  Content addressable memory (CAM) is widely used in associative search tasks
for its highly parallel pattern matching capability. To accommodate the
increasingly complex and data-intensive pattern matching tasks, it is critical
to keep improving the CAM density to enhance the performance and area
efficiency. In this work, we demonstrate: i) a novel ultra-compact 1FeFET CAM
design that enables parallel associative search and in-memory hamming distance
calculation; ii) a multi-bit CAM for exact search using the same CAM cell; iii)
compact device designs that integrate the series resistor current limiter into
the intrinsic FeFET structure to turn the 1FeFET1R into an effective 1FeFET
cell; iv) a successful 2-step search operation and a sufficient sensing margin
of the proposed binary and multi-bit 1FeFET1R CAM array with sizes of practical
interests in both experiments and simulations, given the existing unoptimized
FeFET device variation; v) 89.9x speedup and 66.5x energy efficiency
improvement over the state-of-the art alignment tools on GPU in accelerating
genome pattern matching applications through the hyperdimensional computing
paradigm.
