aj
0df2587cf2
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.
28 lines
3.1 KiB
Markdown
28 lines
3.1 KiB
Markdown
# Fill performance verification
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Opt-in synthetic measurements (`OpenNest.Tests/Fill/FillPerformanceTests.cs`):
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```bash
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OPENNEST_RUN_FILL_PERF=1 dotnet test OpenNest.Tests/OpenNest.Tests.csproj -c Release \
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--filter 'Category=FillPerformance' --logger 'console;verbosity=detailed'
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```
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Only the exact value `1` enables these tests; otherwise they skip; [README](../../README.md) documents the PowerShell equivalent.
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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](fill-performance.md).
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Debug behavior/skipped-work checks:
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```bash
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dotnet test OpenNest.Tests/OpenNest.Tests.csproj -c Debug \
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--filter 'FullyQualifiedName~DefaultFillComparerWorkTests|FullyQualifiedName~FillHelpersTests|FullyQualifiedName~FillExtentsTests|FullyQualifiedName~StrategyOverlapTests|FullyQualifiedName~FillLinearGeometryReuseTests'
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```
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`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.
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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.
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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.
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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.
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