RoleML: a Role-Oriented Programming Model for Customizable Distributed Machine Learning on Edges

Edge AI aims to enable distributed machine learning (DML) on edge resources to fulfill the need for data privacy and low latency. Meanwhile, the challenge of device heterogeneity and discrepancy in data distribution requires more sophisticated DML architectures that differ in topology and communication strategy. This calls for a standardized and general programming interface and framework to develop them. Existing frameworks are only meant for specific architectures (e.g., FedML and Flower for Federated Learning) and do not support others by design.