Re: Matrix multiplication performance

You are going to need some features that are on the pipeline but not 
implemented yet like:
https://github.com/uBLAS/ublas/wiki/feature-ublas_00004_matrix_view
this is not hard to put together.


-N


On 01/27/2016 11:29 AM, Michael Lehn wrote:
> On 27 Jan 2016, at 17:15, Nasos Iliopoulos <[email protected]> wrote:
>
>>
>> On 01/27/2016 10:52 AM, Michael Lehn wrote:
>>>> 5. ublas is one of the fastest libraries for small matrices. Because I think the most prevalent use of dense multiplication is on small matrices ( geometric transformations etc.) we need to make sure this stays that way.
>>> Depends on the domain of usage.  In my domain dense matrix multiplication is the key to both, fast dense linear algebra (LAPACK etc.) and
>>> sparse direct or iterative solvers.  But sure, we should have both.
>>>
>>> I will finish a prototype of BLAS Level 3 the next days but that might require some help on uBLAS.  In particular I want to write a BLAS F77 and
>>> CBLAS  interface so that one can build a BLAS library that can be linked against LAPACK.  Because that’s the message:  First BLAS was written
>>> in Fortran,  then in C and they provided a Fortran interface.  Today one writes a BLAS implementation in C++ and provides a C and Fortran interface.
>> I agree with that. We may want to provide a C and fortran interface eventually
> No, not eventually :-)   I will do it as soon as I have figured out how to create a uBLAS matrix/vector from a raw C-array.  Once I know that
> its a matter or hours.  This also allows us to use the LAPACK test suite as *one* test for the BLAS implementation.  Also we can use the
> ATLAS benchmark suite: It compares the performance of ATLAS with a F77 BLAS implementation.  Personally I never trust any benchmarks
> that can not be reproduced this way.
> _______________________________________________
> ublas mailing list
> [email protected]
> http://lists.boost.org/mailman/listinfo.cgi/ublas
> Sent to: [email protected]