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Execute tensor product functions with RowFn - #9769

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Execute tensor product functions with RowFn#9769
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ct/row-fn-tensor-products-v2

Execute tensor products with RowFn

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CodSpeed HQ / CodSpeed Performance Analysis succeeded Sep 4, 2026 in 0s

Performance Gate Passed

⚠️ Unknown Walltime execution environment detected

Using the Walltime instrument on standard Hosted Runners will lead to inconsistent data.

For the most accurate results, we recommend using CodSpeed Macro Runners: bare-metal machines fine-tuned for performance measurement consistency.

⚠️ Different runtime environments detected

Some benchmarks with significant performance changes were compared across different runtime environments,
which may affect the accuracy of the results.

Open the report in CodSpeed to investigate

⚡ 14 improved benchmarks
✅ 2173 untouched benchmarks
⏩ 218 skipped benchmarks1

Performance Changes

Mode Benchmark BASE HEAD Efficiency
Simulation column_x_constant[2] 486.9 µs 127.7 µs ×3.8
Simulation column_x_constant[32] 422.2 µs 128.5 µs ×3.3
Simulation column_x_constant[256] 637.6 µs 309.6 µs ×2.1
Simulation column_x_column[2] 205.3 µs 101 µs ×2
Simulation column_x_extension_constant[256] 540.2 µs 277.6 µs +94.56%
Simulation nullable[2] 592.5 µs 323.2 µs +83.32%
Simulation non_nullable[2] 594 µs 327.4 µs +81.41%
Simulation column_x_extension_constant[2] 235.4 µs 144.3 µs +63.09%
Simulation nullable[2] 630.5 µs 417.1 µs +51.15%
Simulation non_nullable[2] 631 µs 419.3 µs +50.5%
Simulation column_x_extension_constant[32] 191.7 µs 132.6 µs +44.58%
Simulation column_x_column[32] 96.2 µs 76.8 µs +25.25%
Simulation column_x_column[256] 90.6 µs 74.6 µs +21.47%
Simulation allocate_drop_bytes[0] 520.2 ns 466 ns +11.62%

Tip

Curious why performance improved? Comment @codspeedbot explain why performance improved on this PR, or directly use the CodSpeed MCP with your agent.


Comparing ct/row-fn-tensor-products-v2 (4f0fa1a) with develop (a997c3f)2

Open in CodSpeed

Footnotes

  1. 218 benchmarks were skipped, so the baseline results were used instead. If they were deleted from the codebase, click here and archive them to remove them from the performance reports.

  2. No successful run was found on ct/row-fn-tensor-l2-v2 (5974184) during the generation of this report, so develop (a997c3f) was used instead as the comparison base. There might be some changes unrelated to this pull request in this report.