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Computing With Networks of Oscillatory Dynamical Systems

机译:用振荡动力系统网络进行计算

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As we approach the end of the silicon road map, alternative computing models that can solveat-scaleproblems in the data-centric world are becoming important. This is accompanied by the realization that binary abstraction and Boolean logic, which have been the foundations of modern computing revolution, fall short of the desired performance and power efficiency. In particular, hard computing problems relevant to pattern matching, image and signal processing, optimizations, and neuromorphic applications require alternative approaches. In this paper, we review recent advances in oscillatory dynamical system-based models of computing and their implementations. We show that simple configurations of oscillators connected using simple electrical circuits can result in interesting phase and frequency dynamics of such coupled oscillatory systems. Such networks can be controlled, programmed, and observed to solve computationally hard problems. Although our discussion in this paper is limited to insulator-to-metal transition devices and spin-torque oscillators, the general philosophy of such a computing paradigm of “let physics do the computing” can be translated to other mediums as well, including micromechanical and optical systems. We present an overview of the mathematical treatments necessary to understand the time evolution of these systems and highlight the recent experimental results in this area that suggest the potential of such computational models.
机译:当我们接近芯片路线图的末尾时,可以解决 n 大规模 n问题变得越来越重要。伴随着这样的认识,即二进制抽象和布尔逻辑(它们已成为现代计算革命的基础)未能达到所需的性能和能效。特别是,与模式匹配,图像和信号处理,优化以及神经形态应用相关的硬计算问题需要替代方法。在本文中,我们回顾了基于振荡动力系统的计算模型及其实现的最新进展。我们表明,使用简单电路连接的振荡器的简单配置会导致这种耦合振荡系统产​​生有趣的相位和频率动态。可以对此类网络进行控制,编程和观察,以解决计算难题。尽管我们在本文中的讨论仅限于绝缘体到金属的过渡装置和自旋扭矩振荡器,但这种“让物理学完成计算”的计算范式的一般原理也可以转化为其他介质,包括微机械和光学系统。我们提供了必要的数学方法的概述,以了解这些系统的时间演变,并重点介绍了该领域的最新实验结果,这些结果表明了这种计算模型的潜力。

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