On the Componentwise Accuracy of Complex Floating-Point Division with an FMA

C. Jeannerod, N. Louvet, J. Muller
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引用次数: 9

Abstract

This paper deals with the accuracy of complex division in radix-two floating-point arithmetic. Assuming that a fused multiply-add (FMA) instruction is available and that no underflow/overflow occurs, we study how to ensure high relative accuracy in the component wise sense. Since this essentially reduces to evaluating accurately three expressions of the form ac+bd, an obvious approach would be to perform three calls to Kahan's compensated algorithm for 2 by 2 determinants. However, in the context of complex division, two of those expressions are such that ac and bd have the same sign, suggesting that cheaper schemes should be used here (since cancellation cannot occur). We first give a detailed accuracy analysis of such schemes for the sum of two nonnegative products, providing not only sharp bounds on both their absolute and relative errors, but also sufficient conditions for the output of one of them to coincide with the output of Kahan's algorithm. By combining Kahan's algorithm with this particular scheme, we then deduce two new division algorithms. Our first algorithm is a straight-line program whose component wise relative error is always at most 5u+13u2 with u the unit round off, we also provide examples of inputs for which the error of this algorithm approaches 5u, thus showing that our upper bound is essentially the best possible. When tests are allowed we show with a second algorithm that the bound above can be further reduced to 4.5u+9u2, and that this improved bound is reasonably sharp.
基于FMA的复杂浮点除法分量精度研究
本文讨论了双基数浮点运算中复数除法的精度问题。假设有一个融合乘加(FMA)指令可用,并且没有下溢/溢出的情况下,我们研究了如何在组件意义上保证较高的相对精度。由于这本质上简化为准确地计算三个形式为ac+bd的表达式,因此一个明显的方法是对2 × 2行列式的Kahan补偿算法执行三次调用。然而,在复数除法的上下文中,其中两个表达式使得ac和bd具有相同的符号,这表明这里应该使用更便宜的方案(因为无法进行消去)。我们首先对这两种非负积和方案进行了详细的精度分析,不仅给出了它们的绝对误差和相对误差的明确界限,而且给出了其中一种方案的输出与Kahan算法的输出一致的充分条件。通过将Kahan算法与该方案相结合,我们推导出了两种新的除法算法。我们的第一个算法是一个直线程序,其组件相对误差总是最多5u+13u2,其中u是单位四舍五入,我们还提供了该算法误差接近5u的输入示例,从而表明我们的上限本质上是最好的可能。在允许测试的情况下,我们用第二种算法证明,上面的边界可以进一步减小到4.5u+9u2,并且这个改进的边界相当尖锐。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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