Cellular automata imbedded memristor-based recirculated logic in-memory computing

Yanming Liu, He Tian, Fan Wu, Anhan Liu, Yihao Li, Hao Sun, Mario Lanza, Tian-Ling Ren

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


Memristor-based circuits offer low hardware costs and in-memory computing, but full-memristive circuit integration for different algorithm remains limited. Cellular automata (CA) has been noticed for its well-known parallel, bio-inspired, computational characteristics. Running CA on conventional chips suffers from low parallelism and high hardware costs. Establishing dedicated hardware for CA remains elusive. We propose a recirculated logic operation scheme (RLOS) using memristive hardware and 2D transistors for CA evolution, significantly reducing hardware complexity. RLOS’s versatility supports multiple CA algorithms on a single circuit, including elementary CA rules and more complex majority classification and edge detection algorithms. Results demonstrate up to a 79-fold reduction in hardware costs compared to FPGA-based approaches. RLOS-based reservoir computing is proposed for edge computing development, boasting the lowest hardware cost (6 components/per cell) among existing implementations. This work advances efficient, low-cost CA hardware and encourages edge computing hardware exploration.
Original languageEnglish (US)
JournalNature Communications
Issue number1
StatePublished - May 10 2023

ASJC Scopus subject areas

  • General Biochemistry, Genetics and Molecular Biology
  • General Chemistry
  • General Physics and Astronomy


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