Hi everybody :)
Okay, so in the roadmap i've added Reductions support for ViennaCL 1.6 ...
I plan to take care of it for the three backends, but there are several
things to consider here. For now, I will call them reduce<>, reduce_rows<>,
reduce_cols<>. A convenience layer such that reduce(mat.rows()) or
reduce(mat.cols()) would be better, but this is a completely different
problem :P
>From a certain point of view, if one is a vector full of one (optimized at
compile time), we have the following equivalences :
-> reduce<OP>(lhs) uses the same kernel as inner_prod(lhs,one_vector),
except that the reduction operator is OP and not ADD.
-> reduce_rows<OP>(mat) uses the same kernel as prod(mat,one_vector),
except that the reduction operator is OP and not ADD,.
-> similarly, reduce_cols<OP>(mat) uses the same kernel as
prod(trans(mat),one_vector);
While there is a slight conceptual difference in the kernels (the gemv
kernel has to take care of the reuse of the vector data, the reduce kernel
doesn't), they do show very strong similarities... I see two options here:
(1) - Ignore that slight conceptual difference, and use the same
kernel/backend. This makes sense imho, because the reuse of the vector data
don't matter a lot (it's orders of magnitude smaller in memory than the
matrix). We delegate reduce_impl<OP>(vec) to
inner_prod_impl<OP=AddType>(vec, one_vector())
(2) - Have a specific reduce_impl<>, reduce_rows_impl<>,
reduce_cols_impl<>. I am clearly against this, which would lead to a lot of
duplication for not so much, but well I bring it up for the sake of
Descartes' systematic doubt :)
Best regards,
Philippe
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