Commit Graph
31 Commits
Author SHA1 Message Date
Fr0zkaandClaude Opus 5.5 06f558dc91 streaming: split dense passage-junction grid fills; heavy-first order + far-parent deferral in Unreal (L85)
Tiles with passage-overlap score >= 9 split grid fill over up to 4 helper lanes (disjoint rows,
same per-sample order, join before MC) when workers are idle. FI junction tile fill 173 -> 99 ms;
estimated serial floor ~0.55-0.60 s. Readiness essentially unchanged (FI/TN LOD0-2 ~2.15 s @W12):
the limit is now aggregate work, not single tiles.
Unreal: LOD0-2 ordered by passage overlap before travel/distance (L80 modes kept); far parents
built after LOD0-1, LOD2 gated on them; helper budget via ParallelFor. Unreal null-RHI FI
arrival: LOD0-2 resident at 3.65 s.
All tile hashes identical to L84 (four whole views). Fast tier PASS; Linux UE host builds.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_016dhxM43dnWvUu2B5Ph1iG1
2026-10-28 02:02:32 +01:00
Fr0zkaandClaude Opus 5.5 4661a445be wip(assembler): M2 round 4 -- WorldAssemblerHybridV2: exact contacts, tagged tiles 1.18-1.27x MC
The round-3 'field contact error' measured hit-to-anchor distance; V2 contacts are 0 cm and on the zero
isosurface. Tagged-tile cost 5.7-6.7x -> 1.175-1.270x MC; organic 0.998x. Bound, shelf-thickness and route
audits rerun with negative controls; W1/W8/W16 stable; V1 and MarchingCubesV1 unchanged.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MmSoF64BbRFmk9C3p1VsBJ
2026-10-10 10:41:43 +02:00
Fr0zkaandClaude Opus 5.5 22a6b30494 wip(assembler): M2 round 3 -- opt-in hybrid sharp mesher (WorldAssemblerHybridV1) in the Unreal Core route
Default MarchingCubesV1 unchanged (W1/W8/W16 = round-6 hashes). Hybrid DC only in LOD0 interior cells
with tagged features; tile-border cells and LOD1+ stay MC. BuildHost: fixtures repeat exactly, cooked
collision bounds = render bounds, same-LOD borders pass, sampled SurfaceWorld cliff bit-identical to MC.
Open: tagged tiles cost 5.7-6.7x MC; corner-top field contact error 20 cm; 5 MC doorway LOD cases.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MmSoF64BbRFmk9C3p1VsBJ
2026-10-10 09:53:04 +02:00
Fr0zkaandClaude Opus 5.5 61633cb492 wip(assembler): M1 round 6 -- owner walk fixes: 25 cm geometry scale, one height datum, carve/fill sign, faster relief meshing
Owner saw content floating above native terrain, spiky triangles, reversed carve/fill and late relief.
Causes: shared mesher placed Core tiles on a 12.5 cm grid; content/atmosphere asked strate ranges in
12.5 cm voxels; Core edits add density where the legacy diff subtracts. Horizon LOD8 bridge edge
5.657 -> 2.265 cells. Relief mesh p95 60.8 -> 42.0 ms (LOD0). New BuildHost checks for scale, height,
blueprint carve/fill and per-kind streaming lag.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MmSoF64BbRFmk9C3p1VsBJ
2026-10-09 20:39:24 +02:00
Fr0zkaandClaude Opus 5.5 bc0f9ee791 wip(step3): 12.5 cm voxels, fall-through fixed, brick evaluator in game, organic tunnels -- speed gate FAILS
Stopped by the owner's decision (in-game lit captures were eating the round); he judges the look in
game instead.
1. Fall-through with the research field: fixed. Deep drop, gate on: 2 holds (0.50 s), min foot
   clearance +43 cm; gate off: penetrates (-278 cm). Stress fixture offsets converted to metres.
2. VOXEL_SIZE 25 -> 12.5 cm. Physical sizes kept in metres (player, steps, gate, insets, research
   field sizes, dig radii, test thresholds); class defaults that count chunks/voxels doubled
   (ClipRadius 6, RenderDistanceChunks 1536, ViewDistance*, StrateViewMargin 6,
   PawnCollisionRadius 2, SkirtCells 4, EdgeSealThickness 128, decoration spacings, density volume
   res 256). Asset values override these defaults: the owner must double his own.
   Ring scale, six workers, idle, step-2f field before the look changes: 64 m cube (519^3) 4.55 s;
   32 m cube (259^3) 0.95 s.
3. In game: tiles go through the brick evaluator (proved by a log marker); profile switch rebuilds
   the loaded world (~5,800 tiles); full-detail fill 12.4 s after spawn in the visible-window test.
4. Look: round winding tunnels, per-column ellipsoid/lattice caches. All step-2f geometry gates pass
   at 12.5 cm (0 crumbs, 1 solid component per profile, solid share 69-87%). 259^3 ring, six workers:
   1.08-2.02 s (worst HyperComplex) -- the 600 ms gate FAILS. Lit captures failed (hidden/off-screen
   window, then blank frames); not pursued.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MmSoF64BbRFmk9C3p1VsBJ
2026-10-01 21:21:45 +02:00
Fr0zkaandClaude Opus 5.5 bf22f0ffe0 perf(collision): cook stages measured, no standing on dug-out ground; review F/H/E measured
1. Collision cook breakdown (request -> ready), critical support tile:
   spawn (0,0,-1): generate 107 ms, apply < 1 ms, RMC submit->body 479 ms, total 587 ms;
   deep floor (0,0,-7): generate 82 ms, RMC 1,441 ms, total 1,548 ms.
   Almost all of the wait is inside RMC (end-of-frame update + async pool + Chaos cook + body
   install, not separable from our side). Critical priority does not shorten it. Collision is
   async, complex-as-simple, fast-cook off; skirts are ~16-18% of collision triangles.
   No cook change made. Startup outlier: first support tile waited 2.09 s for its game-thread apply.
   Underfoot dig: a carving brush that intersects the pawn's capsule and support tile now
   disables the old body and withdraws readiness on the carve frame: 0 frames standing on removed
   ground (replacement 91.8 ms later). 8 neighbouring digs: 0 gate frames. Gap audit 0.
2. Stack sampler, 49.4 s game path: top resolved leaf was the profiler's own
   VoxelDensityProfile::BucketFromName (4.86%). Linear label scan -> CRC-keyed lookup with exact
   compare: 59.26 -> 57.87 ms/tile (-2.35%), 980/980 tile hashes identical.
3. Measured only: F (classifier mode 1, no exact check) +48% worker CPU, 0/980 tiles differ ->
   not worth it. H (handoff component scans) p95 0.07 ms/frame -> not worth it.
   E (FullResClipLevels=1): worker CPU 56.7 -> 35.7 s, settle 9.6 -> 7.0 s, crossing samples
   -30%; changes the look, owner's decision.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MmSoF64BbRFmk9C3p1VsBJ
2026-09-29 07:52:18 +02:00
Fr0zkaandClaude Opus 5.5 ce6812dbeb fix(streaming): no false gate on digs, no see-through at tile handoffs; density volume off
- Dig near the pawn: a same-tile collision recook withdrew readiness although the old body was
  still installed, so the gate held a standing pawn (957 of 1,931 frames over 8 near digs).
  A tile now stays ready during a recook while collision is still wanted and its existing body is
  valid. After: 0 gate frames, 0 falling frames over 2,604 frames. Dig directly under the pawn
  still falls (~127 cm, max ~502 cm/s). The reported "accelerating toward the ground" was not
  reproduced; the false hold is the measured part.
- See-through: the retire logic only waited for replacements that overlapped the old tile in
  volume and missed desired neighbours touching at a face/edge/corner. Handoff now includes
  contact. New surface-witness gap audit (24 surface points per tile, skirts excluded, catches an
  injected early hide). 6000 cm/s walk, 75 s: 3 gaps / 51 frames / longest 603 ms -> 0.
  Dig session: 0 -> 0. Overlap audit and edit ghost stay at 0.
- bEnableDensityVolume defaults to false; when off: no volume, no fill thread, uploads or tick
  work, no volume-dependent proof bypass; terrain MIDs get VolP5.z = 0 (enable off), other VolP*
  black, VolTex* null, so M_Test1's volume nodes return their neutral result.

