On Wed, Dec 19, 2012 at 8:40 AM, Henry Gomersall <heng@cantab.net> wrote:
I've written a few simple cython routines for assisting in creating byte-aligned numpy arrays. The point being for the arrays to work with SSE/AVX code.
https://github.com/hgomersall/pyFFTW/blob/master/pyfftw/utils.pxi
The change recently has been to add a check on the CPU as to what flags are supported (though it's not complete, I should make the default return 0 or something).
It occurred to me that this is something that (a) other people almost certainly need and are solving themselves and (b) I lack the necessary platforms to test all the possible CPU/OS combinations to make sure something sensible happens in all cases.
Is this something that can be rolled into Numpy (the feature, not my particular implementation or interface - though I'd be happy for it to be so)?
Regarding (b), I've written a test case that works for Linux on x86-64 with GCC (my platform!). I can test it on 32-bit windows, but that's it. Is ARM supported by Numpy? Neon would be great to include as well. What other platforms might need this?
Your code looks simple and portable to me (at least the alignment part). I can see a good argument for adding this sort of functionality directly to numpy with a nice interface, though, since these kind of requirements seem quite common these days. Maybe an interface like a = np.asarray([1, 2, 3], base_alignment=32) # should this be in bits or in bytes? b = np.empty((10, 10), order="C", base_alignment=32) # etc. assert a.base_alignment == 32 which underneath tries to use posix_memalign/_aligned_malloc when possible, or falls back on the overallocation trick otherwise? -n