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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