Gate: deep gate-on passes (79.9 m, 3 holds, -0.101 cm), gate-off penetrates (-5.1 cm).

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MmSoF64BbRFmk9C3p1VsBJ
2026-09-29 04:53:57 +02:00
Fr0zkaandClaude Opus 5.5 0bcd67a016 perf(review): gate never deadlocks, collision radius, 20x faster digs
From the outside performance review (items 1-4; item 5 prototyped and reverted).

1. Collision gate: a support request outside the stamped desired set was cancelled by the rebuild
   it forced, and the gate held the pawn with gravity 0. Baseline deep-drop (floor at (0,0,-7),
   outside the aligned L0 ring): 1 hold of 30.0 s, never released. Fix: the target and 3 tiles
   below are retained through rebuilds at CollisionCritical; hold only when the swept capsule is
   about to enter pending support; release restores movement mode, gravity and downward speed.
   After: 3 holds, 2.21 s total, 112.8 m horizontal progress; gate off still penetrates (-7.4 cm).
2. Suspected cleanup regression (out-of-layout stacks): not real. 44 paired boundary tiles,
   30.9 ms vs 32.6 ms at b4ac996, hashes 44/44 identical. No change.
3. PawnCollisionRadiusChunks (new, default 1): L0 tiles outside the collision set stay visible
   without Chaos cooks; anchors and the gate's support column are unioned in. Cook requests
   ~217/min -> ~30/min (-86%). Critical support ready time did NOT improve (9.5 s -> 10.6 s in the
   deep-drop fixture; the wait is the cook itself, ~7.4 s cook-to-ready there).
4. Dig: exact pre-edit L0 density cached (one 35^3 grid, 171.5 KB), carve replays current mods on
   it. Sync remesh 99.4 ms -> 4.7 ms. 16/16 random carves hash-identical to full regeneration.
5. Parallel grid fill for the critical tile: 16/16 hash parity, but the waited-on tile was already
   meshed; the wait was collision cooking. Reverted.

Review G answered: M_Test1 still ray-marches VolTex0 (custom HLSL mini-sun shadow), so the density
volume is live. Known and left alone: outside the strate layout the fallback density can be solid
while the gate treats those tiles as air.
Tests: VoxelForgeCollisionDesiredTilesTest, VoxelForgePreEditDensityCacheTest; no-overlap, edit
ghost, descent corridor pass.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MmSoF64BbRFmk9C3p1VsBJ
2026-09-29 02:26:44 +02:00
Claude 26984d38d8 docs(comments): drop history narration, keep the why
Rewrite comments that told the story of past rounds instead of the
current code: dated "fixed on / tried on / reverted on" notes, "this used
to...", "stale paragraph removed", "Phase 1/2" progress labels, and the
"ClassifyTile still does not use ClassifyBox" claim (it does now, via
VF_ClassifyBoxWithWarpRetry). Every invariant, unit, sign convention,
trap and measurement that justified the design is kept, rephrased in the
present tense and in its original language (French or English).

Also fix comments that named symbols removed in the dead-code commit
(EvaluateSDF wrapper, FTunnelCoreWorldEvaluation support-floor fields,
BlendChunks -> TransitionBlendChunks) and the stale function name in the
VF_RollStrateParamsDetailed determinism checkf message.

Comment and message text only; no code token changed. Tests untouched.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01URDGLsu7c4nunqNFPJEFPU
2026-09-28 14:18:36 +00:00
Claude 4753416d4a refactor(sheets): remove the far sheet ring from the runtime
The owner dropped the far sheet ring. Remove it from the streaming path:
- UVoxelMarchingCubesMesher::GenerateSheetMesh (declaration + definition);
- sheet-tile branches in LoadTile / GenerateTileResult / SyncRemeshTile and
  the bSheetTile / SheetChunkZ / Hole* parameters;
- the SheetHole* XY-hole state and its per-crossing re-queue block;
- VF_MaxMarchingCubesLevel (equal to the clamped MaxClipLevel without sheets);
- the sheet-only band arming and the 'sheet' field of the desired-level
  startup-trace events (no tool reads it).

AVoxelWorld now always passes bFarSheetRing=false to the tile selector, and
the descendant index covers levels up to the MaxClipLevel clamp (8) instead
of the old sheet maximum (12); no tile above 8 can exist any more.

Kept on purpose: UVoxelSettings::bFarSheetRing / FarSheetSpanLevels
(UPROPERTYs, now marked unused), the voxel.TestFarSheetRing switch and the
far_sheet_ring / sheet_tile fields the test harness compares (sheet_tile is
always false), and the selector's sheet parameters in
VoxelClipmapDesiredTiles.h, which two automation tests still exercise.
2026-09-28 13:50:55 +00:00
Fr0zkaandClaude Opus 5 10fd0b6e77 fix(determinism): own sin/cos on the world path -- same world on every CPU, 3.5% faster
On Win64, FMath::Sin/Cos resolve to CRT sinf/cosf (GenericPlatformMath.h:521/530; no platform
override), and the UCRT picks FMA3 or non-FMA3 implementations at startup by CPU. /fp:precise
closed only the compiler half, so the same build and seed could build a slightly different world
on two Windows PCs, and on Linux.

- VoxelMath::DetSin/DetCos/DetSinCos (VoxelTypes.h): fixed double-precision period reduction to
  a quarter period, then fixed float minimax polynomials; no CRT, FMath or CPU-dependent
  intrinsic. Measured max error vs sinf 5.96e-8 over the used range (|arg| <= 6.19).
- Every world-deciding FMath::Sin/Cos replaced (generator, op stacks, cave morphology, strate
  manager, content placement, strate measure); none remain in runtime code.
- Pinned test VoxelForge.Determinism.DetSinCos (golden bit patterns + error bound).
- Diagnostic start-up switch -voxel.CrtFma3=0 (Windows) forces the CRT's non-FMA3 path.
- Parse-once console switches now initialise in StartupModule on the game thread; workers only
  read them (was an unsynchronised first parse inside GetDensityAt).
- Corrected the CRC comment that claimed a CRC32 cannot give a false positive.

Proof (Codex round; orchestrator re-checked):
- Before the fix, FMA3 on vs off was identical on this Ryzen 7 5800X3D: the hole exists but was
  not observed in this world. After the fix, the canonical exports are byte-identical with
  FMA3 on and off.
- The world changed once, as expected. New canonical export SHA-256 CBB8AE18...906F (geometry
  B9EF84AC; was B3E5F4C3...377); worms region 9242C093 (was 311CA42C), walk OBJ 20CCF7BD....
  Triangle counts unchanged in every tile. Order-independent nearest-vertex distance, worms
  region: max 8.7 micrometres (the reported "11.4 m" was a line-order artefact of a line-by-line
  OBJ diff); export region max 3e-5 m.
- Capability exact: player-fit 20,830, walk-reachable 10,909, connected. TilePostReachProof,
  sealed-proof, cross-platform and strate-crossing tests pass.
- Performance, headless game path, S/M/S/M vs the committed-tip DLL: static worker 27.41 s vs
  28.44 s (-3.6%), moving 59.59 s vs 61.74 s (-3.5%); LOD0 p50/p95 not worse.

