Swap memory in Python ? - three questions
robert.kern at gmail.com
Wed Jul 30 00:01:19 CEST 2008
Terry Reedy wrote:
> Robert LaMarca wrote:
>> 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;
>> 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.
"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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