Hardware Generator for Edge Artificial Intelligent Inference System

Yeong Kang Lai; Chuan Wei Huang

doi:10.1109/ICCE-TW52618.2021.9603260

Hardware Generator for Edge Artificial Intelligent Inference System

Yeong Kang Lai, Chuan Wei Huang

National Chung Hsing University

研究成果: 圖書/報告稿件的類型 › 會議稿件 › 同行評審

摘要

This paper designs an optimized hardware generator (IP Generator) based on convolutional neural networks. Users can use IP Generator to create any hardware architectures for neural network model they want. By the efficient user interface, the IP generator can output the architecture. You can get the corresponding optimized Verilog code efficiently. The network is a network model that simplifies some network layers by Yolo-v1. It can run 100MHz on Xilinx ZCU102 board which can reach 28.8GOP/s.

原文	英語
主出版物標題	2021 IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021
發行者	Institute of Electrical and Electronics Engineers Inc.
ISBN（電子）	9781665433280
DOIs	https://doi.org/10.1109/ICCE-TW52618.2021.9603260
出版狀態	已出版 - 2021
對外發佈	是
事件	8th IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021 - Penghu, 台灣持續時間: 15 09 2021 → 17 09 2021

出版系列

名字	2021 IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021

Conference

Conference	8th IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021
國家/地區	台灣
城市	Penghu
期間	15/09/21 → 17/09/21

文獻附註

Publisher Copyright:
© 2021 IEEE.

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10.1109/ICCE-TW52618.2021.9603260

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Link to publication in Scopus

引用此

Lai, Y. K., & Huang, C. W. (2021). Hardware Generator for Edge Artificial Intelligent Inference System. 於 2021 IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021 (2021 IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCE-TW52618.2021.9603260

@inproceedings{439d4897743a43239080bafaa9c3983f,

title = "Hardware Generator for Edge Artificial Intelligent Inference System",

abstract = "This paper designs an optimized hardware generator (IP Generator) based on convolutional neural networks. Users can use IP Generator to create any hardware architectures for neural network model they want. By the efficient user interface, the IP generator can output the architecture. You can get the corresponding optimized Verilog code efficiently. The network is a network model that simplifies some network layers by Yolo-v1. It can run 100MHz on Xilinx ZCU102 board which can reach 28.8GOP/s.",

keywords = "Convolution Neural Networks(CNNs), IP Generators (Automatic Verilog Generators)",

author = "Lai, {Yeong Kang} and Huang, {Chuan Wei}",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 8th IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021 ; Conference date: 15-09-2021 Through 17-09-2021",

year = "2021",

doi = "10.1109/ICCE-TW52618.2021.9603260",

language = "英语",

series = "2021 IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2021 IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021",

address = "美国",

}

Lai, YK & Huang, CW 2021, Hardware Generator for Edge Artificial Intelligent Inference System. 於 2021 IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021. 2021 IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021, Institute of Electrical and Electronics Engineers Inc., 8th IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021, Penghu, 台灣, 15/09/21. https://doi.org/10.1109/ICCE-TW52618.2021.9603260

Hardware Generator for Edge Artificial Intelligent Inference System. / Lai, Yeong Kang; Huang, Chuan Wei.
2021 IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021. Institute of Electrical and Electronics Engineers Inc., 2021. (2021 IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021).

研究成果: 圖書/報告稿件的類型 › 會議稿件 › 同行評審

TY - GEN

T1 - Hardware Generator for Edge Artificial Intelligent Inference System

AU - Lai, Yeong Kang

AU - Huang, Chuan Wei

PY - 2021

Y1 - 2021

N2 - This paper designs an optimized hardware generator (IP Generator) based on convolutional neural networks. Users can use IP Generator to create any hardware architectures for neural network model they want. By the efficient user interface, the IP generator can output the architecture. You can get the corresponding optimized Verilog code efficiently. The network is a network model that simplifies some network layers by Yolo-v1. It can run 100MHz on Xilinx ZCU102 board which can reach 28.8GOP/s.

AB - This paper designs an optimized hardware generator (IP Generator) based on convolutional neural networks. Users can use IP Generator to create any hardware architectures for neural network model they want. By the efficient user interface, the IP generator can output the architecture. You can get the corresponding optimized Verilog code efficiently. The network is a network model that simplifies some network layers by Yolo-v1. It can run 100MHz on Xilinx ZCU102 board which can reach 28.8GOP/s.

KW - Convolution Neural Networks(CNNs)

KW - IP Generators (Automatic Verilog Generators)

UR - http://www.scopus.com/inward/record.url?scp=85123047646&partnerID=8YFLogxK

U2 - 10.1109/ICCE-TW52618.2021.9603260

DO - 10.1109/ICCE-TW52618.2021.9603260

M3 - 会议稿件

AN - SCOPUS:85123047646

T3 - 2021 IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021

BT - 2021 IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 8th IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021

Y2 - 15 September 2021 through 17 September 2021

ER -

Hardware Generator for Edge Artificial Intelligent Inference System

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