From Sol's code review (DESIGN-SOL-2026-09-15-CODE.md, section 4.1), branch sol/deterministic-math.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01TaFdXhTdYMkW1xrV6ApT6Y
2026-09-16 00:55:04 +02:00
Fr0zkaandClaude Opus 5 a668833ef5 perf(generation): exact reach gating for the tunnel core (per tile) and passage carving (per 8^3 block)
Applies ce4d878's decide-once-then-prove pattern to the two largest exact targets from the re-rank
(tunnel core 20.8%, passage carving 9.1%). Codex; reviewed by me.

Measured first, where the time is:
  core world:      far 223,860 vs near 35,515,979 cycles   -> tile gate only; the core is
                                                             near-dominated (~99%)
  core tail:       far 363,440 vs near 20,110,219
  passage, tile:   far 7,315,426 vs near 30,168,796        -> refined to an 8^3 block gate
  passage, 8^3:    far 11,233,384 vs near 26,250,838
The core already uses the tunnel spatial index. An exact skip cannot remove its cost: that cost is
in tiles near tunnels. The remaining lever there is the field-changing SDF/core merge (next).

- Core reach per tile, from lattice plus halo: swept capsule reach, floor band, floor-profile
  deviation, relief bound, room-mouth ownership. The GetDensityAt tail is identity unless
  bSupportFloor, bRoomFloor or CoreSDF < -inset.
- Passage carving per 8^3 block: capsule-chain and landing-room domains, the carve threshold and
  the SmoothMin K/6 margin. Malformed descriptors stay candidates (conservative).
- voxel.TileReachCostDiagnostics (default 0) for the far/near cost split.

Soundness: the final-field debug comparison ran 130,285,889 comparisons with 0 differences; shrunk
reach (0.5) produced 140,035 differences (60,098 in the final field) and failed as required.
Field exact: canonical 07C14005 / b3e5f4c3..9b377, 64/64 per-tile ledger identical, capability
20,830 / 10,909, strate-crossing and sealed-proof tests pass.

Final DEFAULT build vs the committed-tip DLL (same command line, two interleaved runs each):
  static  worker 28.84 -> 28.10 s (-2.6%)  LOD0 p50 53.3 -> 51.5 ms  p95 94.4 -> 93.1 ms
  moving  worker 61.39 -> 60.61 s (-1.3%)  LOD0 p50 50.9 -> 49.7 ms  p95 92.21 -> 92.27 ms (flat,
                                                                        +0.06%, within noise)
Maintenance note: these reach proofs must track tunnel/passage geometry. The next round adds an
automation test for the final-field comparison so a geometry change cannot silently break them.
Ledger: 15 builds (one C2065 fixed, one access-denied path retry); rejected TileOnly/BlockLookup
variants were slower; one hung diagnostic (a non-owner PID) was stopped; wrapper quoting failures
launched no editor. No crash folders.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01TaFdXhTdYMkW1xrV6ApT6Y
2026-09-15 11:30:37 +02:00
Fr0zkaandClaude Opus 5 ce4d8783e9 perf(generation): per-tile reach test skips landing and structural posts -- ~12% less worker CPU
The remove-one ablation put landing posts at ~10% and passage structural posts at ~6% of worker
time, though landings exist only near passage ends and the origin. The parked exact-cull round's
per-SAMPLE post bounds had been a net loss. This round decides reach once per TILE (Codex;
reviewed by me).

- VoxelTilePostReach.h: one per-tile reach mask (thread-local byte), set when the tile is set
  up. The origin landing, passage landing SDF/floors, native floors, tunnel air and passage
  structural posts return their input unchanged on tiles no instance can reach. Per sample this
  costs an inline flag read.
- Reach proofs come from each post's geometry (origin rooms, landing SDF and floors, native floor
  band, structural support spheres), not from comments.
- voxel.TilePostReachDebug=1 evaluates the skipped posts anyway and compares the FINAL field;
  voxel.TilePostReachScale=0.5 deliberately shrinks the reach and must fail.

Default build: 694 tiles, landing reachable on 4 (skipped on 690), structural posts skipped on 169.
Soundness: 123,958,673 comparisons, 0 differences; shrunk reach: 13,929 differences, FAIL as
required.

Final DEFAULT build vs the committed-tip DLL (same command line, two interleaved runs each):
  static  worker 34.80 -> 30.52 s (-12%)   LOD0 generation p50/p95 67.0/107.6 -> 55.8/95.8 ms
  moving  worker 75.96 -> 66.66 s (-12%)   LOD0 generation p50/p95 66.3/106.0 -> 56.0/95.8 ms
Field exact: 841/841 keyed tiles vs a fresh committed-tip trace (669,902 triangles, which includes
9260775's gap floors), export b3e5f4c3..9b377, capability 20,830 / 10,909; strate-crossing and
sealed-proof tests pass.
Ledger: all launches passed or failed where designed to; early raw-SDF debug attempts failed
until the comparator was corrected to compare the final field. No crash folders.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01TaFdXhTdYMkW1xrV6ApT6Y
2026-09-15 07:42:13 +02:00
Fr0zkaandClaude Opus 5 5489b5e311 perf(generation): inline exact IsFinite -- LOD0 ~11-12% faster, field-exact
The sampler's last "unknown" LOD0 bucket (~13.8%) was ucrtbase.dll!_finite: FMath::IsFinite is an
out-of-line CRT call on the MSVC game path, hit from the innermost tunnel, passage, density,
spatial-index and meshing loops.

- VoxelMath::IsFiniteFast(float/double) in VoxelTypes.h: memcpy to uint32/uint64,
  (Bits & ExpMask) != ExpMask. It is the same predicate for every bit pattern, with no FP
  comparison for fast-math to fold. The disassembly shows it inlined (movd/movq, mask, compare).
- VoxelMath::IsFinite routes through a plain global, voxel.FastIsFinite (default 1), for the A/B.
  The CRT call remains only on the switch-off branch. Hot generation-path uses are replaced; no
  _finite / std::isfinite remains in Source/VoxelForge. Tool/editor/test code keeps FMath.
- A test that can fail: VoxelForge.Math.IsFiniteExact compares against FMath::IsFinite over 22
  explicit float/double patterns (+-0, denormals, min/max normal, +-Inf, quiet and signalling NaN
  payloads) plus 2,000,000 hashed patterns each: 0 mismatches. The explicit NaNs make a NaN-wrong
  helper fail.

Field exact: 841/841 keyed tiles identical to NextHeadStaticTrace_20260913 (verdict/empty/
triangles), export OBJ unchanged (b3e5f4c3..9b377), capability 20,830 / 10,909.

Within-round A/B, game path, two interleaved runs each, sampler off (off -> on):
  static  LOD0 request p50  95.5 -> 84.8 ms   generation p50/p95  70.3/114.1 -> 62.3/100.6 ms
          worker            35.4 -> 31.6 s (-10.5%)
  moving  LOD0 request p50/p95  70.8/144.2 -> 62.0/126.1 ms
          generation p50/p95    62.6/113.4 -> 55.1/101.0 ms
          worker            102.6 -> 91.3 s (-11.0%)
Sampler-on moving: the _finite/CRT cluster is gone.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01TaFdXhTdYMkW1xrV6ApT6Y
2026-09-13 23:50:30 +02:00
Fr0zkaandClaude Opus 5 2de603cd77 perf(generation): size the room cache to the tile; spatial index; memo-key guard
Coarse tiles thrashed the per-worker 4-chunk room-cache window: 633 BuildChunkCache calls per
LOD3 tile and 1,062 per LOD4 tile. This round was started by one Codex session and finished by a
second, after the orchestrating session died at 06:06 and corrupted the first session's record.
The second session reviewed and built its predecessor's half-finished tree.

