On 08/05/2014 04:00, numpy-discussion-requ...@scipy.org wrote:
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Hi,
I'm compiling information on DLLs for Windows building, in the hope
that it's helpful for deciding on where to go with these.
Please do check and see whether this fits with your understanding - it
can be hard to follow the docs on this stuff:
https://github.com/numpy/numpy/wiki/windows-dll-n
Just a quick question/possibility.
What about just parallelizing ufunc with only 1 inputs that is c or fortran
contiguous like trigonometric function? Is there a fast path in the ufunc
mechanism when the input is fortran/c contig? If that is the case, it would
be relatively easy to add an openmp p
On 2014/05/07 2:14 PM, mfm24 wrote:
> I'm having a problem I haven't seen elsewhere (and apologies if it has
> been answered before).
>
> I see the following behavior (copied verbatim from a python session):
>
> Python 2.7.4 (default, Apr 6 2013, 19:55:15) [MSC v.1500 64 bit (AMD64)] on
> win32
>
I'm having a problem I haven't seen elsewhere (and apologies if it has been
answered before).
I see the following behavior (copied verbatim from a python session):
Python 2.7.4 (default, Apr 6 2013, 19:55:15) [MSC v.1500 64 bit (AMD64)] on
win32Type "help", "copyright", "credits" or "license" for
On 07.05.2014 20:11, Sturla Molden wrote:
> On 03/05/14 23:56, Siegfried Gonzi wrote:
>
> A more technical answer is that NumPy's internals does not play very
> nicely with multithreading. For examples the array iterators used in
> ufuncs store an internal state. Multithreading would imply an ex
On Wed, May 7, 2014 at 7:11 PM, Sturla Molden wrote:
> On 03/05/14 23:56, Siegfried Gonzi wrote:
> > I noticed IDL uses at least 400% (4 processors or cores) out of the box
> > for simple things like reading and processing files, calculating the
> > mean etc.
>
> The DMA controller is working a
On 03/05/14 23:56, Siegfried Gonzi wrote:
> I noticed IDL uses at least 400% (4 processors or cores) out of the box
> for simple things like reading and processing files, calculating the
> mean etc.
The DMA controller is working at its own pace, regardless of what the
CPU is doing. You cannot
On 05/05/14 17:02, Francesc Alted wrote:
> Well, this might be because it is the place where using several
> processes makes more sense. Normally, when you are reading files, the
> bottleneck is the I/O subsystem (at least if you don't have to convert
> from text to numbers), and for calculating
On Wed, May 7, 2014 at 3:22 PM, Neal Becker wrote:
> I needed a histogram that is built incrementally. My need is for 1D only.
>
> The idea is to not require storage of all the data (assume it could be too
> large).
>
> This is a naive implementation, perhaps someone could suggest something
> be
I needed a histogram that is built incrementally. My need is for 1D only.
The idea is to not require storage of all the data (assume it could be too
large).
This is a naive implementation, perhaps someone could suggest something better.
,[ /home/nbecker/sigproc.ndarray/histogram3.py ]
| im
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