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Decentralized AI Simulator

We are developing a scalable framework-agnostic decentralized AI platform for research community.

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View Demo · Documentation · Report Bug · Request Feature


📔 Table of Contents

🌟 About the Project

📷 Screenshots

screenshot

👾 Tech Stack

  • Ubuntu
  • Conda
  • Python 10+
  • Pytorch
  • Torch Vision
  • Node
  • gRPC
  • Docker
  • Kubernetes
  • GitHub
  • React/Typescript/Javascript

🎯 Features (planned)

  • 🤔 Framework-agnostic --> Bring any kind of ML/DL/AI framework from Pytorch and TensorFlow to Keras and Vanilla ML libraries.

  • 🤔 Decentralized --> No single point of failure in the entire system. All agents can communicate without centralized control.

  • 🤔 Scalable --> The platform supports every kind of data source and every kind of compute device/system

  • 🤔 Secure --> The system is designed with security-first approach

  • 🤔 Privacy-preserving --> The privacy of each data producer and data subject is preserved across the system

  • 🤔 Device-Native --> The control and preferences lies at the device-end

  • 🤔 Distributed --> The platform complies with all functional and non-functional requirements of a distributed system

🔑 Environment

To run this project, you will need to create a virtual environment and install

  • Python 3.10+
  • torch
  • torch vision

🧰 Getting Started

🏃 Run Locally

Clone the project

  git clone https://github.com/mhrehman17/decentai.git

Go to the download location, and run following command.

  python -m decentai.main

Now you can see an MNIST example running on screen.

🧭 Roadmap

  • Local multi-agent simulator. You can configure as many training and evaluation agents as you like to.
  • MNIST example
  • CIFAR 10 example
  • Multiple aggregators
  • Multiple metrics
  • Directory structure and stub files for data pipelines
  • Directory structure and stub files for differential privacy
  • Documentation folder added
  • Directory structure and stub files for homomorphic encryption
  • SMPC
  • Device-agnostic gRPC peer-to-peer communication model
  • Dockerisation/Virtualisation/Kubernetes
  • Cloud/Edge/On-Prem Deployment
  • CI/CD
  • GitHub Actions

👋 Contributing

Contributions are always welcome! Please feel free to submit pull request, if you want to propose new features, or submit an issue.

See contributing.md for ways to get started.

📜 Code of Conduct

Please read the Code of Conduct

❔ FAQ (coming soon)

  • Question 1

    • Answer 1

  • Question 2

    • Answer 2

⚠️ License

Distributed under the no License. See LICENSE.txt for more information.

🤝 Contact

Habib Rehman - @habibcomsats - mhrehman@ieee.org

Project Link: https://github.com/mhrehman17/decentai

💎 Acknowledgements

The project is a collective effort of researchers from LEADS and its collaborators.