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Supporting Massive DLRM Inference through Software Defined ..:

, In: 2022 IEEE 42nd International Conference on Distributed Computing Systems (ICDCS),

Ardestani, Ehsan K. ; Kim, Changkyu ; Lee, Seung Jae... - p. 302-312 , 2022

Link: https://doi.org/10.1109/ICDCS54860.2022.00037

RT 
T1 <cTitle>2022 IEEE 42nd International Conference on Distributed Computing Systems (ICDCS)</cTitle>: T1 <Title>Supporting Massive DLRM Inference through Software Defined Memory</Title>

UL https://suche.suub.uni-bremen.de/peid=ieee-9912130&Exemplar=1&LAN=DE
				
A1 Ardestani, Ehsan K.
A1 Kim, Changkyu
A1 Lee, Seung Jae
A1 Pan, Luoshang
A1 Axboe, Jens
A1 Rampersad, Valmiki
A1 Agrawal, Banit
A1 Yu, Fuxun
A1 Yu, Ansha
A1 Le, Trung
A1 Yuen, Hector
A1 Mudigere, Dheevatsa
A1 Juluri, Shishir
A1 Nanda, Akshat
A1 Wodekar, Manoj
A1 Nair, Krishnakumar
A1 Naumov, Maxim
A1 Petersen, Chris
A1 Smelyanskiy, Mikhail
A1 Rao, Vijay
YR 2022
SN 2575-8411
K1 Deep learning
K1 Measurement
K1 Power demand
K1 Computational modeling
K1 Memory management
K1 Software
K1 Hardware
K1 DLRM
K1 Hierarchical Memory
K1 Software Defined Memory
K1 Recommendation Models
K1 Inference
SP 302
OP 312
LK http://dx.doi.org/https://doi.org/10.1109/ICDCS54860.2022.00037
DO https://doi.org/10.1109/ICDCS54860.2022.00037
SF ELIB - SuUB Bremen

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