How to tell if I succeeded to build numpy with amd, umfpack and lapack
Hi there! I have successfully built numpy 1.5 on ubuntu lucid (32 for now). I think I got ATLAS/lapack/BLAS support, and if I
ldd linalg/lapack_lite.so I see that my libptf77blas.so etc. are successfully linked. :-)
However, how to I find out, if (and where) libamd.a and libumfpack.a have been found and (statically) linked. As far as I understand, I they are not present, a fallback in pure python is used, right? Is there a recommended way, I can query against which libs numpy has been built? So I can be sure numpy uses my own compiled versions of libamd, lapack and so forth. And the fftw3 is no longer supported, I guess (even if it is still mentioned in the site.cfg.example) Bests, Samuel -- Dipl.-Inform. Samuel John - - - - - - - - - - - - - - - - - - - - - - - - - PhD student, CoR-Lab(.de) and Neuroinformatics Group, Faculty of Technology, D33594 Bielefeld in cooperation with the HONDA Research Institute Europe GmbH jabber: samueljohn@jabber.org - - - - - - - - - - - - - - - - - - - - - - - - -
Samuel John, on 2011-01-26 15:08, wrote:
Hi there!
I have successfully built numpy 1.5 on ubuntu lucid (32 for now). I think I got ATLAS/lapack/BLAS support, and if I
ldd linalg/lapack_lite.so I see that my libptf77blas.so etc. are successfully linked. :-)
However, how to I find out, if (and where) libamd.a and libumfpack.a have been found and (statically) linked. As far as I understand, I they are not present, a fallback in pure python is used, right?
Is there a recommended way, I can query against which libs numpy has been built? So I can be sure numpy uses my own compiled versions of libamd, lapack and so forth.
Hi Samuel, take a look at numpy.show_config() and scipy.show_config() best, -- Paul Ivanov 314 address only used for lists, off-list direct email at: http://pirsquared.org | GPG/PGP key id: 0x0F3E28F7
Hi Paul, thanks for your answer! I was not aware of numpy.show_config(). However, it does not say anything about libamd.a and libumfpack.a, right? How do I know if they were successfully linked (statically)? Does anybody have a clue? greetings Samuel
Ping. How to tell, if numpy successfully build against libamd.a and libumfpack.a? How do I know if they were successfully linked (statically)? Is it possible from within numpy, like show_config() ? I think show_config() has no information about these in it :-( Anybody? Thanks, Samuel
It certainly does. Here is mine, showing that numpy is linked against mkl:
In [2]: np.show_config()
lapack_opt_info:
libraries = ['mkl_lapack95', 'mkl_intel', 'mkl_intel_thread',
'mkl_core', 'mkl_p4m', 'mkl_p4p', 'pthread']
library_dirs =
['/Library/Frameworks/Python.framework/Versions/1.3.0/lib']
define_macros = [('SCIPY_MKL_H', None)]
include_dirs =
['/Library/Frameworks/Python.framework/Versions/1.3.0/include']
blas_opt_info:
libraries = ['mkl_intel', 'mkl_intel_thread', 'mkl_core', 'mkl_p4m',
'mkl_p4p', 'pthread']
library_dirs =
['/Library/Frameworks/Python.framework/Versions/1.3.0/lib']
define_macros = [('SCIPY_MKL_H', None)]
include_dirs =
['/Library/Frameworks/Python.framework/Versions/1.3.0/include']
lapack_mkl_info:
libraries = ['mkl_lapack95', 'mkl_intel', 'mkl_intel_thread',
'mkl_core', 'mkl_p4m', 'mkl_p4p', 'pthread']
library_dirs =
['/Library/Frameworks/Python.framework/Versions/1.3.0/lib']
define_macros = [('SCIPY_MKL_H', None)]
include_dirs =
['/Library/Frameworks/Python.framework/Versions/1.3.0/include']
blas_mkl_info:
libraries = ['mkl_intel', 'mkl_intel_thread', 'mkl_core', 'mkl_p4m',
'mkl_p4p', 'pthread']
library_dirs =
['/Library/Frameworks/Python.framework/Versions/1.3.0/lib']
define_macros = [('SCIPY_MKL_H', None)]
include_dirs =
['/Library/Frameworks/Python.framework/Versions/1.3.0/include']
mkl_info:
libraries = ['mkl_intel', 'mkl_intel_thread', 'mkl_core', 'mkl_p4m',
'mkl_p4p', 'pthread']
library_dirs =
['/Library/Frameworks/Python.framework/Versions/1.3.0/lib']
define_macros = [('SCIPY_MKL_H', None)]
include_dirs =
['/Library/Frameworks/Python.framework/Versions/1.3.0/include']
If those lists are empty for you, then numpy is not linked properly (of
course yours will be ATLAS and not mkl)
On Fri, Feb 18, 2011 at 5:32 AM, Samuel John
Ping.
How to tell, if numpy successfully build against libamd.a and libumfpack.a? How do I know if they were successfully linked (statically)? Is it possible from within numpy, like show_config() ? I think show_config() has no information about these in it :-(
Anybody?
Thanks, Samuel _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
I think numpy doesn't use umfpack. scipy.sparse used to, but now the
umfpack stuff has been moved out to a scikit.
So you probably won't see anything about those libraries, but if you
install scikits.umfpack and it works then you must be linked
correctly.
Cheers
Robin
On Fri, Feb 18, 2011 at 11:32 AM, Samuel John
Ping.
How to tell, if numpy successfully build against libamd.a and libumfpack.a? How do I know if they were successfully linked (statically)? Is it possible from within numpy, like show_config() ? I think show_config() has no information about these in it :-(
Anybody?
Thanks, Samuel _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Thanks Robin, that makes sense and explains why I could not find any reference. Perhaps the scipy.org wiki and install instructions should be updated. I mean how many people try to compile amd and umfpack, because they think it's good for numpy to have them, because the site.cfg contains those entries! To conclude: numpy does *NOT* use umfpack or libamd at all. Those sections in the site.cfg are outdated.
participants (4)
-
Chris Colbert -
Paul Ivanov -
Robin -
Samuel John