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Apr 21, 2022 at 10:32 comment added Peter Cordes Binary search for the cut-point is unnecessary, just start summing from the end you want to keep, stopping when you get to a value you don't want. (Unless HW prefetching works much worse when looping downwards instead of upwards). Of course, actually taking time to sort is not a useful part of an algorithm that starts with unsorted data. A histogram might be, if you want to answer multiple queries for different cut-points, other than 128, from the same data. (Since the small value-range means there are many duplicates in this smallish array.)
S May 11, 2019 at 11:31 history suggested Konard CC BY-SA 4.0
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Jan 29, 2016 at 1:24 history wiki removed Shog9
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Apr 22, 2015 at 21:07 history edited user1196549 CC BY-SA 3.0
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Dec 20, 2013 at 23:05 history edited Lance Roberts CC BY-SA 3.0
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Jul 24, 2013 at 20:37 comment added user1196549 @DeadMG: this is indeed not the standard dichotomic search for a given key, but a search for the partitioning index; it requires a single compare per iteration. But don't rely on this code, I have not checked it. If you are interested in a guaranteed correct implementation, let me know.
Jul 24, 2013 at 16:31 comment added sehe sum= 3137536 - clever. That's kinda obviously not the point of the question. The question is clearly about explaining surprising performance characteristics. I'm inclined to say that the addition of doing std::partition instead of std::sort is valuable. Though the actual question extends to more than just the synthetic benchmark given.
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Jul 24, 2013 at 7:57 history answered user1196549 CC BY-SA 3.0