Reduce time profiler memory usage with lazy profile tree

[IlyasShabi]

What does this PR do?:
Introduces a new stopAndCollect function for the time profiler that reduces memory usage during profile serialization. Instead of materializing the entire V8 CPU profile tree as JS objects upfront, the new API resolves children on demand using getters.

This also moves totalHitCount() computation to C++ instead of TS to avoid getting children twice from C++

Motivation:
The current stop() API recursively translates the entire profile tree into JS objects, creating a full copy in heap memory which can be significant for large applications.
The new stopAndCollect() API uses a callback to keep the V8 profile alive while the TS serializer traverses the tree lazily.
Scalar properties are set at creation time, but children are resolved on first access, reducing peak memory usage.

Additional Notes:

• Similar to heap profiling
• Benchmark on CI shows:

* ~99% on initial load which normal since we are not materializing the profiler to JS objects.
* ~52% after traversing the profiler tree to explicitly call getters.
* ~58% after calling afterHitCount() which is moved to c++.

How to test the change?:
Unit tests

[github-actions]

Overall package size

Self size: 1.99 MB
Deduped: 2.34 MB
No deduping: 2.34 MB

Dependency sizes

| name | version | self size | total size | |------|---------|-----------|------------| | source-map | 0.7.6 | 185.63 kB | 185.63 kB | | pprof-format | 2.2.1 | 163.06 kB | 163.06 kB | | node-gyp-build | 3.9.0 | 8.81 kB | 8.81 kB |

_{🤖 This report was automatically generated by heaviest-objects-in-the-universe}

[pr-commenter]

Benchmarks

Benchmark execution time: 2026-03-05 10:33:13

Comparing candidate commit 3ed4376 in PR branch ishabi/lazy-time-profiler with baseline commit 2db9741 in branch main.

Found 0 performance improvements and 0 performance regressions! Performance is the same for 91 metrics, 29 unstable metrics.

[IlyasShabi]

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[chatgpt-codex-connector]

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