[Numpy-discussion] Optimization suggestion sought

josef.pktd@gmai... josef.pktd@gmai...
Sun Dec 26 08:34:10 CST 2010


On Sun, Dec 26, 2010 at 3:51 AM, Enzo Michelangeli <enzomich@gmail.com> wrote:
> For a pivoted algorithm, I have to perform an operation that in fully
> vectorized form can be expressed as:
>
>    pivot = tableau[locat,:]/tableau[locat,cand]
>    tableau -= tableau[:,cand:cand+1]*pivot
>    tableau[locat,:] = pivot
>
> tableau is a rather large bidimensional array, and I'd like to avoid the
> allocation of a temporary array of the same size holding the result of the
> right-hand side expression in the second line of code (the outer product of
> tableau[:,cand] and pivot). On the other hand, if I replace that line with:
>
>    for i in xrange(tableau.shape[0]):
>        tableau[i] -= tableau[i,cand]*pivot
>
> ...I incur some CPU overhead for the "for" loop -- and this part of code is
> the botteneck of the whole algorithm. Is there any smarter (i.e., more
> time-efficient) way of achieving my goal?

just a generic answer:

Working in batches can be a good compromise in some cases. I instead
of working in a loop with one row at a time, loop and handle, for
example, 1000 rows at a time.

Josef

>
> TIA --
>
> Enzo
>
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