UniAP: Unifying Inter- and Intra-Layer Automatic Parallelism by Mixed Integer Quadratic Programming

Distributed learning is commonly used for training deep learning models, especially large models. In distributed learning, manual parallelism (MP) methods demand considerable human effort and have limited flexibility. Hence, automatic parallelism (AP) methods have recently been proposed for automati...

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Vydané v:	Proceedings (IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Online) s. 20947 - 20957
Hlavní autori:	Lin, Hao, Wu, Ke, Li, Jie, Li, Jun, Li, Wu-Jun
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 10.06.2025
Predmet:	Computer aided instruction Distance learning Manuals Optimization Parallel processing Pattern recognition Quadratic programming Throughput Training Transformers
ISSN:	1063-6919
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