II.
LibraryProcess JSON
Structured · livelib-process:gpu-programming--dynamic-parallelism-implementation
specializations/gpu-programming/dynamic-parallelism-implementation json
Inspect the normalized record payload exactly as the atlas UI reads it.
{
"id": "lib-process:gpu-programming--dynamic-parallelism-implementation",
"_kind": "LibraryProcess",
"_file": "generated-library/processes.yaml",
"_cluster": "generated-library",
"attributes": {
"displayName": "specializations/gpu-programming/dynamic-parallelism-implementation",
"description": "Dynamic Parallelism Implementation - Process for utilizing CUDA dynamic parallelism to launch\nkernels from device code, enabling recursive and adaptive algorithms.",
"libraryPath": "library/specializations/gpu-programming/dynamic-parallelism-implementation.js",
"specialization": "gpu-programming",
"references": [
"- Dynamic Parallelism: https://docs.nvidia.com/cuda/cuda-c-programming-guide/",
"- Nested Parallelism: https://developer.nvidia.com/blog/introduction-cuda-dynamic-parallelism/"
],
"example": "const result = await orchestrate('specializations/gpu-programming/dynamic-parallelism-implementation', {\n projectName: 'adaptive_mesh_refinement',\n algorithmType: 'recursive',\n maxNestingDepth: 4,\n recursivePattern: 'quadtree'\n});",
"usesAgents": [
"cuda-kernel-expert",
"gpu-performance-engineer"
]
},
"outgoingEdges": [
{
"from": "lib-process:gpu-programming--dynamic-parallelism-implementation",
"to": "skill-area:cuda-kernels",
"kind": "lib_requires_skill_area",
"attributes": {
"weight": 1
}
},
{
"from": "lib-process:gpu-programming--dynamic-parallelism-implementation",
"to": "skill-area:compute-shaders",
"kind": "lib_requires_skill_area",
"attributes": {
"weight": 0.7
}
},
{
"from": "lib-process:gpu-programming--dynamic-parallelism-implementation",
"to": "skill-area:profiling-cuda",
"kind": "lib_requires_skill_area",
"attributes": {
"weight": 0.5
}
},
{
"from": "lib-process:gpu-programming--dynamic-parallelism-implementation",
"to": "domain:scientific-computing",
"kind": "lib_applies_to_domain",
"attributes": {
"weight": 1
}
},
{
"from": "lib-process:gpu-programming--dynamic-parallelism-implementation",
"to": "role:computational-scientist",
"kind": "lib_involves_role",
"attributes": {
"weight": 1
}
},
{
"from": "lib-process:gpu-programming--dynamic-parallelism-implementation",
"to": "role:ml-engineer",
"kind": "lib_involves_role",
"attributes": {
"weight": 0.7
}
},
{
"from": "lib-process:gpu-programming--dynamic-parallelism-implementation",
"to": "workflow:performance-profiling-cycle",
"kind": "lib_implements_workflow",
"attributes": {
"weight": 1
}
},
{
"from": "lib-process:gpu-programming--dynamic-parallelism-implementation",
"to": "specialization:gpu-programming",
"kind": "lib_belongs_to_specialization",
"attributes": {
"weight": 1
}
},
{
"from": "lib-process:gpu-programming--dynamic-parallelism-implementation",
"to": "lib-agent:gpu-programming--cuda-kernel-expert",
"kind": "uses_agent",
"attributes": {
"weight": 0.8
}
},
{
"from": "lib-process:gpu-programming--dynamic-parallelism-implementation",
"to": "lib-agent:gpu-programming--gpu-performance-engineer",
"kind": "uses_agent",
"attributes": {
"weight": 0.8
}
}
],
"incomingEdges": []
}