Hello everybody,
I am done implementing :
x = viennacl::reduce<op>(viennacl::rows(A));
x = viennacl::reduce<op>(viennacl::cols(A));
s = viennacl::reduce<op>(x);
In the generator. For now, the op supported are : add, mult, max, min. I
can't support them all, because I need to provide their neutral element for
kernel generation (so that the shared memory can be initialized with the
neutral element)
I am now working on repmat. About this, I am not sure which should be the
return type of the API function. I am planning to go for some
matrix_expression<matrix, viennacl::tuple<int,int>, op_repmat>(A,
make_tuple(repsize1,repsize2)) ?
Where the tuple would get translated by the scheduler into a binary tree
with operator OP_TUPLE. Does this sound reasonable?
@Toby : There might be some changes of this type in the way the scheduler's
expression tree is generated (for the need of the kernel generator). I'll
try to keep a list of the changes updated, so that the python wrapper does
not diverge too much from the core :)
Philippe
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