Round-off noise estimation of fixed-point algorithms using Modified Affine Arithmetic and Legendre Polynomials

Luis Esteban, J. A. Martín, A. Regadío
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Abstract

The implementation of algorithms in fixed-point format causes the apparition of Round-Off Noise which propagates through the different functional units of the system. This issue causes the Signal-to-Noise Ratio of the outputs is degraded. Given an algorithm, it is essential to estimate the integer and fractional bit-widths of all the variables and operations to comply with the Signal-to-Noise Ratio requirements. In this context, Affine Arithmetic can obtain fast and accurate estimations of the bit-widths for linear systems. However, for non-linear systems, Affine Arithmetic loses the temporal correlation of the variables. Other existing frameworks are either time consuming or lead to inaccurate bound estimations. In this paper, a Modified Affine Arithmetic framework with Legendre polynomials is used to obtain fast and accurate bound estimations also for non-linear systems. Moreover, the approach proposed in this paper obtains speedups in the range of 7 to 100 compared to Monte-Carlo simulations.
基于修正仿射算法和勒让德多项式的不动点算法的舍入噪声估计
以定点格式实现算法会导致舍入噪声的出现,该噪声通过系统的不同功能单元传播。这个问题导致输出的信噪比降低。给定一个算法,估计所有变量和操作的整数和分数比特宽度以符合信噪比要求是至关重要的。在这种情况下,仿射算法可以快速准确地估计线性系统的比特宽度。然而,对于非线性系统,仿射算法失去了变量的时间相关性。其他现有框架要么耗时,要么导致不准确的边界估计。本文提出了一种带有勒让德多项式的改进仿射算法框架,用于非线性系统的快速准确的界估计。此外,与蒙特卡罗模拟相比,本文提出的方法获得了7到100的加速范围。
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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