perf: use Matrix.gram() for XtX#28
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XtX = Xt.mmul(X) is the symmetric Gram matrix XᵀX. ml-matrix 6.13.0 adds Matrix.gram() which computes only the upper triangle and skips zero entries, so it is ~2x faster on dense inputs and far faster on sparse ones. On the 98.7%-sparse spectral test fixture the full fcnnls run drops from ~29.7 ms to ~3.2 ms per iteration (~9x), with bit-identical results. Also bump ml-matrix to ^6.13.0 (required for gram()) and rework the benchmark into a reproducible warmup + best-of-N harness. Assisted-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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XtX = Xt.mmul(X)withX.gram()(new in ml-matrix 6.13.0) and bumpml-matrixto^6.13.0. Bit-identical results;gram()skips zero entries, so on the 98.7%-sparse spectral fixture the XtX product (which dominated runtime) drops ~9×.