[Numpy-discussion] multiprocessing shared arrays and numpy

[Gael Varoquaux]

On Fri, Mar 05, 2010 at 09:53:02AM +0100, Francesc Alted wrote:
> Yeah, 10% of improvement by using multi-cores is an expected figure for
> memory bound problems.  This is something people must know: if their
> computations are memory bound (and this is much more common that one
> may initially think), then they should not expect significant speed-ups
> on their parallel codes.

Hey Francesc,

Any chance this can be different for NUMA (non uniform memory access)
architectures? AMD multicores used to be NUMA, when I was still following
these problems.

FWIW, I observe very good speedups on my problems (pretty much linear in
the number of CPUs), and I have data parallel problems on fairly large
data (~100Mo a piece, doesn't fit in cache), with no synchronisation at
all between the workers. CPUs are Intel Xeons.

Gael