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Automated Backward Error Analysis for Numerical Code

机译:数值代码的自动向后误差分析

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摘要

Numerical code uses floating-point arithmetic and necessarily suffers from roundoff and truncation errors. Error analysis is the process to quantify such uncertainty. Forward error analysis and backward error analysis are two popular paradigms of error analysis. Forward error analysis is intuitive, and has been explored and automated by the programming languages (PL) community. In contrast, although backward error analysis is fundamental for numerical stability and is preferred by numerical analysts, it is less known and unexplored by the PL community. To fill this gap, this paper presents an automated backward error analysis for numerical code to empower both numerical analysts and application developers. In addition, we use the computed backward error results to compute the condition number, an important quantity recognized by numerical analysts for measuring a function's sensitivity to errors in the input and finite precision arithmetic. Experimental results on Intel x87 FPU instructions and widely-used GNU C Library functions demonstrate that our analysis is effective at analyzing the accuracy of floating-point programs.
机译:数值代码使用浮点运算,因此必然会产生舍入和截断错误。误差分析是量化这种不确定性的过程。前向错误分析和后向错误分析是错误分析的两个流行范例。前向错误分析是直观的,并且已由编程语言(PL)社区进行了探索和自动化。相比之下,尽管后向误差分析是数值稳定性的基础,并且是数值分析人员的首选,但PL社区对此却鲜为人知和未开发。为了填补这一空白,本文提出了一种针对数字代码的自动向后错误分析,以增强数字分析人员和应用程序开发人员的能力。另外,我们使用计算出的向后误差结果来计算条件数,这是数值分析人员认可的重要量,用于测量函数对输入和有限精度算术中的误差的敏感性。在Intel x87 FPU指令和广泛使用的GNU C库函数上的实验结果表明,我们的分析有效地分析了浮点程序的准确性。

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