can multi-core improve single funciton?
ptmcg at austin.rr.com
Tue Feb 10 08:38:01 CET 2009
On Feb 10, 12:43 am, Chris Rebert <c... at rebertia.com> wrote:
> Considering the GIL, I highly doubt it so. Also, the algorithm is
> fundamentally linear -- each result depends on previous results -- so
> I don't think you can easily parallelize it (if at all). You'd
> probably get greater speedup using memoization.
Even worse than linear, the function is recursive, which as I
understand it, is inherently a no-no when looking for code that is
If you want multi-core to have some benefit, then your program must
have a way for separate parts of the problem to be processed
independently. Many matrix processing problems fall into this camp,
since the various cells of the matrix can be worked on separately from
all others. Prime number searchers break up a problem by having
separate processes scan different number ranges independently, or have
multiple processes perform rough pass prime filters, who write
possible primes to another queue to be more exhaustively checked.
This saves the expensive/exhaustive check from being done on every
number. Fractal graphics generators (Mandelbrot set plots) can break
up the graphics range among different processors, or keep a "queue" of
pixels to generate, and each calculator process pulls from the queue
until all pixels are computed (some pixels take longer to compute than
More information about the Python-list