An Assessment of Random Dynamical Network Automata for Nanoelectronics

Abstract

Highly structured mesh- or crossbar-like nanoscale architectures have been proposed in the past as possible alternatives to the von Neumann computing architecture. While the top-down engineered semi-conducting technology favors regular and locally interconnected structures, emerging bottom-up self-assembled devices tend to be unstructured and heterogeneous because of the current lack of precise control over these processes. In this paper, we survey and assess two types of random dynamical networks, namely Random Boolean Networks (RBNs) and Random Threshold Networks (RTNs), as candidates for alternative computing architectures and models for future nanoscale information processing devices. In a high-level approach that is based on previous work, we illustrate that they have the potential to offer superior properties over highly structured architectures, such as an inherent and scale-invariant robustness, more efficient communication capabilities, and manufacturing benefits. Our investigation is driven by the need for alternative computing and manufacturing paradigms to mitigate some of the challenges traditional approaches face.