 # Ublas :

From: Nizar Khalifa Sallem (nksallem_at_[hidden])
Date: 2008-08-22 05:40:45

Gunter Winkler wrote:
> Am Mittwoch, 20. August 2008 13:38 schrieb Nizar Khalifa Sallem:
>
>> Hi,
>> I thinks there is a mistake in this documentation page

>> htm but not sure (for version 1.36 also). Anyway the questions are :
>> 1- how axpy_prod (const vector_expression< E1 > &e1, const
>> matrix_expression< E2 > &e2, V &v, bool init=true) could compute v +=
>> A x or v = A x and v += AT x or v = AT x knowing that there is no
>> params to indicate whether to transpose or not. Shouldn't one of the
>> axpy_prod be an opb_prod? 2 - axpy_prod (const matrix_expression< E1
>>
>>> &e1, const matrix_expression< E2 > &e2, M &m, bool init=true) and
>>>
>> opb_prod (const matrix_expression< E1 > &e1, const matrix_expression<
>> E2 > &e2, M &m, bool init=true) seem to compute the same thing (based
>> on the doc) M += A X or M = A X. Shouldn't one of them compute M +=
>> AT X or M = AT X? Can somebody lighten me?
>> Thanks
>>
>
> most products can be called in two ways:
>
> prod(A, x) which computes A x
> prod(x, A) which computes A^T x
>
> the prod(), axpy_prod() and opb_prod() are different implementations for
> the same thing. Depending on the size of the matrix one of the three
> products is faster than the other two.
>
> the transposed matrix-product is a little more tricky, because
> axpy_prod(A, X, Y) and axpy_prod(X, A, Y) have the same signature. Thus
> you have to use axpy_prod(trans(A), X, Y)
>
> mfg
> Gunter
>
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>
Thanks
Just one other question which one is the faster for computing symmetric
matrixes product and sum?
B+= AT A with B symmetric

Best regards,