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Sort Linked Lists 10X Faster Than MergeSort
virusfree tells us about a new algorithm that has been developed that the author claims can sort a linked list up to 10 times faster than MergeSort. "BitFast," a member of the Hash algorithms family, is available in C and C++ under the GPL.
Don't use this code !
:
:-)
First, there are multiple bugs in the code itself :
1) everywhere, it is assumed that 2^16 = 65535 and not 65536. Arrays are allocated for this size too, but are used with 65536 entries. (un)fortunately for him, the space is probably allocated anyway so the program does not crash on this.
2) a similar bug in the random number generator carefully avoids dangerous values, because he generates numbers between min and max by doing a modulo on max-min , which prevents max from being produced. This is not a
big deal anyway, just that it hides the bug.
3) he assumes everywhere that "long" is unsigned and "short int" too. This makes the code SegFault on Linux with negative array indexes. The fix is obvious, though.
And most of all : times are measured in optimal conditions. Indeed, this algorithm is
just a radix sort with a large radix (2^16). A radix algorithm is efficient when the number
of elements is high compared to the radix, because at every level, all radix entries have to
be scanned for existing values. In his example, he sorts 4 million elements. His code is faster
than the merge sort on 4 million entries, just as would be any radix sort. But on smaller sets,
it still takes the same time per level, because it has to scan all 65536 entries even if there
are only 100 numbers. The fact is that for less than 10000 values, the mergesort becomes faster in his own code.
When measuring algorithms complexity, we use the O(x) notation. The time per iteration is never
considered. When the time matters (as in his example), we should consider the time per iteration (T), and the total time (t) will follow
t = T . complexity
In complexity, his algorithm is O(N) on 16 bits, but the time per iteration is very high. Other sorting algorithms are O(N.log(N)). So the total time is :
t1 = T1 . O(N) for his algorithm, and :
t2 = T2 . O(N.log(N)) for the mergesort.
But when T1 > T2.log(N), he looses, which is almost always because log(N) is small for 16 bits, and T2 too because operations are very simple. In his case, T1 is very high because it represents the time required to scan 65536 values.
It's amazing that he fell in such a beginner's trap. I suppose that he's still a student, which would explain the total lack of portability and newbie's bugs in the code.
Well tried anyway
Willy