II.
LibraryProcess JSON
Structured · livelib-process:gpu-programming--tensor-core-programming
specializations/gpu-programming/tensor-core-programming json
Inspect the normalized record payload exactly as the atlas UI reads it.
{
"id": "lib-process:gpu-programming--tensor-core-programming",
"_kind": "LibraryProcess",
"_file": "generated-library/processes.yaml",
"_cluster": "generated-library",
"attributes": {
"displayName": "specializations/gpu-programming/tensor-core-programming",
"description": "Tensor Core Programming - Workflow for utilizing NVIDIA Tensor Cores for accelerated\nmatrix multiply-accumulate operations in deep learning and HPC applications.",
"libraryPath": "library/specializations/gpu-programming/tensor-core-programming.js",
"specialization": "gpu-programming",
"references": [
"- WMMA API: https://docs.nvidia.com/cuda/cuda-c-programming-guide/",
"- Tensor Core Programming: https://developer.nvidia.com/blog/programming-tensor-cores-cuda-9/",
"- CUTLASS: https://github.com/NVIDIA/cutlass"
],
"example": "const result = await orchestrate('specializations/gpu-programming/tensor-core-programming', {\n projectName: 'transformer_attention',\n matrixOperation: 'batched_gemm',\n precision: 'fp16',\n useWmma: true\n});",
"usesAgents": [
"tensor-core-specialist"
]
},
"outgoingEdges": [
{
"from": "lib-process:gpu-programming--tensor-core-programming",
"to": "skill-area:cuda-kernels",
"kind": "lib_requires_skill_area",
"attributes": {
"weight": 1
}
},
{
"from": "lib-process:gpu-programming--tensor-core-programming",
"to": "skill-area:compute-shaders",
"kind": "lib_requires_skill_area",
"attributes": {
"weight": 0.7
}
},
{
"from": "lib-process:gpu-programming--tensor-core-programming",
"to": "domain:scientific-computing",
"kind": "lib_applies_to_domain",
"attributes": {
"weight": 1
}
},
{
"from": "lib-process:gpu-programming--tensor-core-programming",
"to": "role:computational-scientist",
"kind": "lib_involves_role",
"attributes": {
"weight": 1
}
},
{
"from": "lib-process:gpu-programming--tensor-core-programming",
"to": "role:ml-engineer",
"kind": "lib_involves_role",
"attributes": {
"weight": 0.7
}
},
{
"from": "lib-process:gpu-programming--tensor-core-programming",
"to": "workflow:performance-profiling-cycle",
"kind": "lib_implements_workflow",
"attributes": {
"weight": 1
}
},
{
"from": "lib-process:gpu-programming--tensor-core-programming",
"to": "specialization:gpu-programming",
"kind": "lib_belongs_to_specialization",
"attributes": {
"weight": 1
}
},
{
"from": "lib-process:gpu-programming--tensor-core-programming",
"to": "lib-agent:gpu-programming--tensor-core-specialist",
"kind": "uses_agent",
"attributes": {
"weight": 0.8
}
}
],
"incomingEdges": []
}