[Numpy-discussion] supporting quad precision
Charles R Harris
Wed Jun 5 11:21:29 CDT 2013
Long time no see ;)
On Wed, Jun 5, 2013 at 10:07 AM, Anne Archibald <firstname.lastname@example.org> wrote:
> Hi folks,
> I recently came across an application I needed quad precision for
> (high-accuracy solution of a differential equation). I found a C++ library
> (odeint) that worked for the integration itself, but unfortunately it
> appears numpy is not able to work with quad precision arrays. For my
> application the quad precision is only really needed for integrator state,
> so I can manually convert my data to long doubles as I go to and from
> numpy, but it's a pain. So quad precision support would be nice.
> There's a thread discussing quad support:
> Essentially, there isn't any, but since gcc >= 4.6 supports them on Intel
> hardware (in software), it should be possible. (Then the thread got bogged
> down in bike-shedding about what to call them.)
> What would it take to support quads in numpy? I looked into the numpy base
> dtype definitions, and it's a complex arrangement involving detection of
> platform support and templatized C code; in the end I couldn't really see
> where to start. But it seems to me all the basics are available: native C
> syntax for basic arithmetic, "qabs"-style versions of all the basic
> functions, NaNs and Infs. So how would one go about adding quad support?
There are some improvements for user types committed in 1.8-dev. Perhaps
quad support could be added as a user type as it is still platform/compiler
dependent. The rational type added to numpy could supply a template for
adding the new type.
Long term, we need to have quad support. If you run on SUN hardware I think
it is already available as the extended precision type, but that doesn't
help the majority of users at this point and I don't think LAPACK/BLAS
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