[Numpy-discussion] numpy arrays, data allocation and SIMD alignement

[Lisandro Dalcin]

On 8/3/07, David Cournapeau <david at ar.media.kyoto-u.ac.jp> wrote:
>  Here is what I can think of:
>       - adding an API to know whether a given PyArrayObject has its data
> buffer 16 bytes aligned, and requesting a 16 bytes aligned
> PyArrayObject. Something like NPY_ALIGNED, basically.
>       - forcing data allocation to be 16 bytes aligned in numpy (eg
> define PyDataMem_Mem to a 16 bytes aligned allocator instead of malloc).

All this sounds pretty similar to sdt::allocator we can found in C++
STL (http://www.sgi.com/tech/stl/Allocators.html). Perhaps a NumPy
array could be associated with an instance of an 'allocator' object
(surely written in C, perhaps subclassable in Python) providing
appropriate methos for
alloc/dealloc(/realloc?/initialize(memset)?/copy(memcpy)?) memory.

This would be really nice, as it is extensible (you could even write a
custom allocator, perhaps making use of a preallocated,static pool;
use of C++ new/delete; use of any C++ std::allocator, shared memory,
etc. etc.). I think this is the direction to go but no idea how much
difficult it could be to implement.


-- 
Lisandro Dalcín
---------------
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