忠实地舍入浮点计算

M. Lange, S. Rump
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引用次数: 8

摘要

我们给出了四种基本运算和平方根的一对算法。它可以看作是一种简化的、更有效的双双算法。基础算法的中心假设是对一组离散实数的操作进行误差分析的第一个标准模型。我们既不需要浮点网格,也不需要舍入到最近的属性。在此基础上,我们定义了一个相对舍入误差单位u,并证明了任意算术表达式计算结果的严格误差界限,这取决于u、表达式的大小以及可能的条件度量。在本文的第二部分中,我们通过检查需求来扩展误差分析,以确保忠实地舍入输出,并将我们的结果应用于符合IEEE 754标准的浮点系统。对于一类数学表达式,采用IEEE 754标准的以β为底的符合算法,证明了结果可以忠实地四舍五入,最多可进行1 /√βu - 2运算。我们的研究结果涵盖了许多以前发表的算法来计算忠实的四舍五入结果,其中包括霍纳方案、乘积、和、点积或欧几里得范数。除此之外,还可以分析其他几个问题,例如多项式插值、方向问题、Householder变换或大尺寸Hilbert矩阵的最小奇异值。
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Faithfully Rounded Floating-point Computations
We present a pair arithmetic for the four basic operations and square root. It can be regarded as a simplified, more-efficient double-double arithmetic. The central assumption on the underlying arithmetic is the first standard model for error analysis for operations on a discrete set of real numbers. Neither do we require a floating-point grid nor a rounding to nearest property. Based on that, we define a relative rounding error unit u and prove rigorous error bounds for the computed result of an arbitrary arithmetic expression depending on u, the size of the expression, and possibly a condition measure. In the second part of this note, we extend the error analysis by examining requirements to ensure faithfully rounded outputs and apply our results to IEEE 754 standard conform floating-point systems. For a class of mathematical expressions, using an IEEE 754 standard conform arithmetic with base β, the result is proved to be faithfully rounded for up to 1 / √βu - 2 operations. Our findings cover a number of previously published algorithms to compute faithfully rounded results, among them Horner’s scheme, products, sums, dot products, or Euclidean norm. Beyond that, several other problems can be analyzed, such as polynomial interpolation, orientation problems, Householder transformations, or the smallest singular value of Hilbert matrices of large size.
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