Segmentation of DL Models(Cloud-Edge Collaborative Inference)

[swagshaw]

Segmentation of DL Models(Cloud-Edge Collaborative Inference)

[swagshaw]

2. 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]

3. 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]

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]

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

[swagshaw]

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

[swagshaw]

2. 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