Using syndrome compression for memory built-in self-diagnosis

Abstract

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.