- voxel.TileCacheWindow (default 1): the room cache covers the requesting tile's footprint plus a
  fixed collect margin. It is set with TGuardValue around GenerateMesh and classify, so it never
  leaks to other work on the thread. Tile windows are capped at 64 chunks per side;
  unsupported/non-finite params fall back to the legacy window.
- Window invariance, argued by Codex: graph decisions depend on at most two bounded
  MaxTunnelLength hops, and primitives are culled only once their complete bounds are known.
  So the collect margin 2*MaxTunnelLength + max(room reach, pair/chain/tube reach) does not grow
  with the window. Caveat: oversized authored terrain-op radii are not yet in the envelope check.
- PrepareTunnelCoreCache reuses the graph, rebuilding only the exact support-column table for a
  crossed chunk.
- FChunkSDFSpatialIndex: ordered XY buckets over room/join/tunnel bounds; rejection stays exact
  and within-bucket order is preserved. Only 9-13% of candidates reach exact evaluation.
- static_asserts in VoxelStrateTypes.h: VF_STRATE_PARAM_FIELDS lists 83 fields, and their byte sum
  + 8 B padding == sizeof(FStrateGenerationParams). This closes the memo key's known gap (it
  catches omissions and size changes, not same-size replacements or padding-hidden fields).

Verified (game path, two runs each, sampler off):
- field exact: 841/841 per-tile triangle identity, 669,834 triangles; export OBJ SHA-256
  unchanged (b3e5f4c3..9b377); capability 20,830 / 10,909, connected
- cache builds: fused 139,187 -> 1,019 (-99.3%), op-stack 60,598 -> 879
- worker CPU: static 58.4 -> 40.8 s (-30%), moving 138.4 -> 121.2 s (-12%)

REGRESSION, stated plainly: with the switch on, LOD0 gets slower. Generation p50 is ~9% slower,
static 75 -> 82 ms and moving 71 -> 77 ms; request-to-ready p50/p95 is ~5-6% slower. This is
consistent across both runs of both cases. The thrash only lived at LOD2+ (LOD0 had 1.66 builds
per tile), so the next round gates the tile window by LOD and must bring LOD0 back to switch-off
speed while keeping the CPU gain.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01TaFdXhTdYMkW1xrV6ApT6Y
2026-09-13 15:06:24 +02:00
Fr0zkaandClaude Opus 5 c65b015f01 perf(streaming): outer tile classifier off by default; delete mode 2
Owner-approved, on the A/B measured in 83a0e4d: the classifier plus exact validation cost more
than it saved on the game path. With it off, ready p95 is 182 vs 190-195 ms, generation p95 is
125-127 vs 139-141 ms, and density calls drop 18%.

- GVoxelForgeOuterClassifierMode defaults to 0. Mode 1 stays reachable via
  voxel.OuterClassifierMode=1 as an A/B instrument; the clamp is now 0..1.
- Mode 2 (validation samples reused as the mesher core grid) is deleted: the reuse grid,
  FVoxelMesherCoreDensityGrid, GenerateMesh's ReusableCoreGrid parameter, bValidationCoreReused,
  TotalValidationCoreReuseTiles and its log field. It could not fire: it reused the grid only
  when validation disproved a uniform verdict, which never happened, and Mixed tiles never
  validate. The mode-1 validation loop exits early again on the first disagreeing sample.
- All three GenerateMesh call sites checked; the density-count pointer binds after BandVoxHi.

Verified by Codex, checked by me against the logs:
- build ok; the measured process loaded the staged DLL, SHA-256 1024D8CF..04D
- export OBJ SHA-256 unchanged: b3e5f4c3..9b377
- a run WITHOUT the override prints outer_classifier_mode=0 validation_density_calls=0,
  proving the new default took effect
- 841/841 tiles have identical triangle counts between mode 0 and mode 1. The 394 tiles mode 1
  skipped as uniform produce 0 triangles in mode 0, so the strate band cut (applied by the
  mesher, not by validation) was not hiding geometry.

Docs: ARCHITECTURE 8.10, CODEMAP (GenerateTileResult, ClassifyTile) and fable-idea T1.d record
that streaming no longer classifies by default. WORK-NEXT item 1 records the owner's playtest:
he can no longer fall through the world.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01VZS94UH8bSsBeg5sZaxe2Y
2026-09-13 02:06:24 +02:00
Fr0zkaandClaude Opus 5 f2044135ea fix(mesher): stop forcing the nested block classifier on -- but I cannot reproduce the 3.5x
The code contradicted its own documentation. VoxelMarchingCubesMesher.h:150 says to leave
the optional 8^3-block refinement DISABLED in streaming, "repeating a proof on ..." --
and VoxelWorld.cpp forced `Mesher->bUseBlockEarlyOut = true` regardless.

It is now off by default, behind `voxel.UseBlockEarlyOut` (CVar + command line), so the
capability stays available for the focused diagnostics where it was measured to help.

⚠️ THE HEADLINE NUMBER DOES NOT REPRODUCE, AND I AM NOT CLAIMING IT
Sol's second pass read a 3.5x from the attribution table:
    classifier disabled    587.991 ms
    classifier enabled   2,056.596 ms
My own clean A/B on this flag, quiet machine, 3 runs each:
    nested OFF   0.597 / 0.613 / 0.607 s   mean 0.606
    nested ON    0.637 / 0.599 / 0.605 s   mean 0.614
Identical within noise.

So either the 2,056 ms control exercised more than this flag does, or the 3.5x lives on
a path the 128^3 export does not take. PERF-ATTRIBUTION.md describes that figure as "the
separate classifier control", which is not obviously the same lever. Until the game-path
A/B is run, treat the 3.5x as UNCONFIRMED.

What this commit is worth on its own: the code now does what its documentation says, the
behaviour is switchable rather than hardcoded, and geometry is unchanged --
SHA-256 b3e5f4c3..9b377 identical with the flag on, off, and against bb8ec51.

⚠️ An earlier measurement pass in this round was contaminated: a local llama-server was
using 5 GB and competing for cores. Those runs came out 0.67-0.78 s with the on/off
ranges overlapping. Discarded and re-measured on a quiet machine; only the clean numbers
above are reported. Worth recording as a reminder that the machine is part of the
instrument.

NOT DONE -- the round was OOM-killed partway (same llama-server):
- the three-way outer-classifier A/B (no outer / current+discarded validation / ⭐ outer
  with validation samples REUSED as the mesher core grid). That third mode is the
  interesting one: exact validation currently costs 33^3 = 35,937 density calls whose
  results are then DISCARDED, while the mesher then fills 35^3 = 42,875. A successful
  uniform verdict saves at most 16.18%, and a Mixed verdict saves nothing.
- game-path measurement of any of it.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_012aheo2crrZmHuYtPpdY2Cb
2026-09-12 13:19:42 +02:00
Fr0zkaandClaude Opus 5 bb8ec51939 measure(perf): the remaining 4.3x is ALL density evaluation -- and the classifier costs 3.5x in game
Measurement only; no density or meshing decision changed. Full table in
PERF-ATTRIBUTION.md. The profiler self-check finally passes honestly: profiled 606.128
vs unprofiled 602.341 ms, **+0.63%** (it used to inflate 11.5x).

THE ATTRIBUTION, and it is almost embarrassingly one-sided

  mesh ledger, additive, sums to the clock exactly (sum_matches_mesh = true)
    shared density-grid fill    590.923 ms   97.4913%
    tile parallel wall           10.972 ms    1.8102%   cells, interp, normals, streams
    tile merge                    4.232 ms    0.6982%
    pre-tile setup / prep         0.002 ms    ~0%
    remainder                     0.0001 ms   ~0%
    ------------------------------------------------
    total                       606.128 ms

  GetDensityAt parent: 580.184 ms worker-wall, nested inside that 590.923 ms.

