AdaMEC：Context-Aware Deep Model Computing Framework
A Context-Aware Deep Model Mobile Edge Computing Framework for Adaptive Optimization of Collaborative Computation and Offloading Plans in Dynamic Environments to Adapt tuning.
Model Architecture Diagram：
Description： To address this issue, we propose the Context-aware Adaptive Surgery (CAS) framework to actively perceive the changing processing context and adaptively find the appropriate partition solution in real-time. CAS constructs a partition state graph to model different partition solutions of DNNs with imported context resources, and adopts the runtime search algorithm, Graph-based Adaptive DNN Surgery (GADS), to quickly find the appropriate partition that satisfies resource constraints under the guidance of the neighbor effect. The experimental results show that CAS can achieve adaptively rapid tuning of the model partition solutions in 10ms scale even for large DNNs.