perf(dense-ffn): per-op profiling breakdown for decode forward()

[Sujimoshi]

Summary

Second in a planned split of #218 (DFlash speculative decoding) into smaller, independently reviewable PRs (first was #255).

• Adds a prof! macro to crates/spark-model/src/layers/dense_ffn.rs (same shape as the existing pattern in moe/forward.rs / qwen3_ssm/ssm_forward.rs) and wraps every GPU op in DenseFfnLayer::forward()'s decode path with it.
• Covers all four dispatch branches: FP8 fast/slow path, BF16 path, and the NVFP4 default path (use_sw variant, split_silu branch, fused SiLU/GeLU branches).

Note on provenance: the original commit in #218 (18fc6549) targeted an older shape of forward(). Since then, #229 (NVFP4 W4A4 MMQ FFN) restructured the function and added the fp8/use_sw/split_silu branches. This PR re-applies the profiling breakdown against the current (post-#229) structure rather than patching mechanically — more dispatch branches means the per-op breakdown is more useful, not less, for isolating decode cost under whichever config is active.

No behavior change — prof! is a no-op unless ctx.profile is set.

Test plan

• cargo check -p spark-model (ATLAS_SKIP_BUILD=1, CUDA stubbed) — clean
• cargo fmt --check -p spark-model — clean
• cargo clippy -p spark-model --tests (ATLAS_SKIP_BUILD=1) — no warnings

🤖 Generated with Claude Code

[Sujimoshi]

Closing — this was purely diagnostic instrumentation (Dense FFN per-op profiling breakdown) split out of #218. The original perf investigation it supported is already done and documented; no active use case for it right now. Cheap to re-add later against whatever the code looks like at that point if a real need comes up.