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Subject: Re: [ublas] Matrix multiplication performance
From: Nasos Iliopoulos (nasos_i_at_[hidden])
Date: 2016-01-27 11:40:46

You are going to need some features that are on the pipeline but not
implemented yet like:
this is not hard to put together.


On 01/27/2016 11:29 AM, Michael Lehn wrote:
> On 27 Jan 2016, at 17:15, Nasos Iliopoulos <nasos_i_at_[hidden]> 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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