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docs(plan): ppc64le has VSX kernels since v0.2.3; scalar targets unmeasured vs NumPy #21

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tannevaled merged 1 commit into from
Oct 4, 2026
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docs(plan): ppc64le has VSX kernels since v0.2.3; scalar targets unmeasured vs NumPy #21

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9 changes: 6 additions & 3 deletions docs/plan-ndarray.md
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Expand Up @@ -121,9 +121,12 @@ suite (plus the per-arch CI jobs already wired in `.github/workflows/ci.yml`).
validated per-arch in CI (bit-identical to the scalar oracle for the
elementwise/sqrt/max ops; tight-tolerance for the sum reduction, whose
lane-parallel grouping is a valid reordering — the same trade-off as
NumPy's pairwise sum). The other four targets keep the validated scalar
oracles plus a scalar 4×4 GEMM micro-kernel over the packed panels, and
still win via packing + cache-blocking + multicore. Split-CI: the pure-Go
NumPy's pairwise sum). Since v0.2.3 ppc64le has VSX kernels too (sum,
dot, sqrt, elementwise, an 8×8 GEMM micro-kernel), through go-asmgen's
VSX encoders. The other targets (riscv64, loong64, s390x, 32-bit) keep the
validated scalar oracles plus a scalar 4×4 GEMM micro-kernel over the
packed panels, with packing + cache-blocking + multicore; they have not
been measured against NumPy. Split-CI: the pure-Go
core + multicore are held to 100% statement coverage; the generated `.s`
is validated by the per-arch native/qemu execution jobs.
- **SIMD `Sqrt`/`Max` and the packed, cache-blocked GEMM — DONE (no longer
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