Prof. Kahan came up with the notion of an ulp. An ulp of a real number value is the distance between the floating-point numbers which bracket the real value. Of course since the only reals we can represent happen to be floating-point numbers, this corresponds to the distance between adjacent floating-point values. To avoid ambiguities at powers of two (where the distance between numbers changes), we can define an ulp of a floating-point value to be the distance to the next floating-point value larger in magnitude.
In Java, all the arithmetic operations {+, -, *, /, sqrt} have error of less than 1/2 ulp assuming their inputs are exact; i.e. assuming you want to take the square root of the floating-point number closest to 0.1 not 0.1 exactly. Much of the math library must be accurate to 1 ulp although a few functions only require 2 ulps. Of course even with correct rounding at each step, the final answer could be widely inaccurate due to accumulated and amplified round-off errors.
|
|
You can get the freshest copy of this page from: | or possibly from your local J: drive (Java virtual drive/mindprod.com website mirror) |
| http://mindprod.com/jgloss/ulp.html | J:\mindprod\jgloss\ulp.html | |
![]() | Please email your feedback for publication,
letters to the editor, errors, omissions, typos, formatting errors, ambiguities, unclear wording,
broken/redirected link reports, suggestions to improve this page or comments to
Roedy Green :
| |
| Canadian Mind Products | ||
| mindprod.com IP:[65.110.21.43] | ||
| view Blog | Your face IP:[38.107.179.211] | |
| Feedback | You are visitor number 18,279. | |