⇒ **The mesher is exonerated. Marching cubes, vertex interpolation, normals and stream
building are 2.5% combined.** The whole 4.3x is density evaluation, which is where three
of us have been looking and none of us had proven it.

WHAT IS ACTUALLY BEING DONE, per 2,248,091 samples
  rooms        11,099,891 candidates ->  1,730,920 evaluated
  tunnels      28,951,420 candidates ->  3,462,565 evaluated
  tunnel-core  28,951,420 candidates ->  1,881,812 evaluated
  ~31 candidates SCANNED per sample, ~3.1 evaluated
  fused detail ran on 1,079,777 and skipped 1,168,314 samples (52.0%)
  software tunnel cache: 2,248,043 hits / 48 misses -- not the problem

The post-stack structural tail, which I have suspected twice, is small: StructuralTail
20.9 ms CPU / 1.9 ms wall, DensityStructuralPosts 21.9 / 2.0, PassageStructuralPosts
10.5 / 1.0 -- all nested samples against a 590.9 ms wall.

⭐⭐ AND THE FINDING THAT MATTERS MOST FOR THE GAME
  clean export, classifier absent       587.991 ms
  same export with the classifier       2,056.596 ms
The classifier makes generation **3.5x slower**, it is ABSENT from the export path we
have benchmarked for five days, and the GAME PATH USES IT. Its control route runs
211,289 support-column builds, 2,171,763 candidates, 1,370,314 floor queries and
2,296,243 checks -- none of which the fused export route executes at all.

⇒ Every optimisation this week was measured on a path that skips the single largest
cost the player actually pays. That is a measurement-design failure and it is mine.

Also newly visible: the full export wall is 1,004.557 ms, of which mesh is 606.128 ms
(60.3%) and OBJ WRITING is 394.273 ms (39.2%). My "0.556 s" figures have always been
mesh_seconds alone.

One real hot-path improvement landed with the instrumentation: AreCountersEnabled()
returned an unconditional `true`, so counter hooks were live in shipping builds. It is
now a relaxed load gated on diagnostic mode.

VERIFIED BY ME: build 0 errors; export 0.552 / 0.555 / 0.566 s (cf0319d was
0.563-0.566, unchanged); geometry SHA-256 b3e5f4c3..9b377 UNCHANGED.

Honest gaps, as reported: exact per-operation shares inside the density stage, physical
cache-miss counters, and a rebuilt 34f06df binary for a true A/B were all unavailable.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_012aheo2crrZmHuYtPpdY2Cb
2026-09-12 08:45:26 +02:00
Fr0zkaandClaude Opus 5 5ddd96664d perf(opstack): invert the loop + prune per block -- 1.45s to 1.02s, byte-identical
The architecture round. Loop inverted from per-sample-per-op to per-op-per-block,
operators pruned per block by interval bounds, profiler moved out of the hot loop.

  my build, 3 runs:  1.013 / 1.036 / 1.075 s   (adb34df was 1.418 / 1.445 / 1.458)
                     mean 1.041 vs 1.440  =  -28.5%, 1.39x
  geometry SHA-256   b3e5f4c3..9b377  IDENTICAL to adb34df

  pruning removed 20,999 / 31,320 operator-block visits = 67.1%
  surviving ops per block:  LOD0 6.63  LOD1 6.30  LOD2 5.23  LOD3 4.41  LOD4 3.89
                            (out of 22)

⚠️ I PREDICTED THE DISPATCH OVERHEAD WAS "THE 10x". IT WAS NOT.
864,688 virtual dispatches per chunk sounded decisive and is worth ~20-28%. Real, and
worth having, but the order of magnitude is elsewhere. That is my fourth wrong
performance prediction in this project, and the pattern is identical each time: I reason
from a call site's shape instead of measuring what the data actually costs.

⭐⭐ AND THE "5-20x GAME/EXPORT GAP" WAS MY ARITHMETIC ERROR. IT DOES NOT EXIST.
I told the owner the largest unexplained number in the project was that export does
22 ms/tile while the game does 115-500 ms. That 22 ms came from dividing 1.4 s of WALL
CLOCK by 64 tiles -- ignoring that 15 workers ran them in parallel. Per-job means on the
same build:

  nonshared block export   447 ms/job
  shared-grid export       261 ms/job
  game LOD0 meshing        253 ms/tile p50

They are the same. The game is not anomalously slow; generation simply costs ~250 ms per
LOD0 tile. The shared grid's benefit is real but modest, and a neighbourhood cache is NOT
justified by these numbers -- I would have had Codex build one on the strength of a
division error.

GAME PATH, final build (841 profiles, 447 applies)
  meshed p50/p95/max   LOD0 253/521/697 ms   LOD1 79/130/135   LOD2 19/42/51
                       LOD3 36/64/81         LOD4 93/238/271
  LOD0 request-to-ready  p50 47.7 ms  p95 389 ms  max 798 ms
                         worker queue p95 84 ms, generation p95 344 ms
  at 6 m/s: p95 = 2.3 m of travel, max = 4.8 m
  empty LOD0 tiles never enter the mesher; classifier p50 8.7 ms, p95 17.2 ms
  apply is not the bottleneck: p50 0.107 ms, p95 0.161 ms, max 0.296 ms

⭐ THE BINDING CONSTRAINT IS COMPUTE, NOT POLICY:
  logical cores 16, automatic core cap 14, effective generation cap 14, CAP HIT.
Apply limits never bind. We are saturating the machine, which means the remaining wins
must come from doing less work, not from scheduling it better.

NOT DONE, with reasons rather than excuses:
- Coarse-first LOD refinement: coarse tiles carry NO COLLISION, so streaming them first
  would let the player fall through. Needs a conservative collision proxy or an L0
  handoff first. Correct refusal.
- Heading prefetch: desired tiles are sorted by distance only (VoxelWorld.cpp:1748).
  Velocity-weighted prediction with a bounded budget and expiry is the shape, not built.

A failed experiment, reported rather than buried: eagerly filling every classifier leaf
with EvalBlock regressed export to 3.2-3.3 s because it defeated the classifier's early
exit. Removed.

Build 43 actions, 0 errors. Peak RSS under 2.1 GB. Sources: Epic's Tasks System and
Level Streaming docs, Lorensen-Cline.

Cumulative on this region: 342.2 s -> 1.02 s.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_012aheo2crrZmHuYtPpdY2Cb
2026-09-11 18:09:12 +02:00
Fr0zkaandClaude Opus 5 412a7ad219 perf(game): the path he actually walks -- meshed p95 4.91s -> 0.41s, RSS 19.5GB -> 1.7GB
The owner: "I want real performance gain for the ingame path... not in deletion, but
in optimization and tricks." Three rounds of ours had improved the commandlet export
he never runs. This one is the streaming path.

MEMORY -- it was retention, not the new lattice
19.5 GB was worker FChunkSDFCache arrays keeping capacity when keys were replaced
(946 MB across 15 workers in diagnostics), shared graph caches with no byte or
lifetime budget, and batch commandlets holding transient UObject worlds until exit.
BlockSkip is bounded to 8^3 bytes per tile; interval scratch is worker-local and
capped. Fixes: release storage on key replacement, LRU with a 256 MiB resident
budget, limit in-flight graph builds, drop oversized entries, CollectGarbage between
batch cases.

  peak RSS   19.5 GB  ->  1.643 GB (their runs) / 1.71 GB (mine, 3x128^3)   -91%
  a 3-case stress batch showed no accumulation

WHY SOME EMPTY TILES COST 5.6s AND OTHERS 3us -- a 1.9 MILLION x spread
Fast ones returned straight from the layout/edge proof (verdict AllAir/AllSolid,
refine=0, mesh=0). Slow ones returned Mixed, so the caller ran the FULL mesher grid
and only discovered emptiness by brute force -- logs show empty=1 after ~5 s of mesh
work. The interval machinery now reaches a verdict before a mesh job is enqueued.

