[SciPy-dev] Dropping djbfft ?
Mon May 12 22:11:10 CDT 2008
On Mon, May 12, 2008 at 9:44 PM, Robert Kern <email@example.com> wrote:
> >> Neither djbfft vs. fftw nor djbfft vs. MKL are definitive comparisons.
> >> Not everyone can use GPLed code or proprietary code.
> > I understand that, I was merely answering to the fact that djbfft is the
> > fastest. We have fftpack for people who do not care so much about speed,
> > no ? IOW, I understand there are people who care about speed, people who
> > care about open source, and people who care about not depending on both
> > GPL and proprietary code. We support all this, and can still do it
> > without depending on djbfft. But do we need to satisfy all the
> > combinations of the above ?
> I'd drop FFTW and MKL support first before djbfft because they are not
> compatible with the scipy license.
I don't see how this addresses David's argument.
While being the "fastest BSD-compatible FFT for power of 2 problem
sizes" achieves a certain Pareto optimality, wouldn't it be more
productive to provide better support for actively maintained libraries
that are faster and more general?
How large is the djbfft + SciPy user base?
Nathan Bell firstname.lastname@example.org
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