An Efficient Single-Cell Associative Search Engine via Conditional Execution

Content addressable memories (CAMs) embed parallel associative search directly into memory blocks, making them essential for associative memory (AM) applications. CAMs can efficiently perform best or exact search operations that identify a data entry in the database that is the closest or exactly the same as the input entry, respectively. Recently, a single FeFET-based design that is compact and highly efficient has been proposed. However, its multi-step sensing scheme is tailored for best search and is thus inefficient for exact search operations. To address this, we propose a sensing scheme with the concept of conditional execution that dynamically prunes execution steps according to the outputs of the early steps. For higher efficiency, we implement the proposed sensing scheme in the voltage domain and propose an efficient transformation scheme to support current domain arrays. The proposed scheme achieves up to 3.66× and 3× lower energy and latency respectively. The proposed method also achieves a 2.5× lower error rate.