We present FedKit, a federated learning (FL) system tailored for cross-platform FL research on Android and iOS devices. FedKit pipelines cross-platform FL development by enabling model conversion, hardware-accelerated training, and cross-platform model aggregation. Our FL workflow supports flexible machine learning operations (MLOps) in production, facilitating continuous model delivery and training. We have deployed FedKit in a real-world use case for health data analysis on university campuses, demonstrating its effectiveness. FedKit is open-source at https://github.com/FedCampus/FedKit.

翻译：本文提出FedKit，一个专为安卓与iOS设备跨平台联邦学习（FL）研究设计的系统。FedKit通过支持模型转换、硬件加速训练和跨平台模型聚合，实现了跨平台联邦学习的流水线化开发。我们的联邦学习工作流支持生产环境中的灵活机器学习运维（MLOps），便于持续模型交付与训练。已在实际大学校园健康数据分析场景中部署FedKit，验证了其有效性。FedKit开源地址为：https://github.com/FedCampus/FedKit