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A scalable, high-performance serving system for federated learning models

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FATE-Serving

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Introduction

FATE-Serving is a high-performance, industrialized serving system for federated learning models, designed for production environments. for more detail, You can click WIKI for more information for more information

FATE-Serving now supports

  • High performance online Federated Learning algorithms.
  • Federated Learning online inference pipeline.
  • Dynamic loading federated learning models.
  • Can serve multiple models, or multiple versions of the same model.
  • Real-time inference using federated learning models.
  • Support multi-level cache for remote party federated inference result.
  • Support pre-processing, post-processing and data-access adapters for the production deployment.
  • Provide service managerment for grpc interface by using zookeeper as registry
  • Requests for publishing models are persisted to local files,so the loaded model will be loaded automatically when the application is restarted

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A scalable, high-performance serving system for federated learning models

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