IN GAME, 841 requests at streaming radius:

                     count     p50        p95        max
  empty                394   6.087 ms   12.113 ms   25.049 ms
  meshed               447 114.748 ms  410.314 ms  844.043 ms
  LOD0 empty           221   7.126 ms   11.901 ms   25.049 ms
  LOD0 meshed          122 355.794 ms  600.945 ms  844.043 ms

  against d38d4ca:  meshed p50/p95/max 0.6085 / 4.9075 / 5.0199 s
                    LOD4 empty max 5.618 s
  => meshed p50 5.3x, p95 12.0x, and the multi-second empty outliers are gone.

REQUEST-TO-READY -- the number that answers "I can outrun the generation and fall"
  all tiles     p50  57.576 ms   p95 429.052 ms   max 905.633 ms
  empty         p50  30.943 ms   p95  98.302 ms   max 305.505 ms
  meshed        p50 128.521 ms   p95 462.235 ms   max 905.633 ms

At the harness walking speed of 6 m/s: p95 = 2.574 m, worst case = 5.434 m. A walking
player now outruns tile readiness by a couple of metres, not by a strate.

CAPABILITY PRESERVED, which is the point
The owner asked that speed never come from quietly simplifying the world. It did not:
geometry SHA-256 98eaad61..d3c4f is IDENTICAL to d38d4ca, 153,740 triangles, 82,516
vertices, across three runs. No resolution, sample-count, octave or seed reduction.
Unknown intervals still cost the skip. Prove and skip, never simplify and hope.

Export path, my own build, 3 runs: 1.088 / 1.102 / 1.100 s (was 1.171-1.258 s). ~9%,
below the 17% noise floor, so not claimed as a speed win -- the export was not the
target.

Honest remainder: LOD0 empties are ~7 ms p50 with a 25 ms tail, not the 2-5 ms of a
pure layout proof. Those are bounded, sound interval refinements that never invoke
meshing; going lower needs stronger proof bounds, not more skipping.

Verified by me: build 0 errors, binary timestamp checked against sources, peak RSS
measured, hashes compared. Nothing outside Plugins/VoxelForge; RMC untouched.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_012aheo2crrZmHuYtPpdY2Cb
2026-09-10 11:05:09 +02:00
Fr0zkaandClaude Opus 5 d38d4cabef perf(gen): interval propagation -- blocks can finally be PROVEN empty. 1.55s -> 1.21s
Task 4 ran 11 hours and was killed by system memory pressure before it could file a
report. The work survived, builds clean (0 errors), and is verified faster with
byte-identical output. This commit is my verification, not its summary -- it never
got to write one.

THE STRUCTURAL FIX
0e9df9e established why no block could ever be skipped: OriginSpineOp,
PassageCarveOp and the active seals Lerp/Min/Max against the CURRENT density, so
with an unknown incoming density their supremum is genuinely unbounded. Not a
missing bound -- the operator semantics.

The answer is to propagate a density INTERVAL through the stack, and that is what
landed: FVoxelBoxSdfInterval + PropagateSdfOverBox on the operator interface, an
interval fold through every converter and modifier, interval arithmetic down into
the noise primitives themselves (gradient corners, warp, worm frequencies), and a
BlockSkip lattice the mesher consults per 8^3 block.

Its own guiding comment, which is the right default:
  "no finite interval is a proof. Unknown costs the skip and protects the geometry."

  128^3 TunnelNetwork seed 1337 slot 1, freshly built binary, 3 runs each:
    before  1.515 / 1.554 / 1.569 s
    after   1.213 / 1.258 / 1.171 s     -22.5%, 1.28x -- clears the 17% floor

  Geometry SHA-256 98eaad61..d3c4f IDENTICAL to 0e9df9e. 153,740 triangles either
  way. It skips only provably-empty work; nothing about the world changed.

It also fixed one cause of the 5.6 s empty tiles found in 0e9df9e: an LOD4 tile
legitimately spans 19^3 = 6,859 chunk keys and was rebuilding per-chunk state
thousands of times within a single tile. A shared cache removed that failure mode;
remaining slow empties were LOD0 and are a separate fast-classifier bail, still open.

Partially landed, unfinished when killed: RequestStartCycles on FChunkResult, to
report request-to-ready latency rather than worker generation time. Harmless as is.

⚠️ WHAT KILLED IT, AND IT IS OURS
A single UnrealEditor-Cmd commandlet grew to 19.5 GB, leaving 1.3 GB free on a
32 GB machine, and the OS killed the agent. Freeing it restored 21.6 GB. The owner
said twice that his machine should not be under memory pressure and he was right
both times: first the 411 MiB worker caches, now a 19.5 GB commandlet. A generation
run must not need 19.5 GB. Next task.

Cumulative on this region: 342.2 -> 16.2 -> 2.62 -> 1.49 -> 1.21 s  (~283x).
3,374 insertions / 342 deletions across 12 files. Build 0 errors. Nothing outside
Plugins/VoxelForge; RealtimeMeshComponent untouched.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_012aheo2crrZmHuYtPpdY2Cb
2026-09-09 21:11:13 +02:00
Fr0zkaandClaude Opus 5 0e9df9e5a7 perf(gen): the game path is NOTHING like the export path -- and empty tiles cost 5.6s
Overnight task 3. The headline is not a speedup: it is that we have been measuring
the wrong thing all along.

⭐ IN-GAME MEASUREMENT, FINALLY (headless -game -nullrhi, TunnelNetwork PIE map)

  46,078 profiled tile calls
  46,025 EMPTY  (99.885%)
      53 actually meshed
  meshed    p50 0.6085 s   p95 4.9075 s   max 5.0199 s   mean 1.3515 s
  LOD1-3 empty medians ~2-3 us
  LOD4 empty OUTLIERS up to 5.618 s

The pawn fell through successive strata during the run, reproducing the owner's
"I can outrun the generation and fall" exactly.

Two facts to sit with:
1. **Almost nothing is meshed. 99.9% of tile requests produce nothing** -- and some
   of those empty tiles take FIVE AND A HALF SECONDS. A tile that generates no
   geometry costing seconds is the bug, and it is classification cost, not meshing.
2. The export path we have optimised for three rounds does 64 tiles in ~1.5 s
   total. The game does 46,078 calls with multi-second tile latency. **They share
   the density function and nothing else about their cost profile.**

⇒ Every optimisation so far was aimed at the path the owner does not play.

WHY NO BLOCK CAN BE SKIPPED -- answered, and it is structural
Per-op bound-vs-brute-force table produced (op_bounds.json). Most ops bound fine
once given proven suprema, and those were tightened:
  FBM envelope 1.5, cellular 6.0, SdfConvertOp exact 2*|BaseDensity| = 16,
  Lerp radius envelope max(Min,Max), plus state-aware room/column/floor-bias/worm/
  terrace/cliff/arch/dome/pinch/roughness bounds. Structural ops now return exact
  zero outside their geometric bands.

But OriginSpineOp, PassageCarveOp and the active seals **cannot** take a finite
generic density bound: they Lerp/Min/Max against the CURRENT density, so with
arbitrary incoming density their supremum is mathematically unbounded. This is not
a missing EffectOverBox, it is the operator semantics.
⇒ Hierarchical evaluation requires propagating a density INTERVAL through the
stack, or changing those operators. That is the real prerequisite, now named.

Early-out with tightened bounds still skips 0 of 4,096 blocks and costs 96.6%
(3.305 -> 6.497 s). Left opt-in and DISABLED. ClassifyTile's TerrainZ/overhang
guard untouched.

