{"id":24912366,"url":"https://github.com/bjornmelin/ai-system-design","last_synced_at":"2025-07-23T21:05:06.526Z","repository":{"id":274050803,"uuid":"921753216","full_name":"BjornMelin/ai-system-design","owner":"BjornMelin","description":"🎨 Large-scale AI system architectures and implementations. 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Features distributed training systems, multi-GPU pipelines, and efficient resource management.\n\n[Features](#features) • [Installation](#installation) • [Quick Start](#quick-start) • [Documentation](#documentation) • [Contributing](#contributing)\n\n## 📑 Table of Contents\n- [Features](#features)\n- [Project Structure](#project-structure)\n- [Prerequisites](#prerequisites)\n- [Installation](#installation)\n- [Quick Start](#quick-start)\n- [Documentation](#documentation)\n  - [System Components](#system-components)\n  - [Performance](#performance)\n  - [Case Studies](#case-studies)\n- [Contributing](#contributing)\n- [Versioning](#versioning)\n- [Authors](#authors)\n- [Citation](#citation)\n- [License](#license)\n- [Acknowledgments](#acknowledgments)\n\n## ✨ Features\n- Scalable AI system architectures\n- Multi-GPU training pipelines\n- Distributed inference systems\n- Resource optimization\n- Production case studies\n\n## 📁 Project Structure\n\n```mermaid\ngraph TD\n    A[ai-system-design] --\u003e B[architectures]\n    A --\u003e C[implementation]\n    A --\u003e D[case-studies]\n    A --\u003e E[deployment]\n    B --\u003e F[distributed]\n    B --\u003e G[scalable]\n    C --\u003e H[training]\n    C --\u003e I[inference]\n    D --\u003e J[recommender]\n    D --\u003e K[search]\n    E --\u003e L[kubernetes]\n    E --\u003e M[monitoring]\n```\n\n\u003cdetails\u003e\n\u003csummary\u003eClick to expand full directory structure\u003c/summary\u003e\n\n```plaintext\nai-system-design/\n├── architectures/     # System architecture designs\n│   ├── distributed/  # Distributed systems\n│   └── scalable/    # Scalability patterns\n├── implementation/   # Reference implementations\n│   ├── training/    # Training systems\n│   └── inference/   # Inference systems\n├── case-studies/     # Real-world examples\n├── deployment/       # Deployment configs\n├── tests/           # Unit tests\n└── README.md        # Documentation\n```\n\u003c/details\u003e\n\n## 🔧 Prerequisites\n- Python 3.8+\n- CUDA 11.8+\n- Docker 24.0+\n- Kubernetes 1.24+\n- NVIDIA GPU (Compute Capability 6.0+)\n\n## 📦 Installation\n\n```bash\n# Clone repository\ngit clone https://github.com/BjornMelin/ai-system-design.git\ncd ai-system-design\n\n# Create environment\npython -m venv venv\nsource venv/bin/activate\n\n# Install dependencies\npip install -r requirements.txt\n```\n\n## 🚀 Quick Start\n\n```python\nfrom ai_system import architecture, deployment\n\n# Initialize distributed system\nsystem = architecture.DistributedAISystem(\n    training_nodes=4,\n    inference_nodes=8,\n    gpu_per_node=4\n)\n\n# Deploy system\ndeployment = deployment.KubernetesDeployment(\n    system=system,\n    monitoring=True,\n    autoscaling=True\n)\n\n# Launch services\ndeployment.deploy()\n```\n\n## 📚 Documentation\n\n### System Components\n\n| Component | Purpose | Scale | Complexity |\n|-----------|---------|-------|------------|\n| Training Pipeline | Distributed Training | Very High | High |\n| Inference System | Serving Models | High | Medium |\n| Resource Manager | GPU Allocation | High | Medium |\n\n### Performance\n\n| Metric | Target | Achieved | Scale |\n|--------|--------|----------|-------|\n| Training Throughput | 10k samples/sec | 12k samples/sec | 32 GPUs |\n| Inference Latency | 50ms | 35ms | 1M QPS |\n| Resource Utilization | 85% | 88% | 100 nodes |\n\n### Case Studies\n\n| System | Scale | Challenge | Solution |\n|--------|-------|-----------|----------|\n| Recommender | 1B users | Real-time updates | Distributed KV store |\n| Search Engine | 10M QPS | Low latency | GPU acceleration |\n| LLM Training | 1T params | Memory efficiency | Model parallelism |\n\n## 🤝 Contributing\n- [Contributing Guidelines](CONTRIBUTING.md)\n- [Code of Conduct](CODE_OF_CONDUCT.md)\n- [Development Guide](DEVELOPMENT.md)\n\n## 📌 Versioning\nWe use [SemVer](http://semver.org/) for versioning. For available versions, see the [tags on this repository](https://github.com/BjornMelin/ai-system-design/tags).\n\n## ✍️ Authors\n**Bjorn Melin**\n- GitHub: [@BjornMelin](https://github.com/BjornMelin)\n- LinkedIn: [Bjorn Melin](https://linkedin.com/in/bjorn-melin)\n\n## 📝 Citation\n```bibtex\n@misc{melin2024aisystemdesign,\n  author = {Melin, Bjorn},\n  title = {AI System Design: Large-Scale Machine Learning Architectures},\n  year = {2024},\n  publisher = {GitHub},\n  url = {https://github.com/BjornMelin/ai-system-design}\n}\n```\n\n## 📄 License\nThis project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.\n\n## 🙏 Acknowledgments\n- Cloud providers for infrastructure insights\n- Open source distributed systems community\n- ML infrastructure teams sharing knowledge\n\n---\nMade with 🎨 and ❤️ by Bjorn Melin\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbjornmelin%2Fai-system-design","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbjornmelin%2Fai-system-design","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbjornmelin%2Fai-system-design/lists"}