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Reports (Research Report) Year : 2002

Worst Cases and Lattice Reduction


We propose a new algorithm to find worst cases for correct rounding of an analytic function. 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 [4,5,6]. 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 < N [power](-d2/2d-1) from a machine number in time [OMICRON](N[power]((d-1)/(2d-1)+e)). For d=2, this improves on the [OMICRON](N- [power]((2/3)+e)) complexity from Lefèvre's algorithm [12,13] to [OMICRON](N[p- ower]((3/5)+e)). We exhibit some new worst cases found using our algorithm, for double-extended and quadruple precision. For larger d, our algorithm can be used to check that there exist no worst cases at distance < N[power]-k in time [OMICRON](N[power](1/2+[OMICRON](1/k))).
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Dates and versions

inria-00071999 , version 1 (23-05-2006)


  • HAL Id : inria-00071999 , version 1


Damien Stehlé, Vincent Lefèvre, Paul Zimmermann. Worst Cases and Lattice Reduction. [Research Report] RR-4586, INRIA. 2002. ⟨inria-00071999⟩
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