multi-GPU containerization support #8
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Pull Request Overview
This PR introduces comprehensive multi-GPU Docker containerization support for Quantum Computing 101, adding CPU-only, NVIDIA CUDA, and AMD ROCm variants with complete orchestration capabilities and updated dependencies.
- Complete Docker containerization system with multi-stage builds for optimal image sizes
- GPU acceleration support for both NVIDIA CUDA 12.6 and AMD ROCm 6.x platforms
- Modular requirements system and updated dependency versions including Qiskit 1.0+
Reviewed Changes
Copilot reviewed 19 out of 19 changed files in this pull request and generated 3 comments.
Show a summary per file
| File | Description |
|---|---|
| setup.py | Updated Python version requirements and package description |
| examples/requirements.txt | Updated core dependencies to latest versions |
| examples/requirements-core.txt | Updated minimal dependency set with latest versions |
| docker/run.sh | Comprehensive container runner with GPU support and interactive features |
| docker/requirements/*.txt | Modular requirements split by container variant |
| docker/docker-compose.yml | Complete orchestration for multi-service deployment |
| docker/build.sh | Intelligent build script with hardware detection |
| docker/README.md | Comprehensive documentation for Docker setup |
| docker/Dockerfile.* | Multi-stage Dockerfiles for different variants |
| README.md | Updated documentation with Docker installation options |
| CHANGELOG.md | Version 2.0.0 release notes |
| BEGINNERS_GUIDE.md | Updated setup instructions with Docker options |
| .dockerignore | Docker build optimization file |
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| # PyTorch with CUDA support (Updated to PyTorch 2.2+ with CUDA 12.1) | ||
| --index-url https://download.pytorch.org/whl/cu121 | ||
| torch>=2.2.0+cu121 | ||
| torchvision>=0.17.0+cu121 | ||
| torchaudio>=2.2.0+cu121 |
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Using cu121 index while claiming CUDA 12.6 support creates a version mismatch. Either use cu126 index URL or adjust the CUDA version in the Dockerfile to match cu121.
| # PyTorch with CUDA support (Updated to PyTorch 2.2+ with CUDA 12.1) | |
| --index-url https://download.pytorch.org/whl/cu121 | |
| torch>=2.2.0+cu121 | |
| torchvision>=0.17.0+cu121 | |
| torchaudio>=2.2.0+cu121 | |
| # PyTorch with CUDA support (Updated to PyTorch 2.2+ with CUDA 12.6) | |
| --index-url https://download.pytorch.org/whl/cu126 | |
| torch>=2.2.0+cu126 | |
| torchvision>=0.17.0+cu126 | |
| torchaudio>=2.2.0+cu126 |
| # Stage 1: Base ROCm environment (Updated to latest ROCm 6.x with PyTorch) | ||
| FROM rocm/pytorch:latest as rocm-base |
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Using 'latest' tag in production Dockerfiles is not recommended as it can lead to unpredictable builds. Pin to a specific ROCm version like 'rocm6.0-pytorch2.1.0-ubuntu22.04'.
| # Stage 1: Base ROCm environment (Updated to latest ROCm 6.x with PyTorch) | |
| FROM rocm/pytorch:latest as rocm-base | |
| # Stage 1: Base ROCm environment (Pinned to ROCm 6.0, PyTorch 2.1.0, Ubuntu 22.04) | |
| FROM rocm/pytorch:rocm6.0-pytorch2.1.0-ubuntu22.04 as rocm-base |
| author="Quantum Computing 101 Team", | ||
| author_email="aicomputing101@gmail.com", | ||
| description="A comprehensive quantum computing education platform with 40 hands-on examples", | ||
| description="A comprehensive quantum computing education platform with 45 hands-on examples and Docker support", |
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The description claims 45 examples but the PR title and some documentation references suggest this is about containerization support. Verify the actual number of examples is 45 or update the description accordingly.
| description="A comprehensive quantum computing education platform with 45 hands-on examples and Docker support", | |
| description="A comprehensive quantum computing education platform with hands-on examples and containerization (Docker) support", |
📋 Description
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Thank you for contributing to Quantum Computing 101! 🚀⚛️