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1 Ergebnisse
1
Optimizing GPU Deep Learning Operators with Polyhedral Sche..:
, In:
2022 IEEE/ACM International Symposium on Code Generation and Optimization (CGO)
,
Bastoul, Cedric
;
Zhang, Zhen
;
Razanajato, Harenome
... - p. 313-324 , 2022
Link:
https://doi.org/10.1109/CGO53902.2022.9741260
RT T1 <cTitle>2022 IEEE/ACM International Symposium on Code Generation and Optimization (CGO)</cTitle>: T1 <Title>Optimizing GPU Deep Learning Operators with Polyhedral Scheduling Constraint Injection</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-9741260&Exemplar=1&LAN=DE A1 Bastoul, Cedric A1 Zhang, Zhen A1 Razanajato, Harenome A1 Lossing, Nelson A1 Susungi, Adilla A1 de Juan, Javier A1 Filhol, Etienne A1 Jarry, Baptiste A1 Consolaro, Gianpietro A1 Zhang, Renwei YR 2022 K1 Deep learning K1 Codes K1 Costs K1 Neural networks K1 Memory management K1 Graphics processing units K1 Production K1 Polyhedral model K1 scheduling K1 vectorization SP 313 OP 324 LK http://dx.doi.org/https://doi.org/10.1109/CGO53902.2022.9741260 DO https://doi.org/10.1109/CGO53902.2022.9741260 SF ELIB - SuUB Bremen
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