# 🚀 HyperFabric Interconnect
A breakthrough protocol architecture for ultra-low-latency, high-bandwidth interconnects powering AI superclusters and quantum simulation networks.
[](https://badge.fury.io/py/hyper-fabric-interconnect)
[](https://www.python.org/downloads/)
[](https://choosealicense.com/licenses/mit/)
## 🧬 Vision
This protocol is the backbone of next-generation computation — beyond TCP/IP, beyond RDMA. It enables microsecond-scale data propagation, predictive routing, and hardware-level orchestration across AI/ML, HPC, and quantum-hybrid clusters.
## ⚡ Features
- **Ultra-Low Latency**: Microsecond-scale data propagation
- **Predictive Routing**: ML-enhanced path optimization
- **Hardware-Level Orchestration**: Direct hardware signature mapping
- **Fault Tolerance**: Auto self-healing interconnect clusters
- **Zero-Copy Buffers**: Memory-efficient data transfer simulation
- **Quantum-Aware**: Support for QPU entanglement message routing
## 🚀 Installation
```bash
pip install hyper-fabric-interconnect
```
## 📖 Quick Start
```python
from hyperfabric import HyperFabricProtocol, NodeSignature
# Initialize the protocol
protocol = HyperFabricProtocol()
# Register a virtual node
node = NodeSignature(
node_id="gpu-cluster-01",
hardware_type="nvidia-h100",
bandwidth_gbps=400,
latency_ns=100
)
protocol.register_node(node)
# Send data with predictive routing
await protocol.send_data(
source="gpu-cluster-01",
destination="qpu-fabric-02",
data=large_tensor,
priority="ultra_high"
)
```
## 🛠️ CLI Tools
```bash
# Ping fabric nodes
hfabric ping gpu-cluster-01
# View topology
hfabric topo --visualize
# Run diagnostics
hfabric diagnose --full
```
## 📚 Documentation
Full documentation is available at [GitHub Pages](https://krish567366.github.io/hyper-fabric-interconnect/)
## 🧠 Use Cases
- **AI Supercluster Communication**: Synchronizing transformer model shards across distributed GPUs
- **Quantum-Enhanced AI**: Routing QPU entanglement messages for hybrid classical-quantum computation
- **HPC Workloads**: Ultra-low latency scientific simulation data exchange
- **Edge Computing**: Adaptive cyber-physical compute swarm coordination
## 👨💻 Author
**Krishna Bajpai**
Email: bajpaikrishna715@gmail.com
GitHub: [@krish567366](https://github.com/krish567366)
## 📄 License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
## 🤝 Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
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"description": "# \ud83d\ude80 HyperFabric Interconnect\r\n\r\nA breakthrough protocol architecture for ultra-low-latency, high-bandwidth interconnects powering AI superclusters and quantum simulation networks.\r\n\r\n[](https://badge.fury.io/py/hyper-fabric-interconnect)\r\n[](https://www.python.org/downloads/)\r\n[](https://choosealicense.com/licenses/mit/)\r\n\r\n## \ud83e\uddec Vision\r\n\r\nThis protocol is the backbone of next-generation computation \u2014 beyond TCP/IP, beyond RDMA. It enables microsecond-scale data propagation, predictive routing, and hardware-level orchestration across AI/ML, HPC, and quantum-hybrid clusters.\r\n\r\n## \u26a1 Features\r\n\r\n- **Ultra-Low Latency**: Microsecond-scale data propagation\r\n- **Predictive Routing**: ML-enhanced path optimization\r\n- **Hardware-Level Orchestration**: Direct hardware signature mapping\r\n- **Fault Tolerance**: Auto self-healing interconnect clusters\r\n- **Zero-Copy Buffers**: Memory-efficient data transfer simulation\r\n- **Quantum-Aware**: Support for QPU entanglement message routing\r\n\r\n## \ud83d\ude80 Installation\r\n\r\n```bash\r\npip install hyper-fabric-interconnect\r\n```\r\n\r\n## \ud83d\udcd6 Quick Start\r\n\r\n```python\r\nfrom hyperfabric import HyperFabricProtocol, NodeSignature\r\n\r\n# Initialize the protocol\r\nprotocol = HyperFabricProtocol()\r\n\r\n# Register a virtual node\r\nnode = NodeSignature(\r\n node_id=\"gpu-cluster-01\",\r\n hardware_type=\"nvidia-h100\",\r\n bandwidth_gbps=400,\r\n latency_ns=100\r\n)\r\nprotocol.register_node(node)\r\n\r\n# Send data with predictive routing\r\nawait protocol.send_data(\r\n source=\"gpu-cluster-01\",\r\n destination=\"qpu-fabric-02\",\r\n data=large_tensor,\r\n priority=\"ultra_high\"\r\n)\r\n```\r\n\r\n## \ud83d\udee0\ufe0f CLI Tools\r\n\r\n```bash\r\n# Ping fabric nodes\r\nhfabric ping gpu-cluster-01\r\n\r\n# View topology\r\nhfabric topo --visualize\r\n\r\n# Run diagnostics\r\nhfabric diagnose --full\r\n```\r\n\r\n## \ud83d\udcda Documentation\r\n\r\nFull documentation is available at [GitHub Pages](https://krish567366.github.io/hyper-fabric-interconnect/)\r\n\r\n## \ud83e\udde0 Use Cases\r\n\r\n- **AI Supercluster Communication**: Synchronizing transformer model shards across distributed GPUs\r\n- **Quantum-Enhanced AI**: Routing QPU entanglement messages for hybrid classical-quantum computation\r\n- **HPC Workloads**: Ultra-low latency scientific simulation data exchange\r\n- **Edge Computing**: Adaptive cyber-physical compute swarm coordination\r\n\r\n## \ud83d\udc68\u200d\ud83d\udcbb Author\r\n\r\n**Krishna Bajpai** \r\nEmail: bajpaikrishna715@gmail.com \r\nGitHub: [@krish567366](https://github.com/krish567366)\r\n\r\n## \ud83d\udcc4 License\r\n\r\nThis project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.\r\n\r\n## \ud83e\udd1d Contributing\r\n\r\nContributions are welcome! Please feel free to submit a Pull Request.\r\n",
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