| name | gpullama-nsys-analysis |
| description | Nsight Systems workflow for GPULlama3/TornadoVM CUDA runs. Use to capture CUDA timelines, summarize kernel/API/memcpy time, identify hot kernels, launch overhead, syncs, and GPU idle behavior.
|
| tags | ["gpullama","nsys","profiling"] |
| license | Apache-2.0 |
GPULlama3 Nsight Systems Analysis
When To Use
Use nsys when you need the system-level picture:
- which CUDA kernels dominate total time
- whether launch overhead is significant
- whether memory copies or synchronization are visible
- whether GPU is idle between kernels
- whether native CUDA libraries appear in the timeline
Do not use nsys for detailed per-kernel SOL/occupancy/warp-stall diagnosis. Use gpullama-ncu-analysis after identifying a hot kernel.
Workflow
- Pick a focused GPULlama3 command and a CUDA backend run.
- Use a prompt/flag combination that reaches the phase being studied.
- Capture a trace under a timestamped artifact directory.
- Run targeted
nsys stats reports.
- Classify the bottleneck before recommending changes.
Useful reports:
nsys stats -r cuda_gpu_kern_sum,cuda_api_sum,cuda_gpu_mem_time_sum <trace.nsys-rep>
nsys analyze -r all <trace.nsys-rep>
When CUDA libraries are involved and traced:
nsys stats -r cublas_api_sum,cudnn_api_sum <trace.nsys-rep>
Interpretation
Classify:
- hot generated kernel dominates: use
gpullama-ncu-analysis
- many small kernels / high launch API time: launch-overhead-bound
- high memcpy time: transfer-bound or persistence issue
- high synchronization API time: sync-bound
- GPU gaps: host/TornadoVM scheduling or graph/persistence issue
- cuBLAS/cuDNN dominates: inspect native library call shape and stream behavior
Report
Include:
- exact profile command
- exact GPULlama3 command
- trace path
- top kernels by total GPU time
- CUDA API summary
- memory transfer summary
- bottleneck classification
- next action
Every numeric claim must cite nsys stats, nsys analyze, or a parsed trace artifact.
