Fail Memory Configuration Set for RA Estimation

Hayoung Lee, Keewon Cho, Sungho Kang, Wooheon Kang, Seungtaek Lee, Woosik Jeong
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引用次数: 6

Abstract

Since the redundancy analysis (RA) has been introduced for memory yield, many RA researches have been conducted. However, objective comparisons of them are difficult by the absence of real memory models with realistic fault distributions. This paper presents a fail memory configuration set for RA estimation, called as ITC’2020 RA Benchmarks. It enables objective estimations of RAs with respect to effectiveness and efficiency. The fail memory configuration set includes memory models which have various redundancy structures and a fault generation algorithm with fault distribution which can be criteria for objective comparisons of RA. Simulations for estimations and comparisons of RA researches including BIRA are progressed utilizing the fail memory configuration set.
RA估计的Fail Memory Configuration Set
自从引入冗余分析(RA)来研究存储器产出率以来,进行了大量的冗余分析研究。然而,由于缺乏具有真实故障分布的真实内存模型,很难对它们进行客观比较。本文提出了一种用于RA估计的故障内存配置集,称为ITC ' 2020 RA基准。它能够客观地估计RAs的有效性和效率。故障记忆配置集包括具有多种冗余结构的记忆模型和具有故障分布的故障生成算法,该算法可作为RA的客观比较标准。利用故障记忆配置集对包括BIRA在内的RA研究进行了估计和比较仿真。
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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