Optimal distributed parallel algorithms for deep learning framework Tensorflow

Since its release, the Tensorflow framework has been widely used in various fields due to its advantages in deep learning. However, it is still at its early state. Its native distributed implementation has difficulty in expanding for large models because it has issues of low utilization of multiple...

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Bibliographic Details
Published in:	Applied intelligence (Dordrecht, Netherlands) Vol. 52; no. 4; pp. 3880 - 3900
Main Authors:	Xie, Yuanlun, He, Majun, Ma, Tingsong, Tian, Wenhong
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.03.2022 Springer Nature B.V
Subjects:	Algorithms Artificial Intelligence Clusters Computer Science Deep learning Greedy algorithms Machine learning Machines Manufacturing Mechanical Engineering Parallel processing Pipelining (computers) Processes Training Deep learning Tensorflow Data parallelism Model parallelism Optimal distributed parallel algorithms
ISSN:	0924-669X, 1573-7497
Online Access:	Get full text
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