[Rd] Manipulating single-precision (float) arrays in .Call functions
Prof Brian Ripley
ripley at stats.ox.ac.uk
Tue Jul 19 08:26:08 CEST 2011
On Mon, 18 Jul 2011, Alireza Mahani wrote:
> Simon,
>
> Thank you for elaborating on the limitations of R in handling float types. I
> think I'm pretty much there with you.
>
> As for the insufficiency of single-precision math (and hence limitations of
> GPU), my personal take so far has been that double-precision becomes crucial
> when some sort of error accumulation occurs. For example, in differential
> equations where boundary values are integrated to arrive at interior values,
> etc. On the other hand, in my personal line of work (Hierarchical Bayesian
> models for quantitative marketing), we have so much inherent uncertainty and
> noise at so many levels in the problem (and no significant error
> accumulation sources) that single vs double precision issue is often
> inconsequential for us. So I think it really depends on the field as well as
> the nature of the problem.
The main reason to use only double precision in R was that on modern
CPUs double precision calculations are as fast as single-precision
ones, and with 64-bit CPUs they are a single access. So the extra
precision comes more-or-less for free. You also under-estimate the
extent to which stability of commonly used algorithms relies on double
precision. (There are stable single-precision versions, but they are
no longer commonly used. And as Simon said, in some cases stability
is ensured by using extra precision where available.)
I disagree slightly with Simon on GPUs: I am told by local experts
that the double-precision on the latest GPUs (those from the last year
or so) is perfectly usable. See the performance claims on
http://en.wikipedia.org/wiki/Nvidia_Tesla of about 50% of the SP
performance in DP.
>
> Regards,
> Alireza
>
>
> --
> View this message in context: http://r.789695.n4.nabble.com/Manipulating-single-precision-float-arrays-in-Call-functions-tp3675684p3677232.html
> Sent from the R devel mailing list archive at Nabble.com.
>
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--
Brian D. Ripley, ripley at stats.ox.ac.uk
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UK Fax: +44 1865 272595
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