Hum. Makes me wonder if any hardware will ever introduce rational numbers. One 
"rational register" which is 128 bits(?) long. It contains a 64 bit numerator 
and 64 bit denominator. That solves the problem. Except for irrational numbers 
such a pi, e, and others that I don't remember. And, curiously, IIRC, although 
both the rational and irrational number sets are infinate, there are "more" 
irrational numbers that rational numbers.

--
John McKown 
Systems Engineer IV
IT

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> -----Original Message-----
> From: IBM Mainframe Discussion List 
> [mailto:ibm-m...@bama.ua.edu] On Behalf Of Joel C. Ewing
> Sent: Tuesday, May 04, 2010 8:18 AM
> To: IBM-MAIN@bama.ua.edu
> Subject: Re: (may or may not be on topic) Floating point arithmetic
> 
> On 05/03/2010 11:22 AM, McKown, John wrote:
> >> -----Original Message-----
> >> From: IBM Mainframe Discussion List 
> >> [mailto:ibm-m...@bama.ua.edu] On Behalf Of Ed Gould
> >> Sent: Monday, May 03, 2010 10:58 AM
> >> To: IBM-MAIN@bama.ua.edu
> >> Subject: (may or may not be on topic) Floating point arithmetic
> >>
> >> This might be of interest to those wanting to do floating 
> >> point arithmetic.
> >> Please *NOTE* I do NOT know if this pertains to IBM or not.
> >>
> >> http://floating-point-gui.de/
> >>
> >> Ed
> > 
> > It definetly does apply to IBM z hardware. Also if you use 
> HFP (Hex Floating Point - legacy) and BFP (IEEE floating 
> point), then the identical operation can have two different 
> answers, neither of which is necessarily "correct".
> > 
> > --
> > John McKown 
> > Systems Engineer IV
> > IT
> > 
> Starting with z9 there are three flavors of floating-point 
> instructions,
> legacy Hex (HFP),  IEEE binary (BFP), and decimal floating-point.  And
> of course back in the early days of computing when floating point
> operations were frequently done by subroutines or machine 
> architectures
> were decimal, decimal floating point representations were not that
> uncommon.
> 
> All floating point representations, by their nature, 
> represent values by
> a fixed number of significant digits, which means that you can find
> integer and fractional values for all that can't be 
> represented exactly
> and for which results must be an approximation - it's just that the
> examples that introduce error would differ depending on the
> representation used.  If the article implies this  only 
> happens because
> the representation is in binary,  then it is incorrect.  It is the
> finite number of significant digits in floating-point representations
> that is the real culprit.
> 
> Many find the roundoff errors of binary floating point more mysterious
> and unpredictable only because they have limited their thinking to
> decimal representations of values and are only familiar with dealing
> with approximate values in decimal representation.
> 
> -- 
> Joel C. Ewing, Fort Smith, AR        jremoveccapsew...@acm.org
> 
> ----------------------------------------------------------------------
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