I forget a last question,
We currently advise a High Performance Platform for our customers
(Opteron cluster) where our applications are linked with GOTO blas library.
I found in the Numpy distribution the file site.cfg, used to specify the
BLAS to used at the link time. (It could be an interesting feature for
us.) I noted some configuration variables have names depending on the
name of the chosen BLAS library. So, my question is: is GOTO is
supported or is it easy for us to add it? I wonder too if the string
[atlas] written in site.cfg is used or not ?
thanks,
Mathieu.
Travis Oliphant wrote:
mg wrote:
Hi all,
I am doing a feseability study to migrate our Python based FEM
applications from Numarray to Numpy.
First, I tried to install Numpy from Python-2.4 on linux-x86,
linux-86-64bit. So, all work fine. Great! Moreover, I change easily the
BLAS linked libraries. I tried with ATLAS and GOTO. Great again!
Second, I try to do the same think on windows-x86 without success. So my
first question is: is Numpy-1.0b5 has been tested and is supported on
Windows?
Yes, it should work. Builds for windows were provided. But, perhaps
there are configuration issues for your system that we are not handling
correctly.
Third, I tried to install Numpy from Python-2.5, which is our standard
Python, on linux-x86... and the compilation stopped during the
compilation of core/src/multiarraymodule.c. So my second question is: is
there a workaround or is the porting to Python2.5 is yet schedule?
There was a problem with Python 2.5 and NumPy 1.0 that is fixed in SVN.
Look for NumPy 1.0rc1 to come out soon.
My third question is: is the tool to migrate the numarray based Python
scripts (numpy.numarray.alter_code1) work fine? (I suppose yes...)
It needs more testing. It would be great if you could help us find and
fix bugs in it. I don't have a lot of numarray code to test.
We have created a lot of bindings in order to pilote our generic-C++
framework with Python scripts. So, about the Numpy API, is it widely
different than the Numarray API? (We will order the Numpy Guide too.)
It is more similar to the Numeric C-API. However, the numarray C-API is
completely supported by including numpy/libnumarray.h so you should be
able to convert your C code very easily. Any problems encountered
should be noted and we'll get them fixed.
To not duplicate large numerical memory arrays, Numarray allows to
aliasing the memory of some bindings with arrays from Numarray, and we
have used this feature intensively. So, I wonder if it is currently
supported (or even scheduled)?
I'm pretty sure the answer is yes (because the Numarray C-API is
supported), though I'm not exactly sure what you mean. Do you mean that
you have memory created in the C/C++ framework and then you have an
array use that memory for it's data area? If that is what you mean,
then the answer is definitely yes.
-Travis
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