Neuron grouping and mapping methods for 2D-mesh NoC-based DNN accelerators

Deep Neural Networks (DNNs) have gained widespread adoption in various fields; however, their computational cost is often prohibitively high due to the large number of layers and neurons communicating with each other. Furthermore, DNNs can consume a significant amount of energy due to the large volu...

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Vydané v:	Journal of parallel and distributed computing Ročník 193; s. 104949
Hlavní autori:	Nacar, Furkan, Cakin, Alperen, Dilek, Selma, Tosun, Suleyman, Chakrabarty, Krishnendu
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier Inc 01.11.2024
Predmet:	Accelerators Deep Neural Network (DNN) Integer Linear Programming (ILP) Mapping Network-on-Chip (NoC) Simulated Annealing (SA) Deep Neural Network (DNN) Mapping Accelerators Integer Linear Programming (ILP) Network-on-Chip (NoC) Simulated Annealing (SA)
ISSN:	0743-7315
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