An Ultracompact Single‐Ferroelectric Field‐Effect Transistor Binary and Multibit Associative Search Engine

Abstract

Content addressable memory (CAM) is widely used in associative search tasks due to its parallel pattern matching capability. As more complex and data‐intensive tasks emerge, it is becoming increasingly important to enhance CAM density for improved performance and better area efficiency. To reduce the area overheads, various nonvolatile memory (NVM) devices, such as ferroelectric field‐effect transistors (FeFETs), are used in CAM design. Herein, a novel ultracompact 1FeFET CAM design that enables parallel associative search and in‐memory hamming distance calculation is used, as well as a multibit CAM for exact search using the same CAM cell. The proposed CAM design leverages the 1FeFET1R structure, and compact device designs that integrate the series resistor current limiter into the intrinsic FeFET structure are demonstrated to turn the 1FeFET1R structure into an effective 1FeFET cell. A two‐step search operation of the proposed binary and multibit 1FeFET CAM array through both experiments and simulations is proposed, showing a sufficient sensing margin despite unoptimized FeFET device variation. In genome pattern matching applications, using the hyperdimensional computing paradigm, the design results in a 89.9× speedup and 66.5× improvement in energy efficiency over the state‐of‐the‐art alignment tools on GPU.

Keywords

• associative search
• compute-in-memory
• content addressable memory
• ferroelectric field effect transistor
• hyperdimensional computing