Reconfigurable Architecture and Dataflow for Memory Traffic Minimization of CNNs Computation

Computation of convolutional neural network (CNN) requires a significant amount of memory access, which leads to lots of energy consumption. As the increase of neural network scale, this phenomenon is further obvious, the energy consumption of memory access and data migration between on-chip buffer...

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Detalles Bibliográficos
Autores principales: Cheng, Wei-Kai, Liu, Xiang-Yi, Wu, Hsin-Tzu, Pai, Hsin-Yi, Chung, Po-Yao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8624143/
https://www.ncbi.nlm.nih.gov/pubmed/34832777
http://dx.doi.org/10.3390/mi12111365

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8624143/
https://www.ncbi.nlm.nih.gov/pubmed/34832777
http://dx.doi.org/10.3390/mi12111365

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