Diagnostic data compression techniques for embedded memories with built-in self-test

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.