Add automated deployment and benchmark infrastructure

2.projects/dynamo-inference/.gitignore

@@ -1,42 +1,33 @@
-# Build artifacts
+# Claude Code session data
+.claude/
+
+# Generated deployment YAML files
+deployment/
+
+# Temporary files
 *.log
 *.tmp
-build/
-dist/
-*.egg-info/
+*.swp
 
-# Docker
-.dockerignore
+# Python cache
+__pycache__/
+*.py[cod]
+*$py.class
 
 # IDE
 .vscode/
 .idea/
-*.swp
-*.swo
 
-# OS
-.DS_Store
-Thumbs.db
+# Fix/compatibility scripts
+fix_buildconfig_compat.py
+fix_engine_args_compat.py
+tensorrt_llm_metrics_stub.py
 
-# Python
-__pycache__/
-*.pyc
-*.pyo
-*.pyd
-.Python
-env/
-venv/
-.venv/
-.env
+# Documentation and notes
+gpu-cluster-performance-tests.md
+docs/
 
-# Temporary files
-tmp/
-temp/
-*.backup
-
-# Local workspace files
-.claude/
-.cursor/
-.vscode/settings.json
-.idea/workspace.xml
-.mailmap
+# Library directories
+nccl/
+nixl/
+ucx/

2.projects/dynamo-inference/ATTRIBUTION.md

@@ -1,11 +1,142 @@
-# Third-Party Software Attribution
+# Attribution
 
-This container includes the following open-source components:
+This project incorporates components from various open-source projects. We acknowledge and are grateful to the developers and maintainers of these projects.
 
-- **NIXL** - NVIDIA Inter-node Communication Library
-- **vLLM** - High-performance LLM inference engine  
-- **UCX** - Unified Communication X
-- **libfabric** - OpenFabrics Interface
-- **PyTorch** - Deep learning framework
 
-See individual component licenses in their respective directories.
+---
+
+## NVIDIA Components
+
+### NVIDIA Dynamo
+- **Source:** https://github.com/ai-dynamo/dynamo
+- **License:** Apache License 2.0
+- **Description:** Open-source inference runtime for serving large language models at scale with disaggregated architecture.
+
+### NVIDIA NCCL (NVIDIA Collective Communications Library)
+- **Source:** https://github.com/NVIDIA/nccl
+- **License:** BSD-3-Clause License
+- **Description:** Optimized primitives for inter-GPU communication.
+
+### NVIDIA NIXL (NVIDIA Inference Xfer Library)
+- **Source:** https://github.com/NVIDIA/nixl
+- **License:** Apache License 2.0
+- **Description:** GPU-direct transfer library for efficient KV-cache movement in distributed inference.
+
+### TensorRT-LLM
+- **Source:** https://github.com/NVIDIA/TensorRT-LLM
+- **License:** Apache License 2.0
+- **Description:** High-performance inference library for large language models.
+
+### CUDA Toolkit
+- **Source:** https://developer.nvidia.com/cuda-toolkit
+- **License:** NVIDIA CUDA Toolkit EULA
+- **Description:** GPU computing platform and programming model.
+
+---
+
+## Communication Libraries
+
+### UCX (Unified Communication X)
+- **Source:** https://github.com/openucx/ucx
+- **License:** BSD-3-Clause License
+- **Description:** High-performance communication framework for CPU and GPU memory transfers.
+
+### Libfabric
+- **Source:** https://github.com/ofiwg/libfabric
+- **License:** BSD-2-Clause License
+- **Description:** Core component of the Open Fabrics Interfaces (OFI) framework.
+
+### OpenMPI
+- **Source:** https://github.com/open-mpi/ompi
+- **License:** BSD-3-Clause License
+- **Description:** Open-source Message Passing Interface implementation.
+
+---
+
+## AWS Components
+
+### AWS EFA Installer
+- **Source:** https://github.com/aws/aws-efa-installer
+- **License:** Apache License 2.0
+- **Description:** Installer for Elastic Fabric Adapter drivers and libraries.
+
+### AWS OFI NCCL Plugin
+- **Source:** https://github.com/aws/aws-ofi-nccl
+- **License:** Apache License 2.0
+- **Description:** Plugin to enable NCCL communication over AWS EFA.
+
+---
+
+## Container Base Images
+
+### NVIDIA CUDA Container Images
+- **Source:** https://hub.docker.com/r/nvidia/cuda
+- **License:** NVIDIA Deep Learning Container License
+- **Description:** Official NVIDIA CUDA runtime and development images.
+
+---
+
+## Python Libraries
+
+### vLLM
+- **Source:** https://github.com/vllm-project/vllm
+- **License:** Apache License 2.0
+- **Description:** High-throughput and memory-efficient inference and serving engine for LLMs.
+
+### PyTorch
+- **Source:** https://github.com/pytorch/pytorch
+- **License:** BSD-3-Clause License
+- **Description:** Open-source machine learning framework.
+
+### Transformers (Hugging Face)
+- **Source:** https://github.com/huggingface/transformers
+- **License:** Apache License 2.0
+- **Description:** State-of-the-art machine learning library for PyTorch.
+
+---
+
+## Additional References
+
+### AWS Distributed Training Samples
+- **Source:** https://github.com/aws-samples/awsome-distributed-training
+- **License:** MIT-0 License
+- **Description:** Reference implementations for distributed training on AWS.
+
+---
+
+## License Summary
+
+| Component | License |
+|-----------|---------|
+| NVIDIA Dynamo | Apache-2.0 |
+| NCCL | BSD-3-Clause |
+| NIXL | Apache-2.0 |
+| TensorRT-LLM | Apache-2.0 |
+| UCX | BSD-3-Clause |
+| Libfabric | BSD-2-Clause |
+| OpenMPI | BSD-3-Clause |
+| AWS EFA Installer | Apache-2.0 |
+| AWS OFI NCCL | Apache-2.0 |
+| vLLM | Apache-2.0 |
+| PyTorch | BSD-3-Clause |
+| Transformers | Apache-2.0 |
+
+---
+
+## Contributors
+This project was developed with contributions from:
+
+- **Anton Alexander** - Sr. Specialist, WW Foundation Models
+- **Alex Iankoulski** - Principal WW Specialist SA GenAI
+
+---
+
+## Disclaimer
+
+This project is provided "as is" without warranty of any kind. The use of third-party components is subject to their respective licenses. Users are responsible for ensuring compliance with all applicable licenses when using this software.
+
+For questions about licensing or attribution, please open an issue in the repository.
+
+---
+
+**Last Updated:** November 2025