According to the discussions on the ML, they switched from GPL to MPL to enable the kind of distribution numpy/scipy is looking for. They had some hesitations between BSD and MPL, but IIRC their official stand is to allow inclusion inside BSD-licensed code.
Cheers, Matthieu 2014-02-06 20:09 GMT+00:00 Charles R Harris <[email protected]>: > > > > On Thu, Feb 6, 2014 at 5:27 AM, Julian Taylor > <[email protected]> wrote: >> >> >> On Thu, Feb 6, 2014 at 1:11 PM, Thomas Unterthiner >> <[email protected]> wrote: >>> >>> On 2014-02-06 11:10, Sturla Molden wrote: >>> > BTW: The performance of OpenBLAS is far behind Eigen, MKL and ACML, but >>> > better than ATLAS and Accelerate. >>> Hi there! >>> >>> Sorry for going a bit off-topic, but: do you have any links to the >>> benchmarks? I googled around, but I haven't found anything. FWIW, on my >>> own machines OpenBLAS is on par with MKL (on an i5 laptop and an older >>> Xeon server) and actually slightly faster than ACML (on an FX8150) for >>> my use cases (I mainly tested DGEMM/SGEMM, and a few LAPACK calls). So >>> your claim is very surprising for me. >>> >>> Also, I'd be highly surprised if OpenBLAS would be slower than Eigen, >>> given than the developers themselves say that Eigen is "nearly as fast >>> as GotoBLAS"[1], and that OpenBLAS was originally forked from GotoBLAS. >>> >> >> I'm also a little sceptical about the benchmarks, e.g. according to the >> FAQ eigen does not seem to support AVX which is relatively important for >> blas level 3 performance. >> The lazy evaluation is probably eigens main selling point, which is >> something we cannot make use of in numpy currently. >> >> But nevertheless eigen could be an interesting alternative for our binary >> releases on windows. Having the stuff as headers makes it probably easier to >> build than ATLAS we are currently using. >> > > The Eigen license is MPL-2. That doesn't look to be incompatible with BSD, > but it may complicate things. > > Q8: I want to distribute (outside my organization) executable programs or > libraries that I have compiled from someone else's unchanged MPL-licensed > source code, either standalone or part of a larger work. What do I have to > do? > > You must inform the recipients where they can get the source for the > executable program you are distributing (i.e., you must comply with Section > 3.2). You may also distribute any executables you create under a license of > your choosing, as long as that license does not interfere with the > recipients' rights to the source under the terms of the MPL. > > > Chuck > > > _______________________________________________ > NumPy-Discussion mailing list > [email protected] > http://mail.scipy.org/mailman/listinfo/numpy-discussion > -- Information System Engineer, Ph.D. Blog: http://matt.eifelle.com LinkedIn: http://www.linkedin.com/in/matthieubrucher Music band: http://liliejay.com/ _______________________________________________ NumPy-Discussion mailing list [email protected] http://mail.scipy.org/mailman/listinfo/numpy-discussion
