DAEM: A Data- and Application-Aware Error Analysis Methodology for Approximate Adders

IF 2.4 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS
Muhammad Abdullah Hanif, Rehan Hafiz, Muhammad Shafique
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引用次数: 0

Abstract

Approximate adders are some of the fundamental arithmetic operators that are being employed in error-resilient applications, to achieve performance/energy/area gains. This improvement usually comes at the cost of some accuracy and, therefore, requires prior error analysis, to select an approximate adder variant that provides acceptable accuracy. Most of the state-of-the-art error analysis techniques for approximate adders assume input bits and operands to be independent of one another, while some also assume the operands to be uniformly distributed. In this paper, we analyze the impact of these assumptions on the accuracy of error estimation techniques, and we highlight the need to address these assumptions, to achieve better and more realistic quality estimates. Based on our analysis, we propose DAEM, a data- and application-aware error analysis methodology for approximate adders. Unlike existing error analysis models, we neither assume the adder operands to be uniformly distributed nor assume them to be independent. Specifically, we use 2D joint input probability mass functions (PMFs), populated using sample data, in order to incorporate the data and application knowledge in the analysis. These 2D joint input PMFs, along with 2D error maps of approximate adders, are used to estimate the error PMF of an adder network. The error PMF is then utilized to compute different error measures, such as the mean squared error (MSE) and mean error distance (MED). We evaluate the proposed error analysis methodology on audio and video processing applications, and we demonstrate that our methodology provides error estimates having a better correlation with the simulation results, as compared to the state-of-the-art techniques.
近似加法器的数据和应用感知误差分析方法
近似加法器是一些基本的算术运算符,用于抗错误应用中,以实现性能/能量/面积增益。这种改进通常以某些精度为代价,因此需要事先进行误差分析,以选择提供可接受精度的近似加法器变体。大多数最先进的近似加法器误差分析技术假设输入位和操作数彼此独立,而有些还假设操作数均匀分布。在本文中,我们分析了这些假设对误差估计技术准确性的影响,并强调了解决这些假设的必要性,以实现更好和更现实的质量估计。基于我们的分析,我们提出了DAEM,一种数据和应用感知的近似加法器误差分析方法。与现有的误差分析模型不同,我们既不假设加法器操作数均匀分布,也不假设它们是独立的。具体来说,我们使用二维联合输入概率质量函数(pmf),使用样本数据填充,以便将数据和应用知识纳入分析。这些二维联合输入PMF与近似加法器的二维误差映射一起用于估计加法器网络的误差PMF。然后利用误差PMF计算不同的误差度量,如均方误差(MSE)和平均误差距离(MED)。我们评估了音频和视频处理应用中提出的误差分析方法,并证明与最先进的技术相比,我们的方法提供的误差估计与仿真结果具有更好的相关性。
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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来源期刊
Information (Switzerland)
Information (Switzerland) Computer Science-Information Systems
CiteScore
6.90
自引率
0.00%
发文量
515
审稿时长
11 weeks
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