High-Density 3-D Stackable Crossbar 2D2R nvTCAM With Low-Power Intelligent Search for Fast Packet Forwarding in 5G Applications

By virtue of hardware parallelism, ternary content addressable memory (TCAM) is attractive for low-latency search for packet forwarding in routers for network communications in the upcoming fifth-generation (5G) era. However, the demand for high-density TCAM encounters remarkable costs in silicon area and power consumption. In this work, a 16-kb nonvolatile ternary content addressable memory (nvTCAM) test chip based on resistive memory (ReRAM) is demonstrated in 28-nm process with two techniques to deal with the aforementioned issues. First, the crossbar array with 2-diode-2-ReRAM (2D2R) nvTCAM cell is proposed to realize $>3\times $ improvement in storage density. The back-end-of-line integration of both diode and ReRAM resistor also allows for further 3-D stacking to realize larger storage density. Second, the machine learning concept is exploited to realize intelligent search operation. ${K}$ -means clustering is employed to allocate the entry storage and then the search of destination IP address can be targeted to a specific bank for low power. The evaluation shows >70% reduction in search energy with 2% overhead in silicon area for bank count of four. The test chip also achieves a match delay of 2 ns under nominal operating conditions.