Swap memory in Python ? - three questions

Robert Kern robert.kern at gmail.com
Wed Jul 30 00:01:19 CEST 2008


Terry Reedy wrote:
> 
> Robert LaMarca wrote:
>> Hi,
>> I am using numpy and wish to create very large arrays.   My system is 
>> AMD 64 x 2 Ubuntu 8.04.  Ubuntu should be 64 bit. I have 3gb RAM and a 
>> 15 GB swap drive. 
>> The command I have been trying to use is; 
>> g=numpy.ones([1000,1000,1000],numpy.int32)
>>
>> This returns a memory error.  A smaller array ([500,500,500]) worked 
>> fine.. Two smaller arrays again crashed the system.
>>
>> So... I did the math.  a 1000x1000x1000 array at 32 bits should be 
>> around 4gb RAM... Obviously larger than RAM, but much smaller than the 
>> swap drive.
>>
>> 1. So... does Numpy have a really lot of overhead? Or is my system 
>> just not somehow getting to make use of the 15gb swap area. 2. Is 
>> there a way I can access the swap area, or direct numpy to do so? Or 
>> do I have to write out my own numpy cache system... 3. How difficult 
>> is it to use data compression internally on numpy arrays? 
> 
> I do not know what numpy does, but constant arrays only need to store 
> the dimensions and the constant value and have a getitem method that 
> returns that constant value for any valid index.  This is at most a few 
> hundred bytes regardless of the dimensions.

Presumably, he's using numpy.ones() as an example of creating a large array, not 
because he actually needs an array full of 1s.

-- 
Robert Kern

"I have come to believe that the whole world is an enigma, a harmless enigma
  that is made terrible by our own mad attempt to interpret it as though it had
  an underlying truth."
   -- Umberto Eco




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