feat: iterative execution patched array #7345

Performance Regression: -23.81%

❌ 24 regressed benchmarks
✅ 1098 untouched benchmarks
⏩ 1530 skipped benchmarks¹

⚠️ Please fix the performance issues or acknowledge them on CodSpeed.

	Mode	Benchmark	`BASE`	`HEAD`	Efficiency
❌	Simulation	`take_search[(0.005, 1.0)]`	2.3 ms	3.1 ms	-23.81%
❌	Simulation	`take_search[(0.005, 0.1)]`	247.1 µs	320 µs	-22.8%
❌	Simulation	`take_search[(0.01, 0.05)]`	142.6 µs	179.1 µs	-20.4%
❌	Simulation	`take_search[(0.005, 0.05)]`	131.5 µs	168.1 µs	-21.74%
❌	Simulation	`take_search[(0.01, 1.0)]`	2.5 ms	3.3 ms	-22.34%
❌	Simulation	`take_search[(0.1, 1.0)]`	3.5 ms	4.3 ms	-17.11%
❌	Simulation	`take_search[(0.01, 0.1)]`	267.8 µs	340.8 µs	-21.41%
❌	Simulation	`take_search[(0.005, 0.5)]`	1.2 ms	1.5 ms	-23.68%
❌	Simulation	`take_search[(0.1, 0.05)]`	212.4 µs	249 µs	-14.68%
❌	Simulation	`take_search[(0.01, 0.5)]`	1.3 ms	1.6 ms	-22.22%
❌	Simulation	`take_search[(0.1, 0.5)]`	1.8 ms	2.2 ms	-16.95%
❌	Simulation	`take_search_chunked[(0.005, 0.05)]`	165.9 µs	196.9 µs	-15.77%
❌	Simulation	`take_search[(0.1, 0.1)]`	386.5 µs	459.5 µs	-15.89%
❌	Simulation	`take_search_chunked[(0.01, 0.5)]`	1.6 ms	1.9 ms	-15.98%
❌	Simulation	`take_search_chunked[(0.005, 1.0)]`	3 ms	3.6 ms	-17.12%
❌	Simulation	`take_search_chunked[(0.005, 0.5)]`	1.5 ms	1.8 ms	-17.03%
❌	Simulation	`take_search_chunked[(0.01, 0.05)]`	178.8 µs	209.8 µs	-14.78%
❌	Simulation	`take_search_chunked[(0.005, 0.1)]`	314.5 µs	376.5 µs	-16.46%
❌	Simulation	`take_search_chunked[(0.1, 0.1)]`	450 µs	512 µs	-12.12%
❌	Simulation	`take_search_chunked[(0.01, 1.0)]`	3.2 ms	3.9 ms	-16.06%
...	...	...	...	...	...

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

_{Comparing ji/iter-exe-2 (a763197) with develop (a30de02)}

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. ↩