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Neuromorphic Computing Based on Emerging Memory Technologies

机译:基于新兴存储技术的神经形态计算

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In this paper, we review some of the novel emerging memory technologies and how they can enable energy-efficient implementation of large neuromorphic computing systems. We will highlight some of the key aspects of biological computation that are being mimicked in these novel nanoscale devices, and discuss various strategies employed to implement them efficiently. Though large scale learning systems have not been implemented using these devices yet, we will discuss the ideal specifications and metrics to be satisfied by these devices based on theoretical estimations and simulations. We also outline the emerging trends and challenges in the path towards successful implementations of large learning systems that could be ubiquitously deployed for a wide variety of cognitive computing tasks.
机译:在本文中,我们回顾了一些新兴的内存技术,以及它们如何实现大型神经形态计算系统的节能实现。我们将重点介绍这些新颖的纳米级设备中正在模仿的生物计算的一些关键方面,并讨论有效实施它们的各种策略。尽管尚未使用这些设备实现大规模学习系统,但我们将基于理论估计和模拟来讨论这些设备要满足的理想规格和指标。我们还概述了成功实施大型学习系统的趋势中出现的趋势和挑战,这些学习系统可以普遍部署用于各种认知计算任务。

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