Memristors in Cellular-Automata-Based Computing: A Review

被引:2
|
作者
Karamani, Rafailia-Eleni [1 ]
Fyrigos, Iosif-Angelos [1 ]
Ntinas, Vasileios [1 ,2 ]
Vourkas, Ioannis [3 ]
Adamatzky, Andrew [1 ,4 ]
Sirakoulis, Georgios Ch. [1 ]
机构
[1] Democritus Univ Thrace, Dept Elect & Comp Engn, Xanthi 67100, Hellas, Greece
[2] Univ Polytecn Catalunia, Dept Elect Engn, Barcelona, Spain
[3] Univ Tecn Federico Santa Maria, Dept Elect Engn, Valparaiso 2362735, Chile
[4] Univ West England, Dept Comp Sci & Creat Technol, Bristol BS16 1QY, England
关键词
memristor; Cellular Automata; circuit design; parallel and in-memory computing architectures; NETWORKS; DESIGN; MODEL;
D O I
10.3390/electronics12163523
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The development of novel hardware computing systems and methods has been a topic of increased interest for researchers worldwide. New materials, devices, and architectures are being explored as a means to deliver more efficient solutions to contemporary issues. Along with the advancement of technology, there is a continuous increase in methods available to address significant challenges. However, the increased needs to be fulfilled have also led to problems of increasing complexity that require better and faster computing and processing capabilities. Moreover, there is a wide range of problems in several applications that cannot be addressed using the currently available methods and tools. As a consequence, the need for emerging and more efficient computing methods is of utmost importance and constitutes a topic of active research. Among several proposed solutions, we distinguish the development of a novel nanoelectronic device, called a "memristor", that can be utilized both for storing and processing, and thus it has emerged as a promising circuit element for the design of compact and energy-efficient circuits and systems. The memristor has been proposed for a wide range of applications. However, in this work, we focus on its use in computing architectures based on the concept of Cellular Automata. The combination of the memristor's performance characteristics with Cellular Automata has boosted further the concept of processing and storing information on the same physical units of a system, which has been extensively studied in the literature as it provides a very good candidate for the implementation of Cellular Automata computing with increased potential and improved characteristics, compared to traditional hardware implementations. In this context, this paper reviews the most recent advancements toward the development of Cellular-Automata-based computing coupled with memristor devices. Several approaches for the design of such novel architectures, called "Memristive Cellular Automata", exist in the literature. This extensive review provides a thorough insight into the most important developments so far, helping the reader to grasp all the necessary information, which is here presented in an organized and structured manner. Thus, this article aims to pave the way for further development in the field and to bring attention to technological aspects that require further investigation.
引用
收藏
页数:32
相关论文
共 50 条
  • [31] On computing the Lyapunov exponents of reversible cellular automata
    Johan Kopra
    Natural Computing, 2021, 20 : 273 - 286
  • [32] On computing the Lyapunov exponents of reversible cellular automata
    Kopra, Johan
    NATURAL COMPUTING, 2021, 20 (02) : 273 - 286
  • [33] Cellular automata cryptography using reconfigurable computing
    George, DFJ
    George, SE
    DEVELOPMENTS IN APPLIED ARTIFICIAL INTELLIGENCE, 2003, 2718 : 104 - 111
  • [34] Computing the periods of preimages in surjective cellular automata
    Mariot, Luca
    Leporati, Alberto
    Dennunzio, Alberto
    Formenti, Enrico
    NATURAL COMPUTING, 2017, 16 (03) : 367 - 381
  • [35] COMPUTING FRACTAL DIMENSIONS FOR ADDITIVE CELLULAR AUTOMATA
    WILLSON, SJ
    PHYSICA D, 1987, 24 (1-3): : 190 - 206
  • [36] INVERTIBLE CELLULAR AUTOMATA - A REVIEW
    TOFFOLI, T
    MARGOLUS, NH
    PHYSICA D, 1990, 45 (1-3): : 229 - 253
  • [37] A review of Quantum Cellular Automata
    Farrelly, Terry
    QUANTUM, 2020, 4
  • [38] Image Segmentation Based on Learning Cellular Automata Using Soft Computing Approach
    Das, Debasis
    Ray, Abhishek
    INTERNATIONAL CONFERENCE ON MODELING, OPTIMIZATION, AND COMPUTING, 2010, 1298 : 606 - 611
  • [39] Glider-based computing in reaction-diffusion hexagonal cellular automata
    Adamatzky, A
    Wuensche, A
    Costello, BD
    CHAOS SOLITONS & FRACTALS, 2006, 27 (02) : 287 - 295
  • [40] Evolutionary Search for Cellular Automata Logic Gates with Collision-Based Computing
    Sapin, Emmanuel
    Bull, Larry
    COMPLEX SYSTEMS, 2008, 17 (04): : 321 - 338