wiggum loop experiment #7288

Performance Gate Passed

✅ 1122 untouched benchmarks
🆕 178 new benchmarks
⏩ 1530 skipped benchmarks¹

	Mode	Benchmark	`BASE`	`HEAD`	Efficiency
🆕	Simulation	`compare_to_constant[unique_32_invalid_every_16]`	N/A	5.6 ms	N/A
🆕	Simulation	`compare_to_constant[unique_32_invalid_every_4]`	N/A	6.4 ms	N/A
🆕	Simulation	`compare_to_constant[unique_512_invalid_every_16]`	N/A	5.8 ms	N/A
🆕	Simulation	`compare_to_constant[unique_512_invalid_every_4]`	N/A	6.6 ms	N/A
🆕	Simulation	`filter_auto[few_long_slices_runs_16]`	N/A	1.1 ms	N/A
🆕	Simulation	`filter_auto[clustered_few_runs_runs_16]`	N/A	1.1 ms	N/A
🆕	Simulation	`filter_auto[clustered_few_runs_runs_4096]`	N/A	140.1 µs	N/A
🆕	Simulation	`filter_auto[few_long_slices_runs_4096]`	N/A	140.3 µs	N/A
🆕	Simulation	`filter_auto[random_runs_256]`	N/A	2 ms	N/A
🆕	Simulation	`filter_auto[clustered_few_runs_runs_256]`	N/A	905.6 µs	N/A
🆕	Simulation	`filter_auto[few_long_slices_runs_256]`	N/A	905.5 µs	N/A
🆕	Simulation	`filter_auto[long_run_heavy_runs_65536]`	N/A	96.3 µs	N/A
🆕	Simulation	`filter_auto[long_run_heavy_runs_16384]`	N/A	104.4 µs	N/A
🆕	Simulation	`filter_force_encoded[clustered_few_runs_runs_16]`	N/A	11.7 ms	N/A
🆕	Simulation	`filter_auto[random_runs_16]`	N/A	2.2 ms	N/A
🆕	Simulation	`filter_force_encoded[clustered_few_runs_runs_256]`	N/A	843.5 µs	N/A
🆕	Simulation	`filter_auto[many_short_slices_runs_16]`	N/A	1.2 ms	N/A
🆕	Simulation	`filter_force_encoded[few_long_slices_runs_256]`	N/A	844.1 µs	N/A
🆕	Simulation	`filter_force_encoded[long_run_heavy_runs_65536]`	N/A	96.2 µs	N/A
🆕	Simulation	`filter_auto[long_run_heavy_runs_4096]`	N/A	139.1 µs	N/A
...	...	...	...	...	...

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

_{Comparing adam/wiggle (a6a0907) with develop (b2a5a70)}

1530 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. ↩