Enhenced redundancy analysis for memories using geometric faults based search tree

Wooheon Kang, Hyungjun Cho, Sungho Kang
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Abstract

With the growth of memory capacity and density, test cost and yield improvement are becoming more important. To increase yield of memory, redundancy analysis (RA) which analyzes the faults in memory is essential. However, the time for finding solutions to repair memories with faulty cells is very huge because most RA algorithms for automatic test equipment (ATE) are based on a tree structure. To reduce the time of memory test & repair is important to increase the memory yield using ATE. In order to reduce the time of memory test & repair, an RA algorithm with an early termination condition is proposed and it builds a geometric faults based search tree. To build the proposed algorithm, the faults in a memory are classified into geometric faults according to their characteristic. The experimental results show the effectiveness of the proposed algorithm.
基于几何故障的搜索树增强存储器冗余分析
随着存储器容量和密度的增加,测试成本和良率的提高变得越来越重要。为了提高存储器的利用率,需要对存储器中的故障进行冗余分析。然而,由于大多数自动测试设备(ATE)的RA算法是基于树形结构的,因此寻找修复有缺陷细胞的记忆的解决方案需要花费大量的时间。减少记忆体测试与修复时间是提高记忆体成品率的重要途径。为了减少记忆测试和修复的时间,提出了一种具有早期终止条件的RA算法,并构建了基于几何故障的搜索树。为了构建该算法,将存储器中的故障根据其特征分类为几何故障。实验结果表明了该算法的有效性。
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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