National Tsing Hua University Institutional Repository:Diagnostic data compression techniques for embedded memories with built-in self-test
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    National Tsing Hua University Institutional Repository > 電機資訊學院 > 電機資訊學院學士班 > 期刊論文 >  Diagnostic data compression techniques for embedded memories with built-in self-test


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    题名: Diagnostic data compression techniques for embedded memories with built-in self-test
    作者: Li, Jin-Fu;Tzeng, Ruey-Shing;Wu, Cheng-Wen
    教師: 吳誠文
    日期: 2002
    出版者: Springer Verlag
    關聯: Journal of Electronic Testing,Volume 18, pages 515-527, August 2002
    关键词: Built-in self test
    Algorithms
    Computer simulation
    Data compression
    Data structures
    摘要: © 2002 Springer Verlag - A system-on-chip (SOC) usually consists of many memory cores with different sizes and functionality, and they typically represent a significant portion of the SOC and therefore dominate its yield. Diagnostics for yield enhancement of the memory cores thus is a very important issue. In this paper we present two data compression techniques that can be used to speed up the transmission of diagnostic data from the embedded RAM built-in self-test (BIST) circuit that has diagnostic support to the external tester. The proposed syndrome-accumulation approach compresses the faulty-cell address and March syndrome to about 28% of the original size on average under the March-17N diagnostic test algorithm. The key component of the compressor is a novel syndrome-accumulation circuit, which can be realized by a content-addressable memory. Experimental results show that the area overhead is about 0.9% for a 1Mb SRAM with 164 faults. A tree-based compression technique for word-oriented memories is also presented. By using a simplified Huffman coding scheme and partitioning each 256-bit Hamming syndrome into fixed-size symbols, the average compression ratio (size of original data to that of compressed data) is about 10, assuming 16-bit symbols. Also, the additional hardware to implement the tree-based compressor is very small. The proposed compression techniques effectively reduce the memory diagnosis time as well as the tester storage requirement. (
    URI: http://www.springerlink.com/
    http://nthur.lib.nthu.edu.tw/handle/987654321/42022
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