[ExecuTorch][WebGPU] f16-accumulate (pwdqf16acc) steel q4gsw prefill GEMM

[JCNTH]

Stack from ghstack (oldest at bottom):

• [ExecuTorch][WebGPU] Test coverage for the f16-accumulate steel GEMM #20801
• -> [ExecuTorch][WebGPU] f16-accumulate (pwdqf16acc) steel q4gsw prefill GEMM #20800
• [ExecuTorch][WebGPU] Test coverage for the packed-word-dequant f16 steel GEMM #20799
• [ExecuTorch][WebGPU] Packed-word-dequant f16 steel q4gsw prefill GEMM #20798
• [ExecuTorch][WebGPU] Reuse pool for single-op scratch (-86.7 MiB) #20797
• [ExecuTorch][WebGPU] Test coverage for the f16 KV cache #20773
• [ExecuTorch][WebGPU] Add opt-in native f16 KV cache (−280 MiB, default-OFF) #20772
• [ExecuTorch][WebGPU] Test coverage for the f16-multiply steel q4gsw GEMM #20753
• [ExecuTorch][WebGPU] Add f16-multiply variant of the steel q4gsw prefill GEMM #20752
• [ExecuTorch][WebGPU] Steel q4gsw prefill GEMM — test coverage #20731
• [ExecuTorch][WebGPU] Add 256-thread "steel" q4gsw prefill GEMM #20730
• [ExecuTorch][WebGPU] Request shader-f16 device feature (enablement, fail-open) #20729
• [ExecuTorch][WebGPU] Unit tests for the WGSL shader-variant codegen #20728
• [ExecuTorch][WebGPU] WGSL shader-variant codegen (vec1/vec4, fp16-ready) + rms_norm dedup #20727

+46-56% end-to-end prefill tok/s over the shipped f16 steel q4gsw GEMM (Apple M4 Pro / Chrome Canary), behind a new opt-in build flag; perplexity held (13.32 -> 13.37, +0.05).

Problem: the f16 steel prefill GEMM (and its packed-word-dequant variant pwdq) accumulates its 4x4 register tile in f32. WebLLM/MLC accumulate in f16, which halves the accumulator footprint and raises occupancy — the largest remaining prefill gap vs MLC on Apple.

Solution: an f16-accumulate variant of the pwdq kernel — identical staging (dequant-once + hoisted scale) and 64x64/256-thread/BK=16 geometry, but the 4x4 accumulator is kept in f16 with fma() (mirrors MLC's array<f16,16> reduction) and cast to f32 in the epilogue for the f32 output/bias.

Before (pwdq): f16 multiply, f32 accumulate.
After (pwdqf16acc): f16 multiply, f16 accumulate, f32 epilogue.

Implementation:

• New q4gsw_linear_gemm_steel_half_pwdqf16acc.wgsl (+ generated header) + a new CMake option EXECUTORCH_WEBGPU_STEEL_F16ACC (default OFF, mirrors EXECUTORCH_WEBGPU_STEEL_F16) -> WGPU_BACKEND_STEEL_F16ACC.
• When enabled, overrides the f32-accumulate steel kernels for M>1 prefill whenever the device negotiated shader-f16 and group_size % BK == 0; else the f32-accumulate pwdq / half / f32 kernels run (fail-closed).

Constraints: LOSSY — f16 accumulation over the full K (up to 8192) is not bit-exact, so it ships on a perplexity bar, not a bit-exact gate (as MLC does): measured Llama-3.2-1B int4 perplexity 13.32 -> 13.37 (+0.05) on the real prefill path. Default-OFF keeps upstream builds on the strict f32-accumulate golden; the option is opt-in for latency-sensitive deployments.

Co-authored-with: Claude Code.
@exported-using-ghexport

Differential Revision: D111163606

Differential Revision: D111163606

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❌ 4 New Failures, 9 Pending

As of commit 4af5d96 with merge base f4b01a8 ():

NEW FAILURES - The following jobs have failed:

• pull / android / build-android (gh)
• pull / test-binary-size-linux-gcc / linux-job (gh)
  RuntimeError: Command docker exec -t d168394843fa44e10c55cdeda0caf9d68a0fcc247b677f34b15b4f4ba88620d0 /exec failed with exit code 1
• pull / unittest / linux / linux-job (gh)
  RuntimeError: Command docker exec -t f00a8c0839185be22ce011fe880a26f0778cae043c0704457b16cabd7fe65415 /exec failed with exit code 1
• pull / unittest-editable / linux / linux-job (gh)
  RuntimeError: Command docker exec -t 979c61d5d51f1bb07b9238227fbfc9e18525f732a343922e68fdc07b162035b5 /exec failed with exit code 1

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