🚀 go-pugleaf

Yes, once again, the great IEEE floating-point debate.
I'm looking at this from a non-experts point of view: I'm a 'naive scientist'
who doesn't really know much about the subtleties of numerical mathematics,
but I have to do alot of numerical computing for my work.

Here is what I see as the 2 sides:

Pro:  Using a carefully designed standard rules for FP is crucial for
getting the 'right' answer, and you can't expect mere mortals to just do it
any which way which seems convenient.  All the complexity is imperative. Any
body who cheats, or doesn't bother, (e.g. Cray) are silly fools who only care
how fast the program runs, whether or not it gives the "correct" answer. 
IEEE arithmetic is the key for consistency for running programs across
different machines.

Con:  Floating-point is only an approximation to reality anyway, so the
business of "correctness" is silly.  THe answer will never be truly Right,
so who gives a flying rat's ass about eeking out that last bit of 'precision'.
The IEEE standard only serves to make programs "wrong" in the same artificial
way (instilling a false sense of security about the results), but ends up
making computers alot slower and more expensive, only to please some anal ret-
entive nerds in some ivory-tower committee.   (:-))


From a practical scientist's point of view, I'd have to put myself in the
second category.  I mean, if one's models are only valid to 1% anyway, 
the end limits of precision are useless anyway.  And if something in that
last bit makes the algorithm go unstable, then choosing some "standard" way
of dealing with FP arithmetic won't solve the essential problem.



Of course, I should relate this to computer architecture, and so I ask
the experts, what exactly are the costs and benefits of IEEE arithmetic?


Matt Kennel
mbk@inls1.ucsd.edu