alt Hacker NewsThe title is slightly misleading, I mean yes, naive binary search might have larger constant but the algorithm is still O(log(n)). This is still some "divide and conquer" style algorithm just with bunch of CPU specific optimizations. Also this works well with simple data structures, like integers, with more complex objects (custom comparators) it matters less.
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> The title is slightly misleading, I mean yes, naive binary search might have larger constant but the algorithm is still O(log(n)).
I think the title is not misleading since the Big O notation is only supposed to give a rough estimate of the performance of an algorithm.
(I agree though that binary search is already extremely fast, so making something twice as fast won't move the needle for the vast majority of applications where the speed bottleneck is elsewhere. Even infinite speed, i.e. instant sorted search, would likely not be noticeable for most software.)
The complexity of binary search in terms of "search" (comparison) operations is exactly log_2(n)+1, not just O(n). This algorithm just uses modern and current processor architecture artifacts to "improve" it on arrays of up to 4096 elements.
So not exactly "n" as in O(n).
Also: only for 16-bit integers.