[Numpy-discussion] large memory address space on Mac OS X (intel)

[Louis Wicker]

Travis:

yes it does.  Its the Woodcrest server chip which supports 32 and 64  
bit operations.  For example the new Intel Fortran compiler can grab  
more than 2 GB of memory (its a beta10 version).  I think gcc 4.x can  
as well.

However, Tiger (OS X 10.4.x) is not completely 64 bit compliant -  
Leopard is supposed to be pretty darn close.

Is there a numpy flag I could try for compilation....

Lou


On Feb 1, 2007, at 1:41 PM, Travis Oliphant wrote:

> Louis Wicker wrote:
>
>> Dear list:
>>
>> I cannot seem to figure how to create arrays > 2 GB on a Mac Pro
>> (using Intel chip and Tiger, 4.8).  I have hand compiled both Python
>> 2.5 and numpy 1.0.1, and cannot make arrays bigger than 2 GB.  I also
>> run out of space if I try and 3-6 several arrays of 1000 mb or so  
>> (the
>> mem-alloc failure does not seem consistent, depends on whether I am
>> creating them with a "numpy.ones()" call, or creating them on the fly
>> by doing math with the other arrays "e.g., c  = 4.3*a + 3.1*b").
>>
>> Is this a numpy issue, or a Python 2.5 issue for the Mac?  I have
>> tried this on the SGI Altix, and this works fine.
>
> It must be a malloc issue.  NumPy uses the system malloc to construct
> arrays.  It just reports errors back to you if it can't.
>
> I don't think the Mac Pro uses a 64-bit chip, does it?
>
> -Travis
>
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