On 20/03/2013 10:30 AM, Frédéric Bastien wrote: > Hi, > > win32 do not mean it is a 32 bits windows. sys.platform always return > win32 on 32bits and 64 bits windows even for python 64 bits. > > But that is a good question, is your python 32 or 64 bits? 32 bits.
Colin W. > > Fred > > On Wed, Mar 20, 2013 at 10:14 AM, Daπid <davidmen...@gmail.com> wrote: >> Without much detailed knowledge of the topic, I would expect both >> versions to give very similar timing, as it is essentially a call to >> ATLAS function, not much is done in Python. >> >> Given this, maybe the difference is in ATLAS itself. How have you >> installed it? When you compile ATLAS, it will do some machine-specific >> optimisation, but if you have installed a binary chances are that your >> version is optimised for a machine quite different from yours. So, two >> different installations could have been compiled in different machines >> and so one is more suited for your machine. If you want to be sure, I >> would try to compile ATLAS (this may be difficult) or check the same >> on a very different machine (like an AMD processor, different >> architecture...). >> >> >> >> Just for reference, on Linux Python 2.7 64 bits can deal with these >> matrices easily. >> >> %timeit mat=np.random.random((6143,6143)); matinv= np.linalg.inv(mat); >> res = np.dot(mat, matinv); diff= res-np.eye(6143); print >> np.sum(np.abs(diff)) >> 2.41799631031e-05 >> 1.13955868701e-05 >> 3.64338191541e-05 >> 1.13484781021e-05 >> 1 loops, best of 3: 156 s per loop >> >> Intel i5, 4 GB of RAM and SSD. ATLAS installed from Fedora repository >> (I don't run heavy stuff on this computer). >> >> On 20 March 2013 14:46, Colin J. Williams <c...@ncf.ca> wrote: >>> I have a small program which builds random matrices for increasing matrix >>> orders, inverts the matrix and checks the precision of the product. At some >>> point, one would expect operations to fail, when the memory capacity is >>> exceeded. In both Python 2.7 and 3.2 matrices of order 3,071 area handled, >>> but not 6,143. >>> >>> Using wall-clock times, with win32, Python 3.2 is slower than Python 2.7. >>> The profiler indicates a problem in the solver. >>> >>> Done on a Pentium, with 2.7 GHz processor, 2 GB of RAM and 221 GB of free >>> disk space. Both Python 3.2.3 and Python 2.7.3 use numpy 1.6.2. >>> >>> The results are show below. >>> >>> Colin W. >>> >>> aaaa_ssss >>> 2.7.3 (default, Apr 10 2012, 23:31:26) [MSC v.1500 32 bit (Intel)] >>> order= 2 measure ofimprecision= 0.097 Time elapsed (seconds)= >>> 0.004143 >>> order= 5 measure ofimprecision= 2.207 Time elapsed (seconds)= >>> 0.001514 >>> order= 11 measure ofimprecision= 2.372 Time elapsed (seconds)= >>> 0.001455 >>> order= 23 measure ofimprecision= 3.318 Time elapsed (seconds)= >>> 0.001608 >>> order= 47 measure ofimprecision= 4.257 Time elapsed (seconds)= >>> 0.002339 >>> order= 95 measure ofimprecision= 4.986 Time elapsed (seconds)= >>> 0.005747 >>> order= 191 measure ofimprecision= 5.788 Time elapsed (seconds)= >>> 0.029974 >>> order= 383 measure ofimprecision= 6.765 Time elapsed (seconds)= >>> 0.145339 >>> order= 767 measure ofimprecision= 7.909 Time elapsed (seconds)= >>> 0.841142 >>> order= 1535 measure ofimprecision= 8.532 Time elapsed (seconds)= >>> 5.793630 >>> order= 3071 measure ofimprecision= 9.774 Time elapsed (seconds)= >>> 39.559540 >>> order= 6143 Process terminated by a MemoryError >>> >>> Above: 2.7.3 Below: Python 3.2.3 >>> >>> bbb_bbb >>> 3.2.3 (default, Apr 11 2012, 07:15:24) [MSC v.1500 32 bit (Intel)] >>> order= 2 measure ofimprecision= 0.000 Time elapsed (seconds)= >>> 0.113930 >>> order= 5 measure ofimprecision= 1.807 Time elapsed (seconds)= >>> 0.001373 >>> order= 11 measure ofimprecision= 2.395 Time elapsed (seconds)= >>> 0.001468 >>> order= 23 measure ofimprecision= 3.073 Time elapsed (seconds)= >>> 0.001609 >>> order= 47 measure ofimprecision= 5.642 Time elapsed (seconds)= >>> 0.002687 >>> order= 95 measure ofimprecision= 5.745 Time elapsed (seconds)= >>> 0.013510 >>> order= 191 measure ofimprecision= 5.866 Time elapsed (seconds)= >>> 0.061560 >>> order= 383 measure ofimprecision= 7.129 Time elapsed (seconds)= >>> 0.418490 >>> order= 767 measure ofimprecision= 8.240 Time elapsed (seconds)= >>> 3.815713 >>> order= 1535 measure ofimprecision= 8.735 Time elapsed (seconds)= >>> 27.877270 >>> order= 3071 measure ofimprecision= 9.996 Time elapsed >>> (seconds)=212.545610 >>> order= 6143 Process terminated by a MemoryError >>> >>> >>> >>> _______________________________________________ >>> NumPy-Discussion mailing list >>> NumPy-Discussion@scipy.org >>> http://mail.scipy.org/mailman/listinfo/numpy-discussion >>> >> _______________________________________________ >> NumPy-Discussion mailing list >> NumPy-Discussion@scipy.org >> http://mail.scipy.org/mailman/listinfo/numpy-discussion > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion