Ah, thanks, that's good to know. I was under the mistaken impression that loops are always the fastest option in Julia since it's brought up pretty frequently. Out of curiosity, what factor of slow-down would not using the optimized routines cause?
On Wed, Jul 8, 2015 at 10:39 AM, Andreas Noack <[email protected] > wrote: > You could, but unless the matrices are small, it would be slower because > it wouldn't use optimized matrix multiplication. > > 2015-07-08 10:36 GMT-04:00 Josh Langsfeld <[email protected]>: > >> Maybe I'm missing something obvious, but couldn't you easily write your >> own 'cross' function that uses a couple nested for-loops to do the >> arithmetic without any intermediate allocations at all? >> >> On Tuesday, July 7, 2015 at 6:24:34 PM UTC-4, Matthieu wrote: >>> >>> Thanks, this is what I currently do :) >>> >>> However, I'd like to find a solution that is both memory efficient (X >>> can be very large) and which does not modify X in place. >>> >>> Basically, I'm wondering whether there was a BLAS subroutine that would >>> allow to compute cross(X, w, Y) in one pass without creating an >>> intermediate matrix as large as X or Y. >>> >>> >
