II.
LibraryAgent JSON
Structured · livelib-agent:gpu-programming--gpu-performance-engineer
gpu-performance-engineer json
Inspect the normalized record payload exactly as the atlas UI reads it.
{
"id": "lib-agent:gpu-programming--gpu-performance-engineer",
"_kind": "LibraryAgent",
"_file": "generated-library/agents.yaml",
"_cluster": "generated-library",
"attributes": {
"displayName": "gpu-performance-engineer",
"description": "Expert agent for GPU performance analysis and optimization. Specialist in Nsight profiling, roofline model analysis, occupancy optimization, memory bandwidth optimization, and architecture-specific tuning.",
"libraryPath": "library/specializations/gpu-programming/agents/gpu-performance-engineer/AGENT.md",
"specialization": "gpu-programming"
},
"outgoingEdges": [
{
"from": "lib-agent:gpu-programming--gpu-performance-engineer",
"to": "skill-area:cuda-kernels",
"kind": "lib_requires_skill_area",
"attributes": {
"weight": 1
}
},
{
"from": "lib-agent:gpu-programming--gpu-performance-engineer",
"to": "skill-area:compute-shaders",
"kind": "lib_requires_skill_area",
"attributes": {
"weight": 0.7
}
},
{
"from": "lib-agent:gpu-programming--gpu-performance-engineer",
"to": "domain:scientific-computing",
"kind": "lib_applies_to_domain",
"attributes": {
"weight": 1
}
},
{
"from": "lib-agent:gpu-programming--gpu-performance-engineer",
"to": "role:computational-scientist",
"kind": "lib_involves_role",
"attributes": {
"weight": 1
}
},
{
"from": "lib-agent:gpu-programming--gpu-performance-engineer",
"to": "role:ml-engineer",
"kind": "lib_involves_role",
"attributes": {
"weight": 0.7
}
},
{
"from": "lib-agent:gpu-programming--gpu-performance-engineer",
"to": "specialization:gpu-programming",
"kind": "lib_belongs_to_specialization",
"attributes": {
"weight": 1
}
}
],
"incomingEdges": [
{
"from": "lib-process:gpu-programming--atomic-operations-synchronization",
"to": "lib-agent:gpu-programming--gpu-performance-engineer",
"kind": "uses_agent",
"attributes": {
"weight": 0.8
}
},
{
"from": "lib-process:gpu-programming--cuda-stream-concurrency",
"to": "lib-agent:gpu-programming--gpu-performance-engineer",
"kind": "uses_agent",
"attributes": {
"weight": 0.8
}
},
{
"from": "lib-process:gpu-programming--custom-cuda-operator-development",
"to": "lib-agent:gpu-programming--gpu-performance-engineer",
"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
}
},
{
"from": "lib-process:gpu-programming--gpu-image-video-processing",
"to": "lib-agent:gpu-programming--gpu-performance-engineer",
"kind": "uses_agent",
"attributes": {
"weight": 0.8
}
},
{
"from": "lib-process:gpu-programming--gpu-performance-regression-testing",
"to": "lib-agent:gpu-programming--gpu-performance-engineer",
"kind": "uses_agent",
"attributes": {
"weight": 0.8
}
},
{
"from": "lib-process:gpu-programming--hip-porting-cross-platform",
"to": "lib-agent:gpu-programming--gpu-performance-engineer",
"kind": "uses_agent",
"attributes": {
"weight": 0.8
}
},
{
"from": "lib-process:gpu-programming--occupancy-optimization",
"to": "lib-agent:gpu-programming--gpu-performance-engineer",
"kind": "uses_agent",
"attributes": {
"weight": 0.8
}
},
{
"from": "lib-process:gpu-programming--performance-profiling-analysis",
"to": "lib-agent:gpu-programming--gpu-performance-engineer",
"kind": "uses_agent",
"attributes": {
"weight": 0.8
}
},
{
"from": "lib-process:gpu-programming--reduction-scan-implementation",
"to": "lib-agent:gpu-programming--gpu-performance-engineer",
"kind": "uses_agent",
"attributes": {
"weight": 0.8
}
},
{
"from": "lib-process:gpu-programming--stencil-computation-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--gpu-performance-engineer",
"kind": "uses_agent",
"attributes": {
"weight": 0.8
}
}
]
}