Files
OpenNest/docs/performance/fill-verification.md
T
aj 0df2587cf2 perf(fill): reuse offset geometry for translated copies
FillLinear re-prepared offset perimeter geometry (ConvertProgram ->
ShapeProfile -> OffsetOutward) for every part it measured, although
tiled copies share one Program and differ only by Location. A CPU
profile of a 169-part Default job put 62% of wall time there.

Prepare each distinct Program (reference identity) once per public
Fill/FillRow call in local frame, then clone and translate for each
location. The cache is created per call and passed down privately
because FillHelpers.FillPattern calls Fill concurrently on one
instance. PartGeometry gains a local-frame Program overload that the
Part overload now delegates to.

Evaluation order, lazy preparation, fallbacks and tiling are
unchanged. Differential tests against a frozen copy of the previous
FillLinear check bitwise equality, including concurrent calls; Debug
work tests pin preparation counts. With the thread pool capped at one
worker, before/after whole-job layouts are byte-identical. The
Default corpus job median drops from 40,715 to 18,810 ms.
2026-09-26 20:24:34 -04:00

3.1 KiB

Fill performance verification

Opt-in synthetic measurements (OpenNest.Tests/Fill/FillPerformanceTests.cs):

OPENNEST_RUN_FILL_PERF=1 dotnet test OpenNest.Tests/OpenNest.Tests.csproj -c Release \
  --filter 'Category=FillPerformance' --logger 'console;verbosity=detailed'

Only the exact value 1 enables these tests; otherwise they skip; README documents the PowerShell equivalent.

The category covers comparer, group-pattern, rotated-pattern, extents-column, feature-extraction, no-model angle, and FillLinear offset-geometry workloads; individual filters match benchmark method names in FillPerformanceTests.cs. Keep harness, inputs, warmups and batches identical before/after; exclude setup/assertions from timing. Comparer/extents allocations are synchronous and current-thread only; parallel group fills omit allocation totals. No timing CI gates or whole-job speedup claims. Preserve evidence in the measured report.

Debug behavior/skipped-work checks:

dotnet test OpenNest.Tests/OpenNest.Tests.csproj -c Debug \
  --filter 'FullyQualifiedName~DefaultFillComparerWorkTests|FullyQualifiedName~FillHelpersTests|FullyQualifiedName~FillExtentsTests|FullyQualifiedName~StrategyOverlapTests|FullyQualifiedName~FillLinearGeometryReuseTests'

PerfCounters.FillScoreComputations, PartBoundaryPreparations, PartBoundsUpdates, OffsetPerimeterEntities, and FeatureBitmaskCells increments compile away in Release: zero Release counters prove nothing. Serialize counter assertions in FillCacheCollection and reset in finally. Keep OpenNest.Tests/Fill/LegacyFillExtents.cs and OpenNest.Tests/Fill/LegacyFillLinear.cs frozen for differential tests, not production or before timings; measure the actual baseline production code.

Task 4b checks: dotnet test OpenNest.Tests/OpenNest.Tests.csproj -c Release --filter "FullyQualifiedName~AngleCandidateBuilderTests|FullyQualifiedName~AnglePredictorTests|FullyQualifiedName~FeatureExtractorTests" (repeat in Debug for bitmap counters). IrregularAngles_ReportsWarmNoModelPath measures the public builder with a missing model and skips when a model is installed; never remove real model files to benchmark. FeatureExtraction_ReportsFullAndScalarOnly measures extraction separately.

Predictor availability uses the same one-attempt session initialization as inference. Publish completion only after assignment or definitive failure; concurrent callers must wait for the outcome. The builder skips extraction when unavailable and requests scalar-only features when available. Tests use isolated loaders/prediction doubles, not evidence of real ONNX inference.

Whole-job before/after comparisons use OpenNest.Benchmark with a *.manifest.json corpus and --parallel 1 (see the report's Task 5 section for the delivered real-DXF manifest, hashes, outcome confirmation, and inconclusive whole-job timing). Circle-heavy archive drawings can validate INVALID at spacing even on the pre-batch baseline, and larger quantities can crash both trees identically; record such pre-existing behaviors instead of treating them as regressions or tuning around them.