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Published 20 hours ago • verified publisher icon swagshaw

Segmentation of DL Models(Cloud-Edge Collaborative Inference)

Open swagshaw opened this issue 3 years ago • 6 comments

Likes Neurosurgeon the model can be segmented into multiple partitions and then allocated to:

  1. distributed edge nodes A Locally Distributed Mobile Computing Framework for DNN based Android Applications https://readpaper.com/paper/2896769682 DeepThings: Distributed Adaptive Deep Learning Inference on Resource-Constrained IoT Edge Clusters

swagshaw avatar Dec 16 '21 02:12 swagshaw

  1. collaborative “end-edge-cloud” architecture Auto-tuning Neural Network Quantization Framework for Collaborative Inference Between the Cloud and Edge https://readpaper.com/paper/2949701228 DeepX: a software accelerator for low-power deep learning inference on mobile devices https://readpaper.com/paper/2297325673 ECRT: An Edge Computing System for Real-Time Image-based Object Tracking https://readpaper.com/paper/2898495092 Learning IoT in Edge: Deep Learning for the Internet of Things with Edge Computing https://readpaper.com/paper/2786070938

swagshaw avatar Dec 16 '21 03:12 swagshaw

  1. Early Exit of Inference (EEoI) Edge Intelligence: On-Demand Deep Learning Model Co-Inference with Device-Edge Synergy https://readpaper.com/paper/2809251854 Distributed Deep Neural Networks over the Cloud, the Edge and End Devices https://readpaper.com/paper/2734927154 Deep Learning for Smart Industry: Efficient Manufacture Inspection System With Fog Computing https://readpaper.com/paper/2805454539 BranchyNet: Fast inference via early exiting from deep neural networks https://readpaper.com/paper/2962677625 MODI: Mobile Deep Inference Made Efficient by Edge Computing https://par.nsf.gov/servlets/purl/10159019

swagshaw avatar Dec 16 '21 03:12 swagshaw

Different offloading DeepDecision: A Mobile Deep Learning Framework for Edge Video Analytics https://readpaper.com/paper/2792220137 MASM: A Multiple-Algorithm Service Model for Energy-Delay Optimization in Edge Artificial Intelligence https://readpaper.com/paper/2914434280 DeepWear: Adaptive Local Offloading for On-Wearable Deep Learning https://arxiv.org/pdf/1712.03073.pdf IONN: Incremental Offloading of Neural Network Computations from Mobile Devices to Edge Servers https://readpaper.com/paper/2892952080 When deep learning meets edge computing https://ieeexplore.ieee.org/document/8117585

swagshaw avatar Dec 16 '21 04:12 swagshaw

MoDNN: Local distributed mobile computing system for Deep Neural Network https://readpaper.com/paper/2612193523

swagshaw avatar Dec 16 '21 04:12 swagshaw

MobiRNN: Efficient Recurrent Neural Network Execution on Mobile GPU https://arxiv.org/pdf/1706.00878.pdf

swagshaw avatar Dec 17 '21 12:12 swagshaw

  1. collaborative “end-edge-cloud” architecture Auto-tuning Neural Network Quantization Framework for Collaborative Inference Between the Cloud and Edge https://readpaper.com/paper/2949701228 DeepX: a software accelerator for low-power deep learning inference on mobile devices https://readpaper.com/paper/2297325673 ECRT: An Edge Computing System for Real-Time Image-based Object Tracking https://readpaper.com/paper/2898495092 Learning IoT in Edge: Deep Learning for the Internet of Things with Edge Computing https://readpaper.com/paper/2786070938

Done

swagshaw avatar Dec 19 '21 15:12 swagshaw