AdAM: adaptive fault-tolerant approximate multiplier for edge DNN accelerators
author
Taheri, Mahdi
Cherezova, Natalia
Nazari, Samira
Rafiq, Ahsan
Azarpeyvand, Ali
Ghasempouri, Tara
Daneshtalab, Masoud
Raik, Jaan
Jenihhin, Maksim
statement of authorship
Mahdi Taheri, Natalia Cherezova, Samira Nazari, Ahsan Rafiq, Ali Azarpeyvand, Tara Ghasempouri, Masoud Daneshtalab, Jaan Raik, Maksim Jenihhin
source
2024 IEEE European Test Symposium (ETS): ETS 2024 : May 20-24, 2024, The Hague, Netherlands : proceedings
location of publication
Piscataway, NJ
publisher
IEEE
year of publication
2024
conference name, date
29th IEEE European Test Symposium, ETS 2024, 20-24 May 2024
conference location
Hague, the Netherlands
url
https://doi.org/10.1109/ETS61313.2024.10567161
subject term
tehisnärvivõrgud
elektriahelad
kiirendid
rikked
Scopus
https://www.scopus.com/sourceid/21100395950
https://www.scopus.com/record/display.uri?eid=2-s2.0-85197518684&origin=resultslist&sort=plf-f&src=s&sot=b&sdt=b&s=DOI%2810.1109%2FETS61313.2024.10567161%29&sessionSearchId=2694adcfded71cf12565f4df31de58f5&relpos=0
WOS
https://www.webofscience.com/wos/woscc/full-record/WOS:001260970400008
category (general)
Computer science
Arvutiteadus
Engineering
Tehnika
category (sub)
Computer science. Software
Arvutiteadus. Tarkvara
Engineering. Electrical and electronic engineering
Tehnika. Elektri- ja elektroonikatehnika
Engineering. Industrial and manufacturing engineering
Tehnika. Tööstus- ja tootmistehnika
keyword
approximate computing
circuits design
deep neural networks
reliability
resiliency assessment
ISSN
1530-1877
ISBN
979-835034932-0
notes
Bibliogr.: 21 ref
Open Access
Open Access
scientific publication
teaduspublikatsioon
classifier
3.1
TalTech department
arvutisüsteemide instituut
language
inglise