SPATIAL INDEX REMOVED (ee89c4d's, which never earned its keep)
  wall clock   3.1407 s on -> 3.1894 s off   = 1.5%, below the 17% floor
  cache bytes  557,626,564 -> 246,049,920    = -297 MiB
  candidates   19.5M -> 81.6M scanned (4.17x), evaluated +25.6%
Memory the owner can feel beats counters he cannot. Per-primitive broadphase stays.

VERIFIED END-TO-END on a correctly built binary: 1.515 / 1.554 / 1.569 s, geometry
hash 98eaad61..d3c4f unchanged from 2f33870. Task 3 is memory, not speed.

⚠️ PROCESS, second time: the agent's reported DLL timestamp was from a staging copy
it built under the plugin's own Saved/, not Plugins/VoxelForge/Binaries. My first
three runs measured the 05:58 binary again. Verify the binary you are about to
measure, not the one someone says they built.

Determinism: all export hashes ED0F1F31 within the run; classifier vs generator
verdicts zero mismatches. Nothing outside Plugins/VoxelForge; RMC untouched.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_012aheo2crrZmHuYtPpdY2Cb
2026-09-09 09:00:41 +02:00
Fr0zkaandClaude Opus 5 2f33870a84 perf(mesher): adjacent tiles were re-evaluating 18% of the field -- 2.69s to 1.49s
Overnight task 2. Every claim here is end-to-end wall clock on a real 128^3 export,
not a profiled bucket, because the last two rounds shipped large bucket wins worth
0% in reality. Measurement floor is ~17% run-to-run; only Part 2 cleared it.

PART 2 -- KEPT. Density-grid reuse.
The mesher samples an expanded grid (-1..Cells+1), so adjacent tiles re-evaluated
their shared boundary planes. Measured: 2,744,000 requested samples contained
495,909 duplicates -- 18.07% of the field generated twice. A run-scoped read-only
lattice (FVoxelSharedDensityGrid) owns each world sample once and hands it to both
adjacent tile grids. Duplicates now 0.

  128^3 TunnelNetwork seed 1337 slot 1, freshly built binary:
    before  2.603 / 2.693 / 2.697 s
    after   1.488 / 1.499 / 1.486 s      -44.6%, 1.80x

  Geometry SHA-256 98eaad61..d3c4f IDENTICAL to the pre-change binary's output.
  153,740 triangles either way. Pure win, no field change.

The lattice is deliberately not a UObject and not a cache with eviction: ownership,
lifetime and iteration order stay explicit. A malformed or incomplete lattice is
ignored and falls back to the canonical generator path rather than altering geometry.

PART 1 -- REVERTED. Block-level empty-space early-out.
**0 of 4,096 blocks were safely classifiable**, and the attempt made it 85% slower
(3.632 -> 6.735 s). No unsafe bound was retained.
⇒ This is a finding, not just a failure: our conservative bounds are too loose to
prove ANY 8^3 block uniform. Hierarchical evaluation of any kind is blocked until
we know which operator has effectively unbounded reach. Next task.

PART 3 -- REVERTED. Task granularity.
15 workers, 64 tile jobs, mean job 0.594 s, launch fringe ~14.1 us. MinBatchSize=4
was 1.09% SLOWER end-to-end despite a better bucket time -- exactly the trap this
task's rule exists to catch. Default stays 1. ParallelForWithExistingTaskContext
not adopted.

PART 4 -- NO CHANGE. Renderer audited over 3 runs (8.736 s total, 1.483 s raster).
Mesh and BVH are already reused across viewpoints; no per-pixel heap allocation, no
redundant remeshing. Nothing gross to fix; it benefits from the above automatically.

STILL OPEN: the spatial index from ee89c4d has never earned its keep in wall clock
and accounts for ~214 MB of measured allocations. Codex proposes an on/off ablation
then removal if confirmed. Not done unilaterally.

⚠️ PROCESS NOTE: the agent reported "build passed" but the runtime DLL was still
from 03:07 while sources were edited at 05:22/05:42. My first three verification
runs measured the OLD binary and showed no change. Always check binary timestamps
against source timestamps before believing a measurement.

Cumulative on this region: 342.2 s -> 16.2 s -> 2.62 s -> 1.49 s (230x).
Determinism: identical hashes across all repeat runs. Build clean. Nothing outside
Plugins/VoxelForge touched; RealtimeMeshComponent untouched.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_012aheo2crrZmHuYtPpdY2Cb
2026-09-09 05:59:56 +02:00
Fr0zkaandClaude Opus 5 e63f016835 tools(profile): the instrument lied by 11.5x -- now it checks itself, and batching kills startup cost
Overnight task 1 of the owner's mandate: "better diagnostic, profiler and tools,
so we can batch test way more quicker."

WHY THIS CAME BEFORE ANY MORE OPTIMISATION
ee89c4d delivered a 5x candidate reduction and a 16x cheaper support floor for
0% end-to-end gain, because the profiler inflated by ~11.5x (14.74 us/sample
profiled vs 1.28 us/voxel real). Two rounds of bucket rankings were artefacts of
FPlatformTime::Cycles64() wrapped around ~100 ns operations -- the timer pair
calibrates at ~0.1 us, so it was measuring itself.

PROFILER
Deterministic count sampling plus amortised block timing every 64 density calls.
Coarse counters (calls, candidates) stay always-on -- they were never the problem.
Timing-only scopes are opt-in behind -profiledensityfull. UE CPU trace scopes added.

  before   profiled 14.74 us/sample  vs  1.28 us/voxel real   ~11.5x
  after    profiled 0.463050 s       vs  0.558470 s unprofiled   -17.09%
           geometry 235AC2DC in both

⭐ Every profiled report now prints profiled total, unprofiled total, discrepancy,
ratio and geometry equality, and EXITS CODE 2 if the comparison fails. An
intermediate run hit -22.6% and failed loudly, which is the point: this class of
bug must be impossible to miss rather than something noticed three rounds later.

⚠️ The -17% residual is run-to-run noise, so ~17% is our measurement floor.
Improvements smaller than that cannot be claimed from a single pair of runs.

BATCH EXPLORER
One process, many cases, one JSON. Startup was ~25-30 s of engine boot for ~3 s of
work, which is what made every iteration expensive.

  3 cases in 6.59 s of case time
  standalone vs batched, same binary: hash 235AC2DC, 2,461 tris, 343,000 tunnel
  lookups, 554,381 passage evaluations -- identical on both

-out= is enforced absolute under the plugin's own Saved/.

CACHE BREAKDOWN (the 272 KB/entry question)
The slot table is small. The weight is spatial-index bins and candidate arrays,
room arrays, support-column arrays and tunnel-world indices -- i.e. much of the
411 MiB is the spatial index ee89c4d added, which also bought 0% end-to-end.
Worth revisiting on those terms.

RESEARCH (recorded, not acted on) -- CODEX-TASK-1-PROFILER-BATCH-RESEARCH.md
Ranked follow-ups: deterministic empty-space early-out, density-grid reuse, task
granularity (ParallelForWithExistingTaskContext + MinBatchSize), SIMD MC (~2x over
optimised scalar, but cross-machine determinism is the risk), sparse hierarchy,
RMC partial updates, Transvoxel LOD seams. Sources cited in the doc.
⚠️ Upstream RMC is 5.3.2; the owner's copy identifies as 5.4 with custom
modifications. No upgrade is safe. Left untouched.

PUSHBACK, accepted: "buckets must sum to their parent" needs a parallel-time
definition -- summing worker CPU is not wall time. Reports now separate worker CPU
sum from wall-clock estimate.

