Energy Efficient and Low dynamic power Consumption TCAM on FPGA

Artificial Intelligence [AI] and networking applications extensively incorporate Field Programmable Gate Arrays [FPGA] - based Ternary Content Addressable Memories [TCAM]. Since FPGAs cannot support TCAMs, they must be emulated with SRAM-based memories, requiring FPGA resources. Compared to state-of-the-art designs, the proposed FPGA-based TCAM implementation will save significant This methodology makes use of Lookup Table RAMS (LUTRAMs), slice carry-chains, flip-flops (FF) allowing simultaneous mapping rules deeper pipelining respectively. The results in lower power consumption, lesser delays, resource utilization. It outperformed conventional TCAMs terms energy efficiency (EE) performance per area (PA) by at least 3.34 8.4 times respectively, 56% better than existing designs. method outperforms all previous approaches due its low dynamic consumption when considering huge size emulation on FPGAs.