Add nsys profile plotter and improve documentation

docs/user/images/nsys_kernel_profile_example.png.license

@@ -0,0 +1,2 @@
+SPDX-FileCopyrightText: 2026 CERN
+SPDX-License-Identifier: CC-BY-4.0

docs/user/images/nsys_species_pies_example.png.license

@@ -0,0 +1,2 @@
+SPDX-FileCopyrightText: 2026 CERN
+SPDX-License-Identifier: CC-BY-4.0

docs/user/profiling.md

@@ -52,7 +52,7 @@ Run `nsys` with the CUDA profiler API capture range:
 ```console
 nsys profile --capture-range=cudaProfilerApi --capture-range-end=stop \
   --trace=cuda,nvtx --sample=none --cpuctxsw=none \
-  --stats=true --force-overwrite=true \
+  --stats=true --export=sqlite --force-overwrite=true \
   --output adept_transport_profile \
   <application command>
 ```
@@ -63,6 +63,73 @@ Open the report with:
 nsys-ui adept_transport_profile.nsys-rep
 ```
 
+### Plotting AdePT kernel profiles
+
+The exported SQLite file can be summarized with the AdePT profile plotting
+script:
+
+```console
+python3 scripts/plot_adept_nsys_profile.py \
+  --sqlite adept_transport_profile.sqlite \
+  --output-prefix adept_transport_profile \
+  --title "AdePT"
+```
+
+This writes:
+
+- `adept_transport_profile_kernel_profile.png`: total CUDA kernel times,
+  transport shares by particle type, the waited kernel category that most often
+  reaches the end of an AdePT transport iteration, and the corresponding
+  critical-path margin in milliseconds.
+- `adept_transport_profile_species_pies.png`: per-species pie charts showing
+  which split kernels dominate electron, positron, and gamma transport.
+- `adept_transport_profile.txt` plus CSV files with the numeric summaries.
+
+The percentages labelled as "all kernels" are normalized to all CUDA kernels in
+the captured range, including injection, population statistics, and bookkeeping.
+The percentages labelled as "transport" are normalized only to electron,
+positron, and gamma transport kernels.
+
+The limiter plots use the latest-ending waited non-`FinishIteration` CUDA
+kernel before `FinishIteration` as the limiting category. `InitTracks` kernels
+are excluded from this limiter view because they run on a separate injection
+stream and `FinishIteration` does not directly wait for them; they remain visible
+in the total CUDA kernel-time view. The count view shows how often each waited
+category is last. The critical-margin view credits only the time by which that
+latest kernel extends the iteration beyond the runner-up latest kernel, capped
+by the latest kernel's own duration.
+
+```{figure} images/nsys_kernel_profile_example.png
+:name: fig-nsys-kernel-profile-example
+:alt: Example AdePT Nsight Systems kernel profile summary plot.
+:align: center
+:width: 95%
+
+Example kernel summary from an AdePT split-kernel `nsys` profile.
+```
+
+The example above was produced from a CMSSW ttbar simulation. It illustrates why
+both the total kernel-time view and the limiter view are useful: gamma transport
+accounts for about 25% of all CUDA kernel time and about 27% of transport kernel
+time, but gamma kernels almost never determine the end of the transport
+iteration in this profile. Electrons and positrons dominate the waited
+last-kernel counts, and electrons alone account for most of the critical-path
+margin. This means that reducing the gamma workload, for example with Russian
+roulette, is not expected to improve the iteration wall time unless the gamma
+kernels become the latest waited path. Conversely, `InitTracks` is visible as a
+non-negligible total kernel-time bucket, but it is intentionally excluded from
+the limiter view because it runs asynchronously on the injection stream.
+
+```{figure} images/nsys_species_pies_example.png
+:name: fig-nsys-species-pies-example
+:alt: Example AdePT Nsight Systems per-species transport kernel pie charts.
+:align: center
+:width: 95%
+
+Example per-species transport-kernel summary from the same kind of AdePT
+split-kernel `nsys` profile.
+```
+
 ## Nsight Compute
 
 `ncu` is the tool for detailed kernel analysis: register count, achieved