Automatic Numerical Analysis Based on Infinite-Precision Arithmetic

Shuai Wei, Enyi Tang, Tianyu Liu, N. Müller, Zhenyu Chen
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引用次数: 1

Abstract

Numerical analysis is an important process for creating reliable numerical software. However, traditional analysis methods rely on manual estimation by numerical analysts, which is restricted by the problem size. Although some state-of-art software packages can check whether a program is numerical unstable, they cannot tell whether it is caused by ill-posed problem itself or by some improper implementation practices, while these packages work on the floating point values in the program. In this paper, we introduce an automatic framework that utilizes infinite-precision arithmetic to analyze large-scale numerical problems by computer. To eliminate rounding errors, the computing process iterates itself to increase intermediate precision until the calculation reaches the desired final precision. Then the framework perturbs the inputs and intermediate values of a certain numerical problem. By checking the gaps among different program outputs, the framework helps us understand whether the problem is well-conditioned or ill-conditioned. The framework also compares the infinite-precision arithmetic with fixed-precision arithmetic. The evaluation of a bunch of classical problems shows that our framework is able to detect the ill-conditioning in large-scale problems effectively.
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基于无限精度算法的自动数值分析
数值分析是创建可靠的数值软件的重要过程。然而,传统的分析方法依赖于数值分析人员的人工估计,受问题规模的限制。虽然一些最先进的软件包可以检查一个程序是否是数值不稳定的,但它们不能判断它是由病态问题本身引起的还是由一些不适当的实现实践引起的,而这些软件包在程序中的浮点值上工作。本文介绍了一种利用无限精度算法在计算机上分析大规模数值问题的自动框架。为了消除舍入误差,计算过程自我迭代以提高中间精度,直到计算达到所需的最终精度。然后,该框架对某数值问题的输入和中间值进行扰动。通过检查不同程序输出之间的差距,框架帮助我们了解问题是条件良好的还是条件不良的。该框架还比较了无限精度算法和固定精度算法。对一系列经典问题的评估表明,我们的框架能够有效地检测大规模问题中的病态。
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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