InfiniMetrics provides standardized interfaces for benchmarking across multiple layers:

• Hardware-Level: GPU memory bandwidth, cache performance, compute capabilities
• Operator-Level: Individual operation performance (FLOPS, latency)
• Inference-Level: End-to-end model inference throughput and latency
• Communication-Level: NCCL collective operations and inter-GPU communication

• Unified Adapter Interface - Consistent API across all test types and frameworks
• Extensible Architecture - Easy to add new test types, frameworks, and metrics
• Comprehensive Metrics - Scalar values, time-series data, custom measurements
• Framework Agnostic - Support for InfiniLM, vLLM, InfiniCore, and more
• Production Ready - Robust error handling, logging, and result aggregation

For detailed guides, configuration, and examples, see the full documentation.

• Installation Guide - Prerequisites and dependencies
• Configuration - Input format and parameters
• Development Guide - Development setup and extending the framework

Contributions are welcome! Please see our Contributing Guide for details.

1. Fork the repository
2. Create your feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

This project is licensed under the MIT License - see the LICENSE file for details.