InforLorV4, Main, Merge, bibRecord, 005E64

Searching Worst Cases of a One-Variable Function Using Lattice Reduction

Identifieur interne : 005E64 ( Main/Merge ); précédent : 005E63; suivant : 005E65

Searching Worst Cases of a One-Variable Function Using Lattice Reduction

Auteurs : Damien Stehlé [France] ; Paul Zimmermann [France] ; Vincent Lefèvre [France]

Source :

IEEE Transactions on Computers [ 0018-9340 ] ; 2005.

RBID : Hal:inria-00000379

Abstract

We propose a new algorithm to find worst cases for the correct rounding of a mathematical function of one variable. We first reduce this problem to the real small value problem—i.e., for polynomials with real coefficients. Then, we show that this second problem can be solved efficiently by extending Coppersmith's work on the integer small value problem—for polynomials with integer coefficients—using lattice reduction. For floating-point numbers with a mantissa less than N and a polynomial approximation of degree d, our algorithm finds all worst cases at distance less than N^{\frac{-d^2}{2d+1}} from a machine number in time O(N^{{\frac{d+1}{2d+1}}+\varepsilon}). For d=2, a detailed study improves on the O(N^{2/3+\varepsilon}) complexity from Lefèvre's algorithm to O(N^{4/7+\varepsilon}). For larger d, our algorithm can be used to check that there exist no worst cases at distance less than N^{-k} in time O(N^{1/2+\varepsilon}).

Url:

https://hal.inria.fr/inria-00000379

DOI: 10.1109/TC.2005.55

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Le document en format XML

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<idno type="DOI">10.1109/TC.2005.55</idno>
<series><title level="j">IEEE Transactions on Computers</title>
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<front><div type="abstract" xml:lang="en">We propose a new algorithm to find worst cases for the correct rounding of a mathematical function of one variable. We first reduce this problem to the real small value problem—i.e., for polynomials with real coefficients. Then, we show that this second problem can be solved efficiently by extending Coppersmith's work on the integer small value problem—for polynomials with integer coefficients—using lattice reduction. For floating-point numbers with a mantissa less than N and a polynomial approximation of degree d, our algorithm finds all worst cases at distance less than N^{\frac{-d^2}{2d+1}} from a machine number in time O(N^{{\frac{d+1}{2d+1}}+\varepsilon}). For d=2, a detailed study improves on the O(N^{2/3+\varepsilon}) complexity from Lefèvre's algorithm to O(N^{4/7+\varepsilon}). For larger d, our algorithm can be used to check that there exist no worst cases at distance less than N^{-k} in time O(N^{1/2+\varepsilon}).</div>
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Searching Worst Cases of a One-Variable Function Using Lattice Reduction

Searching Worst Cases of a One-Variable Function Using Lattice Reduction

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