28nm Ferroelectric Field Effect Transistor Based Associative Memory Array for Few-Shot Learning and Genome Analysis

Content-Addressable Memories (CAMs) enable data retrieval based on content rather than specific addresses, making them invaluable for rapid data search and pattern matching. Efficient computation in these systems requires minimal latency and power consumption, particularly for embedded applications. The parallelization of in-memory computing (IMC) significantly enhances both search latency and power efficiency. This work presents, the use of ferroelectric field-effect transistors (FeFETs) in a 1 kb CAM array, applied to two key use cases: one/few-shot learning in memory-augmented neural networks and read mapping in genome analysis for bioinformatics. Both applications demonstrate software-level accuracy alongside ultra-low power consumption.