Neuromorphic Computing Based on Emerging Memory Technologies
Neuromorphic Computing Based on Emerging Memory Technologies
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DOI：
10.1109/jetcas.2016.2533298
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发表时间：
2016-06-01
影响因子：
4.6
通讯作者：
Alibart, Fabien
中科院分区：
文献类型：
--
作者：
Rajendran, Bipin;Alibart, Fabien
在本文中，我们回顾了一些新的新兴的内存技术，以及它们如何使大型神经形态计算系统的节能实现。我们将重点介绍在这些新型纳米器件中被模仿的生物计算的一些关键方面，并讨论有效实现它们的各种策略。虽然还没有使用这些设备实现大规模学习系统，但我们将根据理论估计和模拟讨论这些设备所满足的理想规格和指标。我们还概述了在成功实现大型学习系统的道路上出现的趋势和挑战，这些系统可以普遍部署在各种各样的认知计算任务中。
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.