{
  "id": "lib-process:data-science-ml--distributed-training",
  "_kind": "LibraryProcess",
  "_file": "generated-library/processes.yaml",
  "_cluster": "generated-library",
  "attributes": {
    "displayName": "distributed-training",
    "description": "Distributed Training Orchestration - Design and execute distributed training strategies for large-scale ML models\nwith resource allocation, parallelization strategy, fault tolerance, and performance optimization across multiple nodes/GPUs.",
    "libraryPath": "library/specializations/data-science-ml/distributed-training.js",
    "specialization": "data-science-ml",
    "references": [
      "- PyTorch Distributed Training: https://pytorch.org/tutorials/beginner/dist_overview.html\n- TensorFlow Distributed Strategies: https://www.tensorflow.org/guide/distributed_training\n- Horovod Framework: https://horovod.readthedocs.io/\n- DeepSpeed: https://www.deepspeed.ai/\n- Ray Train: https://docs.ray.io/en/latest/train/train.html\n- Model Parallelism Patterns: https://arxiv.org/abs/1909.08053"
    ],
    "example": "const result = await orchestrate('specializations/data-science-ml/distributed-training', {\n  projectName: 'Large Language Model Training',\n  modelArchitecture: 'Transformer with 7B parameters',\n  datasetSize: '500GB text corpus',\n  trainingObjective: 'Pre-train language model from scratch',\n  availableResources: { gpus: 32, nodes: 4, memory: '2TB', storage: '10TB' }\n});",
    "usesAgents": [
      "general-purpose"
    ]
  },
  "outgoingEdges": [
    {
      "from": "lib-process:data-science-ml--distributed-training",
      "to": "domain:data-science",
      "kind": "lib_applies_to_domain",
      "attributes": {
        "weight": 1
      }
    },
    {
      "from": "lib-process:data-science-ml--distributed-training",
      "to": "workflow:data-pipeline-deployment",
      "kind": "lib_implements_workflow",
      "attributes": {
        "weight": 1
      }
    },
    {
      "from": "lib-process:data-science-ml--distributed-training",
      "to": "specialization:data-science-ml",
      "kind": "lib_belongs_to_specialization",
      "attributes": {
        "weight": 0.9
      }
    }
  ],
  "incomingEdges": []
}