sparse_prod is from operation_sparse.h

In my experience it is much faster than axpy_prod. I haven't investigated why, but if anyone can recommend what the most efficient product functions (ideally it should be seamless) are for various matrix types (namely sparse/dense) I would appreciate it.

Thanks,

John


On 12/9/06, Seabook <cipoke@yahoo.com.tw> wrote:

Hello Jihn,

I never used  "sparse_prod".
I need to include which file if I want to use it ?
Thx~


Epic John wrote:
>
> What about sparse_prod? Should that ever be used instead of axpy_prod?When
> I
> tried it, it seemed to run faster for sparse=sparse*sparse .
> John
>
>
>
>
>> My classmate ever demo Altas library for me.
>> It's really fast when your matrix is bigger.
>>
>> any way, thanks a lot again
>>
>> If I am free ,I will try to test all kind  efficiency  of prod .
>>
>> Kuo-Shih
>>
>> Gunter Winkler wrote:
>> >
>> > On Friday 08 December 2006 15:59, Seabook wrote:
>> >> I will try that but I still don't know how to use axpy_prod.
>> >
>> > 1) modify the line in operation.hpp marked with +/i in my diff
>> > 2) use axpy_prod(A,X,Y,true) for Y = prod(A,X)
>> >    and axpy_prod(A,X,Y,false) for Y += prod(A,X)
>> >
>> >> Could you paste your source code with axpy_prod operation?
>> >
>> > I should have atached it already :(
>> >
>> > BTW. ublas' product of dense matrices is a lot slower than any
>> optimized
>> > blas3
>> > routine. However, you can use the atlas-bindings to use blas instead of
>> > prod.
>> >
>> > mfg
>> > Gunter
>> >
>> > _______________________________________________
>> > ublas mailing list
>> > ublas@lists.boost.org
>> > http://lists.boost.org/mailman/listinfo.cgi/ublas
>> >
>> >
>>
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