Tim Cook <z99### [at] gmailcom> wrote:
> I, for one, would be interested in seeing hard number comparisons.

  I have first-hand experience. My FunctionParser library currently supports
many floating point and integer types as its basic data type. Among others,
it supports 'double' (which is a 64-bit floating point type which has a 53-bit
mantissa calculated in hardware, and the same that POV-Ray uses for most of
its calculations) as well as multiple-precision software floating point
numbers using the MPFR library.

  I have a comprehensive regression testbed program which runs over a hundred
tests on the library. It can run it with all the supported data types or
with just one. It uses 80 mantissa bits for the MPFR floating point values
(which is about 24 significant digits of accuracy, compared to the about 15
of double-precision floating point numbers; not much larger, but the speed
of the MPFR library decreases as more mantissa bits are used).

  Running all the current tests for the 'double' in my computer type takes
about 1.7 seconds, while running the same tests for the 80-bits-mantissa
MPFR type takes about 5 minutes.

  (Of course this tests many mathematical functions which wouldn't be
necessary to calculate the Mandelbrot set, which only requires additions
and multiplications, and the difference in speed would most probably not
be as drastic with those, but it gives a good idea of the overall difference
in speed when a wide range of mathematical functions and operations is used.)

-- 
                                                          - Warp

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