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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Veröffentlicht in:	Journal of parallel and distributed computing Jg. 193; S. 104949
Hauptverfasser:	Nacar, Furkan, Cakin, Alperen, Dilek, Selma, Tosun, Suleyman, Chakrabarty, Krishnendu
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Inc 01.11.2024
Schlagworte:	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
Online-Zugang:	Volltext
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