Energy-Efficient High-Speed ASIC Implementation of Convolutional Neural Network Using Novel Reduced Critical-Path Design

Energy-Efficient High-Speed ASIC Implementation of Convolutional Neural Network Using Novel Reduced Critical-Path Design

Convolutional Neural Network (CNN) plays an important role in several machine learning tasks related to speech, image, and video processing applications. The increasing demand for faster processing in real-time applications requires high-speed implementation of CNN. However, in general, CNN involves...

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Bibliographic Details
Main Authors: Lee, S.S (Author), Meher, P.K (Author), Nguyen, T.D (Author), Park, S.Y (Author)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers Inc. 2022
Subjects:
Application specific integrated circuits
ASIC
Budget control
Convolution
convolution layer
Convolution layer
Convolutional neural network
Convolutional neural network (CNN)
Critical Paths
Data flow analysis
Dataflow
Energy efficiency
Forestry
High Speed
Integrated circuit design
modified Booth encoder
Modified booth encoder
Multilayer neural networks
Network architecture
Network layers
Reduction trees
Regression analysis
State of the art
Video signal processing
Wallace reduction tree
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