Predicting the Impact of Functional Approximation: from Component- to Application-Level

Marcello Traiola, A. Savino, M. Barbareschi, S. Carlo, A. Bosio
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引用次数: 15

Abstract

Approximate Computing (AxC) trades off between the level of accuracy required by the user and the actual precision provided by the computing system to achieve several optimizations such as performance improvement, energy and area reduction etc. Several AxCtechniques have been proposed so far in the literature. They work at different abstraction levels and propose both hardware and software implementations. The common issue of all existing approaches is the lack of a methodology to estimate the impact of a given AxC technique on the application-level accuracy. In this paper we propose a probabilistic approach to predict the relation between component-level functional approximation and application-level accuracy. Experimental results on a set of benchmark applications show that the proposed approach is able to estimate the approximation error with good accuracy and very low computation time.
预测函数逼近的影响:从组件到应用级
近似计算(AxC)在用户要求的精度水平和计算系统提供的实际精度之间进行权衡,以实现一些优化,如性能改进,能源和面积减少等。到目前为止,文献中已经提出了几种axc技术。他们在不同的抽象层次上工作,并提出硬件和软件实现。所有现有方法的共同问题是缺乏一种方法来估计给定的AxC技术对应用程序级精度的影响。本文提出了一种概率方法来预测组件级函数逼近与应用级精度之间的关系。一组基准应用的实验结果表明,该方法能够以较低的计算时间和较好的精度估计近似误差。
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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