Optimize list_contains with prepared constant sets

[robert3005]

Replace constant-set membership comparison/OR chains with prepared, single-pass probes

[codspeed]

Merging this PR will regress 7 benchmarks

⚠️ Unknown Walltime execution environment detected

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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.

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⚡ 4 improved benchmarks
❌ 7 regressed benchmarks
✅ 2055 untouched benchmarks
⏩ 503 skipped benchmarks¹

Warning

Please fix the performance issues or acknowledge them on CodSpeed.

Performance Changes

	Mode	Benchmark	BASE	HEAD	Efficiency
❌	WallTime	dict_canonicalize_gt_u8_avx512[1000000]	422.7 µs	836.6 µs	-49.47%
❌	Simulation	optimize_lookup_predicate[ids=192, shape=in_list]	49.9 µs	75.9 µs	-34.2%
❌	Simulation	optimize_lookup_predicate[ids=128, shape=in_list]	50.6 µs	73.2 µs	-30.92%
❌	Simulation	optimize_lookup_predicate[ids=64, shape=in_list]	50.4 µs	70.6 µs	-28.6%
❌	Simulation	optimize_lookup_predicate[ids=16, shape=in_list]	51.2 µs	69.5 µs	-26.23%
❌	Simulation	optimize_lookup_predicate[ids=256, shape=in_list]	79.1 µs	105.3 µs	-24.9%
❌	Simulation	optimize_lookup_predicate[ids=1, shape=in_list]	74.4 µs	89.9 µs	-17.25%
⚡	Simulation	i64_random_chunked[256]	20,802.2 µs	232 µs	×90
⚡	Simulation	i64_random[256]	5,685.6 µs	134.9 µs	×42
⚡	Simulation	utf8_random[256]	14,403.7 µs	371.7 µs	×39
⚡	Simulation	nested_list_random[32]	7.4 ms	1 ms	×7.2

Tip

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

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_{Comparing claude/friendly-knuth-dj6ed1-list-contains (77467d3) with rk/list-contains-benchmarks (27f94c1)}

Footnotes

1. 503 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. ↩

[joseph-isaacs]

How do i extend this to work for new custom kernels?

I really think we want to make probe an array to allow reduce/execute rules?

[robert3005]

this is a hack, we essentially have common setup we would like to share across chunks, if we just dispatch over each chunk there's no place to store the shared state