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emit_wgsl

A single moderately complex shader. Compiled to multiple targets by the harness (same source, varying -target) to isolate generateOutput cost. ``n`` scales the amount of straight-line math the backend must emit. Scaling null: n scales op count and the emitted output is O(n); ideal codegen cost is O(n).

bucket: codegen_source  ·  mode: target  ·  flags: -target wgsl

Phase composition vs N (stacked sub-counters)

compileInner split into phase buckets (named leaves + (self) residuals) stacked across the sweep sizes — the top edge is compileInner, so you can see which phase drives the scaling.

emit_wgsl — phase composition vs N (v2026.12, median ms) emit_wgsl 47.4× over N 100→800 0.0 2156 4312 100 200 400 800 N emit_wgsl — parseTranslationUnit emit_wgsl — SemanticChecking emit_wgsl — generateIR emit_wgsl — frontEndExecute (self) emit_wgsl — specializeModule emit_wgsl — simplifyIR emit_wgsl — linkIR emit_wgsl — unrollLoopsInModule emit_wgsl — legalizeResourceTypes emit_wgsl — legalizeExistentialTypeLayout emit_wgsl — performMandatoryEarlyInlining emit_wgsl — performForceInlining emit_wgsl — emitEntryPointsSourceFromIR emit_wgsl — compileInner (self) phase buckets parseTranslationUnit SemanticChecking generateIR frontEndExecute (self) specializeModule simplifyIR linkIR unrollLoopsInModule legalizeResourceTypes legalizeExistentialTypeLayout performMandatoryEarlyInlining performForceInlining linkAndOptimizeIR (self) emitEntryPointsSourceFromIR generateOutput (self) compileInner (self)

Scaling analysis

floor-subtracted power-law fit (t − floor) = a·Nk; floor = the minimal workload (fixed per-compile cost), k the global exponent, top-2× the local high-end doubling ratio.

N rangefloor (ms)k (work)fit R²t(Nmin)t(Nmax)top-2×
100–800141.920.9958439934.91×

Growth attribution (N=100 → N=800)

compileInner grows by 3909 ms across the sweep; the mutually-exclusive phase buckets below partition that growth exactly (no nested-timer double counting). × lin is the same metric as the top-level panels, per bucket: the end point vs a linear expectation anchored to the bucket's share of the minimal floor and fitted on the low-N half — 1.0 = grew exactly linearly, >1 bends up. The super-linearity lives where × lin (and k) are red.

buckett@N=100t@N=800Δ msshare× lin∝Nk
emitEntryPointsSourceFromIR311960+193049%5.02×1.99
legalizeExistentialTypeLayout9752+74319%5.95×2.14
legalizeResourceTypes8745+73619%5.85×2.15
simplifyIR7330+3238%4.25×1.88

Near-constant (≤2% of growth each): specializeModule (4→78 ms), SemanticChecking (17→69 ms), generateIR (6→54 ms), linkIR (1→2 ms), parseTranslationUnit (0→2 ms), performMandatoryEarlyInlining (0→1 ms), performForceInlining (0→0 ms), frontEndExecute (self) (1→0 ms), unrollLoopsInModule (0→0 ms), compileInner (self) (0→0 ms).

Sweep numbers (median ms)

NcompileInneremitEntryPointsSourceFromIRgenerateOutput
100845959
200244211211
400814761761
800399338693870