AppealNet: An Efficient and Highly-Accurate Edge/Cloud Collaborative Architecture for DNN Inference
2021 58th ACM/IEEE Design Automation Conference (DAC)(2021)
摘要
This paper presents AppealNet, a novel edge/cloud collaborative architecture that runs deep learning (DL) tasks more efficiently than state-of-the-art solutions. For a given input, AppealNet accurately predicts on-the-fly whether it can be successfully processed by the DL model deployed on the resource-constrained edge device, and if not, appeals to the more powerful DL model deployed at the cloud...
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关键词
Training,Design automation,Image edge detection,Computational modeling,Neural networks,Collaboration,Computer architecture
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