Decentralized Learning Framework
Empowering researchers and developers to experiment with distributed machine learning while maintaining privacy.
What is Murmura?
Murmura is a framework for federated learning in decentralized/P2P environments. It helps researchers and developers experiment with distributed machine learning while maintaining privacy.
Decentralized
Built for peer-to-peer environments with no central authority
Privacy-Preserving
Keeps data private while enabling collaborative learning
Experimental
Designed for research and development of new ML techniques
Key Features
Murmura provides a comprehensive toolkit for decentralized federated learning research and development.
Decentralized Federated Learning
Implement federated learning algorithms in fully decentralized environments without central coordination.
P2P Network Simulation
Simulate various network conditions and topologies to test algorithm robustness.
Privacy-Preserving Protocols
Implement and test various privacy-preserving learning protocols and techniques.
Customizable Node Behaviors
Define custom node behaviors and network topologies for diverse experimental setups.
Performance Metrics
Comprehensive metrics and analysis tools to evaluate algorithm performance.
Model Integration
Easily integrate with popular machine learning frameworks and models.
Alpha Release 1
Murmura is currently in active development with key components being implemented and tested for our first alpha release. Our team is working diligently to create a robust framework for decentralized learning research.
- Core P2P networking layerCompleted
- Basic federated learning algorithmsCompleted
- Privacy-preserving protocolsIn Progress
- Performance metrics dashboardIn Progress
- Advanced network simulationPlanned
- Documentation and examplesPlanned
Future Roadmap
Our vision for Murmura extends beyond current capabilities. Here's what we're planning for the future.
AI Agent Integration
Integrate AI agents within the framework to enable autonomous learning and adaptation in decentralized environments.
Quantum Node Emulation
Develop quantum node emulation capabilities for experimenting with quantum federated learning approaches.
Advanced Privacy Techniques
Implement cutting-edge privacy-preserving techniques including homomorphic encryption and secure multi-party computation.
Real-world Deployment Tools
Create tools and frameworks for deploying Murmura-based systems in real-world decentralized environments.
Stay Updated
Subscribe to our newsletter to receive updates on Murmura's development and be the first to know about new features and releases.
We respect your privacy. Unsubscribe at any time.