On Wed, Dec 19, 2012 at 2:57 PM, Charles R Harris <charlesr.har...@gmail.com> wrote: > > > On Wed, Dec 19, 2012 at 7:43 AM, Nathaniel Smith <n...@pobox.com> wrote: >> >> On Wed, Dec 19, 2012 at 8:40 AM, Henry Gomersall <h...@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? >> > > There is a thread about this from several years back. IIRC, David Cournapeau > was interested in the same problem. At first glance, the alignment keyword > looks interesting. One possible concern is keeping alignment for rows, > views, etc., which is probably not possible in any sensible way. But people > who need this most likely know what they are doing and just need memory > allocated on the proper boundary.
Right, my intuition is that it's like order="C" -- if you make a new array by, say, indexing, then it may or may not have order="C", no guarantees. So when you care, you call asarray(a, order="C") and that either makes a copy or not as needed. Similarly for base alignment. I guess to push this analogy even further we could define a set of array flags, ALIGNED_8, ALIGNED_16, etc. (In practice only power-of-2 alignment matters, I think, so the number of flags would remain manageable?) That would make the C API easier to deal with too, no need to add PyArray_FromAnyAligned. -n _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
