agent/profiling.md

Profiling: nsys first, ncu second

They answer different questions. Reaching for ncu too early is the standard mistake.

tool	question it answers
nsys	Is the time even inside a kernel? Launch gaps, dispatch overhead, H2D/D2H stalls, missing overlap, stream serialization.
ncu	Given that the time is in kernel K, which resource is saturated and why.

A real case from this repo: an eager reference measured 185 ms wall against 2.06 ms GPU-busy. nsys shows that in one screen. ncu would have reported a perfectly healthy kernel and told you nothing.

Permissions — this WILL bite first

==ERROR== ERR_NVGPUCTRPERM - The user does not have permission to access NVIDIA GPU Performance Counters

GPU performance counters are privileged. Either:

• run the container with --cap-add SYS_ADMIN (verified working), or
• have the host set NVreg_RestrictProfilingToAdminUsers=0 in the nvidia kernel module options, which fixes it for everyone with no per-container flag.

ncu --version succeeding proves nothing — it does not touch counters. Test with a real metric.

nsys

nsys profile -o /tmp/prof --force-overwrite true --stats=true \
     --trace=cuda,nvtx,osrt python3 my_bench.py
nsys stats --report cuda_gpu_kern_sum /tmp/prof.nsys-rep     # per-kernel totals
nsys stats --report cuda_gpu_trace   /tmp/prof.nsys-rep      # the timeline

What to look for:

• Gaps between kernels — dispatch-bound. Fix with CUDA Graphs, fewer launches, or fusion.
• GPU idle while CPU is busy — python/host overhead, not a kernel problem.
• Kernels not overlapping that should — stream/dependency issue.
• Sum of kernel time << wall time — the kernel is not your problem yet.

Annotate regions with torch.cuda.nvtx.range_push/pop so the timeline is readable.

ncu

Target one kernel; do not --set full by default (it is slow enough to become its own problem).

ncu --target-processes all \
    --kernel-name regex:my_kernel --launch-skip 5 --launch-count 3 \
    --section SpeedOfLight --section MemoryWorkloadAnalysis \
    --section WarpStateStats --section Occupancy \
    -o /tmp/rep python3 my_bench.py
ncu -i /tmp/rep.ncu-rep --page details

Add -lineinfo at compile time (nvcc -lineinfo; Triton emits it) to get per-source-line stall attribution — the single most useful ncu feature and the one most often left off.

metric → conclusion

observation	metric	conclusion
SM high, DRAM low	sm__throughput.avg.pct_of_peak_sustained_elapsed	compute-bound → tensor cores, better instruction mix, less redundant work
DRAM high, SM low	gpu__dram_throughput.avg.pct_of_peak_sustained_elapsed	bandwidth-bound → cut traffic, fuse passes, improve reuse
both low	—	latency-bound → read stall reasons below
↳ memory latency	smsp__pcsamp_warps_issue_stalled_long_scoreboard	more loads in flight: cp.async/TMA, deeper pipeline, unroll
↳ sync	smsp__pcsamp_warps_issue_stalled_barrier	fewer __syncthreads, warp specialization
↳ smem/SFU pressure	smsp__pcsamp_warps_issue_stalled_mio_throttle	fewer smem ops, cut transcendentals
↳ dependency chain	smsp__pcsamp_warps_issue_stalled_wait	more ILP, unroll, independent accumulators
uncoalesced access	l1tex__t_sectors_per_request.avg	fix layout / access pattern (ideal is 4 sectors per 32-thread request for 32-bit)
bank conflicts	l1tex__data_bank_conflicts_pipe_lsu_mem_shared	swizzle the shared-memory layout
low occupancy	sm__warps_active.avg.pct_of_peak_sustained_active	find the limiter: registers, smem, or block size
register spills	launch__registers_per_thread + SASS LDL/STL	cut live values, smaller tile
tensor cores idle	sm__pipe_tensor_op_hmma_cycles_active…	the MMA you think you issued did not issue

tools/profile.sh collects this set and prints the diagnosis rather than the report.

ncu gotchas

• Never time under ncu. It serializes and replays kernels; wall time under the profiler is meaningless.
• Kernel replay breaks stateful kernels — persistent kernels, cross-launch atomics, anything with side effects. Use --replay-mode application (replays the whole process) or range replay.
• Autotuned frameworks compile many variants; use --launch-skip to get past warmup so you profile the steady-state kernel, not a first-call outlier.
• --clock-control none if you are comparing against un-profiled timings; by default ncu locks clocks.