Design and analysis of STTRAM-based ternary content addressable memory cell

Rekha Govindaraj, Swaroop Ghosh

Research output: Contribution to journalArticlepeer-review

18 Scopus citations


Content Addressable Memory (CAM) is widely used in applications where searching a specific pattern of data is a major operation. Conventional CAMs suffer from area, power, and speed limitations. We propose Spin-Torque Transfer RAM-based Ternary CAM (TCAM) cells. The proposed NOR-type TCAM cell has a 62.5% (33%) reduction in number of transistor compared to conventional CMOS TCAMs (spintronic TCAMs). We analyzed the sense margin of the proposed TCAM with respect to 16-, 32-, 64-, 128-, and 256-bit word sizes in 22nm predictive technology. Simulations indicated a reliable sense margin of 50mV even at 0.7V supply voltage for 256-bits word. We also explored a selective threshold voltage modulation of transistors to improve the sense margin and tolerate process and voltage variations. The worst-case search latency and sense margin of 256-bit TCAM is found to be 263ps and 220mV, respectively, at 1V supply voltage. The average search power consumed is 13mW, and the search energy is 4.7fJ/bit search. The write time is 4ns, and the write energy is 0.69pJ/bit. We leverage the NOR-type TCAM design to realize a 9T-2 Magnetic Tunnel Junctions NAND-type TCAM cell that has 43.75% less number of transistors than the conventional CMOS TCAM cell. A NAND-type cell can support up to 64-bit words with a maximum sense margin of up to 33mV. We compare the performance metrics of NOR- and NAND-type TCAM cells with other TCAMs in the literature.

Original languageEnglish (US)
Article number52
JournalACM Journal on Emerging Technologies in Computing Systems
Issue number4
StatePublished - May 2017

All Science Journal Classification (ASJC) codes

  • Software
  • Hardware and Architecture
  • Electrical and Electronic Engineering


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