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 <nasos_i@hotmail.com> 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.
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