gpullama-nsys-analysis

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

1. Pick a focused GPULlama3 command and a CUDA backend run.
2. Use a prompt/flag combination that reaches the phase being studied.
3. Capture a trace under a timestamped artifact directory.
4. Run targeted nsys stats reports.
5. 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.