Test Algorithms for Physical Neighborhood Pattern Sensitive Faults in Reconfigurable RAMS

可重构 RAMS 中物理邻域模式敏感故障的测试算法

• 批准号: 9111886
• 负责人: Kewal Saluja
• 金额: $ 18.54万
• 依托单位: University of Wisconsin-Madison
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1991
• 资助国家: 美国
• 起止时间: 1991-10-01 至 1995-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9111886&HistoricalAwards=false
• 关键词: Test; Algorithms; Physical; Neighborhood; Pattern

Saluja This research addresses testing large, reconfigurable random access memories for faults due to certain patterns originating in the physical neighborhood of a memory cell. These are pattern sensitive faults (PSF). Current methods do not deal with 5 and 9 cell neighborhoods, and are complex. In this research, necessary and sufficient conditions to test check bits for neighborhood pattern sensitive faults are being developed. Based on these results, algorithms to test for 5 and 9 cell physical neighborhood PSFs in random access memories (RAMs) are being designed. These algorithms deal with the cases where logical and physical address spaces are not identical, memories are reconfigured, and where built in error detection and correction techniques are employed. The use of these algorithms for built in self test implementation is being explored.

Saluja 本研究解决测试大型，可重新配置的随机存取存储器的故障，由于某些模式起源于一个存储器单元的物理邻域。 这些是模式敏感故障（PSF）。 目前的方法不处理5和9个小区邻域，并且是复杂的。 在这项研究中，必要和充分条件，以测试检查位的邻域模式敏感故障正在开发。 基于这些结果，正在设计用于测试随机存取存储器（RAM）中的5个和9个单元物理邻域PSF的算法。 这些算法处理的情况下，逻辑和物理地址空间是不相同的，存储器被重新配置，并在错误检测和纠正技术的内置。 正在探索使用这些算法进行内建自测试。