TCAmMCogniGron: Energy Efficient Memristor-Based TCAM for Match-Action Processing

Saad Saleh*, Anouk Goossens, Tamalika Banerjee, Boris Koldehofe

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

2 Citations (Scopus)
273 Downloads (Pure)


The Internet relies heavily on programmable match-action processors for matching network packets against locally available network rules and taking actions, such as forwarding and modification of network packets. This match-action process must be performed at high speed, i.e., commonly within one clock cycle, using a specialized memory unit called Ternary Content Addressable Memory (TCAM). Building on transistor-based CMOS designs, state-of-the-art TCAM architectures have high energy consumption and lack resilient designs for incorporating novel technologies for performing appropriate actions. In this article, we motivate the use of a novel fundamental component, the ‘Memristor’, for the development of TCAM architecture for match-action processing. Memristors can provide energy efficiency, non-volatility and better resource density as compared to transistors. We have proposed a novel memristor-based TCAM architecture called TCAmMCogniGron, built upon the voltage divider principle and requiring only two memristors and five transistors for storage and search operations compared to sixteen transistors in the traditional TCAM architecture. We analyzed its performance over an experimental data set of Nb-doped SrTiO3-based memristor. The analysis of TCAmMCogniGron showed promising power consumption statistics of 16 uW and 1 uW for match and mismatch operations along with twice the improvement in resources density as compared to the traditional architectures.
Original languageEnglish
Title of host publicationProceedings of the 7th International Conference on Rebooting Computing (ICRC 2022)
Number of pages11
ISBN (Print)979-8-3503-4709-8
Publication statusPublished - 17-Mar-2023
Event7th IEEE International Conference on Rebooting Computing - San Francisco, CA, United States
Duration: 8-Dec-20229-Dec-2022


Conference7th IEEE International Conference on Rebooting Computing
Country/TerritoryUnited States
CitySan Francisco, CA


  • Memristor
  • TCAM
  • Match-Action processing


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