Fix: preserve full task IDs for swimlane DAG nodes

[indigo1973]

Summary

• record complete dummy task IDs in a2a3 and a5 scheduler phase data
• render dummy and alloc DAG nodes on AICPU lanes in Worker View
• connect dependency flows to those nodes using complete task identity
• distinguish tasks with the same local ID on different rings

Testing

• python -m pytest tests/ut/py/test_swimlane_converter.py -q (14 passed)
• python -m ruff check simpler_setup/tools/swimlane_converter.py tests/ut/py/test_swimlane_converter.py
• python -m pyright simpler_setup/tools/swimlane_converter.py tests/ut/py/test_swimlane_converter.py
• pip install --no-build-isolation -e . (a2a3/a5 runtime build)
• hardware tests (not run)

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📝 Walkthrough

Walkthrough

The change adds full DummyTask identities to scheduler-phase records and uses them, along with orchestrator allocation metadata, to anchor dependency flows on AICPU worker slices in generated Perfetto traces. Documentation and regression tests describe and verify the updated behavior.

Changes

Dummy and alloc dependency flow anchoring

Layer / File(s)	Summary
Full task identity record contract src/a2a3/platform/include/..., src/a5/platform/include/...	Scheduler-phase APIs and fixed-size records now carry full PTO2 task identities for DummyTask records.
Scheduler recording and export src/a2a3/runtime/..., src/a5/runtime/..., src/common/platform/shared/...	Dummy task dispatch records full identifiers, the collector stores them, and JSON export emits them for dummy phases.
Synthetic worker flow endpoints simpler_setup/tools/swimlane_converter.py	Dependency flows can use synthetic AICPU worker anchors for scheduler dummy tasks and orchestrator allocations.
Trace behavior documentation and tests docs/dfx/l2-swimlane-profiling.md, tests/ut/py/test_swimlane_converter.py	Documentation and tests cover full task identities, worker-slice anchoring, and generated dummy/alloc dependency flows.

Estimated code review effort: 4 (Complex) | ~45 minutes

Sequence Diagram(s)

sequenceDiagram
  participant SchedulerContext
  participant L2SwimlaneCollector
  participant swimlane_converter
  participant Perfetto
  SchedulerContext->>L2SwimlaneCollector: record DummyTask task_id
  L2SwimlaneCollector->>swimlane_converter: export DummyTask task_id
  swimlane_converter->>swimlane_converter: create dummy/alloc worker anchors
  swimlane_converter->>Perfetto: emit dependency flow endpoints

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Possibly related PRs

• hw-native-sys/simpler#942: Introduces the scheduler-phase record and API structure extended here with full dummy task identities.
• hw-native-sys/simpler#1204: Also changes dependency-flow anchoring in the swimlane converter and related documentation/tests.
• hw-native-sys/simpler#1300: Overlaps directly in the converter’s dependency-flow anchoring implementation.

Poem

A bunny watched the dummy flow,
With full task IDs in tow.
Worker slices caught each thread,
Alloc arrows found their bed.
Perfetto hops in rows of blue!

🚥 Pre-merge checks | ✅ 4 | ❌ 1

❌ Failed checks (1 warning)

Check name	Status	Explanation	Resolution
Docstring Coverage	⚠️ Warning	Docstring coverage is 46.67% which is insufficient. The required threshold is 80.00%.	Write docstrings for the functions missing them to satisfy the coverage threshold.

✅ Passed checks (4 passed)

Check name	Status	Explanation
Title check	✅ Passed	The title clearly summarizes the main change: preserving full task IDs for swimlane DAG nodes.
Description check	✅ Passed	The description matches the changeset and its goals around full task IDs, DAG node rendering, and dependency flows.
Linked Issues check	✅ Passed	Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check	✅ Passed	Check skipped because no linked issues were found for this pull request.

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[gemini-code-assist]

Code Review

This pull request updates the swimlane profiling and trace generation to use the full 64-bit task_id instead of the low 32-bit tasks_processed for dummy tasks and alloc DAG nodes, allowing dependency flow arrows to anchor correctly on AICPU worker slices. The changes span documentation, the Python trace converter, C++ runtime schedulers, and unit tests. Feedback in the review suggests adding a fallback to the low 32-bit task ID from tasks_processed for backward compatibility with older trace files that lack the task_id field, preventing dummy tasks from being labeled as 'unknown'.

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