[Numpy-discussion] Execution time difference between 2.7 and 3.2 using numpy
Colin J. Williams
cjwilliams43@gmail....
Wed Mar 20 10:01:33 CDT 2013
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 <davidmenhur@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 <cjw@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
>>>
>>>
>>>
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