A Customized NoC Architecture to Enable Highly Localized Computing-on-the-Move DNN Dataflow

The ever-increasing computation complexity of fast-growing Deep Neural Networks (DNNs) has requested new computing paradigms to overcome the memory wall in conventional Von Neumann computing architectures. The emerging Computing-In-Memory (CIM) architecture has been a promising candidate to accelera...

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Bibliographic Details
Main Authors:	He, Y. (Author), Huang, K. (Author), Liu, J. (Author), Xiao, R. (Author), Zhou, K. (Author)
Format:	Article
Language:	English
Published:	Institute of Electrical and Electronics Engineers Inc. 2022
Subjects:	Computation complexity Computing paradigm computing-in-memory Computing-in-memory computing-on-the-move dataflow Computing-on-the-move dataflow Data movements Dataflow Deep neural networks Distributed computer systems Localised Memory architecture Memory wall Network architecture network-on-chip Network-on-chip Network-on-chip architectures Neumann computing Servers
Online Access:	View Fulltext in Publisher

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View Fulltext in Publisher

A Customized NoC Architecture to Enable Highly Localized Computing-on-the-Move DNN Dataflow

Internet

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