When a floating-point computation is done, it is most of the time incorrect. The rounding error can be bounded by folklore formulas, such as ε|x| or ε|○(x)|. This gets more complicated when underflow is taken into account as an absolute term must be considered. Now, let us compute this error bound in practice. A common method is to use a directed rounding in order to be sure to get an over-approximation of this error bound. This article describes an algorithm that computes a correct bound using only rounding to nearest, therefore without requiring a costly change of the rounding mode. This is formally proved using the Coq formal proof assistant to increase the trust in this algorithm.
CITATION STYLE
Boldo, S. (2017). Computing a correct and tight rounding error bound using rounding-to-nearest. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10152 LNCS, pp. 47–51). Springer Verlag. https://doi.org/10.1007/978-3-319-54292-8_4
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