[Numpy-discussion] Out-of-RAM FFTs
Wed Apr 1 10:26:45 CDT 2009
I'd like to do an FFT of a moderately large 3D cube, 1024^3. Looking
at the run-time of smaller arrays, this is not a problem in terms of
compute time, but the array doesn't fit in memory. So, several
1) Numerical Recipes has an out-of-memory FFT algorithm, but looking
through the numpy and scipy docs and modules, I didn't find a function
that does the same thing. Did I miss it? Should I get to work typing
2) I had high hopes for just memory-mapping the large array and
passing it to the standard fft function. However, the memory-mapped
region must fit into the address space, and I don't seem to be able to
use more than 2 GB at a time. So memory mapping doesn't seem to help
me at all.
This last issue leads to another series of things that puzzle me. I
have an iMac running OS X 10.5 with an Intel Core 2 duo processor and
4 GB of memory. As far as I've learned, the processor is 64 bit, the
operating system is 64 bit, so I should be able to happily memory-map
my entire disk if I want. However, Python seems to run out of steam
when it's used 2 GB. This is true of both 2.5 and 2.6. What gives?
Is this a Python issue?
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