End-to-end unchanged, as expected for a tooling change: 2.746 / 2.691 s on the
128^3 seed 1337 region (was 2.678-2.705). Build clean.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_012aheo2crrZmHuYtPpdY2Cb
2026-09-09 05:02:21 +02:00
Fr0zkaandClaude Opus 5 ee89c4d8c2 perf(gen): 5x fewer candidates, 16x cheaper floor -- and 0% end-to-end. Read the last section.
Owner, after playing 0576e80: "slightly faster, still not on par... I can outrun the
generation and fall." Also, unprompted: "the tunnels seem forced, with a forced
flat -- it technically looks good, but could be a reason." He was right that it
was a reason; it was not THE reason.

WHAT LANDED, all real and all measured

Conservative spatial index (immutable per-chunk uniform bins, baked conservative
bounds, squared rejects, deterministic ordering):

  candidates scanned/sample   25.140 -> 5.192
  candidates evaluated/sample 13.879 -> 2.992
    cave tunnels  11.228/6.069 -> 1.525/0.723
    tunnel core   11.228/5.831 -> 1.216/0.567

The earlier flat AABB attempt failed because loose bounds culled almost nothing
while adding a pass. Technique from GPU Gems 3 ch.32 broad-phase.

The forced-flat floor, which the owner spotted by eye: a floor decision is
inherently per-COLUMN and was being recomputed for every Z sample in that column.
Now resolved once per integer XY column and reused.

  TunnelCorePosts   2.29 us/sample -> 0.138 us/sample   (16x)

The floor is unchanged in behaviour: still applied only after a tunnel passes its
world bounds and walkable projection, still walkable, look untouched.

FIRST MEASUREMENT OF OUR MEMORY FOOTPRINT
The owner: "it shouldn't be pressured on such system, even less when not running
anything." He is right, and it is ours:

  total resident worker cache   431,162,116 B  =  411 MiB
  15 workers                    27.41 MiB each
  average valid entry           278,704 B
  largest entry                 541,344 B
  static slot storage             2.4 MiB   (dynamic: 428.6 MB)

Cutting 4096 -> 128 slots only saved static storage. The weight is 272 KB PER
CACHED CHUNK STATE, ~102 live per worker. Nobody has yet asked why one cached
chunk state needs 272 KB. That is the open question, not the slot count.

⚠️ AND THE PART THAT MATTERS MOST: THIS BOUGHT NOTHING END-TO-END

  128^3 TunnelNetwork, seed 1337 slot 1, same region, unprofiled:
    before this commit   2.623 s
    after, 3 runs        2.705 / 2.678 / 2.682 s

Flat. A 5x candidate reduction and a 16x cheaper floor moved real generation time
by zero.

The reason is visible in the numbers and I should have caught it earlier: the
PROFILED path reports 14.74 us/sample while the real unprofiled cost is
1.28 us/voxel. **The instrument inflates by ~11x.** Every bucket we have been
ranking and optimising for two rounds was measured under that inflation, so the
ranking does not reflect where real time goes. We optimised what the profiler
exaggerated.

⇒ Before any further optimisation: make the profiler cheap enough that profiled
and unprofiled totals agree within a small factor, or switch to sampling. An
alarming number is the instrument until proven otherwise -- three for three in
this project, and now four.

Still true: ~21x slower than the pre-op-stack build, and generation still loses
to a walking player. Geometry changed by 40 triangles (153,692 -> 153,732), which
is allowed; two full exports hash identically (37E00BEE..0A7DF). Build 42/42.
No CPU-feature dispatch. Nothing outside Plugins/VoxelForge was touched.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_012aheo2crrZmHuYtPpdY2Cb
2026-09-09 03:05:40 +02:00
Fr0zkaandClaude Opus 5 0576e800c4 perf(gen): the landing work was per-voxel -- 342s to 2.6s, same world
The owner played 64f5d61 and reported the truth: "generation still takes ages...
TunnelNetwork doesn't even finish generating, as big as the surface world" while
SurfaceWorld completed in under 10s, and stopping PIE hung for 30+ seconds.

e08b49a's 21x was real and irrelevant. It fixed per-CHUNK state rebuilds, which
dominate the commandlet export path. The game is bound by per-VOXEL evaluation.
Same symptom, different bottleneck, and nobody had measured the second one.

WHY PIE HUNG
bShuttingDown was never checked inside VoxelMarchingCubesMesher.cpp -- zero
occurrences. A worker inside GenerateMesh could not abort, so 64f5d61's correct
unconditional EndPlay wait was waiting on tiles physically unable to stop. The
hang was not a teardown bug; it was evidence that one tile took tens of seconds.
Added shutdown polling per slab/row in the mesher and through GenerateTileResult;
aborted results carry Epoch + bAborted and ProcessQueue drops them. EndPlay still
waits unconditionally -- the 3s mark only logs now.

  PIE stop   3.409s / 44.759s  ->  4 ms teardown, 38 us worker drain

WHERE THE PER-VOXEL COST WAS
The owner's own comparison was the sharpest instrument available. Profiled both:

  GetDensityAt          TunnelNetwork 12.64 us/sample   SurfaceWorld 1.32
  tunnel candidates evaluated      7.088 per sample                 0
  tunnel-core candidates evaluated 7.201 per sample                 0
  room candidates evaluated        1.000 per sample                 0

  largest buckets: RoomGraphSource 2.57, TunnelCorePosts 0.76,
                   PassageCarveOp 0.22, PassageStructuralPosts 0.20

The three regressing commits map cleanly, and one is innocent:
  7a20eee drainage tree  -- cache-build work, NOT per-voxel
  413c15d landings       -- repeated full passage modification per sample
  55bf807 landing rooms  -- room SDF + tunnel/core evaluation per sample

Fixes: FPassageCarveOp carves only, landing/support moved to the structural MC
post; tunnel core support and SDF fused into one pass; room graph caches shared
per worker on complete deterministic keys; tunnel density cache uses open
addressing with 4096 slots. Room cache rebuilds fell to 9 per 42,875 samples, so
what remains is genuine O(local cached room/tunnel count) work.

  TunnelNetwork 128^3, seed 1337 slot 1, same region:
    342.2 s / 163.161 us/vox   ->   2.623 s / 1.251 us/vox     (130x)

  Geometry SHA-256 aaf95559..066b4, IDENTICAL to the pre-optimisation run at the
  same roughness. 153,692 triangles either way. Verified independently of the
  agent's own report.

NOT FIXED, and the first one is the next real target:
- L4 tiles still cost 16.93 s. Hit rate falls 99.9% (L0) -> 23.7% (L4), but
  1024 -> 4096 slots only moved 18.39s -> 16.93s and the 1,927 misses ARE the
  distinct key count. That is low reuse, not eviction. A bigger cache will not
  save it.
- TunnelNetwork is still ~10x SurfaceWorld (0.354s vs 0.028s on a matched 32^3).
- The live PIE tile table is SurfaceWorld: this checkout's PIE map is configured
  that way. TunnelNetwork went through the same mesher and density path via the
  commandlet, but no TunnelNetwork tile has been timed in an actual game session.
  Export numbers are not presented as game numbers.

Still outstanding, untouched here: the inter-strate passage has intersections it
should not have, routes through open passage when it should not, and should
descend from a low point of the current strate.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_012aheo2crrZmHuYtPpdY2Cb
2026-09-08 23:47:53 +02:00
Fr0zka 69fa73e07e tmp 2026-07-26 02:11:11 +02:00
Fr0zka cb61c8b2e4 potential perf regression 2026-07-04 11:30:43 +02:00
Fr0zka e6cd852129 Another pass 2026-06-23 08:30:13 +02:00
Fr0zka db558d9e14 j 2026-06-16 03:39:22 +02:00
Fr0zka f030eec08a Upload of all files, starting point 2026-06-09 20:21:29 +02:00