利用综合征压缩进行记忆内置自诊断

Jin-Fu Li, Ruey-Shing Tzeng, Cheng-Wen Wu
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引用次数: 11

摘要

由于引脚数的限制,嵌入式ram的内置自诊断(BISD)通常按顺序导出诊断信息,这导致了诊断时间的开销。本文描述了一种基于树的面向词存储压缩技术。该技术可以在支持bsd的嵌入式RAM中加快诊断数据的传输速度。采用简化的Huffman编码方案,并将每个256位汉明综合征划分为固定大小的符号,假设符号为16位,平均压缩比降至10%左右。所提出的压缩技术减少了诊断测试的时间,以及测试仪的存储需求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using syndrome compression for memory built-in self-diagnosis
Due to the pin-count limitation, built-in self-diagnosis (BISD) for embedded RAMs usually exports diagnosis information serially, which results in the overhead of diagnostic time. This paper describes a tree-based compression technique for word-oriented memories. The technique can speed up the transmission of diagnosis data from the embedded RAM with BISD support. By using a simplified Huffman coding scheme and partitioning each 256-bit Hamming syndrome into fixed-size symbols, the average compression ratio is reduced to about 10%, assuming 16-bit symbols. The proposed compression technique reduces the time for diagnostic test, as well as the tester storage requirement.
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