A Novel Automate Python Edge-to-Edge: From Automated Generation on Cloud to User Application Deployment on Edge of Deep Neural Networks for Low Power IoT Systems FPGA-Based Acceleration

A Novel Automate Python Edge-to-Edge: From Automated Generation on Cloud to User Application Deployment on Edge of Deep Neural Networks for Low Power IoT Systems FPGA-Based Acceleration

Deep Neural Networks (DNNs) deployment for IoT Edge applications requires strong skills in hardware and software. In this paper, a novel design framework fully automated for Edge applications is proposed to perform such a deployment on System-on-Chips. Based on a high-level Python interface that mim...

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Bibliographic Details
Main Authors: Tarek Belabed, Vitor Ramos Gomes da Silva, Alexandre Quenon, Carlos Valderamma, Chokri Souani
Format: Article
Language:English
Published: MDPI AG 2021-09-01
Series:Sensors
Subjects:
cloud computing
deep neural networks (DNNs)
edge computing
field programmable gate array (FPGA)
hardware acceleration
high-level synthesis (HLS) tools
Online Access:https://www.mdpi.com/1424-8220/21/18/6050

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https://www.mdpi.com/1424-8220/21/18/6050

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