NVIDIA Flare Overview and Installation Guide

Introduction

• Presenter: Chris Kirsten, Technical Marketing Engineering team at NVIDIA
• Focus: NVIDIA Flare - Federated Learning Application Runtime Environment
• Objective: Overview of platform, tools, and installation options

What is NVIDIA Flare?

• Open-Source Platform: For collaborative computing
• Licensed: Apache 2.0
• Base Runtime: Secure, distributed, multi-party collaborative compute
• Flexible API: Adapts existing ML/DL workflows to federated paradigm
• Reference Implementations: Federated learning algorithms, privacy preservation, encryption tools

Key Components

1. Central Flare Stack
   • Communication Layer: APIs, reference algorithms
   • Features: Authentication, authorization, resource management, high availability, privacy preservation
2. Reference Workflows
   • Components: Trainers, aggregators, validators
   • Workflows: Scatter and Gather, cyclic weight transfer, global and cross-site evaluation
   • Algorithms: FedAverage, FedOpt, FedProx, Scaffold, Ditto
3. Tools for Developers
   • POC Mode: Simulate federated learning deployment locally
   • Deployment Tools: Provisioning, secure deployment, orchestration, monitoring, experiment management

Installation Options

1. Python Virtual Environment

   • Resources: NVIDIA Developer page, NVFlare GitHub
   • Quick Start Guide: Installation on Linux Ubuntu 20.04, Python 3.8
   • Steps: Create and activate virtual environment, update pip, install NVFlare
   • Tools Access: Local deployment for testing, secure distributed deployment

2. Docker Container

   • Process: Container image build with dependencies
   • Base Image: NGC PyTorch container for deep learning applications
   • Requirements: NVIDIA container toolkit for GPU enablement
   • Steps: Docker file setup, pip installation, build container, access NVFlare tools
   • Benefits: Consistent environment for servers and clients

3. GitHub Source

   • Use Case: Active platform development
   • Steps: Clone repository, install wheel, build with setup.py, install resulting wheel

Conclusion

• Summary: Overview of NVIDIA Flare and installation methods
• Next Steps: Explore platform further, watch additional videos for advanced features
• Contact: Developer channels, NVFlare GitHub discussions