Merge pull request #129 from AdaWorldAPI/claude/post-sprint-direct-pushes

docs: audit trail for 5 direct-to-master post-sprint commits

Author: AdaWorldAPI

DIRECT_PUSH_AUDIT.md

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+# Direct-to-master audit — burn-parity post-sprint (2026-04-30)
+
+5 commits pushed directly to master during live session. This file
+documents the rationale for each — the audit trail that was skipped
+when pushing directly.
+
+## Commits
+
+| SHA | Title | LOC |
+|---|---|---|
+| `ccf5b77b` | fix(deps): surgical hpc-extras gate | +24/-19 |
+| `dfa25a62` | fix(backend): missing cfg gate + CBLAS aliases | +40/-1 |
+| `2cd3d8b1` | feat(backend): unified INT8/BF16 GEMM dispatch | +75 |
+| `00b6ee57` | feat(backend): re-export all slice-level ops | +44 |
+| `c1c7ae42` | feat(simd): elementwise slice ops (simd_ops.rs) | +294 |
+
+## ccf5b77b — surgical hpc-extras gate
+
+PR #116 (sprint A1) gated ALL of `pub mod hpc;` behind `hpc-extras`.
+This hid BF16, F16, quantization, fingerprints, VSA, plane, seal —
+everything burn-ndarray and lance-graph need daily.
+
+Fix: `pub mod hpc;` now `#[cfg(feature = "std")]` (always available).
+Only 5 research modules gated: p64_bridge, crystal_encoder, deepnsm,
+spo_bundle, compression_curves. blake3 made unconditional.
+
+## dfa25a62 — CBLAS-compat aliases
+
+`pub use mkl::{ gemm_f32, ... }` was missing its `#[cfg(feature = "intel-mkl")]`
+gate — broken without the feature. Fixed + added `cblas_sgemm` / `cblas_dgemm`
+as MKL drop-in replacements routing through native SIMD.
+
+## 2cd3d8b1 — unified GEMM dispatch
+
+INT8 GEMM existed in 3 places, BF16 in 2, with no unified entry point.
+Added `backend::gemm_i8()` (VNNI → scalar) and `backend::gemm_bf16()`.
+Plus CBLAS aliases `cblas_gemm_s8s8s32` / `cblas_gemm_bf16bf16f32`.
+
+## 00b6ee57 — unified slice-op re-exports
+
+Scattered across kernels_avx512 (pub(crate)), simd_int_ops, simd_half,
+hpc/reductions. Now all reachable from `ndarray::backend::*`.
+
+## c1c7ae42 — simd_ops.rs
+
+Portable elementwise slice ops using operator traits on polyfill types.
+`ndarray::simd::{add_f32, mul_f32, scale_f32, ...}`.
+Works on all platforms. 11 tests. 1778 total pass.