[Numpy-discussion] numexpr with the new iterator

[Mark Wiebe]

On Mon, Jan 10, 2011 at 9:47 AM, Francesc Alted <faltet at pytables.org> wrote:

> <snip>
>
> so, the new code is just < 5% slower.  I suppose that removing the
> NPY_ITER_ALIGNED flag would give us a bit more performance, but that's
> great as it is now.  How did you do that?  Your new_iter branch in NumPy
> already deals with unaligned data, right?
>

Take a look at  lowlevel_strided_loops.c.src.  In this case, the buffering
setup code calls PyArray_GetDTypeTransferFunction, which in turn calls
PyArray_GetStridedCopyFn, which on an x86 platform returns
_aligned_strided_to_contig_size8.  This function has a simple loop of copies
using a npy_uint64 data type.

> The new code also needs support for the reduce operation.  I didn't
> > look too closely at the code for that, but a nested iteration
> > pattern is probably appropriate.  If the inner loop is just allowed
> > to be one dimension, it could be done without actually creating the
> > inner iterator.
>
> Well, if you can support reduce operations with your patch that would be
> extremely good news as I'm afraid that the current reduce code is a bit
> broken in Numexpr (at least, I vaguely remember seeing it working badly
> in some cases).
>

Cool, I'll take a look at some point.  I imagine with the most obvious
implementation small reductions would perform poorly.

-Mark
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