Architecture of error free content address memory on 16*8 sparse clustered networks

Abstract

We propose a low-power content-addressable memory (16*8-CAM) employing a new algorithm for associativity between the input tag and the corresponding address of the output data. The proposed architecture is based on a recently developed sparse clustered network using binary connections that on-average eliminates most of the parallel comparisons performed during a search. Therefore, the dynamic energy consumption  of the proposed design is significantly lower compared with that of a conventional low-power 16*8- CAM design. Given an input tag, the proposed architecture computes a few possibilities  for the location of the matched tag and performs the comparisons on them to locate a single valid match.