Sorry, should clarify: @data is an array of PDL values. The piddles themselves are simple one dimensional vectors of floats. The maximum size of @data is about 45000, the piddles usually have around 100 values.

$pears is not used because that's the end result I'm going after, it will just get stored to a file or database, there isn't much there, optimization-wise. Similarly, it doesn't matter how @data gets loaded, the time that it takes is negligible compared to the main computation.

So @data is preloaded with PDL vectors of floats, which are the z-scores of the original values. All I need is the fastest way to divide the sum of the products of these standard scores, for each pair of elements of @data, by the size of the piddles, to get the correlation coefficient (they are all the same size, and I know the size from the start).

Say N is the number of elements in @data, and M is the size of those elements; as far as I can tell I need to perform a minimum of N^2/2*M multiplications, N^2/2*(M-1) substractions and N^2/2 divisions - I just don't know how much slower than C perl (and PDL specifically) is at such things.

btw, I am not quite sure what your perl example is doing (especially the sum() sub), I don't think that's what I have in mind.

Should be pretty obvious that I know very little C, though I am sure I should be able to scrape togther something this trivial if it's worth it (and 50X speed up would definitely be worth it, if that is actually the case).

Thanks for the help