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Predicting How CNN Training Time Changes on Various Mini-Ba..:
, In:
Proceedings of the 2021 on Performance EngineeRing, Modelling, Analysis, and VisualizatiOn STrategy
,
Bryzgalov, Peter
;
Maeda, Toshiyuki
;
Shigeto, Yutaro
- p. 11-18 , 2021
Link:
https://dl.acm.org/doi/10.1145/3452412.3462750
RT T1 <cTitle>Proceedings of the 2021 on Performance EngineeRing, Modelling, Analysis, and VisualizatiOn STrategy</cTitle>: T1 <Title>Predicting How CNN Training Time Changes on Various Mini-Batch Sizes by Considering Convolution Algorithms and Non-GPU Time</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3462750&Exemplar=1&LAN=DE A1 Bryzgalov, Peter A1 Maeda, Toshiyuki A1 Shigeto, Yutaro PB ACM YR 2021 K1 convolutional neural networks K1 gpgpus K1 machine learning K1 performance analysis and prediction K1 Software and its engineering K1 Software organization and properties K1 Extra-functional properties K1 Software performance SP 11 OP 18 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3452412.3462750 DO https://dl.acm.org/doi/10.1145/3452412.3462750 SF ELIB - SuUB Bremen
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