[SciPy-user] Arrays and strange memory usage ...

Francesc Alted falted@pytables....
Wed Sep 3 03:49:23 CDT 2008


A Tuesday 02 September 2008, christophe grimault escrigué:
> Hi,
>
> I have a application that is very demanding in memory ressources. So
> I started to to look closer at python + numpy/scipy as far as memory
> is concerned.
>
> I can't explain the following :
>
> I start my python, + import scipy. A 'top' in the console shows that
> :
>
>   PID USER      PR  NI  VIRT  RES  SHR S %CPU %MEM    TIME COMMAND
> 14791 grimault  20   0 21624 8044 3200 S    0  0.4   0:00.43 python
>
> Now after typing :
>
> z = scipy.arange(1000000)
>
> I get :
> 14791 grimault  20   0 25532  11m 3204 S    0  0.6   0:00.44 python
>
> So the memory increased by ~ 7 Mb. I was expecting 4 Mb since the
> data type is int32, giving 4*1000000 = 4 Mb of memory chunk (in C/C++
> at least).

You should look at the "RES" column instead of "VIRT" one.  "RES" column 
shows the *real* memory that you are consuming.  So, in this case, you 
have consumed 11MB - 8044KB ~ 3 MB.  However, you are undergoing here 
the effects of number representation truncation.  Your consumed memory 
should be rather: 8044KB + 3906KB = 11950KB, but as it is converted to 
MB (scale changes happens automatically in 'top' when the figures need 
more than 4 digits to be represented), 11959KB is truncated and 950KB 
are gone, so this is why the final figure you are seeing is 11MB.  This 
can be a bit misleading at first sight, but be sure that your machine 
(and NumPy) is doing fine and works as expected.

Cheers,

-- 
Francesc Alted


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