[Numpy-discussion] Numpy doesn't use RAM

[Sebastian Berg]

On Tue, 2020-03-24 at 13:59 -0400, Keyvis Damptey wrote:
> Hi Numpy dev community,
> 
> I'm keyvis, a statistical data scientist.
> 
> I'm currently using numpy in python 3.8.2 64-bit for a clustering
> problem,
> on a machine with 1.9 TB RAM. When I try using np.zeros to create a
> 600,000
> by 600,000 matrix of dtype=np.float32 it says
> "Unable to allocate 1.31 TiB for an array with shape (600000, 600000)
> and
> 
> data type float32"
> 

If this error happens, allocating the memory failed. This should be
pretty much a simple `malloc` call in C, so this is the kernel
complaining, not Python/NumPy.

I am not quite sure, but maybe memory fragmentation plays its part, or
simply are actually out of memory for that process, 1.44TB is a
significant portion of the total memory after all.

Not sure what to say, but I think you should probably look into other
solutions, maybe using HDF5, zarr, or memory-mapping (although I am not
sure the last actually helps). It will be tricky to work with arrays of
a size that is close to the available total memory.

Maybe someone who works more with such data here can give you tips on
what projects can help you or what solutions to look into.

- Sebastian



> I used psutils to determine how much RAM python thinks it has access
> to and
> it return with 1.8 TB approx.
> 
> Is there some way I can fix numpy to create these large arrays?
> Thanks for your time and consideration
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