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perf(features): parallelize boundary detection with bounded CPU workers - #148
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Boundary detection previously queried and evaluated every point on the caller.
feature-boundarynow shares one KD-tree across bounded scoped CPU workers, reuses angular scratch per worker and writes disjoint bands directly into the final mask. Small/one-worker clouds remain serial; public signatures, per-point math, selected point order, schema, attributes and metadata are preserved.Validation: 1,081,992 exact decisions against the frozen serial API; independent full planar rim and degenerate/normal cases; all six gathered buffer types including signed-zero/NaN words; validation, empty shortcuts and concurrent calls. Seven minimal and nineteen all-feature native tests plus one facade smoke pass. Strict minimal/all-feature Clippy, crate/facade WASM compilation, formatting and diff checks pass.
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boundary_maskmeasurements use twelve conditions, two warmups and twenty rotating paired rounds. All six 32,768/65,536-point conditions favor bounded public staging by 1.45–2.66x. An adverse 16,384-point curved one-worker control (~7% slower) is retained in the notes; small-input neutrality and fixed cross-machine speedups are not claimed. Attribute gathering is outside the measured API.Measurement details:
notes/2026-10-12_parallel_boundary_detection.md.