb_z3zHbLVGJq053fGLlkz1R7ZXKEf3CfT_u39JHAaoZ6qF0OHM2VQEWnXy1NL0MlHVaBaATowVqnQS9ObDDoUbV3qiD1mc5QUPvblIXBcWlQ4wDXtrbjGD8jjaPjQHwdN6YUAurJbB_itFFKIrdwQ8LVSrEwVgj_indaQCOCC6SjTimdMg-RaKsEjoZkyCegyOSTr1bwyR4R2uRKQKsUhzZjkSkaFRpuTYYOJuIA26SyFkb96ho3c3UwimaPgciu4vBFcmxzYtV15zy9rm5wuxZc3Z_A970rLbpdywY__6HZCNnB05oOwT8l6_bYwZ2hj1Orc7a0vuSDOrA
link.rule.ids 315,783,787,799,27937,27938,55087
linkProvider IEEE
linkToHtml http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV3PT9swFH7a2GHjAGNjolA2HziMQ0LSOK59rICqDFoOBYlbFD87UsVIEaQH-Ot5tlNUDU3iZinxD_nZ73v28_sewEElK0RTYlRhihEhdBUp5CZKbY68NJyMYBeNPJ6I0TX_c5PftMHqPhbGWusfn9nYFb0v38xx4a7KjlxMmyMo-wifyLCW_RCu9eo0IGgP5OAp7WE6eS29kok6Ii0Qu0ThcZZxIR0WraCQT6vyRhd7gBluwmQ5tPCu5DZeNDrG539YG9899q-w0ZqabBDWxhZ8sPU3WF8hIPwOs-Px5TTyOqGZ6b-Wnd5pS6rI-FqBXIJNn-qSFAuyE-vUCvttB9OTQ0bWLvPUHndzkhV9DgkiqF1W1tTAGRusOMe34Xp4enU8itrkCxH2VK-JqK8cc0yd5Ajyjda8yjXBPyGeMZhJFJKbpG-06HODShilpUik4dpmaKrsB6zV89ruAOsJLTHXWmDe50polZSGrE5OBS7TEjtwuBRGcR84Ngp_NklUQYIrnOCKVnAd2HZzu_JfmNYOdJfiK9pd-Fj0lOO3y4UUu_-p9gs-j67GF8XF2eR8D75QTzw8ye7CWvOwsPtkcTT6p19nL7Vr0fg
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=CMOS-Compatible+Embedded+Artificial+Synaptic+Device+%28eASD%29+for+Neuromorphic+Computing+and+AI+Applications&rft.jtitle=IEEE+transactions+on+electron+devices&rft.au=Yao-Hung%2C+Huang&rft.au=Hsin-Yuan%2C+Yu&rft.au=Yue-Der+Chih&rft.au=Wang%2C+Yih&rft.date=2024-02-01&rft.pub=The+Institute+of+Electrical+and+Electronics+Engineers%2C+Inc.+%28IEEE%29&rft.issn=0018-9383&rft.eissn=1557-9646&rft.volume=71&rft.issue=2&rft.spage=1313&rft_id=info:doi/10.1109%2FTED.2023.3346857&rft.externalDBID=NO_FULL_TEXT
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0018-9383&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0018-9383&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0018-9383&client=summon