On 18.02.2013 22:47, Pauli Virtanen wrote:
> 18.02.2013 23:29, V. Armando Sole kirjoitti:
> [clip]
>> I find Dag's approach more appealing.
>>
>> SciPy can be problematic (windows 64-bit) and if one could offer
>> access
>> to the linear algebra functions without needing SciPy I would
>> certai
18.02.2013 23:29, V. Armando Sole kirjoitti:
[clip]
> I find Dag's approach more appealing.
>
> SciPy can be problematic (windows 64-bit) and if one could offer access
> to the linear algebra functions without needing SciPy I would certainly
> prefer it.
Well, the two approaches are not exclusi
On 18.02.2013 21:23, Pauli Virtanen wrote:
> 18.02.2013 20:41, Dag Sverre Seljebotn kirjoitti:
> [clip]
>> I think there should be a new project, pylapack or similar, for
>> this,
>> outside of NumPy and SciPy. NumPy and SciPy could try to import it,
>> and
>> if found, fetch a function pointer
On 02/18/2013 09:23 PM, Pauli Virtanen wrote:
> 18.02.2013 20:41, Dag Sverre Seljebotn kirjoitti:
> [clip]
>> I think there should be a new project, pylapack or similar, for this,
>> outside of NumPy and SciPy. NumPy and SciPy could try to import it, and
>> if found, fetch a function pointer table.
18.02.2013 20:41, Dag Sverre Seljebotn kirjoitti:
[clip]
> I think there should be a new project, pylapack or similar, for this,
> outside of NumPy and SciPy. NumPy and SciPy could try to import it, and
> if found, fetch a function pointer table. (If not found, just stay with
> what has been wor
On 02/18/2013 06:48 PM, Pauli Virtanen wrote:
> 18.02.2013 19:20, Dag Sverre Seljebotn kirjoitti:
>> On 02/18/2013 05:29 PM, rif wrote:
>>> But I'd hope that the overhead for going through the wrappers is
>>> constant, rather than dependent on the size, so that for large matrices
>>> you'd get esse
18.02.2013 19:20, Dag Sverre Seljebotn kirjoitti:
> On 02/18/2013 05:29 PM, rif wrote:
>> But I'd hope that the overhead for going through the wrappers is
>> constant, rather than dependent on the size, so that for large matrices
>> you'd get essentially equivalent performance?
>
> That is correct
On 02/18/2013 05:29 PM, rif wrote:
> But I'd hope that the overhead for going through the wrappers is
> constant, rather than dependent on the size, so that for large matrices
> you'd get essentially equivalent performance?
That is correct.
Ah, so then the quality of the BLAS matters much less in
On Mon, Feb 18, 2013 at 9:28 AM, Dag Sverre Seljebotn <
d.s.seljeb...@astro.uio.no> wrote:
> On 02/18/2013 05:26 PM, rif wrote:
> > I have no answer to the question, but I was curious as to why directly
> > calling the cblas would be 10x-20x slower in the first place. That
> > seems surprising, a
But I'd hope that the overhead for going through the wrappers is constant,
rather than dependent on the size, so that for large matrices you'd get
essentially equivalent performance?
On Mon, Feb 18, 2013 at 8:28 AM, Dag Sverre Seljebotn <
d.s.seljeb...@astro.uio.no> wrote:
> On 02/18/2013 05:26
On 02/18/2013 05:28 PM, Dag Sverre Seljebotn wrote:
> On 02/18/2013 05:26 PM, rif wrote:
>> I have no answer to the question, but I was curious as to why directly
>> calling the cblas would be 10x-20x slower in
The statement was that directly (on the Cython level) calling cblas is
10x-20x slower t
On 02/18/2013 05:26 PM, rif wrote:
> I have no answer to the question, but I was curious as to why directly
> calling the cblas would be 10x-20x slower in the first place. That
> seems surprising, although I'm just learning about python numerics.
The statement was that directly (on the Cython lev
Hi Sergio,
I faced a similar problem one year ago. I solved it writing a C function
receiving a pointer to the relevant linear algebra routine I needed.
Numpy does not offers the direct access to the underlying library
functions, but scipy does it:
from scipy.linalg.blas import fblas
dgemm = f
I have no answer to the question, but I was curious as to why directly
calling the cblas would be 10x-20x slower in the first place. That seems
surprising, although I'm just learning about python numerics.
On Mon, Feb 18, 2013 at 7:38 AM, Sergio Callegari <
sergio.calleg...@gmail.com> wrote:
>
Hi,
I have a project that includes a cython script which in turn does some direct
access to a couple of cblas functions. This is necessary, since some matrix
multiplications need to be done inside a tight loop that gets called thousands
of times. Speedup wrt calling scipy.linalg.blas.cblas routine
15 matches
Mail list logo
