A Number Representation Systems Library Supporting New Representations Based on Morris Tapered Floating-point with Hidden Exponent Bit

Stefan-Dan Ciocirlan, Dumitrel Loghin
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Abstract

The introduction of posit reopened the debate about the utility of IEEE754 in specific domains. In this context, we propose a high-level language (Scala) library that aims to reduce the effort of designing and testing new number representation systems (NRSs). The library's efficiency is tested with three new NRSs derived from Morris Tapered Floating-Point by adding a hidden exponent bit. We call these NRSs MorrisHEB, MorrisBiasHEB, and MorrisUnaryHEB, respectively. We show that they offer a better dynamic range, better decimal accuracy for unary operations, more exact results for addition (37.61% in the case of MorrisUnaryHEB), and better average decimal accuracy for inexact results on binary operations than posit and IEEE754. Going through existing benchmarks in the literature, and favorable/unfavorable examples for IEEE754/posit, we show that these new NRSs produce similar (less than one decimal accuracy difference) or even better results than IEEE754 and posit. Given the entire spectrum of results, there are arguments for MorrisBiasHEB to be used as a replacement for IEEE754 in general computations. MorrisUnaryHEB has a more populated ``golden zone'' (+13.6%) and a better dynamic range (149X) than posit, making it a candidate for machine learning computations.
支持基于隐含指数位的Morris锥形浮点数新表示的数字表示系统库
posit的引入重新开启了关于IEEE754非特定域的实用性的争论。在这种情况下,我们提出了一个高级语言(Scala)库,旨在减少设计和测试新的数字表示系统(NRSs)的工作量。通过添加一个隐藏的指数位,从Morris锥形浮点派生出三个新的NRSs,测试了该库的效率。我们分别称这些nrs为MorrisHEB、MorrisBiasHEB和MorrisUnaryHEB。我们表明,它们提供了更好的动态范围,一元操作的更好的小数精度,更精确的加法结果(在MorrisUnaryHEB的情况下为37.61%),以及比正数和IEEE754更好的二进制操作的不精确结果的平均十进制精度。通过文献中的现有基准,以及IEEE754/posit的有利/不利示例,我们表明这些新的NRSs产生与IEEE754和posit相似(小于一个十进制的精度差异)甚至更好的结果。考虑到整个结果范围,在一般计算中使用MorrisBiasHEB作为IEEE754的替代品存在争议。morrisunaryheba拥有比posit更多的“黄金地带”(+13.6%)和更好的动态范围(149X),使其成为机器学习计算的候选对象。
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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