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dc.contributor.author
Hersche, Michael
dc.contributor.author
Sangalli, Sara
dc.contributor.author
Benini, Luca
dc.contributor.author
Rahimi, Abbas
dc.date.accessioned
2020-08-17T07:50:34Z
dc.date.available
2020-06-08T05:12:38Z
dc.date.available
2020-08-07T12:42:23Z
dc.date.available
2020-08-17T07:50:34Z
dc.date.issued
2020
dc.identifier.isbn
978-1-7281-4922-6
en_US
dc.identifier.isbn
978-1-7281-4923-3
en_US
dc.identifier.other
10.1109/AICAS48895.2020.9073871
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/418755
dc.identifier.doi
10.3929/ethz-b-000387115
dc.description.abstract
This paper proposes evolvable hyperdimensional (HD) computing to maintain high classification accuracy as permanent faults occur in emerging non-volatile memory fabrics. Our proposed HD architecture can detect, localize, and isolate faulty PCM blocks in discriminative classifiers, followed by unsupervised regeneration of new blocks to compensate accuracy loss. We demonstrate its application on a language recognition task: it is able to quickly relearn and fully recover the accuracy from 90.48% to 96.86% at fault rates as high as 42% by using solely 4.2 MB of text for regeneration. The new evolved model is still 285× more compact than state-of-the-art fastText.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
IEEE
en_US
dc.rights.uri
http://rightsstatements.org/page/InC-NC/1.0/
dc.subject
Evolvable hardware
en_US
dc.subject
HD computing
en_US
dc.subject
PCM
en_US
dc.title
Evolvable Hyperdimensional Computing: Unsupervised Regeneration of Associative Memory to Recover Faulty Components
en_US
dc.type
Conference Paper
dc.rights.license
In Copyright - Non-Commercial Use Permitted
dc.date.published
2020-04-23
ethz.book.title
2020 2nd IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS)
en_US
ethz.pages.start
281
en_US
ethz.pages.end
285
en_US
ethz.size
5 p. accepted version
en_US
ethz.version.deposit
acceptedVersion
en_US
ethz.event
2nd IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS 2020) (virtual)
en_US
ethz.event.location
Genova, Italy
en_US
ethz.event.date
August 31 - September 2, 2020
en_US
ethz.notes
Conference postponed due to Corona virus (COVID-19). Due to the Corona virus (COVID-19) the conference was conducted virtually.
en_US
ethz.grant
Computation-in-memory architecture based on resistive devices
en_US
ethz.identifier.scopus
ethz.publication.place
Piscataway, NJ
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02140 - Dep. Inf.technologie und Elektrotechnik / Dep. of Inform.Technol. Electrical Eng.::02636 - Institut für Integrierte Systeme / Integrated Systems Laboratory::03996 - Benini, Luca / Benini, Luca
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02140 - Dep. Inf.technologie und Elektrotechnik / Dep. of Inform.Technol. Electrical Eng.::02636 - Institut für Integrierte Systeme / Integrated Systems Laboratory::03996 - Benini, Luca / Benini, Luca
en_US
ethz.grant.agreementno
780215
ethz.grant.agreementno
780215
ethz.grant.fundername
EC
ethz.grant.fundername
EC
ethz.grant.funderDoi
10.13039/501100000780
ethz.grant.funderDoi
10.13039/501100000780
ethz.grant.program
H2020
ethz.grant.program
H2020
ethz.date.deposited
2019-12-23T19:32:20Z
ethz.source
FORM
ethz.source
SCOPUS
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2020-08-17T07:50:45Z
ethz.rosetta.lastUpdated
2022-03-29T02:55:35Z
ethz.rosetta.versionExported
true
dc.identifier.olduri
http://hdl.handle.net/20.500.11850/387115
dc.identifier.olduri
http://hdl.handle.net/20.500.11850/417485
ethz.COinS
ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.atitle=Evolvable%20Hyperdimensional%20Computing:%20Unsupervised%20Regeneration%20of%20Associative%20Memory%20to%20Recover%20Faulty%20Components&rft.date=2020&rft.spage=281&rft.epage=285&rft.au=Hersche,%20Michael&Sangalli,%20Sara&Benini,%20Luca&Rahimi,%20Abbas&rft.isbn=978-1-7281-4922-6&978-1-7281-4923-3&rft.genre=proceeding&rft_id=info:doi/10.1109/AICAS48895.2020.9073871&rft.btitle=2020%202nd%20IEEE%20International%20Conference%20on%20Artificial%20Intelligence%20Circuits%20and%20Systems%20(AICAS)
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