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Tonu Samuel 84d900cfda ml: SIMD for KNN brute-force findNearest distance
Vectorize the per-sample squared-Euclidean distance in
BruteForceImpl::findNearestCore with universal intrinsics (two
independent v_fma accumulators + scalar tail). The scalar reduction
accumulates in float in strict order, which the compiler cannot
auto-vectorize without -ffast-math; independent SIMD accumulators
break that serial-accumulation dependency.

Accumulates in float exactly as before (only summation order changes,
~1e-7, below stored float precision); selected neighbors and distances
matched scalar on all test data, ML_KNearest tests pass. Real
findNearest A/B: 3.76x M4, 3.47x Threadripper, 3.73x Xeon, 4.10x A76,
2.82x A55 (in-order).

Adds modules/ml/perf with a findNearest perf test.
2026-06-24 11:31:38 +03:00
2026-06-04 20:26:54 -07:00
2020-02-26 15:12:45 +03:00
2018-10-11 17:57:51 +00:00
2025-08-01 09:50:10 +03:00
2024-03-03 23:37:07 +05:30

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