On Wed, May 13, 2009 at 11:04 PM, Charles R Harris < charlesr.harris@gmail.com> wrote:
On Wed, May 13, 2009 at 10:50 PM, Glenn Tarbox, PhD
wrote: I'm using the latest version of Sage (3.4.2) which is python 2.5 and numpy something or other (I will do more digging presently)
I'm able to map large files and access all the elements unless I'm using slices
so, for example:
fp = np.memmap("/mnt/hdd/data/mmap/numpy1e10.mmap", dtype='float64', mode='r+', shape=(10000000000,))
which is 1e10 doubles if you don't wanna count the zeros
gives full access to a 75 GB memory image
But when I do:
fp[:] = 1.0 np.sum(fp)
I get 1410065408.0 as the result
As doubles, that is more than 2**33 bytes, so I expect there is something else going on. How much physical memory/swap memory do you have? This could also be a python problem since python does the memmap.
I've been working on some other things lately and that number seemed related to 2^32... now that I look more closely, I don't know where that number comes from. To your question, I have 32GB of RAM and virtually nothing else running... Top tells me I'm getting between 96% and 98% for this process which seems about right. Here's the thing. When I create the mmap file, I get the right number of bytes. I can, from what I can tell, update individual values within the array (I'm gonna bang on it a bit more with some other scripts) Its only when using slicing that things get strange (he says having not really done a more thorough test) Of course, I was assuming this is a 32 bit thing... but you're right... where did that result come from??? The other clue here is that when I create my own slice (as described above) it returns instantly... numpy doesn't throw an error but it doesn't do anything with the slice either. Since I'm IO bound anyways, maybe i'll just write a loop and see if I can't set all the values. The machine could use a little exercise anyways. -glenn
Chuck
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