Memristive Oscillatory Networks for Computing: The Chemical Wave Propagation Paradigm

Theodoros Panagiotis Chatzinikolaou, Iosif-Angelos Fyrigos, V. Ntinas, Stavros Kitsios, P. Bousoulas, Michail-Antisthenis I. Tsompanas, D. Tsoukalas, G. Sirakoulis
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引用次数: 4

Abstract

During the last decade, there is an ever-growing concern regarding the future of CMOS technology, as well as the emerging difficulties on handling upcoming technological issues related with silicon transistors' dimensions, electrical power, energy consumption, and last but not least reaching the physical limits of this technology. At the same time, new computing alternatives beyond the classical computing systems, namely von Neumman architectures, are heavily sought after to tackle energy and memory-wall problems. In this talk, we focus on a hybrid analogue computational circuit-level system with unipolar memristor nanodevices connected in oscillatory networks and based on wave-like propagation of information. These methods are inspired by biochemical processes occurring in nature. The proposed insightful electrochemical wave propagation is apparent in many natural and biological systems and is modelled with powerful, inherently parallel computational tools, like Cellular Automata (CAs). This framework enables us to further proceed into realising alternative types of computations executed on the designed, modelled and fabricated memristor nanodevices, which are finally employed for the design and development of wave based electronic computational units. The proposed nanoelectronic memristive oscillatory networks will be in the advantageous position to perform both classical and unconventional calculations, like multi-digit, in memory and neuromorphic, to name a few of them. Thus, we will have a powerful tool targeting beyond the existing von Neumann information processing techniques and alleviating the aforementioned disadvantages associated with them.
用于计算的记忆振荡网络:化学波传播范式
在过去的十年中,人们越来越关注CMOS技术的未来,以及处理与硅晶体管尺寸,电功率,能耗以及最后但并非最不重要的达到该技术的物理极限相关的即将到来的技术问题的新困难。与此同时,超越经典计算系统的新的计算替代方案,即冯·诺伊曼架构,正在大力寻求解决能源和内存墙问题。在本次演讲中,我们将重点介绍一种混合模拟计算电路级系统,该系统将单极忆阻纳米器件连接在振荡网络中,并基于信息的波状传播。这些方法的灵感来自于自然界中发生的生化过程。所提出的深刻的电化学波传播在许多自然和生物系统中都很明显,并且用强大的、固有的并行计算工具(如细胞自动机(CAs))进行建模。该框架使我们能够进一步实现在设计、建模和制造的忆阻器纳米器件上执行的替代类型的计算,最终用于设计和开发基于波的电子计算单元。所提出的纳米电子记忆振荡网络将在执行经典和非常规计算方面处于有利地位,例如在记忆和神经形态方面,仅举几例。因此,我们将有一个强大的工具,超越现有的冯·诺伊曼信息处理技术,并减轻上述与之相关的缺点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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