  In this paper we present a comprehensive design and benchmarking study of
Content Addressable Memory (CAM) at the 7nm technology node in the context of
similarity search applications. We design CAM cells based on SRAM, spin-orbit
torque, and ferroelectric field effect transistor devices and from their
layouts extract cell parasitics using state of the art EDA tools. These
parasitics are used to develop SPICE netlists to model search operations. We
use a CAM-based dataset search and a sequential recommendation system to
highlight the application-level performance degradation due to interconnect
parasitics. We propose and evaluate two solutions to mitigate interconnect
effects.
