On 5/14/12 2:51 PM, Anthony Scopatz wrote:
Hi Johann,
Thanks for bring this up. I believe that I have determined that this
is not a PyTables / pthreads issue. Doing some profiling
npoints=100, I found that most of the time (97%) was being spent
in the sum() call (see below). This
On Mon, May 14, 2012 at 3:05 PM, Francesc Alted fal...@pytables.org wrote:
[snip]
However, do not expect to use all your cores at full speed in this cases,
as the reductions in numexpr can only make use of one thread (this is
because this has not been implemented yet, not due to a intrinsic
On 5/14/12 3:12 PM, Anthony Scopatz wrote:
On Mon, May 14, 2012 at 3:05 PM, Francesc Alted fal...@pytables.org
mailto:fal...@pytables.org wrote:
[snip]
However, do not expect to use all your cores at full speed in this
cases, as the reductions in numexpr can only make use of one
