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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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Execute tensor products with RowFn

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CodSpeed HQ / CodSpeed Performance Analysis failed Sep 10, 2026 in 0s

5 benchmarks regressed

⚠️ 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

⚡ 25 improved benchmarks
❌ 5 regressed benchmarks
✅ 2157 untouched benchmarks
🆕 10 new benchmarks
⏩ 218 skipped benchmarks1

Warning

Please fix the performance issues or acknowledge them on CodSpeed.

Performance Changes

Mode Benchmark BASE HEAD Efficiency
WallTime mul_u64_nonnull_neon 15.4 µs 20.5 µs -24.89%
Simulation decompress[u64, (4000, 1024)] 70.5 µs 86 µs -18.03%
WallTime mul_i64_nonnull_neon 17.3 µs 20.1 µs -13.81%
WallTime multiply_shapes_neon[(16384, PerRowPerRow)] 17.4 µs 20.1 µs -13.43%
WallTime words_gather_scalar_avx2[65536] 8.3 µs 9.4 µs -11.9%
Simulation column_x_constant[2] 517.8 µs 131 µs ×4
Simulation column_x_constant[32] 473.9 µs 131 µs ×3.6
WallTime filtered_owned_i64_avx2[NineNullsInTen] 36.8 µs 13.3 µs ×2.8
WallTime filtered_owned_i64_avx512[NineNullsInTen] 36.9 µs 13.4 µs ×2.7
WallTime filtered_owned_i64_avx2[OneNullInEight] 56.1 µs 22.2 µs ×2.5
Simulation column_x_constant[256] 742.4 µs 306 µs ×2.4
WallTime filtered_owned_i64_avx512[OneNullInEight] 62.3 µs 26.3 µs ×2.4
WallTime filtered_sink_i64_avx2[NineNullsInTen] 36.8 µs 16.4 µs ×2.3
WallTime filtered_sink_i64_avx512[NineNullsInTen] 36.9 µs 16.5 µs ×2.2
Simulation column_x_extension_constant[256] 573.8 µs 274.4 µs ×2.1
Simulation column_x_column[2] 201 µs 101.8 µs +97.52%
WallTime filtered_sink_i64_avx512[OneNullInEight] 62.2 µs 31.5 µs +97.47%
Simulation column_x_extension_constant[2] 274 µs 147.9 µs +85.31%
Simulation nullable[2] 591.4 µs 323.9 µs +82.57%
Simulation non_nullable[2] 593.6 µs 329 µs +80.44%
... ... ... ... ... ...

ℹ️ Only the first 20 benchmarks are displayed. Go to the app to view all benchmarks.

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Investigate this regression by commenting @codspeedbot fix this regression on this PR, or directly use the CodSpeed MCP with your agent.


Comparing ct/row-fn-tensor-products-v2 (4bd332d) with ct/row-fn-tensor-l2-v2 (929ae6d)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 (c11ae04) during the generation of this report, so b771900 was used instead as the comparison base. There might be some changes unrelated to this pull request in this report.