{
  "id": "lib-process:gpu-programming--warp-efficiency-optimization",
  "_kind": "LibraryProcess",
  "_file": "generated-library/processes.yaml",
  "_cluster": "generated-library",
  "attributes": {
    "displayName": "specializations/gpu-programming/warp-efficiency-optimization",
    "description": "Warp/Wavefront Efficiency Optimization - Workflow for minimizing warp divergence and maximizing\nSIMD efficiency across GPU threads executing in lockstep.",
    "libraryPath": "library/specializations/gpu-programming/warp-efficiency-optimization.js",
    "specialization": "gpu-programming",
    "references": [
      "- Warp Divergence: https://docs.nvidia.com/cuda/cuda-c-best-practices-guide/",
      "- SIMD Efficiency: https://developer.nvidia.com/blog/using-cuda-warp-level-primitives/"
    ],
    "example": "const result = await orchestrate('specializations/gpu-programming/warp-efficiency-optimization', {\n  projectName: 'decision_tree_traversal',\n  targetKernels: ['tree_traverse', 'leaf_compute'],\n  divergenceAnalysis: true\n});",
    "usesAgents": [
      "gpu-performance-engineer",
      "parallel-algorithm-designer"
    ]
  },
  "outgoingEdges": [
    {
      "from": "lib-process:gpu-programming--warp-efficiency-optimization",
      "to": "skill-area:cuda-kernels",
      "kind": "lib_requires_skill_area",
      "attributes": {
        "weight": 1
      }
    },
    {
      "from": "lib-process:gpu-programming--warp-efficiency-optimization",
      "to": "skill-area:compute-shaders",
      "kind": "lib_requires_skill_area",
      "attributes": {
        "weight": 0.7
      }
    },
    {
      "from": "lib-process:gpu-programming--warp-efficiency-optimization",
      "to": "domain:scientific-computing",
      "kind": "lib_applies_to_domain",
      "attributes": {
        "weight": 1
      }
    },
    {
      "from": "lib-process:gpu-programming--warp-efficiency-optimization",
      "to": "role:computational-scientist",
      "kind": "lib_involves_role",
      "attributes": {
        "weight": 1
      }
    },
    {
      "from": "lib-process:gpu-programming--warp-efficiency-optimization",
      "to": "role:ml-engineer",
      "kind": "lib_involves_role",
      "attributes": {
        "weight": 0.7
      }
    },
    {
      "from": "lib-process:gpu-programming--warp-efficiency-optimization",
      "to": "workflow:performance-profiling-cycle",
      "kind": "lib_implements_workflow",
      "attributes": {
        "weight": 1
      }
    },
    {
      "from": "lib-process:gpu-programming--warp-efficiency-optimization",
      "to": "specialization:gpu-programming",
      "kind": "lib_belongs_to_specialization",
      "attributes": {
        "weight": 1
      }
    },
    {
      "from": "lib-process:gpu-programming--warp-efficiency-optimization",
      "to": "lib-agent:gpu-programming--gpu-performance-engineer",
      "kind": "uses_agent",
      "attributes": {
        "weight": 0.8
      }
    },
    {
      "from": "lib-process:gpu-programming--warp-efficiency-optimization",
      "to": "lib-agent:gpu-programming--parallel-algorithm-designer",
      "kind": "uses_agent",
      "attributes": {
        "weight": 0.8
      }
    }
  ],
  "incomingEdges": []
}